rfc9556v4.txt | rfc9556.txt | |||
---|---|---|---|---|
skipping to change at line 14 ¶ | skipping to change at line 14 ¶ | |||
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 | April 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 centralized 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 | |||
skipping to change at line 165 ¶ | skipping to change at line 165 ¶ | |||
energy consumption, security, and privacy [Lin]. Some, less- | energy consumption, security, and privacy [Lin]. Some, less- | |||
resource-constrained Things, can generate a voluminous amount of | resource-constrained Things, can generate a voluminous amount of | |||
data. This range of factors led to IoT designs that integrate Things | data. This range of factors led to IoT designs that integrate Things | |||
into larger distributed systems, for example, edge or cloud computing | into larger distributed systems, for example, edge or cloud computing | |||
systems. | systems. | |||
2.2. Cloud Computing | 2.2. Cloud Computing | |||
Cloud computing has been defined in [NIST]: | Cloud computing has been defined in [NIST]: | |||
| cloud computing is a model for enabling ubiquitous, convenient, | | Cloud computing is a model for enabling ubiquitous, convenient, | |||
| on-demand network access to a shared pool of configurable | | on-demand network access to a shared pool of configurable | |||
| computing resources (e.g., networks, servers, storage, | | computing resources (e.g., networks, servers, storage, | |||
| applications, and services) that can be rapidly provisioned and | | applications, and services) that can be rapidly provisioned and | |||
| released with minimal management effort or service provider | | released with minimal management effort or service provider | |||
| interaction. | | interaction. | |||
The low cost and massive availability of storage and processing power | The low cost and massive availability of storage and processing power | |||
enabled the realization of another computing model in which | enabled the realization of another computing model in which | |||
virtualized resources can be leased in an on-demand fashion and | virtualized resources can be leased in an on-demand fashion and | |||
provided as general utilities. Platform-as-a-Service (PaaS) and | provided as general utilities. Platform-as-a-Service (PaaS) and | |||
skipping to change at line 294 ¶ | skipping to change at line 294 ¶ | |||
reduce the cost of failure through preliminary measures. In the | reduce the cost of failure through preliminary measures. In the | |||
existing manufacturing field, production facilities are manually | existing manufacturing field, production facilities are manually | |||
run according to a program entered in advance; however, edge | run according to a program entered in advance; however, edge | |||
computing in a smart factory enables tailoring solutions by | computing in a smart factory enables tailoring solutions by | |||
analyzing data at each production facility and machine level. | analyzing data at each production facility and machine level. | |||
Digital twins [Jones] of IoT devices have been jointly used with | Digital twins [Jones] of IoT devices have been jointly used with | |||
edge computing in industrial IoT scenarios [Chen]. | edge computing in industrial IoT scenarios [Chen]. | |||
*Smart Grid* | *Smart Grid* | |||
In future smart-city scenarios, the smart grid will be critical in | In future smart-city scenarios, the smart grid will be critical in | |||
ensuring highly available/efficient energy control in city-wide | ensuring highly available and efficient energy control in city- | |||
electricity management [Mehmood]. Edge computing is expected to | wide electricity management [Mehmood]. Edge computing is expected | |||
play a significant role in these systems to improve the | to play a significant role in these systems to improve the | |||
transmission efficiency of electricity, to react to and restore | transmission efficiency of electricity, to react to and restore | |||
power after a disturbance, to reduce operation costs, and to reuse | power after a disturbance, to reduce operation costs, and to reuse | |||
energy effectively since these operations involve local decision- | energy effectively since these operations involve local decision- | |||
making. In addition, edge computing can help monitor power | making. In addition, edge computing can help monitor power | |||
generation and power demand and make local electrical energy | generation and power demand and make local electrical energy | |||
storage decisions in smart grid systems. | storage decisions in smart grid systems. | |||
*Smart Agriculture* | *Smart Agriculture* | |||
Smart agriculture integrates information and communication | Smart agriculture integrates information and communication | |||
