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Li 7 Huawei 8 March 9, 2020 10 Use cases of Application-aware Networking (APN) in Edge Computing 11 draft-liu-apn-edge-usecase-00 13 Abstract 15 The ever-emerging new services are imposing more and more highly 16 demanding requirements on the network. However, the current 17 deployments could not fully accommodate those requirements due to 18 limited capabilities. For example, it is difficult to utilize the 19 traditional centralized deployment mode to meet the low-latency 20 demand of some latency-sensitive applications. Moreover, the total 21 amount of centralized service data is growing exponentially, which 22 brings great pressure on the network bandwidth. There has been a 23 clear trend that decentralized sites comprising of computing and 24 storage resources are deployed at various locations to provide 25 services. In particular, when the sites are deployed at the network 26 edge, i.e. the Edge Computing, it can better handle the business 27 needs of the users nearby, which provides the possibilities to 28 provide differentiated network and computing services. In order to 29 achieve the full benefits of the edge computing, it actually implies 30 a precondition that the network should be aware of the applications' 31 requirements in order to steer their traffic to the network paths 32 that can satisfy their requirements. Application-aware networking 33 (APN) fits as the missing puzzle piece to bridge the applications and 34 the network to accommodate the edge services' needs, fully releasing 35 the benefits of the edge computing. 37 This document describes the various application scenarios in edge 38 computing to which the APN can be beneficial, including augmented 39 reality, cloud gaming and remote control, which empowers the video 40 business, users interaction business and user-device interaction 41 business. In those scenarios, APN can identify the specific 42 requirements of edge computing applications on the network, process 43 close to the users, provide SLA guaranteed network services such as 44 low latency and high reliability. 46 Requirements Language 48 The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", 49 "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this 50 document are to be interpreted as described in RFC 2119 [RFC2119]. 52 Status of This Memo 54 This Internet-Draft is submitted in full conformance with the 55 provisions of BCP 78 and BCP 79. 57 Internet-Drafts are working documents of the Internet Engineering 58 Task Force (IETF). Note that other groups may also distribute 59 working documents as Internet-Drafts. The list of current Internet- 60 Drafts is at https://datatracker.ietf.org/drafts/current/. 62 Internet-Drafts are draft documents valid for a maximum of six months 63 and may be updated, replaced, or obsoleted by other documents at any 64 time. It is inappropriate to use Internet-Drafts as reference 65 material or to cite them other than as "work in progress." 67 This Internet-Draft will expire on September 10, 2020. 69 Copyright Notice 71 Copyright (c) 2020 IETF Trust and the persons identified as the 72 document authors. All rights reserved. 74 This document is subject to BCP 78 and the IETF Trust's Legal 75 Provisions Relating to IETF Documents 76 (https://trustee.ietf.org/license-info) in effect on the date of 77 publication of this document. Please review these documents 78 carefully, as they describe your rights and restrictions with respect 79 to this document. Code Components extracted from this document must 80 include Simplified BSD License text as described in Section 4.e of 81 the Trust Legal Provisions and are provided without warranty as 82 described in the Simplified BSD License. 84 Table of Contents 86 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3 87 2. Usage Scenarios of APN in edge computing . . . . . . . . . . 3 88 2.1. Augmented Reality (AR) . . . . . . . . . . . . . . . . . 4 89 2.1.1. Use Case Description . . . . . . . . . . . . . . . . 4 90 2.1.2. Augmented Reality Today . . . . . . . . . . . . . . . 4 91 2.1.3. Augmented Reality with Edge Computing and APN . . . . 4 92 2.2. Cloud Gaming . . . . . . . . . . . . . . . . . . . . . . 5 93 2.2.1. Use Case Description . . . . . . . . . . . . . . . . 5 94 2.2.2. Cloud Gaming Today . . . . . . . . . . . . . . . . . 6 95 2.2.3. Cloud Gaming with Edge Computing and APN . . . . . . 6 96 2.3. Remote control of industry . . . . . . . . . . . . . . . 7 97 2.3.1. Use Case Description . . . . . . . . . . . . . . . . 7 98 2.3.2. Remote control of industry Today . . . . . . . . . . 8 99 2.3.3. Remote control of industry with Edge Computing and 100 APN . . . . . . . . . . . . . . . . . . . . . . . . . 8 101 3. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 10 102 4. Security Considerations . . . . . . . . . . . . . . . . . . . 10 103 5. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 10 104 6. Normative References . . . . . . . . . . . . . . . . . . . . 