Diff: rfc9699.original.xml

	rfc9699.original.xml	rfc9699.xml

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	<front>	<front>

	<title abbrev="MOPS AR Use Case">Media Operations Use Case for an Extended R	<title abbrev="XR Use Case">Use Case for an Extended
	eality Application on Edge Computing Infrastructure</title>	Reality Application on Edge Computing Infrastructure</title>
	<seriesInfo name="Internet-Draft" value="draft-ietf-mops-ar-use-case-18"/>	<seriesInfo name="RFC" value="9699"/>
	<author fullname="Renan Krishna" initials="R." surname="Krishna">	<author fullname="Renan Krishna" initials="R." surname="Krishna">


	<address>	<address>
	<postal>	<postal>


	<country>United Kingdom</country>	<country>United Kingdom</country>
	</postal>	</postal>
	<email>renan.krishna@gmail.com</email>	<email>renan.krishna@gmail.com</email>

	<uri/>
	</address>	</address>
	</author>	</author>
	<author initials="A." surname="Rahman" fullname="Akbar Rahman">	<author initials="A." surname="Rahman" fullname="Akbar Rahman">
	<organization>Ericsson</organization>	<organization>Ericsson</organization>
	<address>	<address>
	<postal>	<postal>
	<street>349 Terry Fox Drive</street>	<street>349 Terry Fox Drive</street>

	<city>Ottawa Ontario</city>	<city>Ottawa</city>
		<region>Ontario</region>
	<code>K2K 2V6</code>	<code>K2K 2V6</code>
	<country>Canada</country>	<country>Canada</country>

	<region/>
	</postal>	</postal>

	<phone/>
	<email>Akbar.Rahman@ericsson.com</email>	<email>Akbar.Rahman@ericsson.com</email>

	<uri/>
	</address>	</address>
	</author>	</author>

	<date />	<date month="December" year="2024"/>
	<area>Operations and Management</area>	<area>OPS</area>
	<workgroup> MOPS</workgroup>	<workgroup>mops</workgroup>
	<abstract>
	<t>

	This document explores the issues involved in the use of Edge Com
	puting resources to operationalize media use cases
	that involve Extended Reality (XR) applications. In particular, t
	his document discusses those applications that run on devices having different
	form factors (such as different physical sizes and shapes) and ne
	ed Edge computing resources to mitigate the effect of problems such as a need to
	support interactive communication
	requiring low latency, limited battery power, and heat dissipatio
	n from those devices. The intended audience for this document are network
	operators who are interested in providing edge computing resource
	s to operationalize the requirements of such applications.
	This document discusses the expected behavior of XR applications
	which can be used to manage the traffic.
	In addition, the document discusses the service requirements of X
	R applications to be able to run on the network.


		<abstract>
		<t>This document explores the issues involved in the use of edge
		computing resources to operationalize a media use case that involves an
		Extended Reality (XR) application. In particular, this document
		discusses an XR application that can run on devices having different
		form factors (such as different physical sizes and shapes) and needs edge
		computing resources to mitigate the effect of problems such as the need
		to support interactive communication requiring low latency, limited
		battery power, and heat dissipation from those devices. This document
		also discusses the expected behavior of XR applications, which can be
		used to manage traffic, and the service requirements for XR applications
		to be able to run on the network. Network operators who are interested
		in providing edge computing resources to operationalize the requirements
		of such applications are the intended audience for this document.
	</t>	</t>
	</abstract>	</abstract>
	</front>	</front>
	<middle>	<middle>
	<section anchor="introduction" numbered="true" toc="default">	<section anchor="introduction" numbered="true" toc="default">
	<name>Introduction</name>	<name>Introduction</name>
	<t>	<t>

	Extended Reality (XR) is a term that includes Augmented Reality (	Extended Reality (XR) is a term that includes Augmented
	AR), Virtual Reality (VR) and Mixed Reality (MR) <xref target="XR" format="defau	Reality (AR), Virtual Reality (VR), and Mixed Reality (MR)
	lt"/>.	<xref target="XR" format="default"/>. AR combines the real
	AR combines the real and virtual, is interactive and is aligned t	and virtual, is interactive, and is aligned to the physical
	o the physical world of the user <xref target="AUGMENTED_2" format="default"/>.	world of the user <xref target="AUGMENTED_2"
	On the other hand,	format="default"/>. On the other hand, VR places the user
	VR places the user inside a virtual environment generated by a co	inside a virtual environment generated by a computer <xref
	mputer <xref target="AUGMENTED" format="default"/>.MR merges the real and virtua	target="AUGMENTED" format="default"/>. MR merges the real and
	l world along a	virtual along a continuum that connects a completely real
	continuum that connects completely real environment at one end to	environment at one end to a completely virtual environment at
	a completely virtual environment at the other end. In this continuum, all	the other end. In this continuum, all combinations of the real
	combinations of the real and virtual are captured <xref target="A	and virtual are captured <xref target="AUGMENTED"
	UGMENTED" format="default"/>.	format="default"/>.
	</t>	</t>

	<t>
	XR applications will bring several requirements for the network and t	<t>
	he	XR applications have several requirements for the network and the
	mobile devices running these applications. Some XR applications s	mobile devices running these applications. Some XR applications
	uch as AR require a real-time processing of video streams to	(such as AR applications) require real-time processing of video
	recognize specific objects. This is then used to overlay informat	streams to recognize specific objects. This processing is then
	ion on the	used to overlay information on the video being displayed to the
	video being displayed to the user. In addition, XR applications	user. In addition, other XR applications (such as AR and VR applicat
	such as AR and VR will also require generation of new video	ions) also
	frames to be played to the user. Both the real-time processing of	require generation of new video frames to be played to the
	video streams and the generation of overlay information	user. Both the real-time processing of video streams and the
	are computationally intensive tasks that generate heat <xref targ	generation of overlay information are computationally intensive
	et="DEV_HEAT_1" format="default"/>, <xref target="DEV_HEAT_2" format="default"/>	tasks that generate heat <xref target="DEV_HEAT_1"
	and drain battery power <xref target="BATT_DRAIN" format="default	format="default"/> <xref target="DEV_HEAT_2" format="default"/>
	"/> on the mobile device running the XR application.	and drain battery power <xref target="BATT_DRAIN"
	Consequently, in order to run applications with XR characteristic	format="default"/> on the mobile device running the XR
	s	application. Consequently, in order to run applications with XR
	on mobile devices, computationally intensive tasks need to be off	characteristics on mobile devices, computationally intensive tasks
	loaded to resources provided by Edge Computing.	need to be offloaded to resources provided by edge computing.
	</t>	</t>
	<t>	<t>

	Edge Computing is an emerging paradigm where for the purpose of t	Edge computing is an emerging paradigm where, for the purpose of
	his document, computing resources and storage are made available in close	this document, computing resources and storage are made available in close
	network proximity at the edge of the Internet to mobile devices a	network proximity at the edge of the Internet to mobile devices a
	nd sensors <xref target="EDGE_1" format="default"/>, <xref target="EDGE_2" forma	nd sensors <xref target="EDGE_1" format="default"/> <xref target="EDGE_2" format
	t="default"/>. A computing resource or storage is in	="default"/>. A computing resource or storage is in
	close network proximity to a mobile device or sensor if there is a short and high-capacity network path to it	close network proximity to a mobile device or sensor if there is a short and high-capacity network path to it
	such that the latency and bandwidth requirements of applications running on those mobile devices or sensors can be met.	such that the latency and bandwidth requirements of applications running on those mobile devices or sensors can be met.