technologies with farming technology. Intelligent farms use IoT | technologies with farming technology. Intelligent farms use IoT | |||
skipping to change at line 328 ¶ | skipping to change at line 328 ¶ | |||
to cloud servers that process data and recommend actions. The use | to cloud servers that process data and recommend actions. The use | |||
of edge computing can reduce the volume of back-and-forth data | of edge computing can reduce the volume of back-and-forth data | |||
transmissions significantly, resulting in cost and bandwidth | transmissions significantly, resulting in cost and bandwidth | |||
savings. Locally generated data can be processed at the edge, and | savings. Locally generated data can be processed at the edge, and | |||
local computing and analytics can drive local actions. With edge | local computing and analytics can drive local actions. With edge | |||
computing, it is easy for farmers to select large amounts of data | computing, it is easy for farmers to select large amounts of data | |||
for processing, and data can be analyzed even in remote areas with | for processing, and data can be analyzed even in remote areas with | |||
poor access conditions. Other applications include enabling | poor access conditions. Other applications include enabling | |||
dashboarding, for example, to visualize the farm status, as well | dashboarding, for example, to visualize the farm status, as well | |||
as enhancing Extended Reality (XR) applications that require edge | as enhancing Extended Reality (XR) applications that require edge | |||
audio/video processing. As the number of people working on | audio and/or video processing. As the number of people working on | |||
farming has been decreasing over time, increasing automation | farming has been decreasing over time, increasing automation | |||
enabled by edge computing can be a driving force for future smart | enabled by edge computing can be a driving force for future smart | |||
agriculture [OGrady]. | agriculture [OGrady]. | |||
*Smart Construction* | *Smart Construction* | |||
Safety is critical at construction sites. Every year, many | Safety is critical at construction sites. Every year, many | |||
construction workers lose their lives because of falls, | construction workers lose their lives because of falls, | |||
collisions, electric shocks, and other accidents [BigRentz]. | collisions, electric shocks, and other accidents [BigRentz]. | |||
Therefore, solutions have been developed to improve construction | Therefore, solutions have been developed to improve construction | |||
site safety, including the real-time identification of workers, | site safety, including the real-time identification of workers, | |||
skipping to change at line 410 ¶ | skipping to change at line 410 ¶ | |||
With edge computing, real-time data is collected, processed, and | With edge computing, real-time data is collected, processed, and | |||
analyzed directly at the edge, allowing for the accurate | analyzed directly at the edge, allowing for the accurate | |||
monitoring and simulation of physical assets. Moreover, edge | monitoring and simulation of physical assets. Moreover, edge | |||
computing effectively minimizes latency, enabling rapid responses | computing effectively minimizes latency, enabling rapid responses | |||
to dynamic conditions as computational resources are brought | to dynamic conditions as computational resources are brought | |||
closer to the physical object. Running digital twin processing at | closer to the physical object. Running digital twin processing at | |||
the edge enables organizations to obtain timely insights and make | the edge enables organizations to obtain timely insights and make | |||
informed decisions that maximize efficiency and performance. | informed decisions that maximize efficiency and performance. | |||
*Other Use Cases* | *Other Use Cases* | |||
Artificial intelligence (AI) / machine learning (ML) systems at | Artificial intelligence (AI) and machine learning (ML) systems at | |||
the edge empower real-time analysis, faster decision-making, | the edge empower real-time analysis, faster decision-making, | |||
reduced latency, improved operational efficiency, and personalized | reduced latency, improved operational efficiency, and personalized | |||
experiences across various industries by bringing AI and ML | experiences across various industries by bringing AI and ML | |||
capabilities closer to edge devices. | capabilities closer to edge devices. | |||
In addition, oneM2M has studied several IoT edge computing use | In addition, oneM2M has studied several IoT edge computing use | |||
cases, which are documented in [oneM2M-TR0001], [oneM2M-TR0018], | cases, which are documented in [oneM2M-TR0001], [oneM2M-TR0018], | |||
