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Miscellaneous warnings: ---------------------------------------------------------------------------- == The copyright year in the IETF Trust and authors Copyright Line does not match the current year -- The document date (March 13, 2017) is 2600 days in the past. Is this intentional? Checking references for intended status: Informational ---------------------------------------------------------------------------- No issues found here. Summary: 2 errors (**), 0 flaws (~~), 1 warning (==), 1 comment (--). Run idnits with the --verbose option for more detailed information about the items above. -------------------------------------------------------------------------------- 2 ICNRG J. Seedorf 3 Internet-Draft HFT Stuttgart - Univ. of Applied Sciences 4 Intended status: Informational M. Arumaithurai 5 Expires: September 14, 2017 University of Goettingen 6 A. Tagami 7 KDDI R&D Labs 8 K. Ramakrishnan 9 University of California 10 N. Blefari Melazzi 11 University Tor Vergata 12 March 13, 2017 14 Using ICN in disaster scenarios 15 draft-irtf-icnrg-disaster-01 17 Abstract 19 Information Centric Networking (ICN) is a new paradigm where the 20 network provides users with named content, instead of communication 21 channels between hosts. This document outlines some research 22 directions for Information Centric Networking with respect to 23 applying ICN approaches for coping with natural or human-generated, 24 large-scale disasters. 26 Status of This Memo 28 This Internet-Draft is submitted in full conformance with the 29 provisions of BCP 78 and BCP 79. 31 Internet-Drafts are working documents of the Internet Engineering 32 Task Force (IETF). Note that other groups may also distribute 33 working documents as Internet-Drafts. The list of current Internet- 34 Drafts is at http://datatracker.ietf.org/drafts/current/. 36 Internet-Drafts are draft documents valid for a maximum of six months 37 and may be updated, replaced, or obsoleted by other documents at any 38 time. It is inappropriate to use Internet-Drafts as reference 39 material or to cite them other than as "work in progress." 41 This Internet-Draft will expire on September 14, 2017. 43 Copyright Notice 45 Copyright (c) 2017 IETF Trust and the persons identified as the 46 document authors. All rights reserved. 48 This document is subject to BCP 78 and the IETF Trust's Legal 49 Provisions Relating to IETF Documents 50 (http://trustee.ietf.org/license-info) in effect on the date of 51 publication of this document. Please review these documents 52 carefully, as they describe your rights and restrictions with respect 53 to this document. Code Components extracted from this document must 54 include Simplified BSD License text as described in Section 4.e of 55 the Trust Legal Provisions and are provided without warranty as 56 described in the Simplified BSD License. 58 Table of Contents 60 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2 61 2. Disaster Scenarios . . . . . . . . . . . . . . . . . . . . . 3 62 3. Research Challenges and Benefits of ICN . . . . . . . . . . . 4 63 3.1. High-Level Research Challenges . . . . . . . . . . . . . 4 64 3.2. How ICN can be Beneficial . . . . . . . . . . . . . . . . 6 65 3.3. ICN as Starting Point vs. Existing DTN Solutions . . . . 7 66 4. Use Cases and Requirements . . . . . . . . . . . . . . . . . 8 67 5. Solution Design . . . . . . . . . . . . . . . . . . . . . . . 9 68 6. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 12 69 7. References . . . . . . . . . . . . . . . . . . . . . . . . . 12 70 7.1. Normative References . . . . . . . . . . . . . . . . . . 12 71 7.2. Informative References . . . . . . . . . . . . . . . . . 12 72 Appendix A. Acknowledgment . . . . . . . . . . . . . . . . . . . 14 73 Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 14 75 1. Introduction 77 This document summarizes some research challenges for coping with 78 natural or human-generated, large-scale disasters. In particular, 79 the document discusses potential directions for applying Information 80 Centric Networking (ICN) to address these challenges. 82 There are existing research approaches (for instance, see further the 83 discussions in the IETF DTN Research Group [dtnrg] ) and an IETF 84 specification [RFC5050] for disruptant tolerant networking, which is 85 a key necessity for communicating in the disaster scenarios we are 86 considering in this document (see further Section 3.1 ). 