rfc9817v5.txt		rfc9817.txt
	skipping to change at line 497 ¶		skipping to change at line 497 ¶
	fog computing for local information processing, the edge for		fog computing for local information processing, the edge for
	aggregation, and the cloud for image processing.		aggregation, and the cloud for image processing.
	XR stands to benefit significantly from computing capabilities in the		XR stands to benefit significantly from computing capabilities in the
	network. For example, XR applications can offload intensive		network. For example, XR applications can offload intensive
	processing tasks to edge servers, considerably reducing latency when		processing tasks to edge servers, considerably reducing latency when
	compared to cloud-based applications and enhancing the overall user		compared to cloud-based applications and enhancing the overall user
	experience. More importantly, COIN can enable collaborative XR		experience. More importantly, COIN can enable collaborative XR
	experiences, where multiple users interact in the same virtual space		experiences, where multiple users interact in the same virtual space
	in real time, regardless of their physical locations, by allowing		in real time, regardless of their physical locations, by allowing
	resource discovery and re-rerouting of XR streams. While not a		resource discovery and re-routing of XR streams. While not a feature
	feature of most XR implementations, this capability opens up new		of most XR implementations, this capability opens up new
	possibilities for remote collaboration, training, and entertainment.		possibilities for remote collaboration, training, and entertainment.
	Furthermore, COIN can support dynamic content delivery, allowing XR		Furthermore, COIN can support dynamic content delivery, allowing XR
	applications to seamlessly adapt to changing environments and user		applications to seamlessly adapt to changing environments and user
	interactions. Hence, the integration of computing capabilities into		interactions. Hence, the integration of computing capabilities into
	the network architecture enhances the scalability, flexibility, and		the network architecture enhances the scalability, flexibility, and
	performance of XR applications by supplying telemetry and advanced		performance of XR applications by supplying telemetry and advanced
	stream management, paving the way for more immersive and interactive		stream management, paving the way for more immersive and interactive
	experiences.		experiences.
	Indeed, XR applications require real-time interactivity for immersive		Indeed, XR applications require real-time interactivity for immersive
	skipping to change at line 526 ¶		skipping to change at line 526 ¶
	3.2.2. Characterization		3.2.2. Characterization
	As mentioned above, XR experiences, especially those involving		As mentioned above, XR experiences, especially those involving
	collaboration, are difficult to deliver with a client-server cloud-		collaboration, are difficult to deliver with a client-server cloud-
	based solution. This is because they require a combination of		based solution. This is because they require a combination of
	multistream aggregation, low delays and delay variations, means to		multistream aggregation, low delays and delay variations, means to
	recover from losses, and optimized caching and rendering as close as		recover from losses, and optimized caching and rendering as close as
	possible to the user at the network edge. Hence, implementing such		possible to the user at the network edge. Hence, implementing such
	XR solutions necessitates substantial computational power and minimal		XR solutions necessitates substantial computational power and minimal
	latency, which, for now, has spurred the development of better		latency, which, for now, has spurred the development of better
	headsets not networked or distributed solutions as factors like		headsets, rather than spurring networked or distributed solutions, as
	distance from cloud servers and limited bandwidth can still		factors like distance from cloud servers and limited bandwidth can
	significantly lower application responsiveness. Furthermore, when XR		still significantly lower application responsiveness. Furthermore,
	deals with sensitive information, XR applications must also provide a		when XR deals with sensitive information, XR applications must also
	secure environment and ensure user privacy, which represent		provide a secure environment and ensure user privacy, which represent
	additional burdens for delay-sensitive applications. Additionally,		additional burdens for delay-sensitive applications. Additionally,
	the sheer amount of data needed for and generated by XR applications,		the sheer amount of data needed for and generated by XR applications,
	such as video holography, put them squarely in the realm of data-		such as video holography, put them squarely in the realm of data-
	driven applications that can use recent trend analysis and		driven applications that can use recent trend analysis and
	mechanisms, as well as machine learning, in order to find the optimal		mechanisms, as well as machine learning, in order to find the optimal
	caching and processing solution and ideally reduce the size of the		caching and processing solution and ideally reduce the size of the
	data that needs transiting through the network. Other mechanisms,		data that needs transiting through the network. Other mechanisms,
	such as data filtering and reduction, and functional distribution and		such as data filtering and reduction, and functional distribution and
	partitioning, are also needed to accommodate the low delay needs for		partitioning, are also needed to accommodate the low delay needs for
	the same applications.		the same applications.
	skipping to change at line 593 ¶		skipping to change at line 593 ¶
	The XR field has profited from extensive research in the past years		The XR field has profited from extensive research in the past years
	in gaming, machine learning, network telemetry, high resolution		in gaming, machine learning, network telemetry, high resolution
	imaging, smart cities, and the Internet of Things (IoT).		imaging, smart cities, and the Internet of Things (IoT).
	Information-Centric Networking (ICN) (and related) approaches that		Information-Centric Networking (ICN) (and related) approaches that
	combine, publish, subscribe, and distribute storage are also very		combine, publish, subscribe, and distribute storage are also very
	suited for the multisource-multidestination applications of XR. New		suited for the multisource-multidestination applications of XR. New
	AR and VR headsets and glasses have continued to evolve towards		AR and VR headsets and glasses have continued to evolve towards
	autonomy with local computation capabilities, increasingly performing		autonomy with local computation capabilities, increasingly performing
	much of the processing that is needed to render and augment the local		much of the processing that is needed to render and augment the local
	images. Mechanisms aimed at enhancing the computational and storage		images. Mechanisms aimed at enhancing the computational and storage
	capacities of mobile devices could also improve XR capabilities as		capacities of mobile devices could also improve XR capabilities, as
	they include the discovery of available servers within the		they include discovering available servers within the environment and
	environment and using them opportunistically to enhance the		using them opportunistically to enhance the performance of
	performance of interactive applications and distributed file systems.		interactive applications and distributed file systems.
