idnits 2.17.1 draft-ietf-raw-use-cases-01.txt: Checking boilerplate required by RFC 5378 and the IETF Trust (see https://trustee.ietf.org/license-info): ---------------------------------------------------------------------------- No issues found here. Checking nits according to https://www.ietf.org/id-info/1id-guidelines.txt: ---------------------------------------------------------------------------- No issues found here. Checking nits according to https://www.ietf.org/id-info/checklist : ---------------------------------------------------------------------------- ** The document seems to lack a both a reference to RFC 2119 and the recommended RFC 2119 boilerplate, even if it appears to use RFC 2119 keywords. RFC 2119 keyword, line 301: '...echnologies is a MUST in tackling this...' Miscellaneous warnings: ---------------------------------------------------------------------------- == The copyright year in the IETF Trust and authors Copyright Line does not match the current year -- The document date (February 22, 2021) is 1159 days in the past. Is this intentional? -- Found something which looks like a code comment -- if you have code sections in the document, please surround them with '' and '' lines. Checking references for intended status: Proposed Standard ---------------------------------------------------------------------------- (See RFCs 3967 and 4897 for information about using normative references to lower-maturity documents in RFCs) == Outdated reference: A later version (-16) exists of draft-ietf-detnet-security-13 == Outdated reference: A later version (-14) exists of draft-ietf-raw-ldacs-06 Summary: 1 error (**), 0 flaws (~~), 3 warnings (==), 2 comments (--). Run idnits with the --verbose option for more detailed information about the items above. -------------------------------------------------------------------------------- 2 RAW G. Papadopoulos 3 Internet-Draft IMT Atlantique 4 Intended status: Standards Track P. Thubert 5 Expires: August 26, 2021 Cisco 6 F. Theoleyre 7 CNRS 8 CJ. Bernardos 9 UC3M 10 February 22, 2021 12 RAW use cases 13 draft-ietf-raw-use-cases-01 15 Abstract 17 The wireless medium presents significant specific challenges to 18 achieve properties similar to those of wired deterministic networks. 19 At the same time, a number of use cases cannot be solved with wires 20 and justify the extra effort of going wireless. This document 21 presents wireless use cases demanding reliable and available 22 behavior. 24 Status of This Memo 26 This Internet-Draft is submitted in full conformance with the 27 provisions of BCP 78 and BCP 79. 29 Internet-Drafts are working documents of the Internet Engineering 30 Task Force (IETF). Note that other groups may also distribute 31 working documents as Internet-Drafts. The list of current Internet- 32 Drafts is at https://datatracker.ietf.org/drafts/current/. 34 Internet-Drafts are draft documents valid for a maximum of six months 35 and may be updated, replaced, or obsoleted by other documents at any 36 time. It is inappropriate to use Internet-Drafts as reference 37 material or to cite them other than as "work in progress." 39 This Internet-Draft will expire on August 26, 2021. 41 Copyright Notice 43 Copyright (c) 2021 IETF Trust and the persons identified as the 44 document authors. All rights reserved. 46 This document is subject to BCP 78 and the IETF Trust's Legal 47 Provisions Relating to IETF Documents 48 (https://trustee.ietf.org/license-info) in effect on the date of 49 publication of this document. Please review these documents 50 carefully, as they describe your rights and restrictions with respect 51 to this document. Code Components extracted from this document must 52 include Simplified BSD License text as described in Section 4.e of 53 the Trust Legal Provisions and are provided without warranty as 54 described in the Simplified BSD License. 56 Table of Contents 58 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3 59 2. Aeronautical Communications . . . . . . . . . . . . . . . . . 5 60 2.1. Problem Statement . . . . . . . . . . . . . . . . . . . . 5 61 2.2. Specifics . . . . . . . . . . . . . . . . . . . . . . . . 5 62 2.3. Challenges . . . . . . . . . . . . . . . . . . . . . . . 6 63 2.4. The Need for Wireless . . . . . . . . . . . . . . . . . . 7 64 2.5. Requirements for RAW . . . . . . . . . . . . . . . . . . 7 65 3. Amusement Parks . . . . . . . . . . . . . . . . . . . . . . . 7 66 3.1. Use Case Description . . . . . . . . . . . . . . . . . . 7 67 3.2. Specifics . . . . . . . . . . . . . . . . . . . . . . . . 8 68 3.3. The Need for Wireless . . . . . . . . . . . . . . . . . . 8 69 3.4. Requirements for RAW . . . . . . . . . . . . . . . . . . 9 70 4. Wireless for Industrial Applications . . . . . . . . . . . . 9 71 4.1. Use Case Description . . . . . . . . . . . . . . . . . . 9 72 4.2. Specifics . . . . . . . . . . . . . . . . . . . . . . . . 10 73 4.2.1. Control Loops . . . . . . . . . . . . . . . . . . . . 10 74 4.2.2. Unmeasured Data . . . . . . . . . . . . . . . . . . . 10 75 4.3. The Need for Wireless . . . . . . . . . . . . . . . . . . 11 76 4.4. Requirements for RAW . . . . . . . . . . . . . . . . . . 11 77 5. Pro Audio and Video . . . . . . . . . . . . . . . . . . . . . 12 78 5.1. Use Case Description . . . . . . . . . . . . . . . . . . 12 79 5.2. Specifics . . . . . . . . . . . . . . . . . . . . . . . . 12 80 5.2.1. Uninterrupted Stream Playback . . . . . . . . . . . . 12 81 5.2.2. Synchronized Stream Playback . . . . . . . . . . . . 12 82 5.3. The Need for Wireless . . . . . . . . . . . . . . . . . . 12 83 5.4. Requirements for RAW . . . . . . . . . . . . . . . . . . 13 84 6. Wireless Gaming . . . . . . . . . . . . . . . . . . . . . . . 13 85 6.1. Use Case Description . . . . . . . . . . . . . . . . . . 13 86 6.2. Specifics . . . . . . . . . . . . . . . . . . . . . . . . 14 87 6.3. The Need for Wireless . . . . . . . . . . . . . . . . . . 