10 105 Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 11 107 1. Introduction 109 Edge computing is to deploy service sites near the user side to 110 provide users with better network and computing services. The 111 services of edge computing can not only be implemented in the edge 112 data center, but also be integrated in the network equipment, which 113 brings the possibility for the convergence of network and computing, 114 and also puts forward the requirements for the technology combining 115 of different industries. On the one hand, the demand of different 116 applications for the network need to be exposed; on the other hand, 117 the network needs to be aware of computing power and steers the 118 traffic along the appropriate path towards the suitable sites. 120 The existing network can only identify the application demands in a 121 coarse granularity. When the application demand is high causing the 122 heavy network load, it usually fails to guarantee the latency and 123 reliability of the applications especially the mission-critical 124 applications. Application-aware networking (APN) is to solve the 125 problem of mutual recognition between network and application. APN 126 enables the network to be aware of the applications' requirements in 127 a fine granularity, and then either steer the corresponding traffic 128 onto the appropriate network path (if exist) that can satisfy these 129 requirements or establish an exclusive network path which wouldn't be 130 influenced by other applications' traffic flow. 132 2. Usage Scenarios of APN in edge computing 134 This section presents several typical scenarios which require edge 135 computing to interconnect and to co-ordinate with APN to meet the 136 service requirements and ensure user experience. 138 2.1. Augmented Reality (AR) 140 2.1.1. Use Case Description 142 Augmented reality is a relatively new application that promotes the 143 integration of real world information and virtual world information 144 content. It includes several technologies, such as track 145 registration, display, virtual object generation, interaction and 146 merging. 148 2.1.2. Augmented Reality Today 150 AR gives users an immersive experience. It is widely used in the 151 consumer industry presently, and may also be applied in industrial 152 fields such as health care and education in the future.The general 153 process of AR / VR is as follows: 155 * Image acquisition equipment (such as camera) collects image or 156 video information and sends it to data center. 158 * Data center carries out identification, feature extraction and 159 template rendering, and sends them to AR terminal. 161 * The AR terminal plays the synthesized information. 163 Considering the user experience, AR usually needs a high bandwidth of 164 100mbps due to multi-channel acquisition of image or video data, and 165 a low end-to-end latency less than 60ms. With centralized 166 deployment, the network transmission distance is too long, so the 167 latency demand can't be met; the large volume of traffic load also 168 imposes high challenge on the network bandwidth. 170 2.1.3. Augmented Reality with Edge Computing and APN 172 If the deployment mode of edge computing is adopted, the following 173 functions can be realized: 175 * The collected image or video information can be encoded/decode and 176 compressed by the edge equipment to reduce the bandwidth requirements 177 of data transmission. 179 * The edge data center can process the collected image or video data 180 nearby and send it to the AR terminal equipment, which reduces the 181 distance of network transmission and greatly reduces the latency. 183 Although edge computing can reduce the overall latency of services 184 and reduce the demand for network bandwidth, it still needs 185 differentiated network services to provide the ultimate guarantee for 186 application with high SLA requirements. APN can achieve: 188 * Edge device obtains and encapsulates AR application feature 189 information and sends it to the head end node. 191 * Head end node in the APN identifies the AR data flow and steers it 192 into a specific transmission path according to the demanded 193 bandwidth, latency and reliability. 195 * Mid point in the APN forwards the data stream along the specific 196 path. 198 * End point in the APN receives AR data stream and forwards it either 199 to Data Centre for processing or to the AR player for playing. 201 In the whole process, because APN identifies the traffic of AR 202 application, it can provide corresponding network services to provide 203 customized high reliability, low latency and other SLA guarantee. 205 +------+ Camera +------+ 206 |Source| ->| AR | 207 |data |-\ / |Player| 208 +------+| +-----+ +-------+ +---------+ +-------+ / +------+ 209 \->|App- | | APN | | Edge | | APN |-/ 210 |aware|-->| |-->| Data |-->| | 211 /->|Edge | |Network| | Center | |Network|-\ 212 +------+ | +-----+ +-------+ +---------+ +-------+ \ +------+ 213 |Source|-/ \ | AR | 214 |data | ->|Player| 215 +------+ Camera +------+ 217 Augmented Reality with Edge Computing and APN 219 2.2. Cloud Gaming 221 2.2.1. Use Case Description 223 Cloud gaming is to deploy the game application in the data center, 224 and realize the functions includes the logical process of game 225 command control, as well as the tasks of game acceleration, video 226 rendering and other tasks with high requirements for chips. In this 227 way, the terminal is a video player. Users can get a good game 228 experience without the support of high-end system and chips. 