and [oneM2M-TR0026]. The edge-computing-related requirements | and [oneM2M-TR0026]. The edge-computing-related requirements | |||
raised through the analysis of these use cases are captured in | raised through the analysis of these use cases are captured in | |||
[oneM2M-TS0002]. | [oneM2M-TS0002]. | |||
skipping to change at line 624 ¶ | skipping to change at line 624 ¶ | |||
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 centralized 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 and sensors, handling IoT data, and delivering | |||
data to its final destination in a cloud network. An IoT gateway | IoT data to its final destination in a cloud network. An IoT | |||
requires interactions with the cloud; however, it can also operate | gateway requires interactions with the cloud; however, it can also | |||
independently in a disconnected mode. | operate 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 | |||
in such distributed systems owing to advances in hardware | in such distributed systems owing to advances in hardware | |||
technology. In this model, edge computing nodes can collaborate | technology. In this model, edge computing nodes can collaborate | |||
to share resources. | to share resources. | |||
* A hybrid system involving both IoT gateways and supporting | * A hybrid system involving both IoT gateways and supporting | |||
functions in distributed computing nodes. | functions in distributed computing nodes. | |||
In the general model described in Figure 1, the edge computing domain | In the general model described in Figure 1, the edge computing domain | |||
is interconnected with IoT devices (southbound connectivity), | is interconnected with IoT devices (southbound connectivity), | |||
possibly with a remote/cloud network (northbound connectivity), and | possibly with a remote (e.g., cloud) network (northbound | |||
with a service operator's system. Edge computing nodes provide | connectivity), and with a service operator's system. Edge computing | |||
multiple logical functions or components that may not be present in a | nodes provide multiple logical functions or components that may not | |||
given system. They may be implemented in a centralized or | be present in a given system. They may be implemented in a | |||
distributed fashion, at the network edge, or through interworking | centralized or distributed fashion, at the network edge, or through | |||
between the edge network and remote cloud networks. | interworking between the edge network and remote cloud networks. | |||
+---------------------+ | +---------------------+ | |||
| Remote Network | +---------------+ | | Remote Network | +---------------+ | |||
|(e.g., cloud network)| | Service | | |(e.g., cloud network)| | Service | | |||
+-----------+---------+ | Operator | | +-----------+---------+ | Operator | | |||
| +------+--------+ | | +------+--------+ | |||
| | | | | | |||
+--------------+-------------------+-----------+ | +--------------+-------------------+-----------+ | |||
| Edge Computing Domain | | | Edge Computing Domain | | |||
| | | | | | |||
skipping to change at line 693 ¶ | skipping to change at line 693 ¶ | |||
| End | | End | ... |Node/End| | | End | | End | ... |Node/End| | |||
|Device 1| |Device 2| ...| |Device n| | | |Device 1| |Device 2| ...| |Device n| | | |||
+--------+ +--------+ +--------+ | +--------+ +--------+ +--------+ | |||
+ - - - - - - - -+ | + - - - - - - - -+ | |||
Figure 1: Model of IoT Edge Computing | Figure 1: Model of IoT Edge Computing | |||
In the distributed model described in Figure 2, the edge computing | In the distributed model described in Figure 2, the edge computing | |||
domain is composed of IoT edge gateways and IoT devices that are also | domain is composed of IoT edge gateways and IoT devices that are also | |||
used as computing nodes. Edge computing domains are connected to a | used as computing nodes. Edge computing domains are connected to a | |||
remote/cloud network and their respective service operator's system. | remote (e.g., cloud) network and their respective service operator's | |||
IoT devices/computing nodes provide logical functions, for example, | system. The computing nodes provide logical functions, for example, | |||
as part of distributed machine learning or distributed image | as part of distributed machine learning or distributed image | |||
processing applications. The processing capabilities in IoT devices | processing applications. The processing capabilities in IoT devices | |||
are limited; they require the support of other nodes. In a | are limited; they require the support of other nodes. In a | |||
distributed machine learning application, the training process for AI | distributed machine learning application, the training process for AI | |||