14 88 6.4. Requirements for RAW . . . . . . . . . . . . . . . . . . 14 89 7. UAV platooning and control . . . . . . . . . . . . . . . . . 15 90 7.1. Use Case Description . . . . . . . . . . . . . . . . . . 15 91 7.2. Specifics . . . . . . . . . . . . . . . . . . . . . . . . 15 92 7.3. The Need for Wireless . . . . . . . . . . . . . . . . . . 15 93 7.4. Requirements for RAW . . . . . . . . . . . . . . . . . . 16 94 8. Edge Robotics control . . . . . . . . . . . . . . . . . . . . 16 95 8.1. Use Case Description . . . . . . . . . . . . . . . . . . 16 96 8.2. Specifics . . . . . . . . . . . . . . . . . . . . . . . . 17 97 8.3. The Need for Wireless . . . . . . . . . . . . . . . . . . 17 98 8.4. Requirements for RAW . . . . . . . . . . . . . . . . . . 17 99 9. Emergencies: Instrumented emergency vehicle . . . . . . . . . 17 100 9.1. Use Case Description . . . . . . . . . . . . . . . . . . 17 101 9.2. Specifics . . . . . . . . . . . . . . . . . . . . . . . . 18 102 9.3. The Need for Wireless . . . . . . . . . . . . . . . . . . 18 103 9.4. Requirements for RAW . . . . . . . . . . . . . . . . . . 18 104 10. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 19 105 11. Security Considerations . . . . . . . . . . . . . . . . . . . 19 106 12. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 19 107 13. Informative References . . . . . . . . . . . . . . . . . . . 19 108 Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 22 110 1. Introduction 112 Based on time, resource reservation, and policy enforcement by 113 distributed shapers, Deterministic Networking provides the capability 114 to carry specified unicast or multicast data streams for real-time 115 applications with extremely low data loss rates and bounded latency, 116 so as to support time-sensitive and mission-critical applications on 117 a converged enterprise infrastructure. 119 Deterministic Networking in the IP world is an attempt to eliminate 120 packet loss for a committed bandwidth while ensuring a worst case 121 end-to-end latency, regardless of the network conditions and across 122 technologies. It can be seen as a set of new Quality of Service 123 (QoS) guarantees of worst-case delivery. IP networks become more 124 deterministic when the effects of statistical multiplexing (jitter 125 and collision loss) are mostly eliminated. This requires a tight 126 control of the physical resources to maintain the amount of traffic 127 within the physical capabilities of the underlying technology, e.g., 128 by the use of time-shared resources (bandwidth and buffers) per 129 circuit, and/or by shaping and/or scheduling the packets at every 130 hop. 132 Key attributes of Deterministic Networking include: 134 o time synchronization on all the nodes, 136 o centralized computation of network-wide deterministic paths, 138 o multi-technology path with co-channel interference minimization, 140 o frame preemption and guard time mechanisms to ensure a worst-case 141 delay, and 143 o new traffic shapers within and at the edge to protect the network. 145 Wireless operates on a shared medium, and transmissions cannot be 146 fully deterministic due to uncontrolled interferences, including 147 self-induced multipath fading. RAW (Reliable and Available Wireless) 148 is an effort to provide Deterministic Networking Mechanisms on across 149 a path that include a wireless physical layer. Making Wireless 150 Reliable and Available is even more challenging than it is with 151 wires, due to the numerous causes of loss in transmission that add up 152 to the congestion losses and the delays caused by overbooked shared 153 resources. 155 The wireless and wired media are fundamentally different at the 156 physical level, and while the generic Problem Statement [RFC8557] for 157 DetNet applies to the wired as well as the wireless medium, the 158 methods to achieve RAW necessarily differ from those used to support 159 Time-Sensitive Networking over wires. 161 So far, Open Standards for Deterministic Networking have prevalently 162 been focused on wired media, with Audio/Video Bridging (AVB) and Time 163 Sensitive Networking (TSN) at the IEEE and DetNet [RFC8655] at the 164 IETF. But wires cannot be used in a number of cases, including 165 mobile or rotating devices, rehabilitated industrial buildings, 166 wearable or in-body sensory devices, vehicle automation and 167 multiplayer gaming. 169 Purpose-built wireless technologies such as [ISA100], which 170 incorporates IPv6, were developped and deployed to cope for the lack 171 of open standards, but they yield a high cost in OPEX and CAPEX and 172 are limited to very few industries, e.g., process control, concert 173 instruments or racing. 175 This is now changing [I-D.thubert-raw-technologies]: 177 o IMT-2020 has recognized Ultra-Reliable Low-Latency Communication 178 (URLLC) as a key functionality for the upcoming 5G. 180 o IEEE 802.11 has identified a set of real-applications 181 [ieee80211-rt-tig] which may use the IEEE802.11 standards. They 182 typically emphasize strict end-to-end delay requirements. 184 o The IETF has produced an IPv6 stack for IEEE Std. 802.15.4 185 TimeSlotted Channel Hopping (TSCH) and an architecture 186 [I-D.ietf-6tisch-architecture] that enables Reliable and Available 187 Wireless (RAW) on a shared MAC. 189 This draft extends the "Deterministic Networking Use Cases" document 190 [RFC8578] and describes a number of additional use cases which 191 require "reliable/predictable and available" flows over wireless 192 links and possibly complex multi-hop paths called Tracks. This is 193 covered mainly by the "Wireless for Industrial Applications" use 194 case, as the "Cellular Radio" is mostly dedicated to the (wired) 195 transport part of a Radio Access Network (RAN). Whereas the 196 "Wireless for Industrial Applications" use case certainly covers an 197 area of interest for RAW, it is limited to 6TiSCH, and thus its scope 198 is narrower than the use cases described next in this document. 