rfc9556v2.txt		rfc9556.txt
	Internet Research Task Force (IRTF) J. Hong		Internet Research Task Force (IRTF) J. Hong
	Request for Comments: 9556 ETRI		Request for Comments: 9556 ETRI
	Category: Informational Y.-G. Hong		Category: Informational Y-G. Hong
	ISSN: 2070-1721 Daejeon University		ISSN: 2070-1721 Daejeon University
	X. de Foy		X. de Foy
	InterDigital Communications, LLC		InterDigital Communications, LLC
	M. Kovatsch		M. Kovatsch
	Huawei Technologies Duesseldorf GmbH		Huawei Technologies Duesseldorf GmbH
	E. Schooler		E. Schooler
	University of Oxford		University of Oxford
	D. Kutscher		D. Kutscher
	HKUST(GZ)		HKUST(GZ)
	March 2024		March 2024
	Internet of Things (IoT) Edge Challenges and Functions		Internet of Things (IoT) Edge Challenges and Functions
	Abstract		Abstract
	Many Internet of Things (IoT) applications have requirements that		Many Internet of Things (IoT) applications have requirements that
	cannot be satisfied by traditional cloud-based systems (i.e., cloud		cannot be satisfied by centralized cloud-based systems (i.e., cloud
	computing). These include time sensitivity, data volume,		computing). These include time sensitivity, data volume,
	connectivity cost, operation in the face of intermittent services,		connectivity cost, operation in the face of intermittent services,
	privacy, and security. As a result, IoT is driving the Internet		privacy, and security. As a result, IoT is driving the Internet
	toward edge computing. This document outlines the requirements of		toward edge computing. This document outlines the requirements of
	the emerging IoT edge and its challenges. It presents a general		the emerging IoT edge and its challenges. It presents a general
	model and major components of the IoT edge to provide a common basis		model and major components of the IoT edge to provide a common basis
	for future discussions in the Thing-to-Thing Research Group (T2TRG)		for future discussions in the Thing-to-Thing Research Group (T2TRG)
	and other IRTF and IETF groups. This document is a product of the		and other IRTF and IETF groups. This document is a product of the
	IRTF T2TRG.		IRTF T2TRG.
	skipping to change at line 531 ¶		skipping to change at line 531 ¶
	[EDGE-COMPUTING-BACKGROUND].		[EDGE-COMPUTING-BACKGROUND].
	IoT gateways, both open-source (such as EdgeX Foundry or Home Edge)		IoT gateways, both open-source (such as EdgeX Foundry or Home Edge)
	and proprietary products, represent a common class of IoT edge		and proprietary products, represent a common class of IoT edge
	computing products, where the gateway provides a local service on		computing products, where the gateway provides a local service on
	customer premises and is remotely managed through a cloud service.		customer premises and is remotely managed through a cloud service.
	IoT communication protocols are typically used between IoT devices		IoT communication protocols are typically used between IoT devices
	and the gateway, including a Constrained Application Protocol (CoAP)		and the gateway, including a Constrained Application Protocol (CoAP)
	[RFC7252], Message Queuing Telemetry Transport (MQTT) [MQTT5], and		[RFC7252], Message Queuing Telemetry Transport (MQTT) [MQTT5], and
	many specialized IoT protocols (such as Open Platform Communications		many specialized IoT protocols (such as Open Platform Communications
	Unified Architecture (OPC UA) and Discovery Domain Set (DDS) in the		Unified Architecture (OPC UA) and Data Distribution Service (DDS) in
	industrial IoT space), while the gateway communicates with the		the industrial IoT space), while the gateway communicates with the
	distant cloud typically using HTTPS. Virtualization platforms enable		distant cloud typically using HTTPS. Virtualization platforms enable
	the deployment of virtual edge computing functions (using Virtual		the deployment of virtual edge computing functions (using Virtual
	Machines (VMs) and application containers), including IoT gateway		Machines (VMs) and application containers), including IoT gateway
	software, on servers in the mobile network infrastructure (at base		software, on servers in the mobile network infrastructure (at base
	stations and concentration points), edge data centers (in central		stations and concentration points), edge data centers (in central
	offices), and regional data centers located near central offices.		offices), and regional data centers located near central offices.
	End devices are envisioned to become computing devices in forward-		End devices are envisioned to become computing devices in forward-
	looking projects but are not commonly used at the time of writing.		looking projects but are not commonly used at the time of writing.
	In addition to open-source and proprietary solutions, a horizontal		In addition to open-source and proprietary solutions, a horizontal
	skipping to change at line 596 ¶		skipping to change at line 596 ¶
	distributed storage such as that provided by a distributed storage		distributed storage such as that provided by a distributed storage
	platform (e.g., EdgeFS and Ceph) or, in more experimental settings,		platform (e.g., EdgeFS and Ceph) or, in more experimental settings,
	by an Information-Centric Networking (ICN) network, for example,		by an Information-Centric Networking (ICN) network, for example,
	systems such as Chipmunk [Chipmunk] and Kua [Kua] have been proposed		systems such as Chipmunk [Chipmunk] and Kua [Kua] have been proposed
	as distributed information-centric objects stores. External storage,		as distributed information-centric objects stores. External storage,
	for example, on databases in a distant or local IT cloud, is		for example, on databases in a distant or local IT cloud, is
	typically used for filtered data deemed worthy of long-term storage;		typically used for filtered data deemed worthy of long-term storage;
	although, in some cases, it may be for all data, for example, when		although, in some cases, it may be for all data, for example, when
	required for regulatory reasons.		required for regulatory reasons.
