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Towards a New Routing Framework in MANETs Task 3: Theory of Scalable and Robust Protocols

Towards a New Routing Framework in MANETs Task 3: Theory of Scalable and Robust Protocols. Marcelo Carvalho, Hari Rangarajan, Marco Spohn, Ravindra Vaishampayan, Rolando Menchaca, Zhenjiang Li J.J. Garcia-Luna-Aceves. University of California, Santa Cruz jj@soe.ucsc.edu.

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Towards a New Routing Framework in MANETs Task 3: Theory of Scalable and Robust Protocols

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  1. Towards a New Routing Framework in MANETsTask 3: Theory of Scalable and Robust Protocols Marcelo Carvalho, Hari Rangarajan, Marco Spohn, Ravindra Vaishampayan, Rolando Menchaca, Zhenjiang Li J.J. Garcia-Luna-Aceves University of California, Santa Cruz jj@soe.ucsc.edu http://www.cse.ucsc.edu/research/ccrg/home.html

  2. Outline • Summary of results obtained over the past year • Analytical models, routing, multicasting • Recent results on ordering in distributed algorithms • Plan for the next year.

  3. Summary of Results: Analytical Models of MAC Protocols • First analytical model of IEEE 802.11 DCF that considers directional antennas or space time block codes (STBC) operating in a multihop MANET taking into account the characteristics of PHY layer in detail. • Effective SINR of the Alamouti scheme under multiple access interference (MAI). • A new Markov model for the operation of the IEEE 802.11DCF that includes: (a) the impact of the carrier-sensing activity, (b) the finite-retry limit of frame retransmissions, and (c) the impact of errors in both control and data frames within a four-way handshake. • M. Carvalho, "Analytical Modeling of Medium Access Control Protocols in Wireless Networks," PhD Thesis, Computer Engineering, University of California, Santa Cruz, CA 95064, March 2006. • M. Carvalho and J.J. Garcia-Luna-Aceves, ``Modeling Wireless Ad Hoc Networks with Directional Antennas,'' Proc. IEEE Infocom 2006, Barcelona, Spain, 23--29 April, 2006. • M. Carvalho and J.J. Garcia-Luna-Aceves, ``Analytical Modeling of Ad Hoc Networks that Utilize Space-Time Coding,'' Proc. IEEE WiOpt 2006: 4th Intl. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, Boston, Massachusetts, April 3--7, 2006.

  4. Summary of Results: Distributed QoS Routing in MANETs • First distributed algorithms for QoS routing with multiple constraints that only require local information to operate. • MPOR (multi-constrained path optimization routing) algorithm supports (a) multi-constrained path selection (finding feasible paths satisfying constraints) and (b) multi-constrained path optimization (obtaining feasible paths that are optimal w.r.t. optimization metric. • Key ideas: • Define “logical distance” computed by an optimization function that is monotone and isotone. • Compute a k-optimal path set (the first k shortest paths w.r.t. logical distance) for each destination using ordering invariants. • Z. Li and J.J. Garcia-Luna-Aceves, ``Finding Multi-Constrained Feasible Paths by Using Depth-First Search,'' accepted for publication in ACM WINET Journal, 2005. • Z. Li and J.J. Garcia-Luna-Aceves, ''A Distributed Approach for Multi-Constrained Path Selection and Routing Optimization'', Proc. QShine 06: Third International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks, Waterloo, Ontario, Canada, August 7-9, 2006.

  5. Summary of Results: Multicast Routing in MANETs • Robustness through learning and and cross-layer designs for mesh-based multicast routing in MANETs • Incorporation of directional antennas in mesh-bsed multicasting. • Ravindra Vaishampayan, "Efficient and Robust Multicast Routing in Mobile Ad Hoc Networks," PhD Thesis, Computer Science, University of California, Santa Cruz, CA 95064, March 2006. • R. Vaishampayan and J.J. Garcia-Luna-Aceves, ``An Adaptive Redundancy Protocol for Mesh Based Multicasting,'' accepted for publication in Computer Communications Journal, special issue on Advances in Computer Communication Networks, 2006. • R. Vaishampayan and J.J. Garcia-Luna-Aceves, ``Cross Layer Ad hoc Multiple Channel Multicasting Protocol,'' Proc. IEEE MASS 2006, Vancouver, Canada, October 9--12, 2006. • R. Menchaca-Mendez, R. Menchaca-Mendez and J.J. Garcia-Luna-Aceves, "ADMP: An Adaptive Multicast Routing Protocol for Mobile Ad Hoc Networks," Proc. 19th IFIP World Computer Congress, Santiago, Chile,August 20--25, 2006. • R. Vaishampayan and J.J. Garcia-Luna-Aceves, ``Efficient Multicasting in Multi-Hop Ad Hoc Networks Using Directional Antennas,'' Proc. IEEE MASS 2005: 2nd IEEE International Conference on Mobile Ad-Hoc and Sensor Systems, 7--10 November 2005, Washington, D.C.