200 2. Aeronautical Communications 202 Aircraft are currently connected to ATC (Air-Traffic Control) and AOC 203 (Airline Operational Control) via voice and data communications 204 systems through all phases of a flight. Within the airport terminal, 205 connectivity is focused on high bandwidth communications while during 206 en-route high reliability, robustness and range is the main focus. 208 2.1. Problem Statement 210 Up to 2020 civil air traffic has been growing constantly at a 211 compound rate of 5.8% per year [ACI19] and despite the severe impact 212 of the COVID-19 pandemic, air traffic growth is expected to resume 213 very quickly in post-pandemic times [IAT20] [IAC20]. Thus, legacy 214 systems in air traffic management (ATM) are likely to reach their 215 capacity limits and the need for new aeronautical communication 216 technologies becomes apparent. Especially problematic is the 217 saturation of VHF band in high density areas in Europe, the US, and 218 Asia [KEAV20] [FAA20] calling for suitable new digital approaches 219 such as AeroMACS for airport communications, SatCOM for remote 220 domains, and LDACS as long-range terrestrial aeronautical 221 communications system. Making the frequency spectrum's usage more 222 efficient a transition from analogue voice to digital data 223 communication [PLA14] is necessary to cope with the expected growth 224 of civil aviation and its supporting infrastructure. A promising 225 candidate for long range terrestrial communications, already in the 226 process of being standardized in the International Civil Aviation 227 Organization (ICAO), is the L-band Digital Aeronautical 228 Communications System (LDACS) [ICAO18] [I-D.ietf-raw-ldacs]. 230 2.2. Specifics 232 During the creation process of new communications system, analogue 233 voice is replaced by digital data communication. This sets a 234 paradigm shift from analogue to digital wireless communications and 235 supports the related trend towards increased autonomous data 236 processing that the Future Communications Infrastructure (FCI) in 237 civil aviation must provide. The FCI is depicted in Figure 1: 239 Satellite 240 # # 241 # # # 242 # # # 243 # # # 244 # # # 245 # # # 246 # # # 247 # Satellite-based # # 248 # Communications # # 249 # SatCOM (#) # # 250 # # Aircraft 251 # # % % 252 # # % % 253 # # % Air-Air % 254 # # % Communications % 255 # # % LDACS A/A (%) % 256 # # % % 257 # Aircraft % % % % % % % % % % Aircraft 258 # | Air-Ground | 259 # | Communications | 260 # | LDACS A/G (|) | 261 # Communications in | | 262 # and around airports | | 263 # AeroMACS (-) | | 264 # | | 265 # Aircraft-------------+ | | 266 # | | | 267 # | | | 268 # Ground network | | Ground network | 269 SatCOM <---------------------> Airport <----------------------> LDACS 270 transceiver based GS 271 transceiver 273 Figure 1: The Future Communication Infrastructure (FCI): AeroMACS for 274 APT/TMA domain, LDACS A/G for TMA/ENR domain, LDACS A/G for ENR/ORP 275 domain, SatCOM for ORP domain communications 277 2.3. Challenges 279 This paradigm change brings a lot of new challenges: 281 o Efficiency: It is necessary to keep latency, time and data 282 overhead (routing, security) of new aeronautical datalinks at a 283 minimum. 285 o Modularity: Systems in avionics usually operate up to 30 years, 286 thus solutions must be modular, easily adaptable and updatable. 288 o Interoperability: All 192 members of the international Civil 289 Aviation Organization (ICAO) must be able to use these solutions. 291 2.4. The Need for Wireless 293 In a high mobility environment such as aviation, the envisioned 294 solutions to provide worldwide coverage of data connections with in- 295 flight aircraft require a multi-system, multi-link, multi-hop 296 approach. Thus air, ground and space-based datalink providing 297 technologies will have to operate seamlessly together to cope with 298 the increasing needs of data exchange between aircraft, air traffic 299 controller, airport infrastructure, airlines, air network service 300 providers (ANSPs) and so forth. Thus, making use of wireless 301 technologies is a MUST in tackling this enormous need for a worldwide 302 digital aeronautical datalink infrastructure. 304 2.5. Requirements for RAW 306 Different safety levels need to be supported, from extremely safety 307 critical ones requiring low latency, such as a WAKE warning - a 308 warning that two aircraft come dangerously close to each other - and 309 high resiliency, to less safety critical ones requiring low-medium 310 latency for services such as WXGRAPH - graphical weather data. 312 Overhead needs to be kept at a minimum since aeronautical data links 313 provide comparatively small data rates in the order of kbit/s. 315 Policy needs to be supported when selecting data links. The focus of 316 RAW here should be on the selectors, responsible for the routing path 317 a packet takes to reach its end destination. This would minimize the 318 amount of routing information that has to travel inside the network 319 because of precomputed routing tables with the selector being 320 responsible for choosing the most appropriate option according to 321 policy and safety. 323 3. Amusement Parks 325 3.1. Use Case Description 327 The digitalization of Amusement Parks is expected to decrease 328 significantly the cost for maintaining the attractions. Such 329 deployment is a mix between industrial automation (aka. Smart 330 Factories) and multimedia entertainment applications. 332 Attractions may rely on a large set of sensors and actuators, which 333 react in real time. Typical applications comprise: 335 o Emergency: safety has to be preserved, and must stop the 336 attraction when a failure is detected. 338 o Video: augmented and virtual realities are integrated in the 339 attraction. Wearable mobile devices (e.g., glasses, virtual 340 reality headset) need to offload one part of the processing tasks. 