230 Compared with the traditional game mode, there are several advantages 231 of cloud game, such as no installation, no upgrade, no repair, quick 232 to play and reduce the terminal cost, so it will have stronger 233 promotion. 235 2.2.2. Cloud Gaming Today 237 The biggest feature of cloud games is that users interact with each 238 other through the network. The general process is as follows: 240 * The data center sends game video streaming information to the 241 terminal, including game background picture, characters, etc. 243 * The user makes corresponding operation instructions according to 244 the received game video stream information and sends them to the data 245 center. 247 * The data center constantly updates the video stream and other data 248 of the game according to the user's operation instructions. 250 Game users usually pursue consumption experience. Currently, most 251 users are willing to spend extra money in order to obtain better user 252 experience. Generally speaking, the network latency of game is 253 required to be less than 30ms. For competitive game, the latency 254 will be required to be less than 10ms, because professional players 255 usually can feel the millisecond level latency difference. With 256 centralized deployment, the network transmission distance is too 257 long, which is a huge challenge to the network load, so the latency 258 demand can't be met; the large volume of traffic load also imposes 259 high challenge on the network bandwidth. 261 2.2.3. Cloud Gaming with Edge Computing and APN 263 If the deployment of edge computing is adopted, the following 264 functions can be realized with the deployment of edge data center: 266 * The edge data center sends the game video stream information to the 267 terminal, and receives the user's control instruction information for 268 processing. 270 * users can make corresponding operation instructions according to 271 the received video stream information, and get quick response. 273 Edge computing can reduce the latency of game data transmission as a 274 whole, but it should be noted that cloud games usually have multiple 275 players playing a game together, which requires the deterministic 276 latency of multi-party network path, which needs to be realized with 277 APN: 279 * Multiple edge devices obtain and encapsulate cloud game application 280 feature information and send it to the head end node. 282 * Head end node in the APN identifies the data flow of cloud games 283 (maybe the same game), and steers it into a specific transmission 284 path according to its requirements for bandwidth, delay, reliability, 285 etc., which needs to ensure that the latency of multi-user control 286 instructions arriving at the edge data center is consistent. 288 * Mid point in the APN forwards game data stream according to the 289 predetermined path. 291 * The end point in the APN receives the cloud game data stream and 292 steers it either to the data center for processing the users' control 293 instruction or to the user for playing. 295 The whole process requires APN not only to identify the cloud game 296 traffic and provide customized network forwarding services for it, 297 but also to ensure the deterministic latency of multi-user in the 298 same game and provide better game experience. 300 Client A 301 +---------+ 302 |Game data| 303 +---------+-\ +----------+ +-----------+ +-----------+ 304 |<->|App-aware |-A-| APN |-A-| | 305 | Edge A | | Network A | | | 306 +----------+ +-----------+ | Edge Data | 307 +----------+ +-----------+ | Center | 308 |App-aware | | APN | | | 309 |<->| Edge B |-B-| Network B |-B-| | 310 +---------+-/ +----------+ +-----------+ +-----------+ 311 |Game data| 312 +---------+ 313 Client B 315 Cloud Gaming with Edge Computing and APN 317 2.3. Remote control of industry 319 2.3.1. Use Case Description 321 Industrial remote control refers to the remote control of field 322 equipment in areas that are not convenient for manual field control, 323 such as high-temperature and high-risk areas. In the past, signaling 324 was usually transmitted through industrial private networks and 325 protocols. With the development of industrial Internet, the industry 326 also gradually has the demand of network interconnection. Its 327 network tends to adopt L3 protocol and flat architecture, which makes 328 it possible for cross distance remote control service. 330 2.3.2. Remote control of industry Today 332 In the process of remote control, workers constantly make control 333 instructions according to the received image or video information of 334 field equipment, which requires interaction between personnel and 335 equipment through the network. Because the field environment that 336 needs remote control is generally poor, it is also a challenge for 337 the security of the operation equipment. If the latency is too large 338 or the reliability is not enough, it may cause the operation failure, 339 equipment damage and other serious consequences. Therefore, the 340 remote control service requires low latency and high reliability. 