87 'Disconnection tolerance' can thus be achieved with these existing 88 DTN approaches. However, while these approaches can provide 89 independence from an existing communication infrastructure (which 90 indeed may not work anymore after a disaster has happened), ICN 91 offers as key concepts suitable naming schemes and multicast 92 communication which together enable many key (publish/subribe-based) 93 use cases for communication after a disaster (e.g. message 94 prioritisation, one-to-many delivery of important messages, or group 95 communication among rescue teams, see further Section 4 ). One could 96 add such features to existing DTN protocols and solutions; however, 97 in this document we explore the use of ICN as starting point for 98 building a communication architecture that works well before and 99 after a disaster. We discuss the relationship between the ICN 100 approaches (for enabling communication after a disaster) discussed in 101 this document with existing work from the DTN community in more depth 102 in Section 3.3 . 104 'Emergency Support and Disaster Recovery' is also listed among the 105 ICN Baseline Scenarios in [RFC7476] as a potential scenario that 'can 106 be used as a base for the evaluation of different information-centric 107 networking (ICN) approaches so that they can be tested and compared 108 against each other while showcasing their own advantages' [RFC7476] . 109 In this regard, this document complements [RFC7476] by investigating 110 the use of ICN approaches for 'Emergency Support and Disaster 111 Recovery' in depth and discussing the relationship to existing work 112 in the DTN community. 114 Section 2 gives some examples of what can be considered a large-scale 115 disaster and what the effects of such disasters on communication 116 networks are. Section 3 outlines why ICN can be beneficial in such 117 scenarios and provides a high-level overview on corresponding 118 research challenges. Section 4 describes some concrete use cases and 119 requirements for disaster scenarios. In Section 5 , some concrete 120 ICN-based solutions approaches are outlined. 122 2. Disaster Scenarios 124 An enormous earthquake hit Northeastern Japan (Tohoku areas) on March 125 11, 2011, and caused extensive damages including blackouts, fires, 126 tsunamis and a nuclear crisis. The lack of information and means of 127 communication caused the isolation of several Japanese cities. This 128 impacted the safety and well-being of residents, and affected rescue 129 work, evacuation activities, and the supply chain for food and other 130 essential items. Even in the Tokyo area that is 300km away from the 131 Tohoku area, more than 100,000 people became 'returner' refugees, who 132 could not reach their homes because they had no means of public 133 transportation (the Japanese government has estimated that more than 134 6.5 million people would become returner refugees if such a 135 catastrophic disaster were to hit the Tokyo area). 137 That earthquake in Japan also showed that the current network is 138 vulnerable against disasters and that mobile phones have become the 139 lifelines for communication including safety confirmation. The 140 aftermath of a disaster puts a high strain on available resources due 141 to the need for communication by everyone. Authorities such as the 142 President/Prime-Minister, local authorities, Police, fire brigades, 143 and rescue and medical personnel would like to inform the citizens of 144 possible shelters, food, or even of impending danger. Relatives 145 would like to communicate with each other and be informed about their 146 wellbeing. Affected citizens would like to make enquiries of food 147 distribution centres, shelters or report trapped, missing people to 148 the authorities. Moreover, damage to communication equipment, in 149 addition to the already existing heavy demand for communication 150 highlights the issue of fault-tolerance and energy efficiency. 152 Additionally, disasters caused by humans such as a terrorist attack 153 may need to be considered, i.e. disasters that are caused 154 deliberately and willfully and have the element of human intent. In 155 such cases, the perpetrators could be actively harming the network by 156 launching a Denial-of-Service attack or by monitoring the network 157 passively to obtain information exchanged, even after the main 158 disaster itself has taken place. Unlike some natural disasters that 159 are predictable using weather forecasting technologies and have a 160 slower onset and occur in known geographical regions and seasons, 161 terrorist attacks may occur suddenly without any advance warning. 