  6. Summary of Results: Dominating Sets in MANETs • The first distributed algorithm that solves the (k, r) domination problem in arbitrary graphs and MANETs using only local information: • Each node is covered by k dominating nodes that are at most r hops away. • Applicable to many problems in protocol design for multicasting, broadcasting and topology control. • Marco A. Spohn, "Domination in Graphs in the Context of Mobile Ad Hoc Networks," PhD Thesis, Computer Science, University of California, Santa Cruz, CA 95064, 2005 • M.A. Spohn and J.J. Garcia-Luna-Aceves, ``Bounded-Distance Multi-Clusterhead Formation in Wireless Ad Hoc Networks,'' Ad Hoc Networks Journal, accepted for publication, 2006. • M.A. Spohn and J.J. Garcia-Luna-Aceves, ``Multicasting in Ad Hoc Networks in the Context of Multiple Channels and Multiple Interfaces,'' Proc. International Workshop on Localized Communication and Topology Protocols for Ad hoc Networks (LOCAN 2005) 7 November 2005, Washington, D.C.

  7. Summary of Results: Secure and Robust Routing in MANETs • The first secure routing algorithm for MANETs based on self-certifying keys. • Enables secure routing in disrupted networks; no need for connectivity to a certifying authority once the network is deployed. • Z. Li and J.J. Garcia-Luna-Aceves, ``Non-Interactive Key Establishment in Mobile Ad Hoc Networks,'' accepted for publication in Ad Hoc Networks, 2006. • Z. Li and J.J. Garcia-Luna-Aceves, `` New Non-Interactive Key Agreement and Progression (NIKAP) Protocols and Their Applications to Security in Ad Hoc Networks,'' Proc. International workshop on Wireless and Sensor Networks Security (WSNS'05), 7 November 2005, Washington, D.C.

  8. Summary of Results: Distributed Ordering in MANETs • The first on-demand routing algorithm for MANETs based only on source-based sequence numbers. • Much better performance and much simpler than AODV, DSR, and variations on destination-based sequence numbers or path caching. • Proof that routing framework based on distributed ordering sequences is feasible. • Hari Rangarajan, "Robust Loop-free On-demand Routing in Ad hoc Networks," PhD Thesis, Computer Engineering, University of California, Santa Cruz, CA 95064, June 2006. • H. Rangarajan and J.J. Garcia-Luna-Aceves, ``Efficient Use of Route Requests for Loop-free On-demand Routing in Ad hoc Networks,'’ accepted for publication in Computer Networks, Elsevier, 2006. • H. Rangarajan and J.J. Garcia-Luna-Aceves, ``On-demand Loop-Free Routing in Ad hoc Networks Using Source Sequence Numbers,'' Proc. IEEE MASS 2005: 2nd IEEE International Conference on Mobile Ad-Hoc and Sensor Systems, 7--10 November 2005, Washington, D.C. Best Paper Award

  9. Distributed Ordering Using Source Sequence Numbers Motivation: • All on-demand routing protocols require unique identifiers for RREQs, all dissemination protocols require unique IDs for packets being disseminated. • All on-demand routing schemes to date have used additional mechanisms to ensure loop freedom (e.g., AODV uses destination sequence-numbers, DSR uses source-routes). • We have to identify RREQs and disseminated packets! • Can we realize routing protocols and dissemination protocols that maintain ordering solely on the basis of the sequence numbers already used to identify RREQs or similar messages? • Does the new approach attain the desired simplicity with the same or better performance than previous schemes?