341 The general process of remote control is as follows: 343 * Field equipment (such as camera) collects image or video 344 information and sends it to data center. 346 * The data center receives the field information of the equipment and 347 sends it to the workers in the office. 349 * Workers send control instructions and control equipment according 350 to the received field information. 352 Many industrial enterprises rent public cloud resources to construct 353 their own data center, but the long distance of network transmission 354 is not conducive to the timely transmission of image / video data 355 stream, which will cause large latency and packet loss. 357 2.3.3. Remote control of industry with Edge Computing and APN 359 If the deployment mode of edge computing is adopted, and the data 360 center and edge computing access equipment (such as gateway) are 361 deployed in a location or enterprise park close to the business site, 362 the following functions can be realized: 364 * The collected image or video information can be encoded/ decoded 365 and compressed by edge access equipment to reduce the bandwidth 366 requirements. 368 * The control instruction information can be identified by the edge 369 equipment, so as to provide exclusive network transmission service. 371 * The forwarding path of image / video and control information is 372 shortened, which can greatly reduce the latency. 374 Although edge computing can reduce the overall delay of services and 375 reduce the demand of network bandwidth, it still needs to achieve 376 differentiated network services through APN to provide the ultimate 377 network guarantee for the services with the highest network 378 requirements. 380 For users, APN can realize those functions. 382 * Edge device obtains and encapsulates the image or video information 383 of the remote field device, then sends it to the head end node. 385 * Head end in the APN identifies the information and steers the flow 386 into a specific transmission path according to its requirements for 387 bandwidth, delay, reliability, etc.. 389 * Mid point in the APN forwards along the specific path. 391 * End point receives image or video data stream of field equipment 392 and forwards it to users. 394 For field equipment, APN can realize those functions. 396 * Edge device obtains and encapsulates the control instruction 397 information and sends it to the head end node. 399 * Head end in the APN identifies the control data flow and steers 400 into a specific transmission path according to the demand for 401 bandwidth, latency and reliability. 403 * Mid point in the APN forwards along the specific path. 405 * End point receives control information and forwards to the field 406 equipment. 408 In the whole process, APN identifies the traffic of remote control 409 service, which can provide customized high reliability, low latency 410 and other network guarantee. 412 Worker 413 +------------+ 414 |Control data| 415 +------------+-\ +----------+ +-----------+ +-----------+ 416 |<->|App-aware |-W->| APN |-W->| | 417 | Edge A |<-C-| Network A |<-C-| | 418 +----------+ +-----------+ | Edge Data | 419 +----------+ +-----------+ | Center | 420 |App-aware |-C->| APN |-C->| | 421 Camera |<->| Edge B |<-W-| Network B |<-W-| | 422 +------------+-/ +----------+ +-----------+ +-----------+ 423 | Video data | 424 +------------+ 425 On-site Device 427 Remote control of industry with Edge Computing and APN 429 3. Conclusion 431 APN is able to identify the traffic of specific application, and 432 provide low latency and high reliability network services in various 433 edge computing scenarios such as AR, cloud gaming, remote industrial 434 control, etc.. 436 4. Security Considerations 438 TBD. 440 5. IANA Considerations 442 TBD. 444 6. Normative References 446 [I-D.li-apn-framework] 447 Li, Z., Peng, S., Voyer, D., Li, C., Geng, L., Cao, C., 448 Ebisawa, K., Previdi, S., and J. Guichard, "Application- 449 aware Networking (APN) Framework", draft-li-apn- 450 framework-00 (work in progress), March 2020. 452 [I-D.li-apn-problem-statement-usecases] 453 Li, Z., Peng, S., Voyer, D., Xie, C., Liu, P., Qin, Z., 454 Ebisawa, K., Previdi, S., and J. Guichard, "Problem 455 Statement and Use Cases of Application-aware Networking 456 (APN)", draft-li-apn-problem-statement-usecases-00 (work 457 in progress), March 2020. 459 [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate 460 Requirement Levels", BCP 14, RFC 2119, 461 DOI 10.17487/RFC2119, March 1997, 462 . 464 Authors' Addresses 466 Peng Liu 467 China Mobile 468 Beijing 100053 469 China 471 Email: liupengyjy@chinamobile.com 473 Liang Geng 474 China Mobile 475 Beijing 100053 476 China 478 Email: gengliang@chinamobile.com 480 Shuping Peng 481 Huawei 482 Beijing 100053 483 China 485 Email: pengshuping@huawei.com 487 Zhenbin Li 488 Huawei 489 Beijing 100053 490 China 492 Email: lizhenbin@huawei.com