162 Nevertheless, there exist many commonalities between natural and 163 human-induced disasters, particularly relating to response and 164 recovery, communication, search and rescue, and coordination of 165 volunteers. 167 The timely dissemination of information generated and requested by 168 all the affected parties during and the immediate aftermath of a 169 disaster is difficult to provide within the current context of global 170 information aggregators (such as Google, Yahoo, Bing etc.) that need 171 to index the vast amounts of specialized information related to the 172 disaster. Specialized coverage of the situation and timely 173 dissemination are key to successfully managing disaster situations. 174 We believe that network infrastructure capability provided by 175 Information Centric Networks can be suitable, in conjunction with 176 application and middleware assistance. 178 3. Research Challenges and Benefits of ICN 180 3.1. High-Level Research Challenges 182 Given a disaster scenario as described in Section 2 , on a high-level 183 one can derive the following (incomplete) list of corresponding 184 technical challenges: 186 o Enabling usage of functional parts of the infrastructure, even 187 when these are disconnected from the rest of the network: Assuming 188 that parts of the network infrastructure (i.e. cables/links, 189 routers, mobile bases stations, ...) are functional after a 190 disaster has taken place, it is desirable to be able to continue 191 using such components for communication as much as possible. This 192 is challenging when these components are disconnected from the 193 backhaul, thus forming fragmented networks. This is especially 194 true for today's mobile networks which are comprised of a 195 centralised architecture, mandating connectivity to central 196 entities (which are located in the core of the mobile network) for 197 communication. But also in fixed networks, access to a name 198 resolution service is often necessary to access some given 199 content. 201 o Decentralised authentication and trust: In mobile networks, users 202 are authenticated via central entities. In order to communicate 203 in fragmented or disconnected parts of a mobile network, the 204 challenge of decentralising such user authentication arises. 205 Independently of the network being fixed or mobile, data origin 206 authentication of content retrieved from the network is 207 challenging when being 'offline' (e.g. disconnected from servers 208 of a security infrastructure such as a PKI). As the network 209 suddenly becomes fragmented or partitioned, trust models may shift 210 accordingly to the change in authentication infrastructure being 211 used (e.g., one may switch from a PKI to a web-of-trust model such 212 as PGP). 214 o Delivering/obtaining information and traffic prioritization in 215 congested networks: Due to broken cables, failed routers, etc., it 216 is likely that in a disaster scenario the communication network 217 has much less overall capacity for handling traffic. Thus, 218 significant congestion can be expected in parts of the 219 infrastructure. It is therefore a challenge to guarantee message 220 delivery in such a scenario. This is even more important as in 221 the case of a disaster aftermath, it may be crucial to deliver 222 certain information to recipients (e.g. warnings to citizens) with 223 higher priority than other content. 225 o Delay/Disruption Tolerant Approach: Fragmented networks makes it 226 difficult to support end-to-end communication. However, 227 communication in general and especially during disaster can 228 tolerate some form of delay. E.g. in order to know if his/her 229 relatives are safe or a 'SOS' call need not be supported in an 230 end-to-end manner. It is sufficient to improve communication 231 resilience in order to deliver such important messages. 233 o Energy Efficiency: Long-lasting power outages may lead to 234 batteries of communication devices running out, so designing 235 energy-efficient solutions is very important in order to maintain 236 a usable communication infrastructure. 238 o Contextuality: Like any communication in general, disaster 239 scenarios are inherently contextual. Aspects of geography, the 240 people affected, the rescue communities involved, the languages 241 being used and many other contextual aspects are highly relevant 242 for an efficient realization of any rescue effort and, with it, 243 the realization of the required communication. 