	These edge computing devices use cloud technologies that enable t hem to support offloaded XR applications. In particular, cloud implementation te chniques <xref target="EDGE_3" format="default"/> such as the follows can be dep loyed:	These edge computing devices use cloud technologies that enable t hem to support offloaded XR applications. In particular, cloud implementation te chniques <xref target="EDGE_3" format="default"/> such as the following can be d eployed:
	</t>	</t>


	<ul spacing="normal">	<dl spacing="normal">
	<li>Disaggregation (using SDN to break vertically integrated systems int	<dt>Disaggregation:</dt><dd>Using Software-Defined Networking (SDN) to b
	o independent components- these components can have open interfaces which are st	reak vertically integrated systems into independent components. These components
	andard, well documented and not proprietary),	can have open interfaces that are standard, well documented, and non-proprietar
	</li>	y.</dd>
	<li>Virtualization (being able to run multiple independent copies of tho
	se components such as SDN Controller apps, Virtual Network Functions on a	<dt>Virtualization:</dt><dd>Being able to run multiple independent copie
	common hardware platform).</li>	s of those components, such as SDN Controller applications and Virtual Network F
	<li>Commoditization (being able to elastically scale those virtual compo	unctions, on a
	nents across commodity hardware as the workload dictates).</li>	common hardware platform.</dd>
	</ul>	<dt>Commoditization:</dt><dd>Being able to elastically scale those virtu
		al components across commodity hardware as the workload dictates.</dd>
		</dl>

	<t>	<t>

	Such techniques enable XR applications requiring low-latency and high bandwidth to be delivered by proximate edge devices. This is because the d isaggregated components can run on proximate edge devices rather than on remote cloud several hops away and deliver low latency, high bandwidth service to offlo aded applications <xref target="EDGE_2" format="default"/>.	Such techniques enable XR applications that require low latency and high bandwidth to be delivered by proximate edge devices. This is because th e disaggregated components can run on proximate edge devices rather than on a re mote cloud several hops away and deliver low-latency, high-bandwidth service to offloaded applications <xref target="EDGE_2" format="default"/>.
	</t>	</t>


	<t>	<t>

	This document discusses the issues involved when edge computing resourc	This document discusses the issues involved when edge computing
	es are offered by network operators to	resources are offered by network operators to operationalize the
	operationalize the requirements of XR applications running on devices w	requirements of XR applications running on devices with various form
	ith various form factors. A network operator for the purposes of this	factors. For the purpose of this document, a network operator is any
	document is any organization or individual that manages or operates the	organization or individual that manages or operates the computing
	compute resources or storage in close network proximity	resources or storage in close network proximity to a mobile device
	to a mobile device or sensors. Examples of form factors	or sensor. Examples of form factors include the following: 1)
	include Head Mounted Displays (HMD) such as Optical-see through HMDs an	head-mounted displays (HMDs), such as optical see-through HMDs and
	d video-see-through HMDs and Hand-held displays.	video see-through HMDs, 2) hand-held displays, and 3) smartphones
	Smart phones with video cameras and location sensing capabilities using	with video cameras and location-sensing capabilities using systems
	systems such as a global navigation satellite system (GNSS) are another example	such as a global navigation satellite system (GNSS). These devices
	of such devices. These devices have limited	have limited battery capacity and dissipate heat when running. Also,
	battery capacity and dissipate heat when running. Besides as the user o	as the user of these devices moves around as they run the XR
	f these devices moves around as they run the	application, the wireless latency and bandwidth available to the
	XR application, the wireless latency and bandwidth available to the dev	devices fluctuates, and the communication link itself might fail. As
	ices fluctuates and the communication link itself	a result, algorithms such as those based on Adaptive Bitrate (ABR)
	might fail. As a result, algorithms such as those based on adaptive-bit	techniques that base their policy on heuristics or models of
	-rate techniques that base their policy on heuristics	deployment perform sub-optimally in such dynamic environments <xref
	or models of deployment perform sub-optimally in such dynamic environme	target="ABR_1" format="default"/>. In addition, network operators
	nts <xref target="ABR_1" format="default"/>.	can expect that the parameters that characterize the expected
	In addition, network operators can expect that the parameters that char	behavior of XR applications are heavy-tailed. Heaviness of tails is
	acterize the expected behavior of XR applications	defined as the difference from the normal distribution in the
	are heavy-tailed. Heaviness of tails is defined as the difference from	proportion of the values that fall a long way from the mean <xref
	the normal distribution in the proportion of the values that fall a long way fro	target="HEAVY_TAIL_3" format="default"/>. Such workloads require
	m the mean <xref target="HEAVY_TAIL_3" format="default"/>. Such workloads requir	appropriate resource management policies to be used on the edge.
	e appropriate resource management policies to be used on the Edge.	The service requirements of XR applications are also challenging
	The service requirements of XR applications are also challenging when c	when compared to current video applications. In particular, several
	ompared to the current video applications.	Quality-of-Experience (QoE) factors such as motion sickness are
	In particular several Quality of Experience (QoE) factors such as motio	unique to XR applications and must be considered when
	n sickness are unique to XR applications and must be considered when operational	operationalizing a network.
	izing a network.


	This document motivates these issues with a use-case that is pres ented in the following sections.	This document examines these issues with the use case presented i n the following section.
	</t>	</t>
	</section>	</section>

	<section anchor="use_case" numbered="true" toc="default">	<section anchor="use_case" numbered="true" toc="default">
	<name>Use Case</name>	<name>Use Case</name>


	<t>	<t>

	A use case is now described that involves an application with	This use case involves an XR application running on a mobile device. Consider
	XR systems' characteristics. Consider a group of tourists who ar	a group of tourists who are taking a tour around the historical site of the
	e being	Tower of London. As they move around the site and within the historical
	conducted in a tour around the historical site of the Tower of L	buildings, they can watch and listen to historical scenes in 3D that are
	ondon.	generated by the XR application and then overlaid by their XR headsets onto
	As they move around the site and within the historical buildings	their real-world view. The headset continuously updates their view as they
	, they can	move around.
	watch and listen to historical scenes in 3D that are generated b
	y the XR application and then
	overlaid by their XR headsets onto their real-world view. The he
	adset then continuously updates their view as they move around.
	</t>	</t>
	<t>	<t>

	The XR application first processes the scene that the walking to urist is watching in real-time and identifies objects	The XR application first processes the scene that the walking to urist is watching in real time and identifies objects
	that will be targeted for overlay of high-resolution videos. It t hen generates high-resolution 3D images	that will be targeted for overlay of high-resolution videos. It t hen generates high-resolution 3D images

	of historical scenes related to the perspective of the tourist i	of historical scenes related to the perspective of the tourist in
	n real-time. These generated video images are then	real time. These generated video images are then
	overlaid on the view of the real-world as seen by the tourist.	overlaid on the view of the real world as seen by the tourist.
	</t>	</t>
	<t>	<t>
	This processing of scenes	This processing of scenes

	and generation of high-resolution images is now discussed in grea ter detail.	and generation of high-resolution images are discussed in greater detail below.

	</t>	</t>
	<section anchor="processsing_of_scenes" numbered="true" toc="default">	<section anchor="processsing_of_scenes" numbered="true" toc="default">
	<name>Processing of Scenes</name>	<name>Processing of Scenes</name>
	<t>	<t>

	The task of processing a scene can be broken down into a pipeline	The task of processing a scene can be broken down into a pipeline
	of three consecutive subtasks namely tracking, followed by an acquisition of a	of three consecutive subtasks: tracking, acquisition of a
	model of the real world, and finally registration <xref target="A	model of the real world, and registration <xref target="AUGMENTED
	UGMENTED" format="default"/>.	" format="default"/>.

	</t>
	<t>
	Tracking: The XR application that runs on the mobile device needs
	to track the six-dimensional pose (translational in the three perpendicular axe
	s and rotational about those three axes)
	of the user's head, eyes and the objects that are in view <xref t
	arget="AUGMENTED" format="default"/>. This requires tracking natural features (f
	or example points or edges of objects) that are then used in the next stage of t
	he pipeline.
	</t>
	<t>
	Acquisition of a model of the real world: The tracked natural fea
	tures are used to develop a model of the real world. One of the ways this is don
	e is to develop an annotated
	point cloud (a set of points in space that are annotated with des
	criptors) based model that is then stored in a database. To ensure that this dat
	abase can be scaled up, techniques such as
	combining a client-side simultaneous tracking and mapping and a s
	erver-side localization
	are used to construct a model of the real world <xref target="SLA
	M_1" format="default"/>, <xref target="SLAM_2" format="default"/>, <xref target=
	"SLAM_3" format="default"/>, <xref target="SLAM_4" format="default"/>. Another m
	odel that can be built is based on polygon mesh and texture mapping technique. T
	he polygon mesh encodes a 3D object's shape which is expressed as a collection o
	f small flat surfaces that are polygons. In texture mapping, color patterns are
	mapped on to an object's surface. A third modelling technique uses a 2D lightfie
	ld that describes the intensity or color of the light rays arriving at a single
	point from arbitrary directions. Such a 2D lightfield is stored as a two-dimensi
	onal table. Assuming distant light sources, the single point is approximately va
	lid for small scenes. For larger scenes, many 3D positions are additionally stor
	ed making the table 5D. A set of all such points (either 2D or 5D lightfield) ca
	n then be used to construct a model of the real world <xref target="AUGMENTED" f
	ormat="default"/>.
	</t>	</t>

	<t>
	Registration: The coordinate systems, brightness, and color
	of virtual and real objects need to be aligned with each other an
	d this process is called registration <xref target="REG" format="default"/>.
	Once the
	natural features are tracked as discussed above, virtual objects
	are geometrically aligned with those features by geometric registration. This is
	followed by
	resolving occlusion that can occur between virtual and the real o
	bjects <xref target="OCCL_1" format="default"/>, <xref target="OCCL_2" format="d
	efault"/>.