	Stateful computing is supported on platforms that host native		Stateful computing is the default on most systems, VMs, and
	programs, VMs, or containers. Stateless computing is supported on		containers. Stateless computing is supported on platforms providing
	platforms providing a "serverless computing" service (also known as		a "serverless computing" service (also known as function-as-
	function-as-a-service, e.g., using stateless containers) or on		a-service, e.g., using stateless containers) or on systems based on
	systems based on named function networking.		named function networking.
	In many IoT use cases, a typical network usage pattern is a high-		In many IoT use cases, a typical network usage pattern is a high-
	volume uplink with some form of traffic reduction enabled by		volume uplink with some form of traffic reduction enabled by
	processing over edge computing devices. Alternatives to traffic		processing over edge computing devices. Alternatives to traffic
	reduction include deferred transmission (to off-peak hours or using		reduction include deferred transmission (to off-peak hours or using
	physical shipping). Downlink traffic includes application control		physical shipping). Downlink traffic includes application control
	and software updates. Downlink-heavy traffic patterns are not		and software updates. Downlink-heavy traffic patterns are not
	excluded but are more often associated with non-IoT usage (e.g.,		excluded but are more often associated with non-IoT usage (e.g.,
	video Content Delivery Networks (CDNs)).		video Content Delivery Networks (CDNs)).
	4.2. General Model		4.2. General Model
	Edge computing is expected to play an important role in deploying new		Edge computing is expected to play an important role in deploying new
	IoT services integrated with big data and AI enabled by flexible in-		IoT services integrated with big data and AI enabled by flexible in-
	network computing platforms. Although there are many approaches to		network computing platforms. Although there are many approaches to
	edge computing, this section lays out an attempt at a general model		edge computing, this section lays out an attempt at a general model
	and lists associated logical functions. In practice, this model can		and lists associated logical functions. In practice, this model can
	be mapped to different architectures, such as:		be mapped to different architectures, such as:
	* A single IoT gateway, or a hierarchy of IoT gateways, typically		* A single IoT gateway, or a hierarchy of IoT gateways, typically
	connected to the cloud (e.g., to extend the traditional cloud-		connected to the cloud (e.g., to extend the centralized cloud-
	based management of IoT devices and data to the edge). The IoT		based management of IoT devices and data to the edge). The IoT
	gateway plays a common role in providing access to a heterogeneous		gateway plays a common role in providing access to a heterogeneous
	set of IoT devices/sensors, handling IoT data, and delivering IoT		set of IoT devices/sensors, handling IoT data, and delivering IoT
	data to its final destination in a cloud network. An IoT gateway		data to its final destination in a cloud network. An IoT gateway
	requires interactions with the cloud; however, it can also operate		requires interactions with the cloud; however, it can also operate
	independently in a disconnected mode.		independently in a disconnected mode.
	* A set of distributed computing nodes, for example, embedded in		* A set of distributed computing nodes, for example, embedded in
	switches, routers, edge cloud servers, or mobile devices. Some		switches, routers, edge cloud servers, or mobile devices. Some
	IoT devices have sufficient computing capabilities to participate		IoT devices have sufficient computing capabilities to participate
	skipping to change at line 1117 ¶		skipping to change at line 1117 ¶
	accessible MEC sandbox work recently initiated in ETSI [ETSI_Sandbox]		accessible MEC sandbox work recently initiated in ETSI [ETSI_Sandbox]
	and open-source simulators and emulators ([AdvantEDGE] emulator and		and open-source simulators and emulators ([AdvantEDGE] emulator and
	tools cited in [SimulatingFog]). EdgeNet [Senel] is a globally		tools cited in [SimulatingFog]). EdgeNet [Senel] is a globally
	distributed edge cloud for Internet researchers, which uses nodes		distributed edge cloud for Internet researchers, which uses nodes
	contributed by institutions and which is based on Docker for		contributed by institutions and which is based on Docker for
	containerization and Kubernetes for deployment and node management.		containerization and Kubernetes for deployment and node management.
	Digital twins are virtual instances of a physical system (twin) that		Digital twins are virtual instances of a physical system (twin) that
	are continually updated with the latter's performance, maintenance,		are continually updated with the latter's performance, maintenance,
	and health status data throughout the life cycle of the physical		and health status data throughout the life cycle of the physical
	system [Madni]. In contrast to a traditional emulation or simulated		system [Madni]. In contrast to an emulation or simulated
	environment, digital twins, once generated, are maintained in sync by		environment, digital twins, once generated, are maintained in sync by
	their physical twin, which can be, among many other instances, an IoT		their physical twin, which can be, among many other instances, an IoT
	device, edge device, or an edge network. The benefits of digital		device, edge device, or an edge network. The benefits of digital
	twins go beyond those of emulation and include accelerated business		twins go beyond those of emulation and include accelerated business
	processes, enhanced productivity, and faster innovation with reduced		processes, enhanced productivity, and faster innovation with reduced
	costs [NETWORK-DIGITAL-TWIN-ARCH].		costs [NETWORK-DIGITAL-TWIN-ARCH].
	5. Security Considerations		5. Security Considerations
	Privacy and security are drivers of the adoption of edge computing		Privacy and security are drivers of the adoption of edge computing
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