245 The list above is most likely incomplete; future revisions of this 246 document intend to add additional challenges to the list. 248 3.2. How ICN can be Beneficial 250 Several aspects of ICN make related approaches attractive candidates 251 for addressing the challenges described in Section 3.1 . Below is an 252 (incomplete) list of considerations why ICN approaches can be 253 beneficial to address these challenges: 255 o Routing-by-name: ICN protocols natively route by named data 256 objects and can identify objects by names, effectively moving the 257 process of name resolution from the application layer to the 258 network layer. This functionality is very handy in a fragmented 259 network where reference to location-based, fixed addresses may not 260 work as a consequence of disruptions. For instance, name 261 resolution with ICN does not necessarily rely on the reachability 262 of application-layer servers (e.g. DNS resolvers). In highly 263 decentralised scenarios (e.g. in infrastructureless, opportunistic 264 environments) the ICN routing-by-name paradigm effectively may 265 lead to a 'replication-by-name' approach, where content is 266 replicated depending on its name. 268 o Authentication of named data objects: ICN is built around the 269 concept of named data objects. Several proposals exist for 270 integrating the concept of 'self-certifying data' into a naming 271 scheme (see e.g. [RFC6920] ). With such approaches, the origin 272 of data retrieved from the network can be authenticated without 273 relying on a trusted third party or PKI. 275 o Content-based access control: ICN promotes a data-centric 276 communication model which is better suited to content-based 277 security (e.g. allowing access to content only to a specific user 278 or class of users); this functionality could facilitate trusted 279 communications among peer users in isolated areas of the network. 281 o Caching: Caching content along a delivery path is an inherent 282 concept in ICN. Caching helps in handling huge amounts of 283 traffic, and can help to avoid congestion in the network (e.g. 284 congestion in backhaul links can be avoided by delivering content 285 from caches at access nodes). 287 o Sessionless: ICN does not require full end-to-end connectivity. 288 This feature facilitates a seemless aggregation between a normal 289 network and a fragmented network, which needs DTN-like message 290 forwarding. 292 o Potential to run traditional IP-based services (IP-over-ICN): 293 While ICN and DTN promote the development of novel applications 294 that fully utilize the new capabiliticbies of the ICN/DTN network, 295 work in [Trossen2015] has shown that an ICN-enabled network can 296 transport IP-based services, either directly at IP or even at HTTP 297 level. With this, IP- and ICN/DTN-based services can coexist, 298 providing the necessary support of legacy applications to affected 299 users, while reaping any benefits from the native support for ICN 300 in future applications. 302 o Opportunities for traffic engineering and traffic prioritization: 303 ICN provides the possibility to perform traffic engineering based 304 on the name of desired content. This enables priority based 305 replication depending on the scope of a given message [Psaras2014] 306 . In addition, as [Trossen2015] , among others, have pointed out, 307 the realization of ICN services and particularly of IP-based 308 services on top of ICN provide further traffic engineering 309 opportunities. The latter not only relate to the utilization of 310 cached content, as outlined before, but to the ability to flexbily 311 adapt to route changes (important in unreliable infrastructure 312 such as in disaster scenarios), mobility support without anchor 313 points (again, important when parts of the infrastructure are 314 likely to fail) and the inherent support for multicast and 315 multihoming delivery. 317 The list above is most likely incomplete; future revisions of this 318 document intend to add more considerations to the list and to argue 319 in more detail why ICN is suitable for addressing the aforementioned 320 research challenges. 