	The XR application also applies photometric registration <xref ta	<dl newline="false" spacing="normal">
	rget="PHOTO_REG" format="default"/>
	by aligning the brightness and color between the virtual and	<dt>Tracking:</dt><dd>The XR application that runs on the mobile
	real objects. Additionally, algorithms that calculate global illu	device
	mination of both the virtual and real objects <xref target="GLB_ILLUM_1" format=	needs to track the six-dimensional pose (translational in the
	"default"/>,	three perpendicular axes and rotational about those three
	<xref target="GLB_ILLUM_2" format="default"/> are executed. Vario	axes) of the user's head, eyes, and objects that are in
	us algorithms to deal with artifacts generated by lens distortion <xref target="	view <xref target="AUGMENTED" format="default"/>. This
	LENS_DIST" format="default"/>,	requires tracking natural features (for example, points or
	blur <xref target="BLUR" format="default"/>, noise <xref target="	edges of objects) that are then used in the next stage of the
	NOISE" format="default"/> etc. are also required.	pipeline.</dd>
	</t>
		<dt>Acquisition of a model of the real world:</dt><dd>The
		tracked natural features are used to develop a model of the
		real world. One of the ways this is done is to develop a model ba
		sed on an
		annotated point cloud (a set of points in space that are
		annotated with descriptors) that is then stored in
		a database. To ensure that this database can be scaled up,
		techniques such as combining client-side simultaneous
		tracking and mapping with server-side localization are used
		to construct a model of the real world <xref target="SLAM_1"
		format="default"/> <xref target="SLAM_2" format="default"/>
		<xref target="SLAM_3" format="default"/> <xref target="SLAM_4"
		format="default"/>. Another model that can be built is based
		on a polygon mesh and texture mapping technique. The polygon
		mesh encodes a 3D object's shape, which is expressed as a
		collection of small flat surfaces that are polygons. In
		texture mapping, color patterns are mapped onto an object's
		surface. A third modeling technique uses a 2D lightfield that
		describes the intensity or color of the light rays arriving at
		a single point from arbitrary directions. Such a 2D lightfield
		is stored as a two-dimensional table. Assuming distant light
		sources, the single point is approximately valid for small
		scenes. For larger scenes, many 3D positions are additionally
		stored, making the table 5D. A set of all such points (either a
		2D or 5D lightfield) can then be used to construct a model of
		the real world <xref target="AUGMENTED"
		format="default"/>.</dd>

		<dt>Registration:</dt><dd>The coordinate systems,
		brightness, and color of virtual and real objects need to be
		aligned with each other; this process is called
		"registration" <xref target="REG" format="default"/>. Once the
		natural features are tracked as discussed above, virtual
		objects are geometrically aligned with those features by
		geometric registration. This is followed by resolving
		occlusion that can occur between virtual and real objects
		<xref target="OCCL_1" format="default"/> <xref target="OCCL_2"
		format="default"/>.

		The XR application also applies photometric registration <xref
		target="PHOTO_REG" format="default"/> by aligning
		brightness and color between the virtual and real
		objects. Additionally, algorithms that calculate global
		illumination of both the virtual and real objects <xref
		target="GLB_ILLUM_1" format="default"/> <xref
		target="GLB_ILLUM_2" format="default"/> are executed. Various
		algorithms are also required to deal with artifacts generated by
		lens distortion
		<xref target="LENS_DIST" format="default"/>, blur <xref
		target="BLUR" format="default"/>, noise <xref target="NOISE"
		format="default"/>, etc.</dd>
		</dl>
	</section>	</section>
	<section anchor="generation" numbered="true" toc="default">	<section anchor="generation" numbered="true" toc="default">
	<name>Generation of Images</name>	<name>Generation of Images</name>


	<t>	<t>

	The XR application must generate a high-quality video that has th	The XR application must generate a high-quality video that has the
	e properties described in the previous step	properties described above and overlay the video on the XR device's
	and overlay the video on the XR device's display- a step called s	display. This step is called "situated visualization". A situated
	ituated visualization. A situated visualization is a visualization in which the	visualization is a visualization in which the virtual objects that need to
	virtual objects that need to be seen by the XR user are overlaid correctly on th	be seen by the XR user are overlaid correctly on the real world. This
	e real world. This entails dealing with registration errors that	entails dealing with registration errors that may arise, ensuring that
	may arise, ensuring that there is no visual interference <xref ta	there is no visual interference <xref target="VIS_INTERFERE"
	rget="VIS_INTERFERE" format="default"/>, and finally maintaining	format="default"/>, and finally maintaining temporal coherence by adapting
	temporal coherence by adapting to the movement of user's eyes and	to the movement of user's eyes and head.
	head.
	</t>	</t>
	</section>	</section>
	</section>	</section>
	<section anchor="Req" numbered="true" toc="default">	<section anchor="Req" numbered="true" toc="default">
	<name>Technical Challenges and Solutions</name>	<name>Technical Challenges and Solutions</name>


	<t>	<t>

	As discussed in section 2, the components of XR applications perform task	As discussed in <xref target="use_case"/>, the components of XR
	s such as real-time generation and processing of	applications perform tasks that are computationally intensive, such as
	high-quality video content that are computationally intensive. Th	real-time generation and processing of high-quality video content.
	is section will discuss the challenges such applications can face as a consequen	This section discusses the challenges such applications can face as a
	ce.</t> <t>As a result of performing computationally intensive tasks on XR devic	consequence and offers some solutions.
	es such as XR glasses,	</t>
	excessive heat is generated by the chip-sets that are involved	<t>As a result of performing computationally intensive tasks on XR devices
	in the computation <xref target="DEV_HEAT_1" format="default"/>,	such as XR glasses,
	<xref target="DEV_HEAT_2" format="default"/>. Additionally,	excessive heat is generated by the chipsets that are involved
		in the computation <xref target="DEV_HEAT_1" format="default"/> <
		xref target="DEV_HEAT_2" format="default"/>. Additionally,
	the battery on such devices discharges quickly when running	the battery on such devices discharges quickly when running
	such applications <xref target="BATT_DRAIN" format="default"/>.	such applications <xref target="BATT_DRAIN" format="default"/>.

	</t>	</t>
	<t>	<t>

	A solution to the heat dissipation and battery drainage problem is to off load the processing and video generation tasks	A solution to problem of heat dissipation and battery drainage is to offl oad the processing and video generation tasks
	to the remote cloud. However, running such tasks on the cloud is not feas ible as the end-to-end delays	to the remote cloud. However, running such tasks on the cloud is not feas ible as the end-to-end delays
	must be within the order of a few milliseconds. Additionally, suc h applications require high bandwidth	must be within the order of a few milliseconds. Additionally, suc h applications require high bandwidth
	and low jitter to provide a high QoE to the user. In order to ach ieve such hard timing constraints, computationally intensive	and low jitter to provide a high QoE to the user. In order to ach ieve such hard timing constraints, computationally intensive

	tasks can be offloaded to Edge devices.	tasks can be offloaded to edge devices.