342 o Real-time interactions: visitors may interact with an attraction, 343 like in a real-time video game. The visitors may virtually 344 interact with their environment, triggering actions in the real 345 world (through actuators) [robots]. 347 o Geolocation: visitors are tracked with a personal wireless tag so 348 that their user experience is improved. 350 o Predictive maintenance: statistics are collected to predict the 351 future failures, or to compute later more complex statistics about 352 the attraction's usage, the downtime, its popularity, etc. 354 3.2. Specifics 356 Amusement parks comprise a variable number of attractions, mostly 357 outdoor, over a large geographical area. The IT infrastructure is 358 typically multi-scale: 360 o Local area: the sensors and actuators controlling the attractions 361 are co-located. Control loops trigger only local traffic, with a 362 small end-to-end delay, typically inferior than 10 milliseconds, 363 like classical industrial systems [ieee80211-rt-tig]. 365 o Wearable mobile devices are free to move in the park. They 366 exchange traffic locally (identification, personalization, 367 multimedia) or globally (billing, child tracking). 369 o Computationally intensive applications offload some tasks. Edge 370 computing seems an efficient way to implement real-time 371 applications with offloading. Some non time-critical tasks may 372 rather use the cloud (predictive maintenance, marketing). 374 3.3. The Need for Wireless 376 Amusement parks cover large areas and a global interconnection would 377 require a huge length of cables. Wireless also increases the 378 reconfigurability, enabling to update cheaply the attractions. The 379 frequent renewal helps to increase customer loyalty. 381 Some parts of the attraction are mobile, e.g., trucks of a roller- 382 coaster, robots. Since cables are prone to frequent failures in this 383 situation, wireless transmissions are recommended. 385 Wearable devices are extensively used for a user experience 386 personalization. They typically need to support wireless 387 transmissions. Personal tags may help to reduce the operating costs 388 [disney-VIP] and to increase the number of charged services provided 389 to the audience (VIP tickets, interactivity, etc.) Some applications 390 rely on more sophisticated wearable devices such as digital glasses 391 or Virtual Reality (VR) headsets for an immersive experience. 393 3.4. Requirements for RAW 395 The network infrastructure has to support heterogeneous traffic, with 396 very different critical requirements. Thus, flow isolation has to be 397 provided. 399 We have to schedule appropriately the transmissions, even in presence 400 of mobile devices. While the [I-D.ietf-6tisch-architecture] already 401 proposes an architecture for synchronized, IEEE Std. 802.15.4 Time- 402 Slotted Channel Hopping (TSCH) networks, we still need multi- 403 technology solutions, able to guarantee end-to-end requirements 404 across heterogeneous technologies, with strict SLA requirements. 406 Nowadays, long-range wireless transmissions are used mostly for best- 407 effort traffic. On the contrary, [IEEE802.1TSN] is used for critical 408 flows using Ethernet devices. However, we need an IP enabled 409 technology to interconnect large areas, independent of the PHY and 410 MAC layers. 412 We expect to deploy several different technologies (long vs. short 413 range) which have to cohabit in the same area. Thus, we need to 414 provide layer-3 mechanisms able to exploit multiple co-interfering 415 technologies. 417 4. Wireless for Industrial Applications 419 4.1. Use Case Description 421 A major use case for networking in Industrial environments is the 422 control networks where periodic control loops operate between a 423 sensor that measures a physical property such as the temperature of a 424 fluid, a Programmable Logic Controller (PLC) that decides an action 425 such as warm up the mix, and an actuator that performs the required 426 action, e.g., inject power in a resistor. 428 4.2. Specifics 430 4.2.1. Control Loops 432 Process Control designates continuous processing operations, e.g., 433 heating Oil in a refinery or mixing drinking soda. Control loops in 434 the Process Control industry operate at a very low rate, typically 4 435 times per second. Factory Automation, on the other hand, deal with 436 discrete goods such as individual automobile parts, and requires 437 faster loops, in the order of 10ms. Motion control that monitors 438 dynamic activities may require even faster rates in the order of a 439 few ms. Finally, some industries exhibit hybrid behaviors, like 440 canned soup that will start as a process industry while mixing the 441 food and then operate as a discrete manufacturing when putting the 442 final product in cans and shipping them. 444 In all those cases, a packet must flow reliably between the sensor 445 and the PLC, be processed by the PLC, and sent to the actuator within 446 the control loop period. In some particular use cases that inherit 447 from analog operations, jitter might also alter the operation of the 448 control loop. A rare packet loss is usually admissible, but 449 typically 4 losses in a row will cause an emergency halt of the 450 production and incur a high cost for the manufacturer. 452 4.2.2. Unmeasured Data 454 A secondary use case deals with monitoring and diagnostics. This so- 455 called unmeasured data is essential to improve the performances of a 456 production line, e.g., by optimizing real-time processing or 457 maintenance windows using Machine Learning predictions. For the lack 458 of wireless technologies, some specific industries such as Oil and 459 Gas have been using serial cables, literally by the millions, to 460 perform their process optimization over the previous decades. But 461 few industries would afford the associated cost and the Holy Grail of 462 the Industrial Internet of Things is to provide the same benefits to 463 all industries, including SmartGrid, Transportation, Building, 464 Commercial and Medical. This requires a cheap, available and 465 scalable IP-based access technology. 