322 3.3. ICN as Starting Point vs. Existing DTN Solutions 324 There has been quite some work in the DTN (Delay Tolerant Networking) 325 community on disaster communication (for instance, see further the 326 discussions in the IETF DTN Research Group [dtnrg] ). However, most 327 DTN work lacks important features such as publish/subscribe (pub/sub) 328 capabilities, caching, multicast delivery, and message prioritisation 329 based on content types, which are needed in the disaster scenarios we 330 consider. One could add such features to existing DTN protocols and 331 solutions, and indeed individual proposals for adding such features 332 to DTN protocols have been made (e.g. [Greifenberg2008] [Yoneki2007] 333 propose the use of a pub/sub-based multicast distribution 334 infrastructure for DTN-based opportunistic networking environments). 336 However, arguably ICN---having these intrinsic properties (as also 337 outlined above)---makes a better starting point for building a 338 communication architecture that works well before and after a 339 disaster. For a disaster-enhanced ICN system this would imply the 340 following advantages: a) ICN data mules would have built-in caches 341 and can thus return content for interests straight on, b) requests do 342 not necessarily need to be routed to a source (as with existing DTN 343 protocols), instead any data mule or end-user can in principle 344 respond to an interest, c) built-in multi-cast delivery implies 345 energy-efficient large-scale spreading of important information which 346 is crucial in disaster scenarios, and d) pub/sub extension for 347 popular ICN implementations exist [COPSS2011] which are very suitable 348 for efficient group communication in disasters and provide better 349 reliability, timeliness and scalability as compared to existing pub/ 350 sub approaches in DTN [Greifenberg2008] [Yoneki2007] . 352 Finally, most DTN routing algorithms have been solely designed for 353 particular DTN scenarios. By extending ICN approaches for DTN-like 354 scenarios, one ensures that a solution works in regular (i.e. well- 355 connected) settings just as well (which can be important in reality, 356 where a routing algorithm should work before and after a disaster). 357 It is thus reasonable to start with existing ICN approaches and 358 extend them with the necessary features needed in disaster scenarios. 360 4. Use Cases and Requirements 362 This Section describes some use cases for the aforementioned disaster 363 scenario (as outlined in Section 2 ) and discusses the corresponding 364 technical requirements for enabling these use cases. 366 o Delivering Messages to Relatives/Friends: After a disaster 367 strikes, citizens want to confirm to each other that they are 368 safe. For instance, shortly after a large disaster (e.g., 369 Earthquake, Tornado), people have moved to different refugee 370 shelters. The mobile network is not fully recovered and is 371 fragmented, but some base stations are functional. This use case 372 imposes the following high-level requirements: a) People must be 373 able to communicate with others in the same network fragment, b) 374 people must be able to communicate with others that are located in 375 different fragmented parts of the overall network. More 376 concretely, the following requirements are needed to enable the 377 use case: a) a mechanism for scalable message forwarding scheme 378 that dynamically adapts to changing conditions in disconnected 379 networks, b) DTN-like mechanisms for getting information from 380 disconnected island to another disconnected island, c) data origin 381 authentication so that users can confirm that the messages they 382 receive are indeed from their relatives or friends, and d) the 383 support for contextual caching in order to provide the right 384 information to the right set of affected people in the most 385 efficient manner. 387 o Spreading Crucial Information to Citizens: State authorities want 388 to be able to convey important information (e.g. warnings, or 389 information on where to go or how to behave) to citizens. These 390 kinds of information shall reach as many citizens as possible. 391 i.e. Crucial content from legal authorities shall potentially 392 reach all users in time. The technical requirements that can be 393 derived from this use case are: a) Data origin authentication, 394 such that citizens can confrim the authenticity of messages sent 395 by authorities, b) mechanisms that guarantee the timeliness and 396 loss-free delivery of such information, which may include 397 techniques for prioritizing certain messages in the network 398 depending on who sent them, and c) DTN-like mechanisms for getting 399 information from disconnected island to another disconnected 400 island. 