	</t>	</t>
	<t>	<t>

		Another requirement for our use case and similar applications, such as 36
	Another requirement for our use case and similar applications such as 360	0-degree streaming (streaming of video that represents a view in every direction
	-degree streaming (streaming of video that represents a view in every direction	in 3D space), is that the display on
	in 3D space) is that the display on
	the XR device should synchronize the visual input with the way the user i s moving their head. This synchronization	the XR device should synchronize the visual input with the way the user i s moving their head. This synchronization

	is necessary to avoid motion sickness that results from a time-lag betwee	is necessary to avoid motion sickness that results from a time lag betwee
	n when the user moves their head and	n when the user moves their head and
	when the appropriate video scene is rendered. This time lag is often call	when the appropriate video scene is rendered. This time lag is often call
	ed "motion-to-photon" delay.	ed "motion-to-photon delay".
	Studies have shown <xref target="PER_SENSE" format="default"/>, <xref target="XR	Studies have shown that this delay
	" format="default"/>, <xref target="OCCL_3" format="default"/> that this delay	can be at most 20 ms and preferably between 7-15 ms in
	can be at most 20ms and preferably between 7-15ms in	order to avoid motion sickness <xref target="PER_SENSE" format="default"/> <xref
	order to avoid the motion sickness problem. Out of these 20ms, display technique	target="XR" format="default"/> <xref target="OCCL_3" format="default"/>. Out of
	s including the refresh	these 20 ms, display techniques including the refresh
	rate of write displays and pixel switching take 12-13ms <xref target="OCCL_3" fo	rate of write displays and pixel switching take 12-13 ms <xref target="OCCL_3" f
	rmat="default"/>, <xref target="CLOUD" format="default"/>. This leaves 7-8ms for	ormat="default"/> <xref target="CLOUD" format="default"/>. This leaves 7-8 ms fo
	the processing of	r the processing of
	motion sensor inputs, graphic rendering, and round-trip-time (RTT) between the X	motion sensor inputs, graphic rendering, and round-trip time (RTT) between the X
	R device and the Edge.	R device and the edge.
	The use of predictive techniques to mask latencies has been considered as a miti gating strategy to reduce motion sickness <xref target="PREDICT" format="default "/>.	The use of predictive techniques to mask latencies has been considered as a miti gating strategy to reduce motion sickness <xref target="PREDICT" format="default "/>.

	In addition, Edge Devices that are proximate to the user might be used to offloa	In addition, edge devices that are proximate to the user might be used to offloa
	d these computationally intensive tasks.	d these computationally intensive tasks.
	Towards this end, a 3GPP study indicates an Ultra Reliable Low Latency of 0.1ms	Towards this end, a 3GPP study suggests an Ultra-Reliable Low Latency of
	to 1ms for	0.1 to 1 ms for communication between an edge server and User Equipment
	communication between an Edge server and User Equipment (UE) <xref target="URLL	(UE) <xref target="URLLC" format="default"/>.
	C" format="default"/>.

	</t>	</t>
	<t>	<t>

	Note that the Edge device providing the computation and storage i	Note that the edge device providing the computation and storage i
	s itself limited in such resources compared to the Cloud. So,	s itself limited in such resources compared to the cloud.
	for example, a sudden surge in demand from a large group of touri	For example, a sudden surge in demand from a large group of touri
	sts can overwhelm that device. This will result in a degraded user	sts can overwhelm the device. This will result in a degraded user
	experience as their XR device experiences delays in receiving th e video frames. In order to deal	experience as their XR device experiences delays in receiving th e video frames. In order to deal

	with this problem, the client XR applications will need to use A daptive Bit Rate (ABR) algorithms that choose bit-rates policies	with this problem, the client XR applications will need to use A BR algorithms that choose bitrate policies
	tailored in a fine-grained manner	tailored in a fine-grained manner

	to the resource demands and playback the videos with appropriate QoE metrics as the user moves around with the group of tourists.	to the resource demands and play back the videos with appropriat e QoE metrics as the user moves around with the group of tourists.
	</t>	</t>


	<t>	<t>

	However, heavy-tailed nature of several operational parameters m	However, the heavy-tailed nature of several operational parameters (e.g.,
	akes prediction-based adaptation by ABR algorithms sub-optimal <xref target="AB	buffer occupancy, throughput, client-server latency, and variable
	R_2" format="default"/>.	transmission times) makes prediction-based adaptation by ABR algorithms
	This is because with such distributions, law of large numbers (ho	sub-optimal <xref target="ABR_2" format="default"/>. This is because with
	w long does it take for sample mean to stabilize) works too slowly <xref target=	such distributions, the law of large numbers (how long it takes for the
	"HEAVY_TAIL_2" format="default"/>, the mean of sample does not equal the mean of	sample mean to stabilize) works too slowly <xref target="HEAVY_TAIL_2"
	distribution <xref target="HEAVY_TAIL_2" format="default"/>,	format="default"/> and the mean of sample does not equal the mean of
	and as a result standard deviation and variance are unsuitable as	distribution <xref target="HEAVY_TAIL_2" format="default"/>; as a result,
	metrics for such operational parameters <xref target="HEAVY_TAIL_1" format="def	standard deviation and variance are unsuitable as metrics for such
	ault"/>. Other subtle issues with	operational parameters <xref target="HEAVY_TAIL_1"
	these distributions include the "expectation paradox" <xref targe	format="default"/>.
	t="HEAVY_TAIL_1" format="default"/> where the longer the wait for an event, the	Other subtle issues with these distributions include
	longer a further need to wait and the	the "expectation paradox" <xref target="HEAVY_TAIL_1" format="default"/>
	issue of mismatch between the size and count of events <xref targ	(the longer the wait for an event, the longer a further need to wait) and
	et="HEAVY_TAIL_1" format="default"/>. This makes designing an algorithm for	the mismatch between the size and count of events <xref
	adaptation error-prone and challenging.	target="HEAVY_TAIL_1" format="default"/>. These issues make designing an algo
	Such operational parameters include but are not limited to buffer	rithm
	occupancy, throughput, client-server latency, and variable transmission	for adaptation error-prone and challenging.
	times. In addition, edge devices and communication links may fai	In addition, edge devices and
	l and logical communication relationships between various software components	communication links may fail, and logical communication relationships
	change frequently as the user moves around with their XR device <	between various software components change frequently as the user moves
	xref target="UBICOMP" format="default"/>.	around with their XR device <xref target="UBICOMP" format="default"/>.

	</t>	</t>

	</section>	</section>
	<section anchor="ArTraffic" numbered="true" toc="default">	<section anchor="ArTraffic" numbered="true" toc="default">
	<name>XR Network Traffic</name>	<name>XR Network Traffic</name>

	<section anchor="traffic_workload" numbered="true" toc="default">	<section anchor="traffic_workload" numbered="true" toc="default">
	<name>Traffic Workload</name>	<name>Traffic Workload</name>

	<t>	<t>

	As discussed earlier, the parameters that capture the characteris	As discussed in Sections <xref target="introduction" format="coun
	tics of XR application behavior are heavy-tailed.	ter"/> and <xref target="Req" format="counter" />, the parameters that capture t
	Examples of such parameters include the distribution of arrival t	he characteristics of XR application behavior are heavy-tailed.
	imes between XR application invocation, the amount	Examples of such parameters include the distribution of arrival t
		imes between XR application invocations, the amount
	of data transferred, and the inter-arrival times of packets withi n a session. As a result, any traffic model based on	of data transferred, and the inter-arrival times of packets withi n a session. As a result, any traffic model based on

	such parameters are themselves heavy-tailed. Using	such parameters is also heavy-tailed. Using
	these models to predict performance under alternative resource al locations by the network operator is challenging. For example, both uplink and d ownlink traffic to a user device has parameters such as volume of XR data, burst time, and idle time that are heavy-tailed.	these models to predict performance under alternative resource al locations by the network operator is challenging. For example, both uplink and d ownlink traffic to a user device has parameters such as volume of XR data, burst time, and idle time that are heavy-tailed.
	</t>	</t>
	<t>	<t>