  10. Distributed Ordering Using Source Sequence Numbers Approach: • Use the source sequence labels (SSL) needed in RREQs to build destination-based directed acyclic graphs (DAG). • Since multiple DAGs can be created, each node remembers the DAG in which it participates, and its neighbors inform it of the DAG in which they collaborated. • Ensure that no node can “jump back” to a prior DAG, which can create loops. • A node can change its relative order by changing DAGs • Nodes use an SSL and a reported sequence label (RSL) to uniquely identify a DAG in the presence of topology changes. • RSL is used to avoid joining the wrong DAGs • SSL is used together with RSL for ordering within a DAG to enable local repairs • Enable local repairs based on the ordering of nodes within a DAG. • Many strategies are possible. • We have only explored the simplest ones.

  11. A SSL (C,2) RSL (A,2) SSL (C,2) RSL (A,2) SSL (C,2) RSL (F,2) SSL (C,2) RSL (F,2) F G B SSL (C,2) RSL (G,1) SSL (C,2) RSL (G,1) SSL (A,1) RSL (B,1) SSL (A,1) RSL (B,1) SSL (A,1) RSL (A,1) C SSL (C,2) RSL (C,2) SSL (C,2) RSL (C,2) X SSL (A,1) RSL (C,1) D SSL (A,1) RSL (A,1) SSL (A,1) RSL (A,1) SSL (C,2) RSL (A,2) 1 2 Loop-freedom when Destination Replies (DLSR) A RREQ 1 RREP 1 F G RREQ 2 B RREP 2 C X D Node A cannot accept RREP from B, Because it belongs to an invalid DAG Node A can only accept RREPs in DAG 2, or become part of a new DAG.  Valid DAG at Node A:

  12. Intermediate node replies in AODV SN: 1 SN: 1 SN: 1 X Y Z S D A B C SN: 1 SN: 1 SN: 1 SN: 2 SN: 1 Only a node with SN > 1 can answer source S’s RREQ. All RREQs will have to be answered by the destination.

  13. SSDL: [(A,1), inf) A SSL (A,2) RSL (A,2) A SSDL: [(A,2),2) P P SSDL: [(A,1),2) B B SSL (A,2) RSL (P,1) Q Q SSDL: [(A,1),1) SSDL: [(A,2),1) C C SSL (A,2) RSL (Q,1) D D [(A,2), 1)] is fresher than [(A,2), 2) is fresher than [(A,1), inf] Distances as Labels for Local Repairs (LSR-D) A SSDL: [(A,1), inf ) SSL (A,1) RSL (A,1) B SSDL: [(A,1),2) SSL (A,1) RSL (B,1)] SSDL: [(A,1),1) C SSL (A,1) RSL (C,1)] D [(A,1), 1)] is fresher than [(A,1), 2) is fresher than [(A,1), inf] We can use source-sequence numbers instead of destination-sequence numbers to identify fresh distances

  14. Performance Summary * Standard test scenarios

  15. Packet Delivery Ratio 30-random flows, 100 nodes SSL-based Protocols AODV, DSR, OLSR

  16. Control Overhead 30-random flows, 100 nodes AODV SSL-based protocols, OLSR DSR: Drops data packets

  17. Delivery Latency 30-random flows, 100 nodes DSR,OLSR AODV SSL-based protocols

  18. Implications • We have shown that distributed ordering of nodes in dynamic networks is possible using SSLs (same information needed to disseminate packets w/o replications). • Performance results show that this new way or ordering nodes renders protocols that are simpler (in logic) and out-perform the current state-of-the-art MANET routing protocols in terms of packet delivery, delivery latency, and control overhead. • Protocols for any type of routing and dissemination (proactive and on-demand unicast, multicast, dissemination, publish-subscribe, etc.) can be cast as a problem of distributed ordering in graphs. • So, we have the start of a new framework for routing in dynamic networks.

  19. Next Steps • Develop a unified framework for routing in MANETs centered around “distributed ordering of sequences” • Integrate routing and scheduling using the notion of ordering in a neighborhood and ordering in the network. • Limit signaling overhead incurred in informing nodes about interest in certain destinations or the presence of such destinations while nodes move.