402 It can be observed that different key use cases for disaster 403 scenarios imply overlapping and similar technical requirements for 404 fulfilling them. As discussed in Section 3.2 , ICN approaches are 405 envisioned to be very suitable for addressing these requirements with 406 actual technical solutions. In [Robitzsch2015] , a more elaborate 407 set of requirements is provided that addresses, among disaster 408 scenarios, a communication infrastructure for communities facing 409 several geographic, economic and political challenges. 411 5. Solution Design 413 This Section outlines some ICN-based approaches that aim at 414 fulfilling the previously mentioned use cases and requirements. 416 o ICN 'data mules': To facilitate the exchange of messages between 417 different network fragments, mobile entitites can act as ICN 'data 418 mules' which are equipped with storage space and move around the 419 disaster-stricken area gathering information to be disseminated. 420 As the mules move around, they deliver messages to other 421 individuals or points of attachment to different fragments of the 422 network. These 'data mules' could have a pre-determined path (an 423 ambulance going to and from a hospital), a fixed path (drone/robot 424 assigned specifically to do so) or a completely random path 425 (doctors moving from one camp to another). 427 o Priority-dependent or popularity-dependent name-based replication: 428 By allowing spatial and temporal scoping of named messages, 429 priority based replication depending on the scope of a given 430 message is possible. Clearly, spreading information in disaster 431 cases involves space and time factors that have to be taken into 432 account as messages spread. A concrete approach for such scope- 433 based prioritisation of ICN messages in disasters, called 'NREP', 434 has been proposed [Psaras2014] , where ICN messages have 435 attributes such as user-defined priority, space, and temporal- 436 validity. These attributes are then taken into account when 437 prioritizing messages. In [Psaras2014] , evaluations show how 438 this approach can be applied to the use case 'Delivering Messages 439 to Relatives/Friends' decribed in Section 4. In [Seedorf2016], a 440 scheme is presented that enables to estimate the popularity of ICN 441 interest messages in a completely decentralized manner among data 442 mules in a scenario with random, unpredictable movements of ICN 443 data mules. The approach exploits the use of nonces associated 444 with end user requests, common in most ICN architectures. It 445 enables for a given ICN data mule to estimate the overall 446 popularity (among end-users) of a given ICN interest message. 447 This enables data mules to optimize content dissemination with 448 limited caching capabilities by prioritizing interests based on 449 their popularity. 451 o Information Resilience through Decentralised Forwarding: In a 452 dynamic or disruptive environment, such as the aftermath of a 453 disaster, both users and content servers may dynamically join and 454 leave the network (due to mobility or network fragmentation). 455 Thus, users might attach to the network and request content when 456 the network is fragmented and the corresponding content origin is 457 not reachable. In order to increase information resilience, 458 content cached both in in-network caches and in end-user devices 459 should be exploited. A concrete approach for the exploitation of 460 content cached in user devices is presented in [Sourlas2015] . The 461 proposal in [Sourlas2015] includes enhancements to the NDN router 462 design, as well as an alternative Interest forwarding scheme which 463 enables users to retrieve cached content when the network is 464 fragmented and the content origin is not reachable. Evaluations 465 show that this approach is a valid tool for the retrieval of 466 cached content in disruptive cases and can be applied to tackle 467 the challenges presented in Section 3.1 . 