	<xref target="TABLE_1" format="default"/> below shows various streaming
	video applications and their associated throughput requirements <xref target="M	<xref target="TABLE_1" format="default"/> below shows various
	ETRICS_1" format="default"/>. Since our use case envisages a 6 degrees of freedo	streaming video applications and their associated throughput
	m (6DoF) video or point cloud, it can be seen from the table that it will requir	requirements <xref target="METRICS_1" format="default"/>. Since our
	e 200 to 1000Mbps of bandwidth.	use case envisages a 6 degrees of freedom (6DoF) video or point
	As seen from the table, the XR application such as our use case transmit a large	cloud, the table indicates that it will require 200 to 1000 Mbps of
	r amount of data per unit time as compared to traditional video applications. As	bandwidth. Also, the table shows that XR applications, such as the
	a result, issues arising out of heavy-tailed parameters such as long-range depe	one in our use case, transmit a larger amount of data per unit time
	ndent traffic <xref target="METRICS_2" format="default"/>, self-similar traffic	as compared to regular video applications. As a result, issues
	<xref target="METRICS_3" format="default"/>, would be experienced at time scales	arising from heavy-tailed parameters, such as long-range dependent
	of milliseconds and microseconds rather than hours or seconds. Additionally, bu	traffic <xref target="METRICS_2" format="default"/> and self-similar
	rstiness at the time scale of tens of milliseconds due to multi-fractal spectrum	traffic <xref target="METRICS_3" format="default"/>, would be
	of traffic will be experienced <xref target="METRICS_4" format="default"/>.	experienced at timescales of milliseconds and microseconds rather
	Long-range dependent traffic can have long bursts and various traffic parameters	than hours or seconds. Additionally, burstiness at the timescale of
	from widely separated time can show correlation <xref target="HEAVY_TAIL_1" for	tens of milliseconds due to the multi-fractal spectrum of traffic
	mat="default"/>. Self-similar traffic contains bursts at a wide range of time sc	will be experienced <xref target="METRICS_4" format="default"/>.
	ales <xref target="HEAVY_TAIL_1" format="default"/>. Multi-fractal spectrum burs	Long-range dependent traffic can have long bursts, and various
	ts for traffic summarizes the statistical distribution of local scaling exponent	traffic parameters from widely separated times can show correlation
	s found in a traffic trace <xref target="HEAVY_TAIL_1" format="default"/>.	<xref target="HEAVY_TAIL_1" format="default"/>. Self-similar traffic
	The operational consequences of XR traffic having characteristics such as long-r	contains bursts at a wide range of timescales <xref
	ange dependency, and self-similarity is that the edge servers to which multiple	target="HEAVY_TAIL_1" format="default"/>. Multi-fractal spectrum
	XR devices are connected wirelessly could face long bursts of traffic <xref targ	bursts for traffic summarize the statistical distribution of local
	et="METRICS_2" format="default"/>, <xref target="METRICS_3" format="default"/>.	scaling exponents found in a traffic trace <xref
	In addition, multi-fractal spectrum burstiness at the scale of milli-seconds cou	target="HEAVY_TAIL_1" format="default"/>. The operational
	ld induce jitter contributing to motion sickness <xref target="METRICS_4" format	consequence of XR traffic having characteristics such as long-range
	="default"/>. This is because bursty traffic combined with variable queueing del	dependency and self-similarity is that the edge servers to which
	ays leads to large delay jitter <xref target="METRICS_4" format="default"/>.	multiple XR devices are connected wirelessly could face long bursts
	The operators of edge servers will need to run a 'managed edge cloud service' <x	of traffic <xref target="METRICS_2" format="default"/> <xref
	ref target="METRICS_5" format="default"/> to deal with the above problems. Funct	target="METRICS_3" format="default"/>. In addition, multi-fractal
	ionalities that such a managed edge cloud service could operationally provide in	spectrum burstiness at the scale of milliseconds could induce jitter
	clude dynamic placement of XR servers, mobility support and energy management <x	contributing to motion sickness <xref target="METRICS_4"
	ref target="METRICS_6" format="default"/>. Providing Edge server support for the	format="default"/>. This is because bursty traffic combined with
	techniques being developed at the DETNET Working Group at the IETF <xref target	variable queueing delays leads to large delay jitter <xref
	="RFC8939" format="default"/>, <xref target="RFC9023" format="default"/>, <xref	target="METRICS_4" format="default"/>. The operators of edge servers
	target="RFC9450" format="default"/> could guarantee performance of XR applicatio	will need to run a "managed edge cloud service" <xref
	ns. For example, these techniques could be used for the link between the XR devi	target="METRICS_5" format="default"/> to deal with the above
	ce and the edge as well as within the managed edge cloud service. Another option	problems. Functionalities that such a managed edge cloud service
	for the network operators could be to deploy equipment that supports differenti	could operationally provide include dynamic placement of XR servers,
	ated services <xref target="RFC2475" format="default"/> or per-connection qualit	mobility support, and energy management <xref target="METRICS_6"
	y-of-service guarantees <xref target="RFC2210" format="default"/>.	format="default"/>. Providing support for edge servers in techniques
		such as those described in <xref target="RFC8939" format="default"/>,
		<xref target="RFC9023" format="default"/>, and <xref target="RFC9450"
		format="default"/> could guarantee performance of XR
		applications. For example, these techniques could be used for the
		link between the XR device and the edge as well as within the managed
		edge cloud service. Another option for network operators could be to
		deploy equipment that supports differentiated services <xref
		target="RFC2475" format="default"/> or per-connection
		Quality-of-Service (QoS) guarantees using RSVP <xref target="RFC2210"
		format="default"/>.

	</t>	</t>

		<t>
		Thus, the provisioning of edge servers (in terms of the number of
		servers, the topology, the placement of servers, the assignment of link
		capacity, CPUs, and Graphics Processing Units (GPUs)) should be performed
		with the above factors in mind.
		</t>

	<table anchor="TABLE_1">	<table anchor="TABLE_1">

	<name>Throughput requirement for streaming video applications</name>	<name>Throughput Requirements for Streaming Video Applications</name>
	<thead>	<thead>
	<tr>	<tr>

	<th> Application</th> <th> Throughput Required</th>	<th>Application</th>
		<th>Throughput Required</th>
	</tr>	</tr>
	</thead>	</thead>
	<tbody>	<tbody>
	<tr>	<tr>

	<td> <t>Real-world objects annotated with text and images for w	<td><t>Real-world objects annotated with text and images for wo
	orkflow assistance (e.g. repair)</t></td> <td> <t>1 Mbps</t></td>	rkflow assistance (e.g., repair)</t></td>
		<td> <t>1 Mbps</t></td>
	</tr>	</tr>


	<tr>	<tr>

	<td> <t>Video Conferencing</t></td> <td> <t>2 Mbps</t></td>	<td><t>Video conferencing</t></td>
		<td> <t>2 Mbps</t></td>
	</tr>	</tr>
	<tr>	<tr>

	<td> <t>3D Model and Data Visualization</t></td> <td> <t>2 to 2	<td> <t>3D model and data visualization</t></td>
	0 Mbps</t></td>	<td> <t>2 to 20 Mbps</t></td>
	</tr>	</tr>


	<tr>	<tr>

	<td> <t>Two-way 3D Telepresence</t></td> <td> <t>5 to 25 Mbps</	<td> <t>Two-way 3D telepresence</t></td>
	t></td>	<td> <t>5 to 25 Mbps</t></td>
	</tr>	</tr>


	<tr>	<tr>

	<td> <t>Current-Gen 360-degree video (4K)</t></td> <td> <t>10 t	<td> <t>Current-Gen 360-degree video (4K)</t></td>
	o 50 Mbps</t></td>	<td> <t>10 to 50 Mbps</t></td>
	</tr>	</tr>


	<tr>	<tr>

	<td> <t>Next-Gen 360-degree video (8K, 90+ Frames-per-second, H	<td> <t>Next-Gen 360-degree video (8K, 90+ frames per second, h
	igh Dynamic Range, Stereoscopic)</t></td> <td> <t>50 to 200 Mbps</t></td>	igh dynamic range, stereoscopic)</t></td>
		<td> <t>50 to 200 Mbps</t></td>
	</tr>	</tr>


	<tr>	<tr>

	<td> <t>6 Degree of Freedom Video or Point Cloud</t></td> <td>	<td> <t>6DoF video or point cloud</t></td>
	<t>200 to 1000 Mbps</t></td>	<td> <t>200 to 1000 Mbps</t></td>
	</tr>	</tr>


	</tbody>	</tbody>
	</table>	</table>


	<t>
	Thus, the provisioning of edge servers in terms of the number of servers, the t
	opology, where to place them, the assignment of link capacity, CPUs and GPUs sho
	uld keep the above factors in mind.

	</t>

	</section>	</section>

	<section anchor="traffic_performance" numbered="true" toc="default">	<section anchor="traffic_performance" numbered="true" toc="default">
	<name>Traffic Performance Metrics</name>	<name>Traffic Performance Metrics</name>

	<t>	<t>
	The performance requirements for XR traffic have characteristics that n eed to be considered when operationalizing a network.	The performance requirements for XR traffic have characteristics that n eed to be considered when operationalizing a network.