	While there is still no specific COIN research in AR and VR, the need		While there is still no specific COIN research in AR and VR, the need
	for network support is important to offload some of the computations		for network support is important to offload some of the computations
	related to movement, multiuser interactions, and networked		related to movement, multiuser interactions, and networked
	applications, notably in gaming but also in health [NetworkedVR].		applications, notably in gaming but also in health [NetworkedVR].
	This new approach to networked AR and VR is exemplified in [eCAR] by		This new approach to networked AR and VR is exemplified in [eCAR] by
	using synchronized messaging at the edge to share the information		using synchronized messaging at the edge to share the information
	that all users need to interact. In [CompNet2021] and		that all users need to interact. In [CompNet2021] and
	[WirelessNet2024], the offloading uses Artificial Intelligence (AI)		[WirelessNet2024], the offloading uses Artificial Intelligence (AI)
	to assign the 5G resources necessary for the real-time interactions,		to assign the 5G resources necessary for the real-time interactions,
	skipping to change at line 623 ¶		skipping to change at line 623 ¶
	In summary, some XR solutions exist, and headsets continue to evolve		In summary, some XR solutions exist, and headsets continue to evolve
	to what is now claimed to be spatial computing. Additionally, with		to what is now claimed to be spatial computing. Additionally, with
	recent work on the metaverse, the number of publications related to		recent work on the metaverse, the number of publications related to
	XR has skyrocketed. However, in terms of networking, which is the		XR has skyrocketed. However, in terms of networking, which is the
	focus of this document, current deployments do not take advantage of		focus of this document, current deployments do not take advantage of
	network capabilities. The information is rendered and displayed		network capabilities. The information is rendered and displayed
	based on the local processing but does not readily discover the other		based on the local processing but does not readily discover the other
	elements in the vicinity or in the network that could improve its		elements in the vicinity or in the network that could improve its
	performance either locally, at the edge, or in the cloud. Yet, there		performance either locally, at the edge, or in the cloud. Yet, there
	are still very few interactive and immersive media applications over		are still very few interactive and immersive media applications over
	networks that allow for federating systems capabilities.		networks that allow for the federation of systems capabilities.
	3.2.4. Opportunities		3.2.4. Opportunities
	While delay is inherently related to information transmission, if we		While delay is inherently related to information transmission, if we
	continue the analogy of the computer board to highlight some of the		continue the analogy of the computer board to highlight some of the
	COIN capabilities in terms of computation and storage but also		COIN capabilities in terms of computation and storage but also
	allocation of resources, there are some opportunities that XR could		allocation of resources, there are some opportunities that XR could
	take advantage of:		take advantage of:
	* Round trip time: 20 ms is usually cited as an upper limit for XR		* Round trip time: 20 ms is usually cited as an upper limit for XR
	skipping to change at line 672 ¶		skipping to change at line 672 ¶
	* RQ 3.2.1: Can current PNDs provide the speed required for		* RQ 3.2.1: Can current PNDs provide the speed required for
	executing complex filtering operations, including metadata		executing complex filtering operations, including metadata
	analysis for complex and dynamic scene rendering?		analysis for complex and dynamic scene rendering?
	* RQ 3.2.2: Where should PNDs equipped with these operations be		* RQ 3.2.2: Where should PNDs equipped with these operations be
	located for optimal performance gains?		located for optimal performance gains?
	* RQ 3.2.3: Can the use of distributed AI algorithms across both		* RQ 3.2.3: Can the use of distributed AI algorithms across both
	data center and edge computers be leveraged for creating optimal		data center and edge computers be leveraged for creating optimal
	function allocation and the creation of semi-permanent datasets		function allocation? Can the creation of semi-permanent datasets
	and analytics for usage trending and flow management resulting in		and analytics for usage trending and flow management result in
	better localization of XR functions?		better localization of XR functions?
	* RQ 3.2.4: Can COIN improve the dynamic distribution of control,		* RQ 3.2.4: Can COIN improve the dynamic distribution of control,
	forwarding, and storage resources and related usage models in XR,		forwarding, and storage resources and related usage models in XR,
	such as to integrate local and fog caching with cloud-based pre-		such as to integrate local and fog caching with cloud-based pre-
	rendering, thus jointly optimizing COIN and higher layer protocols		rendering? Could this jointly optimize COIN and higher layer
	to reduce latency and, more generally, manage the quality of XR		protocols to reduce latency and, more generally, manage the
	sessions (e.g., through reduced in-network congestion and improved		quality of XR sessions (e.g., through reduced in-network
	flow delivery by determining how to prioritize XR data)?		congestion and improved flow delivery by determining how to
			prioritize XR data)?
	* RQ 3.2.5: Can COIN provide the necessary infrastructure for the		* RQ 3.2.5: Can COIN provide the necessary infrastructure for the
	use of interactive XR everywhere? Particularly, how can a COIN		use of interactive XR everywhere? Particularly, how can a COIN
	system enable the joint collaboration across all segments of the		system enable the joint collaboration across all segments of the
	network (fog, edge, core, and cloud) to support functional		network (fog, edge, core, and cloud) to support functional
	decompositions, including using edge resources without the need		decompositions, including using edge resources without the need
	for a (remote) cloud connection?		for a (remote) cloud connection?
	* RQ 3.2.6: How can COIN systems provide multistream efficient		* RQ 3.2.6: How can COIN systems provide multistream efficient
	transmission and stream combining at the edge, including the		transmission and stream combining at the edge, including the
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