services can be executed at IoT edge gateways or cloud networks, and | services can be executed at IoT edge gateways or cloud networks, and | |||
the prediction (inference) service is executed in the IoT devices. | the prediction (inference) service is executed in the IoT devices. | |||
Similarly, in a distributed image processing application, some image | Similarly, in a distributed image processing application, some image | |||
processing functions can be executed at the edge or in the cloud. To | processing functions can be executed at the edge or in the cloud. To | |||
limit the amount of data to be uploaded to central cloud functions, | limit the amount of data to be uploaded to central cloud functions, | |||
IoT edge devices may pre-process data. | IoT edge devices may pre-process data. | |||
skipping to change at line 833 ¶ | skipping to change at line 833 ¶ | |||
* Support for scaling and enabling fault tolerance or self-healing | * Support for scaling and enabling fault tolerance or self-healing | |||
[Jeong]. In addition to using a hierarchical organization to cope | [Jeong]. In addition to using a hierarchical organization to cope | |||
with scaling, another available and possibly complementary | with scaling, another available and possibly complementary | |||
mechanism is multicast [RFC7390] [CORE-GROUPCOMM-BIS]. Other | mechanism is multicast [RFC7390] [CORE-GROUPCOMM-BIS]. Other | |||
approaches include relying on blockchains [Ali]. | approaches include relying on blockchains [Ali]. | |||
* Integration of edge computing with virtualized Radio Access | * Integration of edge computing with virtualized Radio Access | |||
Networks (Fog RAN) [SFC-FOG-RAN] and 5G access networks. | Networks (Fog RAN) [SFC-FOG-RAN] and 5G access networks. | |||
* Sharing resources in multi-vendor/operator scenarios to optimize | * Sharing resources in multi-vendor and multi-operator scenarios to | |||
criteria such as profit [Anglano], resource usage, latency, and | optimize criteria such as profit [Anglano], resource usage, | |||
energy consumption. | latency, and energy consumption. | |||
* Capacity planning, placement of infrastructure nodes to minimize | * Capacity planning, placement of infrastructure nodes to minimize | |||
delay [Fan], cost, energy, etc. | delay [Fan], cost, energy, etc. | |||
* Incentives for participation, for example, in peer-to-peer | * Incentives for participation, for example, in peer-to-peer | |||
federation schemes. | federation schemes. | |||
* Design of federated AI over IoT edge computing systems [Brecko], | * Design of federated AI over IoT edge computing systems [Brecko], | |||
for example, for anomaly detection. | for example, for anomaly detection. | |||
skipping to change at line 895 ¶ | skipping to change at line 895 ¶ | |||
and from a network node. [Cloudlets] describes an example of | and from a network node. [Cloudlets] describes an example of | |||
offloading computation from an end device to a network node. In | offloading computation from an end device to a network node. In | |||
contrast, oneM2M is an example of a system that allows a cloud-based | contrast, oneM2M is an example of a system that allows a cloud-based | |||
IoT platform to transfer resources and tasks to a target edge node | IoT platform to transfer resources and tasks to a target edge node | |||
[oneM2M-TR0052]. Once transferred, the edge node can directly | [oneM2M-TR0052]. Once transferred, the edge node can directly | |||
support IoT devices that it serves with the service offloaded by the | support IoT devices that it serves with the service offloaded by the | |||
cloud (e.g., group management, location management, etc.). | cloud (e.g., group management, location management, etc.). | |||
QoS can be provided in some systems through the combination of | QoS can be provided in some systems through the combination of | |||
network QoS (e.g., traffic engineering or wireless resource | network QoS (e.g., traffic engineering or wireless resource | |||
scheduling) and compute/storage resource allocations. For example, | scheduling) and compute and storage resource allocations. For | |||
in some systems, a bandwidth manager service can be exposed to enable | example, in some systems, a bandwidth manager service can be exposed | |||
allocation of the bandwidth to/from an edge computing application | to enable allocation of the bandwidth to or from an edge computing | |||
instance. | application instance. | |||
In-network computation can leverage the underlying services provided | In-network computation can leverage the underlying services provided | |||
using data generated by IoT devices and access networks. Such | using data generated by IoT devices and access networks. Such | |||