	These characteristics are now discussed.</t>	These characteristics are discussed in this section.</t>
	<t>The bandwidth requirements of XR applications are substantially higher than t hose of video-based applications.</t>	<t>The bandwidth requirements of XR applications are substantially higher than t hose of video-based applications.</t>


	<t>The latency requirements of XR applications have been studied recently <xref target="XR_TRAFFIC" format="default"/>. The following characteristics we re identified.:	<t>The latency requirements of XR applications have been studied recently <xref target="XR_TRAFFIC" format="default"/>. The following characteristics we re identified:
	</t>	</t>
	<ul spacing="normal">	<ul spacing="normal">
	<li>The uploading of data from an XR device to a remote server for proce ssing dominates the end-to-end latency.	<li>The uploading of data from an XR device to a remote server for proce ssing dominates the end-to-end latency.
	</li>	</li>
	<li> A lack of visual features in the grid environment can cause increas ed latencies as the XR device	<li> A lack of visual features in the grid environment can cause increas ed latencies as the XR device
	uploads additional visual data for processing to the r emote server.</li>	uploads additional visual data for processing to the r emote server.</li>
	<li>XR applications tend to have large bursts that are separated by sign ificant time gaps.</li>	<li>XR applications tend to have large bursts that are separated by sign ificant time gaps.</li>
	</ul>	</ul>


	<t> Additionally, XR applications interact with each other on a time sca le of a round-trip-time propagation, and this must be considered when operationa lizing a network.</t>	<t> Additionally, XR applications interact with each other on a timescal e of an RTT propagation, and this must be considered when operationalizing a net work.</t>

	<t>	<t>

	The following <xref target="TABLE_2" format="default"/> <xref target	<xref target="TABLE_2" format="default"/> shows a taxonomy of
	="METRICS_6" format="default"/> shows a taxonomy of applications with their asso	applications with their associated required response times and
	ciated required response times and bandwidths. Response times can	bandwidths (this data is from Table V in <xref target="METRICS_6"
	be defined as the time interval between the end of a request submission and the	format="default"/>). Response times can be defined as the time
	end of the corresponding response from a system. If the XR device offloads a tas	interval between the end of a request submission and the end of
	k to an edge server, the response time of the server is the round-trip time from	the corresponding response from a system. If the XR device
	when a data packet is sent from the XR device until a response is received. Not	offloads a task to an edge server, the response time of the server
	e that the required response time provides an upper bound on the sum of the time	is the RTT from when a data packet is sent from the XR device
	taken by computational tasks such as processing of scenes, generation of images	until a response is received. Note that the required response time
	and the round-trip time. This response time depends only on the Quality of Serv	provides an upper bound for the sum of the time taken by
	ice (QOS) required by an application. The response time is therefore independent	computational tasks (such as processing of scenes and generation
	of the underlying technology of the network and the time taken by the computati	of images) and the RTT. This response time depends only on the QoS
	onal tasks.	required by an application. The response time is therefore
		independent of the underlying technology of the network and the
		time taken by the computational tasks.

	</t>	</t>

	<t>
	Our use case requires a response time of 20ms at most and preferably between 7-1
	5ms as discussed earlier. This requirement for response time is similar to the f
	irst two entries of <xref target="TABLE_2" format="default"/> below. Additionall
	y, the required bandwidth for our use case as discussed in section 5.1, <xref t
	arget="TABLE_1" format="default"/>, is 200Mbps-1000Mbps.
	Since our use case envisages multiple users running the XR applications on their
	devices, and connected to an edge server that is closest to them, these latency
	and bandwidth connections will grow linearly with the number of users. The oper
	ators should match the network provisioning to the maximum number of tourists th
	at can be supported by a link to an edge server.


		<t>
		Our use case requires a response time of 20 ms at most and
		preferably between 7-15 ms, as discussed earlier. This requirement
		for response time is similar to the first two entries in <xref
		target="TABLE_2" format="default"/>. Additionally, the required
		bandwidth for our use case is 200 to 1000 Mbps (see <xref
		target="traffic_workload"/>). Since our use case envisages multiple
		users running the XR application on their devices and connecting to
		the edge server that is closest to them, these latency and bandwidth
		connections will grow linearly with the number of users.
		The operators should match the network provisioning to the maximum
		number of tourists that can be supported by a link to an edge
		server.
	</t>	</t>


	<table anchor="TABLE_2">	<table anchor="TABLE_2">
	<name>Traffic Performance Metrics of Selected XR Applications</name>	<name>Traffic Performance Metrics of Selected XR Applications</name>
	<thead>	<thead>
	<tr>	<tr>

	<th> Application</th> <th> Required Response Time</th> <th> Ex	<th> Application</th>
	pected Data Capacity</th> <th> Possible Implementations/ Examples</th>	<th> Required Response Time</th>
		<th> Expected Data Capacity</th>
		<th> Possible Implementations/ Examples</th>
	</tr>	</tr>
	</thead>	</thead>
	<tbody>	<tbody>


	<tr>	<tr>

	<td> <t>Mobile XR based remote assistance with uncompressed 4K	<td><t>Mobile XR-based remote assistance with uncompressed
	(1920x1080 pixels) 120 fps HDR 10-bit real-time video stream</t></td>	4K (1920x1080 pixels) 120 fps HDR 10-bit real-time video
	<td> <t>Less than 10 milliseconds</t></td>	stream</t></td>
	<td> <t>Greater than 7.5 Gbps</t></td>	<td><t>Less than 10 milliseconds</t></td>
	<td> <t>Assisting maintenance technicians, Industry 4.0 remote	<td><t>Greater than 7.5 Gbps</t></td>
	maintenance, remote assistance in robotics industry</t></td>	<td><t>Assisting maintenance technicians, Industry 4.0
		remote maintenance, remote assistance in robotics
		industry</t></td>
	</tr>	</tr>
	<tr>	<tr>

	<td> <t>Indoor and localized outdoor navigation </t></td>	<td><t>Indoor and localized outdoor navigation </t></td>
	<td> <t>Less than 20 milliseconds</t></td>	<td><t>Less than 20 milliseconds</t></td>
	<td> <t>50 to 200 Mbps</t></td>	<td><t>50 to 200 Mbps</t></td>
	<td> <t>Theme Parks, Shopping Malls, Archaeological Sites, Muse	<td><t>Guidance in theme parks, shopping malls, archaeological
	um guidance</t></td>	sites, and
		museums</t></td>
	</tr>	</tr>


	<tr>	<tr>

	<td> <t>Cloud-based Mobile XR applications</t></td>	<td><t>Cloud-based mobile XR applications</t></td>
	<td> <t>Less than 50 milliseconds</t></td>	<td><t>Less than 50 milliseconds</t></td>
	<td> <t>50 to 100 Mbps</t></td>	<td><t>50 to 100 Mbps</t></td>
	<td> <t>Google Live View, XR-enhanced Google Translate </t></td	<td><t>Google Live View, XR-enhanced Google Translate </t></td>
	>
	</tr>	</tr>


	</tbody>	</tbody>

	</table>	</table>

	</section>	</section>

	</section>	</section>

	<section anchor="conclusion" numbered="true" toc="default">	<section anchor="conclusion" numbered="true" toc="default">
	<name>Conclusion</name>	<name>Conclusion</name>
	<t>	<t>

	In order to operationalize a use case such as the one presented in th	In order to operationalize a use case such as the one presented in th
	is document, a network operator could dimension their network to provide a short	is document, a network operator could dimension their network to provide a short
	and high-capacity network path from the edge compute	and high-capacity network path from the edge computing
	resources or storage to the mobile devices running the XR application	resources or storage to the mobile devices running the XR application
	. This is required to ensure a response time of 20ms at most and preferably betw	. This is required to ensure a response time of 20 ms at most and preferably bet
	een 7-15ms. Additionally, a bandwidth of 200	ween 7-15 ms. Additionally, a bandwidth of 200
	to 1000Mbps is required by such applications. To deal with the charac	to 1000 Mbps is required by such applications. To deal with the chara
	teristics of XR traffic as discussed in this document, network operators could d	cteristics of XR traffic as discussed in this document, network operators could
	eploy a managed edge cloud service that operationally	deploy a managed edge cloud service that operationally
	provides dynamic placement of XR servers, mobility support and energy	provides dynamic placement of XR servers, mobility support, and energ
	management. Although the use case is technically feasible, economic viability i	y management. Although the use case is technically feasible, economic viability
	s an important factor that must be considered.	is an important factor that must be considered.

	</t>	</t>
	</section>	</section>

	<section anchor="iana" numbered="true" toc="default">	<section anchor="iana" numbered="true" toc="default">
	<name>IANA Considerations</name>	<name>IANA Considerations</name>
	<t>	<t>
	This document has no IANA actions.	This document has no IANA actions.

	</t>	</t>
	</section>	</section>

	<section anchor="Sec" numbered="true" toc="default">	<section anchor="Sec" numbered="true" toc="default">
	<name>Security Considerations</name>	<name>Security Considerations</name>

	<t>
	The security issues for the presented use case are similar to other s
	treaming applications <xref target="DIST" format="default"/>, <xref target="NIST
	1" format="default"/>, <xref target="CWE" format="default"/>, <xref target="NIST
	2" format="default"/>. This document itself introduces no new security issues.

