Vehicular Content Centric Network (VCCN): A Survey and Research Challenges
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This document discusses vehicular content centric networks (VCCN) and related challenges. It provides an overview of vehicular networks, content centric networking (CCN), and how CCN could be applied to vehicular networks. The document identifies several challenges for VCCN, including data structures for content names, interests, and routing with high mobility. Preliminary results show the potential benefits of VCCN in reducing interest satisfaction delay and processing overhead compared to conventional networks. Future work is needed to develop smarter forwarding, efficient data structures, and evaluate the impact of various design decisions.
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Vehicular Content Centric Network (VCCN): A Survey and Research Challenges
- 1. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr Vehicular Content Centric Network (VCCN): A Survey and Research Challenges Safdar H. Bouk, Syed H. Ahmed and Dongkyun Kim 4/20/2015 1 ACM SAC 2015 Salamanca, Spain April 13-17 2015
- 2. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr Agenda • Motivation • Vehicular Networks • Content Centric Networking (CCN) • Vehicular CCN • Challenges • Preliminary Results • Conclusion and Future Work 4/20/2015 2
- 3. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr Motivation 4/20/2015 3 Source: http://share.cisco.com/vni14/ 1. Internet Users 1. 2. Networked Devices 2. 3. M2M Connections 3. 4. IP Traffic 4.
- 4. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr Motivation The Mobile Network Through 2018 Mobile data traffic: • Surpass 15EB monthly by 2018. • Worldwide mobile connection speed will surpass 2 Mbps by 2016. • Smartphones data traffic will reach 66% of mobile data traffic by 2018. • Mobile tablet traffic will surpass 2.5 EB/month by 2018. • 4G traffic will be more than half of the total mobile traffic by 2018. TB = Terabyte (1000 GB) PB = Petabyte (1000 TB) EB = Exabyte (1000 PB) Source: Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2013–2018 Communication of huge amount of DATA/CONTENTS with addressed devices. Information Centric Networking 4/20/2015 4
- 5. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr Network Today Today’s Networking: ◦ Device Centric ◦ Communicate by addressing the device. ◦ >90% of traffic is accessing different kind of Content. ◦ Inefficient for Content/data dissemination. ◦ Multicast ~ at huge cost of Network resources. ◦ Addressing ~ Inefficient : DNS, IPv6, etc. to identify devices. ◦ Service Discovery ~ Many protocols, with no standard. ◦ Mobility? ~ Achievable but not inherent in today’s networks. ◦ Security? ~ Connection: IPSec, VPN, SSL, but not Content …. Result --> spam. 4/20/2015 5
- 6. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr Vehicular Network • Highly dynamic topology. • Unpredictable link lifetime. • Safety and Non-Safety applications. • Large data requirements. • Delay constraints, etc. • With/Without infrastructure support. • Data ranges from short messages to Large video contents. V2V Communication V2I / I2V Communication 4/20/2015 6
- 7. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr Information Centric Networking (ICN) ICN represents the third revolution in telecommunication networks…. Van Jacobson ◦ Information/Contents/Data are at the center of networking not nodes/machines. ◦ Name DATA not Location/Device. ◦ Pull based consumer driven communication: ◦ Broadcast Interest Packet ~ Wait for Data Packet ◦ Request DATA in Network (Not data provider/host) ◦ Any node with the DATA (or copy in its Cache), Responds the Request. (Authenticate Data not connection). ◦ Less delay, More Security, DNS…. 4/20/2015 7
- 8. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr Vehicular Information Centric Network V2V Communication V2I Communication Name Prefixes Out. Face(s) FIB Names In. Face(s) PIT CS Maintained at each Vehicle Name each content • Maintaining Names (specially in PIT) • Data Structure with minimum space…. • Fast addition and deletion of names …. • Searching Names from PIT and FIB. • Speed and accuracy. • Forwarding based on the search result. 4/20/2015 8
- 9. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr Vehicular Information Centric Network 4/20/2015 9 Node D Node E Node C Node B Node A CS Check PIT Check FIB Check Add In Face in PIT NO NO YES YES NoYES Interest DATA Interest Drop/NACK Add CS? Remove PIT Entry YES No DATA DATA Discard DATA PIT Check Downstream Upstream Interest Forwarding Data Forwarding CONSUMER PROVIDER
- 10. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr Challenges 4/20/2015 10 Contents Interest Mobility CS, FIB, PIT Security Naming Routing / Forwarding Caching VCCN
- 11. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr Preliminary Results 4/20/2015 11 0 5 10 15 20 25 30 35 40 45 50 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Avg.No.ofSatisfiedInterests/hop Satisfied Interests - 1/2s Satisfied Interests - 4/2s Satisfied Interests - 7/2s 0 0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 AverageSatisfactionDelay(s) HOPS Conv. Satisfied Interests - 1/2s Prop. Satisfied Interests - 1/2s 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 AverageSatisfactionDelay HOPS Conv. Satisfied Interests - 7/2s Prop. Satisfied Interests - 7/2s Tx 500 Node 90 Speed 70
- 12. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr Preliminary Results 4/20/2015 12 Tx 500 Node 90 Speed 70 0.0048 0.005 0.0052 0.0054 0.0056 0.0058 0.006 0.0062 0.0064 1 2 3 4 5 6 7 InterestSatisfactionDelay(s) Interest/2s Proposed 1 Proposed 2 Conventional ICN 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 1 2 3 4 5 6 7 No.ofProcessedDataPkts Interest/2s Proposed 1 Proposed 2 Conventional ICN 0 0.2 0.4 0.6 0.8 1 1.2 1 2 3 4 5 6 7 Max.PITEntryTime(s) Interests/2s Proposed 1 Proposed 2 Conventional ICN
- 13. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr Conclusion We identified the challenges in the Vehicular Information Centric Networks. The current focus is on Data and Interest flooding minimization. Content Naming scheme for Vehicular Networks. Future Work Smart Forwarding. Efficient PIT, FIB and CS Search. Effect of PIT, FIB and CS Size on Interest Satisfaction Rate and Delay. …….. 4/20/2015 13
- 14. 4/20/2015 14 KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr Thanks
- 15. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr What Next…. VANET/V2X Which ICN architecture? Naming? Requester Mobility: OK Provider Mobility: ? Role of RSUs? Role of Backoffice Network? Routing? Caching Policy? Security? 4/20/2015 15
- 16. KYUNGPOOK NATIONAL UNIVERSITY, Daegu, Korea. MoNet Laboratory www.monet.knu.ac.kr ICN Working Principle Routing Table The concept of an ICN does not force applications to take on host-centric information. Instead, it detaches the application from such concerns. Gareth Tyson et al. Where’s in the name? 4/20/2015 16