services include IoT device location, radio network information, | services include IoT device location, radio network information, | |||
bandwidth management, and congestion management (e.g., the congestion | bandwidth management, and congestion management (e.g., the congestion | |||
management feature of oneM2M [oneM2M-TR0052]). | management feature of oneM2M [oneM2M-TR0052]). | |||
Related challenges include: | Related challenges include: | |||
* Computation placement: in a centralized or distributed/peer-to- | * Computation placement: in a centralized or distributed (e.g., | |||
peer manner, selecting an appropriate compute device. The | peer-to-peer) manner, selecting an appropriate compute device. | |||
selection is based on available resources, location of data input | The selection is based on available resources, location of data | |||
and data sinks, compute node properties, etc. with varying goals. | input and data sinks, compute node properties, etc. with varying | |||
These goals include end-to-end latency, privacy, high | goals. These goals include end-to-end latency, privacy, high | |||
availability, energy conservation, or network efficiency (for | availability, energy conservation, or network efficiency (for | |||
example, using load-balancing techniques to avoid congestion). | example, using load-balancing techniques to avoid congestion). | |||
* Onboarding code on a platform or computing device and invoking | * Onboarding code on a platform or computing device and invoking | |||
remote code execution, possibly as part of a distributed | remote code execution, possibly as part of a distributed | |||
programming model and with respect to similar concerns of latency, | programming model and with respect to similar concerns of latency, | |||
privacy, etc. For example, offloading can be included in a | privacy, etc. For example, offloading can be included in a | |||
vehicular scenario [Grewe]. These operations should deal with | vehicular scenario [Grewe]. These operations should deal with | |||
heterogeneous compute nodes [Schafer] and may also support end | heterogeneous compute nodes [Schafer] and may also support end | |||
devices, including IoT devices, as compute nodes [Larrea]. | devices, including IoT devices, as compute nodes [Larrea]. | |||
skipping to change at line 966 ¶ | skipping to change at line 966 ¶ | |||
system. | system. | |||
Related challenges include: | Related challenges include: | |||
* Cache and data placement: using cache positioning and data | * Cache and data placement: using cache positioning and data | |||
placement strategies to minimize data retrieval delay [Liu] and | placement strategies to minimize data retrieval delay [Liu] and | |||
energy consumption. Caches may be positioned in the access- | energy consumption. Caches may be positioned in the access- | |||
network infrastructure or on end devices. | network infrastructure or on end devices. | |||
* Maintaining consistency, freshness, reliability, and privacy of | * Maintaining consistency, freshness, reliability, and privacy of | |||
stored/cached data in systems that are distributed, constrained, | data stored or cached in systems that are distributed, | |||
and dynamic (e.g., due to node mobility, energy-saving regimes, | constrained, and dynamic (e.g., due to node mobility, energy- | |||
and disruptions) and which can have additional data governance | saving regimes, and disruptions) and which can have additional | |||
constraints on data storage location. For example, [Mortazavi] | data governance constraints on data storage location. For | |||
describes leveraging a hierarchical storage organization. | example, [Mortazavi] describes leveraging a hierarchical storage | |||
Freshness-related metrics include the age of information [Yates] | organization. Freshness-related metrics include the age of | |||
that captures the timeliness of information received from a sender | information [Yates] that captures the timeliness of information | |||
(e.g., an IoT device). | received from a sender (e.g., an IoT device). | |||
4.4.3. Communication | 4.4.3. Communication | |||
An edge cloud may provide a northbound data plane or management plane | An edge cloud may provide a northbound data plane or management plane | |||
interface to a remote network, such as a cloud, home, or enterprise | interface to a remote network, such as a cloud, home, or enterprise | |||
network. This interface does not exist in stand-alone (local-only) | network. This interface does not exist in stand-alone (local-only) | |||
scenarios. To support such an interface when it exists, an edge | scenarios. To support such an interface when it exists, an edge | |||
computing component needs to expose an API, deal with authentication | computing component needs to expose an API, deal with authentication | |||