	</t>

	</section>


	<section anchor="ack" numbered="true" toc="default">
	<name>Acknowledgements</name>
	<t>	<t>

	Many Thanks to Spencer Dawkins, Rohit Abhishek, Jake Holland, Kir	The security issues for the presented use case are similar to
	an Makhijani, Ali Begen, Cullen Jennings, Stephan Wenger, Eric Vyncke, Wesley Ed	those described in <xref target="DIST" format="default"/>, <xref
	dy, Paul Kyzivat, Jim Guichard, Roman Danyliw, Warren Kumari, and Zaheduzzaman S	target="NIST1" format="default"/>, <xref target="CWE"
	arker for providing very helpful feedback, suggestions and comments.	format="default"/>, and <xref target="NIST2"
		format="default"/>. This document does not introduce any new
		security issues.
	</t>	</t>


	</section>	</section>

	</middle>	</middle>
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	</author>	</author>


	<author initials="R." surname="Sherman" fullname="Robert Sherman">	<author initials="R." surname="Sherman" fullname="Robert Sherman">
	<organization/>	<organization/>
	</author>	</author>


	<author initials="D.V." surname="Wilson" fullname="Daniel V. Wilson">	<author initials="D.V." surname="Wilson" fullname="Daniel V. Wilson">
	<organization/>	<organization/>
	</author>	</author>

		<date month="February" year="1997"/>
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	</front>	</front>

	<seriesInfo name="In" value="IEEE/ACM Transactions on Networking, pp. 7	<refcontent>IEEE/ACM Transactions on Networking, vol. 5, no. 1, pp. 71-8
	1-86."/>	6</refcontent>
		<seriesInfo name="DOI" value="10.1109/90.554723"/>
	</reference>	</reference>


	<reference anchor="METRICS_4" target="">	<reference anchor="METRICS_4" target="https://www.sciencedirect.com/scienc e/article/pii/S1063520300903427">
	<front>	<front>

	<title> Multiscale Analysis and Data Networks.</title>	<title>Multiscale Analysis and Data Networks</title>
	<author initials="A.C." surname="Gilbert" fullname="A. C. Gilbert">	<author initials="A.C." surname="Gilbert" fullname="A.C. Gilbert">
	<organization/>	<organization/>
	</author>	</author>

		<date month="May" year="2001"/>
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	<seriesInfo name="In" value="Applied and Computational Harmonic Analysis	<refcontent>Applied and Computational Harmonic Analysis, vol. 10, no. 3,
	, pp. 185-202."/>	pp. 185-202</refcontent>
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	<reference anchor="METRICS_5" target="">	<reference anchor="METRICS_5" target="https://research.google/pubs/site-re liability-engineering-how-google-runs-production-systems/">
	<front>	<front>

	<title> Site Reliability Engineering: How Google Runs Production Syste	<title>Site Reliability Engineering: How Google Runs Production System
	ms.</title>	s</title>
	<author initials="B." surname="Beyer" fullname="Betsy Beyer">	<author initials="B." surname="Beyer" fullname="Betsy Beyer" role="edi
		tor">
	<organization/>	<organization/>
	</author>	</author>

		<author initials="C." surname="Jones" fullname="Chris Jones" role="edit
	<author initials="C." surname="Jones" fullname="Chris Jones">	or">
	<organization/>	<organization/>
	</author>	</author>

		<author initials="J." surname="Petoff" fullname="Jennifer Petoff" role=
	<author initials="J." surname="Petoff" fullname="Jennifer Petoff">	"editor">
	<organization/>	<organization/>
	</author>	</author>

		<author initials="N.R." surname="Murphy" fullname="Niall Richard Murphy
	<author initials="N.R." surname="Murphy" fullname="Niall Richard Murphy	" role="editor">
	">
	<organization/>	<organization/>
	</author>	</author>


	<date year="2016"/>	<date year="2016"/>
	</front>	</front>

	<seriesInfo name="" value="O'Reilly Media, Inc."/>	<refcontent>O'Reilly Media, Inc.</refcontent>
	</reference>	</reference>


	<reference anchor="METRICS_6" target="">	<reference anchor="METRICS_6" target="https://ieeexplore.ieee.org/document /9363323">
	<front>	<front>

	<title> A survey on mobile augmented reality with 5G mobile edge compu ting: architectures, applications, and technical aspects.</title>	<title>A Survey on Mobile Augmented Reality With 5G Mobile Edge Comput ing: Architectures, Applications, and Technical Aspects</title>
	<author initials="Y." surname="Siriwardhana" fullname="Yushan Siriward hana">	<author initials="Y." surname="Siriwardhana" fullname="Yushan Siriward hana">
	<organization/>	<organization/>
	</author>	</author>


	<author initials="P." surname="Porambage" fullname="Pawani Porambage">	<author initials="P." surname="Porambage" fullname="Pawani Porambage">
	<organization/>	<organization/>
	</author>	</author>


	<author initials="M." surname="Liyanage" fullname="Madhusanka Liyanage" >	<author initials="M." surname="Liyanage" fullname="Madhusanka Liyanage" >
	<organization/>	<organization/>
	</author>	</author>


	<author initials="M." surname="Ylianttila" fullname="Mika Ylianttila">	<author initials="M." surname="Ylianttila" fullname="Mika Ylianttila">
	<organization/>	<organization/>
	</author>	</author>


	<date year="2021"/>	<date year="2021"/>
	</front>	</front>

	<seriesInfo name="In" value="IEEE Communications Surveys and Tutorials,	<refcontent>IEEE Communications Surveys and Tutorials, vol. 23, no. 2, p
	Vol 23, No. 2"/>	p. 1160-1192</refcontent>
		<seriesInfo name="DOI" value="10.1109/COMST.2021.3061981"/>
	</reference>	</reference>


	<reference anchor="HEAVY_TAIL_3" target="">	<reference anchor="HEAVY_TAIL_3" target="https://www.wiley.com/en-us/A+Pri mer+in+Data+Reduction%3A+An+Introductory+Statistics+Textbook-p-9780471101352">
	<front>	<front>

	<title> A Primer in Data Reduction.</title>	<title>A Primer in Data Reduction: An Introductory Statistics Textbook </title>
	<author initials="A." surname="Ehrenberg" fullname="A.S.C Ehrenberg ">	<author initials="A." surname="Ehrenberg" fullname="A.S.C Ehrenberg ">
	<organization/>	<organization/>
	</author>	</author>

		<date year="2007"/>
	<date year="1982"/>
	</front>	</front>

	<seriesInfo name="John" value="Wiley, London"/>	<refcontent>John Wiley and Sons</refcontent>
	</reference>	</reference>


	<reference anchor="RFC9023" target="https://www.rfc-editor.org/info/rfc9023">	<xi:include href="https://bib.ietf.org/public/rfc/bibxml/reference.RFC.902
	<front>	3.xml"/>
	<title>Deterministic Networking (DetNet) Data Plane: IP over IEEE 802.1 Time-Sen	<xi:include href="https://bib.ietf.org/public/rfc/bibxml/reference.RFC.893
	sitive Networking (TSN)</title>	9.xml"/>
	<author fullname="B. Varga" initials="B." role="editor" surname="Varga"/>	<xi:include href="https://bib.ietf.org/public/rfc/bibxml/reference.RFC.945
	<author fullname="J. Farkas" initials="J." surname="Farkas"/>	0.xml"/>
	<author fullname="A. Malis" initials="A." surname="Malis"/>
	<author fullname="S. Bryant" initials="S." surname="Bryant"/>
	<date month="June" year="2021"/>
	<abstract>
	<t>This document specifies the Deterministic Networking IP data plane when opera
	ting over a Time-Sensitive Networking (TSN) sub-network. This document does not
	define new procedures or processes. Whenever this document makes statements or r
	ecommendations, these are taken from normative text in the referenced RFCs.</t>
	</abstract>
	</front>
	<seriesInfo name="RFC" value="9023"/>
	<seriesInfo name="DOI" value="10.17487/RFC9023"/>
	</reference>