467 Inside the factory, wires may already be available to operate the 468 Control Network. But unmeasured data are not welcome in that network 469 for a number of reasons. On the one hand it is rich and 470 asynchronous, meaning that using they may influence the deterministic 471 nature of the control operations and impact the production. On the 472 other hand, this information must be reported to the carpeted floor 473 over IP, which means the potential for a security breach via the 474 interconnection of the Operational Technology (OT) network with the 475 Internet technology (IT) network and possibly enable a rogue access. 477 4.3. The Need for Wireless 479 Ethernet cables used on a robot arm are prone to breakage after a few 480 thousands flexions, a lot faster than a power cable that is wider inn 481 diameter, and more resilient. In general, wired networking and 482 mobile parts are not a good match, mostly in the case of fast and 483 recurrent activities, as well as rotation. 485 When refurbishing older premises that were built before the Internet 486 age, power is usually available everywhere, but data is not. It is 487 often impractical, time consuming and expensive to deploy an Ethernet 488 fabric across walls and between buildings. Deploying a wire may take 489 months and cost tens of thousands of US Dollars. 491 Even when wiring exists, e.g., in an existing control network, 492 asynchronous IP packets such as diagnostics may not be welcome for 493 operational and security reasons (see Section 4.2.1). An alternate 494 network that can scale with the many sensors and actuators that equip 495 every robot, every valve and fan that are deployed on the factory 496 floor and may help detect and prevent a failure that could impact the 497 production. IEEE Std. 802.15.4 Time-Slotted Channel Hopping (TSCH) 498 [RFC7554] is a promising technology for that purpose, mostly if the 499 scheduled operations enable to use the same network by asynchronous 500 and deterministic flows in parallel. 502 4.4. Requirements for RAW 504 As stated by the "Deterministic Networking Problem Statement" 505 [RFC8557], a Deterministic Network is backwards compatible with 506 (capable of transporting) statistically multiplexed traffic while 507 preserving the properties of the accepted deterministic flows. While 508 the [I-D.ietf-6tisch-architecture] serves that requirement, the work 509 at 6TiSCH was focused on best-effort IPv6 packet flows. RAW should 510 be able to lock so-called hard cells for use by a centralized 511 scheduler, and program so-called end-to-end Tracks over those cells. 513 Over the course of the recent years, major Industrial Protocols, 514 e.g., [ODVA] with EtherNet/IP [EIP] and [Profinet], have been 515 migrating towards Ethernet and IP. In order to unleash the full 516 power of the IP hourglass model, it should be possible to deploy any 517 application over any network that has the physical capacity to 518 transport the industrial flow, regardless of the MAC/PHY technology, 519 wired or wireless, and across technologies. RAW mechanisms should be 520 able to setup a Track over a wireless access segment such as TSCH and 521 a backbone segment such as Ethernet or WI-Fi, to report a sensor data 522 or a critical monitoring within a bounded latency. It is also 523 important to ensure that RAW solutions are interoperable with 524 existing wireless solutions in place, and with legacy equipment which 525 capabilities can be extended using retrofitting. Maintanability, as 526 a broader concept than reliability is also important in industrial 527 scenarios [square-peg]. 529 5. Pro Audio and Video 531 5.1. Use Case Description 533 Many devices support audio and video streaming by employing 802.11 534 wireless LAN. Some of these applications require low latency 535 capability. For instance, when the application provides interactive 536 play, or when the audio takes plays in real time (i.e. live) for 537 public addresses in train stations or in theme parks. 539 The professional audio and video industry ("ProAV") includes: 541 o Virtual Reality / Augmented Reality (VR/AR) 543 o Public address, media and emergency systems at large venues 544 (airports, train stations, stadiums, theme parks). 546 5.2. Specifics 548 5.2.1. Uninterrupted Stream Playback 550 Considering the uninterrupted audio or video stream, a potential 551 packet losses during the transmission of audio or video flows cannot 552 be tackled by re-trying the transmission, as it is done with file 553 transfer, because by the time the packet lost has been identified it 554 is too late to proceed with packet re-transmission. Buffering might 555 be employed to provide a certain delay which will allow for one or 556 more re-transmissions, however such approach is not efficient in 557 application where delays are not acceptable. 559 5.2.2. Synchronized Stream Playback 561 In the context of ProAV, latency is the time between the transmitted 562 signal over a stream and its reception. Thus, for sound to remain 563 synchronized to the movement in the video, the latency of both the 564 audio and video streams must be bounded and consistent. 566 5.3. The Need for Wireless 568 The devices need the wireless communication to support video 569 streaming via 802.11 wireless LAN for instance. 571 During the public address, the deployed announcement speakers, for 572 instance along the platforms of the train stations, need the wireless 573 communication to forward the audio traffic in real time. 575 5.4. Requirements for RAW 577 The network infrastructure needs to support heterogeneous types of 578 traffic (including QoS). 