and authorization, and support secure communication. | and authorization, and support secure communication. | |||
An edge cloud may provide an API or interface to local or mobile | An edge cloud may provide an API or interface to local or mobile | |||
users, for example, to provide access to services and applications or | users, for example, to provide access to services and applications or | |||
to manage data published by local/mobile devices. | to manage data published by local or mobile devices. | |||
Edge computing nodes communicate with IoT devices over a southbound | Edge computing nodes communicate with IoT devices over a southbound | |||
interface, typically for data acquisition and IoT device management. | interface, typically for data acquisition and IoT device management. | |||
Communication brokering is a typical function of IoT edge computing | Communication brokering is a typical function of IoT edge computing | |||
that facilitates communication with IoT devices, enables clients to | that facilitates communication with IoT devices, enables clients to | |||
register as recipients for data from devices, forwards traffic to or | register as recipients for data from devices, forwards traffic to or | |||
from IoT devices, enables various data discovery and redistribution | from IoT devices, enables various data discovery and redistribution | |||
patterns (for example, north-south with clouds and east-west with | patterns (for example, north-south with clouds and east-west with | |||
other edge devices [EDGE-DATA-DISCOVERY-OVERVIEW]). Another related | other edge devices [EDGE-DATA-DISCOVERY-OVERVIEW]). Another related | |||
skipping to change at line 1031 ¶ | skipping to change at line 1031 ¶ | |||
Section 2.4. While describing the components of individual | Section 2.4. While describing the components of individual | |||
applications is out of our scope, some of those applications share | applications is out of our scope, some of those applications share | |||
similar functions, such as IoT device management and data management, | similar functions, such as IoT device management and data management, | |||
as described below. | as described below. | |||
4.5.1. IoT Device Management | 4.5.1. IoT Device Management | |||
IoT device management includes managing information regarding IoT | IoT device management includes managing information regarding IoT | |||
devices, including their sensors and how to communicate with them. | devices, including their sensors and how to communicate with them. | |||
Edge computing addresses the scalability challenges of a large number | Edge computing addresses the scalability challenges of a large number | |||
of IoT devices by separating the scalability domain into edge/local | of IoT devices by separating the scalability domain into local (e.g., | |||
networks and remote networks. For example, in the context of the | edge) networks and remote networks. For example, in the context of | |||
oneM2M standard, a device management functionality (called "software | the oneM2M standard, a device management functionality (called | |||
campaign" in oneM2M) enables the installation, deletion, activation, | "software campaign" in oneM2M) enables the installation, deletion, | |||
and deactivation of software functions/services on a potentially | activation, and deactivation of software functions and services on a | |||
large number of edge nodes [oneM2M-TR0052]. Using a dashboard or | potentially large number of edge nodes [oneM2M-TR0052]. Using a | |||
management software, a service provider issues these requests through | dashboard or management software, a service provider issues these | |||
an IoT cloud platform supporting the software campaign functionality. | requests through an IoT cloud platform supporting the software | |||
campaign functionality. | ||||
The challenges listed in Section 4.3.1 may be applicable to IoT | The challenges listed in Section 4.3.1 may be applicable to IoT | |||
device management as well. | device management as well. | |||
4.5.2. Data Management and Analytics | 4.5.2. Data Management and Analytics | |||
Data storage and processing at the edge are major aspects of IoT edge | Data storage and processing at the edge are major aspects of IoT edge | |||
computing, directly addressing the high-level IoT challenges listed | computing, directly addressing the high-level IoT challenges listed | |||
in Section 3. Data analysis, for example, through AI/ML tasks | in Section 3. Data analysis, for example, through AI/ML tasks | |||
performed at the edge, may benefit from specialized hardware support | performed at the edge, may benefit from specialized hardware support | |||
End of changes. 14 change blocks. | ||||
48 lines changed or deleted | 49 lines changed or added | |||
This html diff was produced by rfcdiff 1.48. |