	<reference anchor="RFC8939" target="https://www.rfc-editor.org/info/rfc8939">	<reference anchor="DIST" target="https://dl.acm.org/doi/10.5555/2029110">
	<front>	<front>
	<title>Deterministic Networking (DetNet) Data Plane: IP</title>	<title> Distributed Systems: Concepts and Design</title>
	<author fullname="B. Varga" initials="B." role="editor" surname="Varga"/>	<author initials="G" surname="Coulouris" fullname="George Coulouris">
	<author fullname="J. Farkas" initials="J." surname="Farkas"/>	<organization/>
	<author fullname="L. Berger" initials="L." surname="Berger"/>	</author>
	<author fullname="D. Fedyk" initials="D." surname="Fedyk"/>	<author initials="J" surname="Dollimore" fullname="Jean Dollimore">
	<author fullname="S. Bryant" initials="S." surname="Bryant"/>	<organization/>
	<date month="November" year="2020"/>	</author>
	<abstract>	<author initials="T" surname="Kindberg" fullname="Tim Kindberg">
	<t>This document specifies the Deterministic Networking (DetNet) data plane oper	<organization/>
	ation for IP hosts and routers that provide DetNet service to IP-encapsulated da	</author>
	ta. No DetNet-specific encapsulation is defined to support IP flows; instead, th	<author initials="G" surname="Blair" fullname="Gordon Blair">
	e existing IP-layer and higher-layer protocol header information is used to supp	<organization/>
	ort flow identification and DetNet service delivery. This document builds on the	</author>
	DetNet architecture (RFC 8655) and data plane framework (RFC 8938).</t>	<date year="2011"/>
	</abstract>	</front>
	</front>	<refcontent>Addison-Wesley</refcontent>
	<seriesInfo name="RFC" value="8939"/>	</reference>
	<seriesInfo name="DOI" value="10.17487/RFC8939"/>
	</reference>


	<reference anchor="RFC9450" target="https://www.rfc-editor.org/info/rfc9450">	<reference anchor="NIST1" target="https://csrc.nist.gov/pubs/sp/800/146/fi
	<front>	nal">
	<title>Reliable and Available Wireless (RAW) Use Cases</title>	<front>
	<author fullname="CJ. Bernardos" initials="CJ." role="editor" surname="Bernardos	<title>Cloud Computing Synopsis and Recommendations</title>
	"/>	<author>
	<author fullname="G. Papadopoulos" initials="G." surname="Papadopoulos"/>	<organization>NIST</organization>
	<author fullname="P. Thubert" initials="P." surname="Thubert"/>	</author>
	<author fullname="F. Theoleyre" initials="F." surname="Theoleyre"/>	<date month="May" year="2012"/>
	<date month="August" year="2023"/>	</front>
	<abstract>	<seriesInfo name="NIST SP" value="800-146"/>
	<t>The wireless medium presents significant specific challenges to achieve prope	<seriesInfo name="DOI" value="10.6028/NIST.SP.800-146"/>
	rties similar to those of wired deterministic networks. At the same time, a numb	</reference>
	er of use cases cannot be solved with wires and justify the extra effort of goin
	g wireless. This document presents wireless use cases (such as aeronautical comm
	unications, amusement parks, industrial applications, pro audio and video, gamin
	g, Unmanned Aerial Vehicle (UAV) and vehicle-to-vehicle (V2V) control, edge robo
	tics, and emergency vehicles), demanding reliable and available behavior.</t>
	</abstract>
	</front>
	<seriesInfo name="RFC" value="9450"/>
	<seriesInfo name="DOI" value="10.17487/RFC9450"/>
	</reference>


	<reference anchor="DIST" target="">	<reference anchor="CWE" target="https://www.sans.org/top25-software-errors
	<front>	/">
	<title> Distributed Systems: Concepts and Design</title>	<front>
	<author initials="G" surname="Coulouris" fullname="George Coulouris">	<title>CWE/SANS TOP 25 Most Dangerous Software Errors</title>
	<organization/>	<author>
	</author>	<organization>SANS Institute</organization>
	<author initials="J" surname="Dollimore" fullname="Jean Dollimore">	</author>
	<organization/>	</front>
	</author>	</reference>
	<author initials="T" surname="Kindberg" fullname="Tim Kindberg">
	<organization/>
	</author>
	<author initials="G" surname="Blair" fullname="Gordon Blair">
	<organization/>
	</author>
	<date year="2011"/>
	</front>
	<seriesInfo name="" value="Addison Wesley"/>
	</reference>
	<reference anchor="NIST1" target="">
	<front>
	<title> NIST SP 800-146: Cloud Computing Synopsis and Recommendations</title>
	<author initials="" surname="" fullname="NIST">
	<organization/>
	</author>
	<date year="2012"/>
	</front>
	<seriesInfo name="" value="National Institute of Standards and Technology, US De
	partment of Commerce"/>
	</reference>
	<reference anchor="CWE" target="">
	<front>
	<title> CWE/SANS TOP 25 Most Dangerous Software Errorss</title>
	<author initials="" surname="" fullname="SANS Institute">
	<organization/>
	</author>
	<date year="2012"/>
	</front>
	<seriesInfo name="" value="Common Weakness Enumeration, SANS Institute"/>
	</reference>
	<reference anchor="NIST2" target="">
	<front>
	<title> NIST SP 800-123: Guide to General Server Security</title>
	<author initials="" surname="" fullname="NIST">
	<organization/>
	</author>
	<date year="2008"/>
	</front>
	<seriesInfo name="" value="National Institute of Standards and Technology, US De
	partment of Commerce"/>
	</reference>


	<reference anchor="RFC2210" target="https://www.rfc-editor.org/info/rfc22	<reference anchor="NIST2" target="https://csrc.nist.gov/pubs/sp/800/123/fi
	10">	nal">
	<front>	<front>
	<title>The Use of RSVP with IETF Integrated Services</title>	<title>Guide to General Server Security</title>
	<author fullname="J. Wroclawski" initials="J." surname="Wroclawski"/>	<author>
	<date month="September" year="1997"/>	<organization>NIST</organization>
	<abstract>	</author>
	<t>This note describes the use of the RSVP resource reservation protocol with th	<date month="July" year="2008"/>
	e Controlled-Load and Guaranteed QoS control services. [STANDARDS-TRACK]</t>	</front>
	</abstract>	<seriesInfo name="NIST SP" value="800-123"/>
	</front>	<seriesInfo name="DOI" value="10.6028/NIST.SP.800-123"/>
	<seriesInfo name="RFC" value="2210"/>	</reference>
	<seriesInfo name="DOI" value="10.17487/RFC2210"/>
	</reference>


	<reference anchor="RFC2475" target="https://www.rfc-editor.org/info/rfc2475">	<xi:include href="https://bib.ietf.org/public/rfc/bibxml/reference.RFC.22
	<front>	10.xml"/>
	<title>An Architecture for Differentiated Services</title>	<xi:include href="https://bib.ietf.org/public/rfc/bibxml/reference.RFC.24
	<author fullname="S. Blake" initials="S." surname="Blake"/>	75.xml"/>
	<author fullname="D. Black" initials="D." surname="Black"/>
	<author fullname="M. Carlson" initials="M." surname="Carlson"/>	</references>
	<author fullname="E. Davies" initials="E." surname="Davies"/>
	<author fullname="Z. Wang" initials="Z." surname="Wang"/>	<section anchor="ack" numbered="false" toc="default">
	<author fullname="W. Weiss" initials="W." surname="Weiss"/>	<name>Acknowledgements</name>
	<date month="December" year="1998"/>	<t>Many thanks to <contact fullname="Spencer Dawkins"/>, <contact
	<abstract>	fullname="Rohit Abhishek"/>, <contact fullname="Jake Holland"/>,
	<t>This document defines an architecture for implementing scalable service diffe	<contact fullname="Kiran Makhijani"/>, <contact fullname="Ali
	rentiation in the Internet. This memo provides information for the Internet comm	Begen"/>, <contact fullname="Cullen Jennings"/>, <contact
	unity.</t>	fullname="Stephan Wenger"/>, <contact fullname="Eric Vyncke"/>,
	</abstract>	<contact fullname="Wesley Eddy"/>, <contact fullname="Paul Kyzivat"/>,
	</front>	<contact fullname="Jim Guichard"/>, <contact fullname="Roman
	<seriesInfo name="RFC" value="2475"/>	Danyliw"/>, <contact fullname="Warren Kumari"/>, and <contact
	<seriesInfo name="DOI" value="10.17487/RFC2475"/>	fullname="Zaheduzzaman Sarker"/> for providing helpful feedback,
	</reference>	suggestions, and comments.</t>
		</section>


	</references>
	</back>	</back>
	</rfc>	</rfc>

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