469 o Energy Efficiency: A large-scale disaster causes a large-scale 470 blackout and thus a number of base stations (BSs) will be operated 471 by their batteries. Capacities of such batteries are not large 472 enough to provide cellular communication for several days after 473 the disaster. In order to prolong the batteries' life from one 474 day to several days, different techniques need to be explored: 475 Priority control, cell-zooming, and collaborative upload. Cell 476 zooming switches-off some of the BSs because switching-off is the 477 only way to reduce power consumed at the idle time. In cell 478 zooming, areas covered by such inactive BSs are covered by the 479 active BSs. Collaborative communication is complementary to cell 480 zooming and reduces power proportional to a load of a BS. The 481 load represents cellular frequency resources. In collaborative 482 communication, end-devices delegate sending and receiving messages 483 to and from a base station to a representative end-device of which 484 radio propagation quality is better. The design of an ICN-based 485 publish/subscribe protocol that incorporates collaborative upload 486 is ongoing work. In particular, the integration of collaborative 487 upload techniques into the COPSS (Content Oriented Publish/ 488 Subscribe System)} framework is envisioned [COPSS2011] . 490 o Data-centric confidentiality and access control: In ICN, the 491 requested content is not anymore associated to a trusted server or 492 an endpoint location, but it can be retrieved from any network 493 cache or a replica server. This call for 'data-centric' security, 494 where security relies on information exclusively contained in the 495 message itself, or, if extra information provided by trusted 496 entities is needed, this should be gathered through offline, 497 asynchronous, and non interactive communication, rather than from 498 an explicit online interactive handshake with trusted servers. 499 The ability to guarantee security without any online entities is 500 particularly important in disaster scenarios with fragmented 501 networks. One concrete cryptographic technique is 'Ciphertext- 502 Policy Attribute Based Encryption' (CP-ABE), allowing a party to 503 encrypt a content specifying a policy, which consists in a Boolean 504 expression over attributes, that must be satisfied by those who 505 want to decrypt such content. Such encryption schemes tie 506 confidentiality and access-control to the transferred data, which 507 can be transmitted also in an unsecured channel, enabling the 508 source to specify the set of nodes allowed to decrypt. 510 o Decentralised authentication of messages: Self-certifying names 511 provide the property that any entity in a distributed system can 512 verify the binding between a corresponding public key and the 513 self-certifying name without relying on a trusted third party. 514 Self-certifying names thus provide a decentralized form of data 515 origin authentication. However, self-certifying names lack a 516 binding with a corresponding real-world identity. Given the 517 decentralised nature of a disaster scenario, a PKI-based approach 518 for binding self-certifying names with real-world identities is 519 not feasible. Instead, a Web-of-Trust can be used to provide this 520 binding. Not only are the cryptograohic signatures used within a 521 Web-of-Trust independent of any central authority; there are also 522 technical means for making the inherent trust relationships of a 523 Web-of-Trust available to network entities in a decentralised, 524 'offline' fashion, such that information received can be assessed 525 based on these trust relationships. A concrete scheme for such an 526 approach has been published in [Seedorf2014] , where also concrete 527 examples for fulfilling the use case 'Delivering Messages to 528 Relatives/Friends' with this approach are given. 530 6. Conclusion 532 This document outlines some research directions for Information 533 Centric Networking (ICN) with respect to applying ICN approaches for 534 coping with natural or human-generated, large-scale disasters. The 535 document describes high-level research challenges as well as a 536 general rationale why ICN approaches could be beneficial to address 537 these challenges. Further, the document provides an overview of 538 examples for concrete ICN-based solutions that address the previously 539 outlined research challenges. 541 7. References 543 7.1. Normative References 545 [RFC5050] Scott, K. and S. Burleigh, "Bundle Protocol 546 Specification", RFC 5050, DOI 10.17487/RFC5050, November 547 2007, . 549 [RFC6920] Farrell, S., Kutscher, D., Dannewitz, C., Ohlman, B., 550 Keranen, A., and P. Hallam-Baker, "Naming Things with 551 Hashes", RFC 6920, DOI 10.17487/RFC6920, April 2013, 552 . 554 [RFC7476] Pentikousis, K., Ed., Ohlman, B., Corujo, D., Boggia, G., 555 Tyson, G., Davies, E., Molinaro, A., and S. Eum, 556 "Information-Centric Networking: Baseline Scenarios", 557 RFC 7476, DOI 10.17487/RFC7476, March 2015, 558 . 