  20. Distributed Ordering in Routing MAX ordering sequence (2) i (3) (4) u g R (5) k f (1) (2) h p j e (3) MIN (0) (4) m RREQ, Update, Subscription, Interest c d (1) v b R (3) (5) (3) (2) (4) a Nodes are ordered for each destination, which can be a node, a service, content or a role. Ordering is maintained as nodes move around carrying content. Ordering of nodes forms a directed acyclic graph (DAG) independently of any routing metric used

  21. Distributed Ordering in Routing MAX ordering sequence (2) i (3) (4) u g R (5) k f (1) (2) h p j e (3) MIN (0) (4) m RREQ, Update, Subscription, Interest c d (1) v b R (3) (5) (3) (2) (4) a Load balancing and constraints (e.g., end-to-end delay and jitter) used for forwarding over DAG. Constraints can be made part of the ordering

  22. Different than Virtual Circuits! i (3) (4) x g R (5) source k f h p j e (3) (4) m c d y (3) b R (5) (3) (2) (4) a Nodes b, h, and x can reply to the request (for route, content, service) from p, rather than just d (destination, origin of content or service). Each node has multiple paths to reach destination while satisfying the given constraints.

  23. Proactive Routing: Too many nodes are forced to know about how to reach each destination! Does not work well with random partitions Path first, then data forwarding c f D D h e a S Information about D propagates away from D in a circle of radius r b

  24. On-Demand Routing: Too many nodes are forced to help find or repair ways to reach a few destinations! (RREQ flooding). Does not work with partitioned networks! Path first, then data forwarding Nodes with paths to D reply to S. Information from S propagates away from S in a circle of radius r c f D h e a S S Too few nodes keep state for D. So too many nodes try to fix broken paths b

  25. Epidemic Routing Too many nodes are forced to relay data from S to D. Does not work with partitioned networks, unless infinite storage is assumed. Data create paths Information from S propagates away from S in a circle of radius r c f D h e a S S b

  26. Goal Limit the number of nodes that incur signaling and forwarding overhead between S and D c f Region of interest is a function of the source and destination D h e a S b

  27. Goal Limit the number of nodes that incur signaling and forwarding overhead between S and D c f Conjecture: Use elipitic curves defined by the distances to source and destination D D h e a S S b

  28. f Goals Enable Correct Signaling and Forwarding in Partitioned Networks. Preserve efficiency in each network component D e h S

  29. J.J. Garcia-Luna-Aceves (PI) Hamid Sadjadpour Katia Obraczka Muriel Medard Andrea Goldsmith Pravin Varaiya Rajive Bagrodia Mario Gerla Jennifer Hou Nitin Vaidya Tony Ephremides UCSC: MIT: Stanford University: UC Berkeley: UCLA: UIUC: University of Maryland: http://www.soe.ucsc.edu/research/ccrg/DAWN

  30. Summary of Scientific Progress • 19 journal papers published or accepted for publication. • ACM WINET, ACM/IEEE Trans. Networking, IEEE Trans. Comm., IEEE Trans. Wireless Comm., ACM Trans. Sensor Networks, Computer Communications, Ad Hoc Networks • 35 peer-reviewed papers in conference proceedings • ACM Mobicom, ACM Mobihoc, ACM SIGCOMM, IEEE Infocom, IEEE WiOpt, IEEE MASS, IEEE Qshine, IEEE ICC, IEEE IPSN • One Best Paper Award (IEEE MASS 2005) • 8 Invited papers • 12 manuscripts • 13 Ph.D. theses completed, at least 2 graduates with faculty positions • Active and growing intercampus collaboration (e.g., UCLA-MIT, UCLA-UCSC, Stanford-MIT)

  31. Summary of Scientific Progress (2) • More accurate treatments of the effects of the physical layer in the protocol stack • First analytical models that accurately reflect the impact of node mobility in links and paths • New approaches on how MAI should be treated • New modeling tools for the characterization of energy consumption in MANETs • New performance trade-offs involving node complexity, node mobility, packet length, channel utilization, and delay. • First results on network coding applied to unicasting and multicasting in MANETs • The first algorithm for on-demand routing that operates solely with source-originated sequence numbers • New approaches to information dissemination • New optimization techniques for large-scale simulations

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