580 Content delivery with bounded (lowest possible) latency. 582 The deployed network topology should allow for multipath. This will 583 enable for multiple streams to have different (and multiple) paths 584 through the network to support redundancy. 586 6. Wireless Gaming 588 6.1. Use Case Description 590 The gaming industry includes [IEEE80211RTA] real-time mobile gaming, 591 wireless console gaming and cloud gaming. For RAW, wireless console 592 gaming is the most relevant one. We next summarize the three: 594 o Real-time Mobile Gaming: Different from traditional games, real 595 time mobile gaming is very sensitive to network latency and 596 stability. The mobile game can connect multiple players together 597 in a single game session and exchange data messages between game 598 server and connected players. Real-time means the feedback should 599 present on screen as users operate in game. For good game 600 experience, the end to end latency plus game servers processing 601 time should not be noticed by users as they play the game. 603 o Wireless Console Gaming: Playing online on a console has 2 types 604 of internet connectivity, which is either wired or Wi-Fi. Most of 605 the gaming consoles today support Wi-Fi 5. But Wi-Fi has an 606 especially bad reputation among the gaming community. The main 607 reasons are high latency, lag spikes and jitter. 609 o Cloud Gaming: The cloud gaming requires low latency capability as 610 the user commands in a game session need to be sent back to the 611 cloud server, the cloud server would update game context depending 612 on the received commands, and the cloud server would render the 613 picture/video to be displayed at user devices and stream the 614 picture/video content to the user devices. User devices might 615 very likely be connected wirelessly. 617 6.2. Specifics 619 While a lot of details can be found on [IEEE80211RTA], we next 620 summarize the main requirements in terms of latency, jitter and 621 packet loss: 623 o Intra BSS latency: less than 5 ms. 625 o Jitter variance: less than 2 ms. 627 o Packet loss: less than 0.1 percent. 629 6.3. The Need for Wireless 631 It is clear that gaming is evolving towards wireless, as players 632 demand being able to play anywhere. Besides, the industry is 633 changing towards playing from mobile phones, which are inherently 634 connected via wireless technologies. 636 6.4. Requirements for RAW 638 o Time sensitive networking extensions. Extensions, such as time- 639 aware shaping and redundancy (FRE) can be explored to address 640 congestion and reliability problems present in wireless networks. 642 o Priority tagging (Stream identification). One basic requirement 643 to provide better QoS for time-sensitive traffic is the capability 644 to identify and differentiate time-sensitive packets from other 645 (e.g. best-effort) traffic. 647 o Time-aware shaping. This capability (defined in IEEE 802.1Qbv) 648 consists of gates to control the opening/closing of queues that 649 share a common egress port within an Ethernet switch. A scheduler 650 defines the times when each queue opens or close, therefore 651 eliminating congestion and ensuring that frames are delivered 652 within the expected latency bounds. 654 o Dual/multiple link. Due to the competitions and interference are 655 common and hardly in control under wireless network, in order to 656 improve the latency stability, dual/multiple link proposal is 657 brought up to address this issue. Two modes are defined: 658 duplicate and joint. 660 o Admission Control. Congestion is a major cause of high/variable 661 latency and it is well known that if the traffic load exceeds the 662 capability of the link, QoS will be degraded. QoS degradation 663 maybe acceptable for many applications today, however emerging 664 time-sensitive applications are highly susceptible to increased 665 latency and jitter. In order to better control QoS, it is 666 important to control access to the network resources. 668 7. UAV platooning and control 670 7.1. Use Case Description 672 Unmanned Aerial Vehicles (UAVs) are becoming very popular for many 673 different applications, including military and civil use cases. The 674 term drone is commonly used to refer to a UAV. 676 UAVs can be used to perform aerial surveillance activities, traffic 677 monitoring (e.g., Spanish traffic control has recently introduced a 678 fleet of drones for quicker reactions upon traffic congestion related 679 events), support of emergency situations, and even transportation of 680 small goods. 682 UAVs typically have various forms of wireless connectivity: 684 o cellular: for communication with the control center, for remote 685 maneuvering as well as monitoring of the drone; 687 o IEEE 802.11: for inter-drone communications (e.g., platooning) and 688 providing connectivity to other devices (e.g., acting as Access 689 Point). 691 7.2. Specifics 693 Some of the use cases/tasks involving drones require coordination 694 among drones. Others involve complex compute tasks that might not be 695 performed using the limited computing resources that a drone 696 typically has. These two aspects require continuous connectivity 697 with the control center and among drones. 699 Remote maneuvering of a drone might be performed over a cellular 700 network in some cased, however, there are situations that need very 701 low latencies and deterministic behavior of the connectivity. 702 Examples involve platooning of drones or share of computing resources 703 among drones (e.g., a drone offload some function to a neighboring 704 drone). 706 7.3. The Need for Wireless 708 UAVs cannot be connected through any type of wired media, so it is 709 obvious that wireless is needed. 711 7.4. Requirements for RAW 713 The network infrastructure is actually composed by the UAVs 714 themselves, requiring self-configuration capabilities. 