560 7.2. Informative References 562 [COPSS2011] 563 Chen, J., Arumaithurai, M., Jiao, L., Fu, X., and K. 564 Ramakrishnan, "COPSS: An Efficient Content Oriented 565 Publish/Subscribe System", Seventh ACM/IEEE Symposium on 566 Architectures for Networking and Communications Systems 567 (ANCS), 2011. 569 [dtnrg] Fall, K. and J. Ott, "Delay-Tolerant Networking Research 570 Group - DTNRG", https://irtf.org/dtnrg. 572 [Greifenberg2008] 573 Greifenberg, J. and D. Kutscher, "Efficient publish/ 574 subscribe-based multicast for opportunistic networking 575 with self-organized resource utilization", Advanced 576 Information Networking and Applications-Workshops, 2008. 578 [Psaras2014] 579 Psaras, I., Saino, L., Arumaithurai, M., Ramakrishnan, K., 580 and G. Pavlou, "Name-Based Replication Priorities in 581 Disaster Cases", 2nd Workshop on Name Oriented Mobility 582 (NOM), 2014. 584 [Robitzsch2015] 585 Robitzsch, S., Trossen, D., Theodorou, C., Barker, T., and 586 A. Sathiaseel, "D2.1: Usage Scenarios and Requirements"", 587 H2020 project RIFE, public deliverable, 2015. 589 [Seedorf2014] 590 Seedorf, J., Kutscher, D., and F. Schneider, 591 "Decentralised Binding of Self-Certifying Names to Real- 592 World Identities for Assessment of Third-Party Messages in 593 Fragmented Mobile Networks", 2nd Workshop on Name 594 Oriented Mobility (NOM), 2014. 596 [Seedorf2016] 597 Seedorf, J., Kutscher, D., and B. Gill, "Decentralised 598 Interest Counter Aggregation for ICN in Disaster 599 Scenarios", Workshop on Information Centric Networking 600 Solutions for Real World Applications (ICNSRA), 2016. 602 [Sourlas2015] 603 Sourlas, V., Tassiulas, L., Psaras, I., and G. Pavlou, 604 "Information Resilience through User-Assisted Caching in 605 Disruptive Content-Centric Networks", 14th IFIP 606 NETWORKING, May 2015. 608 [Trossen2015] 609 Trossen, D., "IP over ICN - The better IP?", 2015 610 European Conference onNetworks and Communications (EuCNC), 611 June/July 2015, pp. 413 - 417. 613 [Yoneki2007] 614 Yoneki, E., Hui, P., Chan, S., and J. Crowcroft, "A socio- 615 aware overlay for publish/subscribe communication in delay 616 tolerant networks", Proceedings of the 10th ACM Symposium 617 on Modeling, Analysis, and Simulation of Wireless and 618 Mobile Systems, 2007. 620 Appendix A. Acknowledgment 622 The authors would like to thank Ioannis Psaras for useful comments. 623 Also, the authors are grateful to Christopher Wood and Daniel Corujo 624 for valuable feedback and suggestions on concrete text for improving 625 the document. Further, the authors would like to thank Joerg Ott and 626 Dirk Trossen for valuable comments and input, in particular regarding 627 existing work from the DTN community which is highly related to the 628 ICN approaches suggested in this document. 630 This document has been supported by the GreenICN project (GreenICN: 631 Architecture and Applications of Green Information Centric Networking 632 ), a research project supported jointly by the European Commission 633 under its 7th Framework Program (contract no. 608518) and the 634 National Institute of Information and Communications Technology 635 (NICT) in Japan (contract no. 167). The views and conclusions 636 contained herein are those of the authors and should not be 637 interpreted as necessarily representing the official policies or 638 endorsements, either expressed or implied, of the GreenICN project, 639 the European Commission, or NICT. More information is available at 640 the project web site http://www.greenicn.org/. 642 Authors' Addresses 644 Jan Seedorf 645 HFT Stuttgart - Univ. of Applied Sciences 646 Schellingstrasse 24 647 Stuttgart 70174 648 Germany 650 Phone: +49 711 8926 2801 651 Fax: +49 711 8926 2553 652 Email: jan.seedorf@hft-stuttgart.de 654 Mayutan Arumaithurai 655 University of Goettingen 656 Goldschmidt Str. 7 657 Goettingen 37077 658 Germany 660 Phone: +49 551 39 172046 661 Fax: +49 551 39 14416 662 Email: arumaithurai@informatik.uni-goettingen.de 663 Atsushi Tagami 664 KDDI R&D Labs 665 2-1-15 Ohara 666 Fujimino, Saitama 356-85025 667 Japan 669 Phone: +81 49 278 73651 670 Fax: +81 49 278 7510 671 Email: tagami@kddilabs.jp 673 K. K. Ramakrishnan 674 University of California 675 Riverside CA 676 USA 678 Email: kkramakrishnan@yahoo.com 680 Nicola Blefari Melazzi 681 University Tor Vergata 682 Via del Politecnico, 1 683 Roma 00133 684 Italy 686 Phone: +39 06 7259 7501 687 Fax: +39 06 7259 7435 688 Email: blefari@uniroma2.it