716 Heterogeneous types of traffic need to be supported, from extremely 717 critical ones requiring ultra low latency and high resiliency, to 718 traffic requiring low-medium latency. 720 When a given service is decomposed into functions -- hosted at 721 different drones -- chained, each link connecting two given functions 722 would have a well-defined set of requirements (latency, bandwidth and 723 jitter) that have to be met. 725 8. Edge Robotics control 727 8.1. Use Case Description 729 The Edge Robotics scenario consists of several robots, deployed in a 730 given area (for example a shopping mall), inter-connected via an 731 access network to a network's edge device or a data center. The 732 robots are connected to the edge so complex computational activities 733 are not executed locally at the robots, but offloaded to the edge. 734 This brings additional flexibility in the type of tasks that the 735 robots do, as well as reducing the costs of robot manufacturing (due 736 to their lower complexity), and enabling complex tasks involving 737 coordination among robots (that can be more easily performed if 738 robots are centrally controlled). 740 A simple example of the use of multiples robots is cleaning, 741 delivering of goods from warehouses to shops or video surveillance. 742 Multiple robots are simultaneously instructed to perform individual 743 tasks by moving the robotic intelligence from the robots to the 744 network's edge (e.g., data center). That enables easy 745 synchronization, scalable solution and on-demand option to create 746 flexible fleet of robots. 748 Robots would have various forms of wireless connectivity: 750 o IEEE 802.11: for connection to the edge and also inter-robot 751 communications (e.g., for coordinated actions). 753 o Cellular: as an additional communication link to the edge, though 754 primarily as backup, since ultra low latencies are needed. 756 8.2. Specifics 758 Some of the use cases/tasks involving robots might benefit from 759 decomposition of a service in small functions that are distributed 760 and chained among robots and the edge. These require continuous 761 connectivity with the control center and among drones. 763 Robot control is an activity requiring very low latencies between the 764 robot and the location where the control intelligence resides (which 765 might be the edge or another robot). 767 8.3. The Need for Wireless 769 Deploying robots in scenarios such as shopping malls for the 770 aforementioned applications cannot be done via wired connectivity. 772 8.4. Requirements for RAW 774 The network infrastructure needs to support heterogeneous types of 775 traffic, from robot control to video streaming. 777 When a given service is decomposed into functions -- hosted at 778 different robots -- chained, each link connecting two given functions 779 would have a well-defined set of requirements (latency, bandwidth and 780 jitter) that have to be met. 782 9. Emergencies: Instrumented emergency vehicle 784 9.1. Use Case Description 786 An instrumented ambulance would be one that has a LAN to which are 787 connected these end systems: 789 o vital signs sensors attached to the casualty in the ambulance. 790 Relay medical data to hospital emergency room, 792 o radionavigation sensor to relay position data to various 793 destinations including dispatcher, 795 o voice communication for ambulance attendant (e.g. consult with ER 796 doctor), 798 o voice communication between driver and dispatcher, 800 o etc. 802 The LAN needs to be routed through radio-WANs to complete the 803 internetwork linkage. 805 9.2. Specifics 807 What we have today is multiple communications systems to reach the 808 vehicle: 810 o A dispatching system, 812 o a cellphone for the attendant, 814 o a special purpose telemetering system for medical data, 816 o etc. 818 This redundancy of systems, because of its stovepiping, does not 819 contribute to availability as a whole. 821 Most of the scenarios involving the use of an instrumented ambulance 822 are composed of many different flows, each of them with slightly 823 different requirements in terms of reliability and latency. 824 Destinations might be either at the ambulance itself (local traffic), 825 at a near edge cloud or at the general Internet/cloud. 827 9.3. The Need for Wireless 829 Local traffic between the first responders/ambulance staff and the 830 ambulance equipment cannot be doine via wireled connectivity as the 831 responders perform initial treatment outside of the ambulance. The 832 communications from the ambulance to external services has to be 833 wireless as well. 835 9.4. Requirements for RAW 837 We can derive some pertinent requirements from this scenario: 839 o High availability of the internetwork is required. 841 o The internetwork needs to operate in damaged state (e.g. during an 842 earthquake aftermath, heavy weather, wildfire, etc.). In addition 843 to continuity of operations, rapid restoral is a needed 844 characteristic. 846 o End-to-end security, both authenticity and confidentiality, is 847 required of traffic. All data needs to be authenticated; some 848 (such as medical) needs to be confidential. 850 o The radio-WAN has characteristics similar to cellphone -- the 851 vehicle will travel from one radio footprint to another. 853 10. IANA Considerations 855 This document has no IANA actions. 857 11. Security Considerations 859 This document covers a number of representative applications and 860 network scenarios that are expected to make use of RAW technologies. 861 Each of the potential RAW use cases will have security considerations 862 from both the use-specific perspective and the RAW technology 863 perspective. [I-D.ietf-detnet-security] provides a comprehensive 864 discussion of security considerations in the context of Deterministic 865 Networking, which are generally applicable also to RAW. 867 12. Acknowledgments 869 Nils Maeurer, Thomas Graeupl and Corinna Schmitt have contributed 870 significantly to this document, providing input for the Aeronautical 871 communications section. Rex Buddenberg has also contributed to the 872 document, providing input to the Emergency: instrumented emergency 873 vehicle section. 875 The authors would like to thank Toerless Eckert, Xavi Vilajosana 876 Guillen and Rute Sofia for their valuable comments on previous 877 versions of this document. 879 The work of Carlos J. Bernardos in this draft has been partially 880 supported by the H2020 5Growth (Grant 856709) and 5G-DIVE projects 881 (Grant 859881). 883 13. Informative References 885 [ACI19] Airports Council International (ACI), "Annual World 886 Aitport Traffic Report 2019", November 2019, 887 . 890 [disney-VIP] 891 Wired, "Disney's $1 Billion Bet on a Magical Wristband", 892 March 2015, 893 . 895 [EIP] http://www.odva.org/, "EtherNet/IP provides users with the 896 network tools to deploy standard Ethernet technology (IEEE 897 802.3 combined with the TCP/IP Suite) for industrial 898 automation applications while enabling Internet and 899 enterprise connectivity data anytime, anywhere.", 900 . 904 [FAA20] U.S. Department of Transportation Federal Aviation 905 Administration (FAA), "Next Generation Air Transportation 906 System", 2019, . 908 [I-D.ietf-6tisch-architecture] 909 Thubert, P., "An Architecture for IPv6 over the TSCH mode 910 of IEEE 802.15.4", draft-ietf-6tisch-architecture-30 (work 911 in progress), November 2020. 913 [I-D.ietf-detnet-security] 914 Grossman, E., Mizrahi, T., and A. Hacker, "Deterministic 915 Networking (DetNet) Security Considerations", draft-ietf- 916 detnet-security-13 (work in progress), December 2020. 918 [I-D.ietf-raw-ldacs] 919 Maeurer, N., Graeupl, T., and C. Schmitt, "L-band Digital 920 Aeronautical Communications System (LDACS)", draft-ietf- 921 raw-ldacs-06 (work in progress), January 2021. 923 [I-D.thubert-raw-technologies] 924 Thubert, P., Cavalcanti, D., Vilajosana, X., Schmitt, C., 925 and J. Farkas, "Reliable and Available Wireless 926 Technologies", draft-thubert-raw-technologies-05 (work in 927 progress), May 2020. 929 [IAC20] Iacus, S., Natale, F., Santamaria, C., Spyratos, S., and 930 V. Michele, "Estimating and projecting air passenger 931 traffic during the COVID-19 coronavirus outbreak and its 932 socio- economic impact", Safety Science 129 (2020) 933 104791 , 2020. 935 [IAT20] International Air Transport Association (IATA), "Economic 936 Performance of the Airline Industry", November 2020, 937 . 941 [ICAO18] International Civil Aviation Organization (ICAO), "L-Band 942 Digital Aeronautical Communication System (LDACS)", 943 International Standards and Recommended Practices Annex 10 944 - Aeronautical Telecommunications, Vol. III - 945 Communication Systems , 2018. 947 [IEEE802.1TSN] 948 IEEE standard for Information Technology, "IEEE 949 802.1AS-2011 - IEEE Standard for Local and Metropolitan 950 Area Networks - Timing and Synchronization for Time- 951 Sensitive Applications in Bridged Local Area Networks". 953 [ieee80211-rt-tig] 954 IEEE, "IEEE 802.11 Real Time Applications TIG Report", 955 Nov. 2018, 956 . 958 [IEEE80211RTA] 959 IEEE standard for Information Technology, "IEEE 802.11 960 Real Time Applications TIG Report", Nov 2018. 962 [ISA100] ISA/ANSI, "ISA100, Wireless Systems for Automation", 963 . 965 [KEAV20] T. Keaveney and C. Stewart, "Single European Sky ATM 966 Research Joint Undertaking", 2019, 967 . 969 [ODVA] http://www.odva.org/, "The organization that supports 970 network technologies built on the Common Industrial 971 Protocol (CIP) including EtherNet/IP.". 973 [PLA14] Plass, S., Hermenier, R., Luecke, O., Gomez Depoorter, D., 974 Tordjman, T., Chatterton, M., Amirfeiz, M., Scotti, S., 975 Cheng, Y., Pillai, P., Graeupl, T., Durand, F., Murphy, 976 K., Marriott, A., and A. Zaytsev, "Flight Trial 977 Demonstration of Seamless Aeronautical Networking", IEEE 978 Communications Magazine, vol. 52, no. 5 , May 2014. 980 [Profinet] 981 http://us.profinet.com/technology/profinet/, "PROFINET is 982 a standard for industrial networking in automation.", 983 . 985 [RFC7554] Watteyne, T., Ed., Palattella, M., and L. Grieco, "Using 986 IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH) in the 987 Internet of Things (IoT): Problem Statement", RFC 7554, 988 DOI 10.17487/RFC7554, May 2015, 989 . 991 [RFC8557] Finn, N. and P. Thubert, "Deterministic Networking Problem 992 Statement", RFC 8557, DOI 10.17487/RFC8557, May 2019, 993 . 995 [RFC8578] Grossman, E., Ed., "Deterministic Networking Use Cases", 996 RFC 8578, DOI 10.17487/RFC8578, May 2019, 997 . 999 [RFC8655] Finn, N., Thubert, P., Varga, B., and J. Farkas, 1000 "Deterministic Networking Architecture", RFC 8655, 1001 DOI 10.17487/RFC8655, October 2019, 1002 . 1004 [robots] Kober, J., Glisson, M., and M. Mistry, "Playing catch and 1005 juggling with a humanoid robot.", 2012, 1006 . 1008 [square-peg] 1009 Martinez, B., Cano, C., and X. Vilajosana, "A Square Peg 1010 in a Round Hole: The Complex Path for Wireless in the 1011 Manufacturing Industry", 2019, 1012 . 1014 Authors' Addresses 1016 Georgios Z. Papadopoulos 1017 IMT Atlantique 1018 Office B00 - 114A 1019 2 Rue de la Chataigneraie 1020 Cesson-Sevigne - Rennes 35510 1021 FRANCE 1023 Phone: +33 299 12 70 04 1024 Email: georgios.papadopoulos@imt-atlantique.fr 1025 Pascal Thubert 1026 Cisco Systems, Inc 1027 Building D 1028 45 Allee des Ormes - BP1200 1029 MOUGINS - Sophia Antipolis 06254 1030 FRANCE 1032 Phone: +33 497 23 26 34 1033 Email: pthubert@cisco.com 1035 Fabrice Theoleyre 1036 CNRS 1037 ICube Lab, Pole API 1038 300 boulevard Sebastien Brant - CS 10413 1039 Illkirch 67400 1040 FRANCE 1042 Phone: +33 368 85 45 33 1043 Email: theoleyre@unistra.fr 1044 URI: http://www.theoleyre.eu 1046 Carlos J. Bernardos 1047 Universidad Carlos III de Madrid 1048 Av. Universidad, 30 1049 Leganes, Madrid 28911 1050 Spain 1052 Phone: +34 91624 6236 1053 Email: cjbc@it.uc3m.es 1054 URI: http://www.it.uc3m.es/cjbc/