1. Energy-aware Self-stabilizing Multicasting for MANETs Tridib Mukherjee IMPACT Lab Arizona State University impact.asu.edu

2. IPDPS 2007 03/28/07 2 Mobile Ad hoc Networks (MANETs) Network Model mobile nodes (PDAs, laptops etc.) multi-hop routes between nodes no fixed infrastructure A B C D A D B C Network Characteristics Dynamic Topology Constrained resources  battery power Links formed and broken with mobility Applications Battlefield operations Disaster Relief Personal area networking Multi-hop routes generated among nodes

3. IPDPS 2007 03/28/07 3 Motivation Traditional Routing Protocols  No action localization Routing information exchange across the network. Scalability is an issue. MANETs No Fixed Infrastructure Dynamic Topology Energy Constraints AdaptabilityEnergy- efficiency Localized Actions Routing Requirements Network Characteristics  Two basic types Proactive – DSDV, TBRPF, IAR, FSR, etc.  Adaptive but NOT energy-efficient Reactive – AODV, ODMRP, etc.  Adaptive & Energy-efficient but high latency.

4. IPDPS 2007 03/28/07 4 Designed for Sensor Networks Data dissemination from sensors in the vicinity of actions. Does not address mobile nodes  Can not guarantee adaptability. Fixed infra-structure (base station / sink).  Not Applicable for MANETs. Localized Algorithms Activity Sources Sink Algorithms for MANETs are not Action Localized and develop routes to locations where destination is located.

5. IPDPS 2007 03/28/07 5 Self-stabilization in Distributed Computing Valid State Invalid State Applied to Multicasting in MANETs Convergence Closure Fault Topological Changes and Node Failures for MANETs. Local actions in distributed nodes. Self-stabilizing distributed systems Guarantee convergence to valid state through local actions in distributed nodes. Ensure closure to remain in valid state until any fault occurs. Can adapt to topological changes Can it be used for routing in MANETs?

6. IPDPS 2007 03/28/07 6 Self-stabilizing Multicast for MANETs Multicast source Topological Change Convergence Based on Local actions Maintains source-based multi-cast tree. Actions based on local information in the nodes and neighbors. Best effort model. Pro-active neighbor monitoring through periodic beacon messages. Neighbor check at each round (with at least one beacon reception from all the neighbors) Trigger actions only in case of changes in the neighborhood. Self-Stabilizing Shortest Path Spanning Tree (SS-SPST) How applicable is self-stabilization for MANETs?

7. IPDPS 2007 03/28/07 7 Problems Energy-awareness Fault diffusion  improper sequence of node execution  leads to high stabilization latency  Fault-containment can reduce latency Energy-awareness in self-stabilizing multicast Energy-efficient tree construction algorithm Energy Consumption Model (Min Energy Bcast / Mcast is NP Complete) Heuristics for Tree Construction (E.g. BIP/MIP, S-REMIT) Reducing beacon transmission Verify effect on the performance Level = k - 1 Level = k Level = k + 1 A B C E D F G Level becomes k + 2 Goal: Solve these problems

8. IPDPS 2007 03/28/07 8 Outline Energy Consumption Model Protocol Specification Fault-containment Simulation Study

9. IPDPS 2007 03/28/07 9 Energy Consumption Model T i reaches all nodes in range i TiTi Overhearing at j, k, and l i j k l non-intended neighbor No communication schedule during broadcast in random access MAC (e.g. 802.11). Transmission energy of node i Variable through Power Control One transmission reaches all in range Cost metric for node i C i = T i + N i x R Reception energy at intended neighbors. Overhearing energy at non-intended neighbors. Reception cost at all the neighbors intended neighbor C i = T i + 7R What is the additional cost if a node selects a parent?

10. IPDPS 2007 03/28/07 10 Energy Aware Self-Stabilizing Protocol (SS-SPST-E) A B F C E D X Select Parent with minimum Additional Cost Minimum overall cost when parent is locally selected Execute action when any action trigger is on Tree validity – Tree will remain connected with no loops. Not in tree Loop Detected Potential Parents of XAdditionalCost (A → X) = T A + 2R AdditionalCost (B → X) = T B + R Actions at each node (parent selection) Identify potential parents. Estimate additional cost after joining potential parent. Select parent with minimum additional cost. Change distance to root. Action Triggers Parent disconnection. Parent additional cost not minimum. Change in distance of parent to root.

11. IPDPS 2007 03/28/07 11 SS-SPST-E Execution S B A D C F E H No multicast tree  parent of each node NULL.  hop distance from root of each node infinity.  cost of each node is E max. First Round – source (root) stabilizes  hop distance of root from itself is 0.  no additional cost. Second Round – neighbors of root stabilizes  hop distance of root’s neighbors is 1.  parent of root’s neighbors is root. 2 2 2 2 2 2 2 3 1 AdditionalCost (S → {A, B, C, D} ) = T s + 4R No potential parents for any node. Potential parent for A, B, C, D, F = {S}. Potential parent for E = {D, F}. AdditionalCost (F → E) = T F + 2R AdditionalCost (D → E) = T D + 3R Potential parent for F = {S, C}. AdditionalCost (S → F) = T S + R AdditionalCost (C → F) = T C + 3R And so on …… Tolerance to topological changes. AdditionalCost (D → E) = T D + 3R Convergence - From any invalid state the total energy cost of the graph reduces after every round till all the nodes in the system are stabilized. Proof - through induction on round #. Closure: Once all the nodes are stabilized it stays there until further faults occur. G 1 1 Multicast source AdditionalCost (S → F) = T s + 5R

12. IPDPS 2007 03/28/07 12 Stabilization Latency Stabilization Latency for SS-SPST-E is O(N).  Prove by induction on the height of the tree. Base Case – height is 1  Only one node (Root Node).  Stabilization latency O(1). Induction Hypothesis – height is m  Total nodes M = ∑ i = 1 to m c (i – 1).  Stabilization latency O(M). Induction Step – height is m + 1  Worst case time to receive beacons from nodes at level m is O(c m ).  Stabilization latency is O(∑ i = 1 to m c (i – 1) + c m ) = O(∑ i = 1 to (m + 1) c (i – 1) ) = O(N). height = 1 height = m height = m + 1 Number of nodes = c 1-1 =1 Number of nodes = c m - 1 Number of nodes = c m

13. IPDPS 2007 03/28/07 13 Fault-containment over SS-SPST-E (SS-SPST-FC) Local actions are not taken for every action trigger. Enforce proper sequence of node execution. Contains effect of fault  No fault diffusion. Additional information in beacons.  increases energy consumption. Can reduce stabilization latency considerably  O(N) for SS-SPST-E.  O(1) for SS-SPST-FC. Level = k - 1 Level = k Level = k + 1 A B C E D F G Select Parent with minimum Additional Cost only if local action is required Action trigger is on Check if local actions in the neighbors can remove the trigger

14. IPDPS 2007 03/28/07 14 Simulation Model Goals  performance analysis with beacon reduction.  study reliability energy-efficiency trade-off.  scalability study with number of receivers.  comparative analysis with SS-SPST – non-energy efficient self-stabilizing multicast MAODV – tree-based multicast ODMRP – mesh-based multicast NS-2 used for simulating 50 nodes placed at random positions  Random way-point mobility model.  Omni-directional antenna with power control.  CBR packets @ 64Kbps. Performance Measures: 1. Packet Delivery Ratio (PDR) - for reliability 2. Energy Consumed / Packet Delivered - for energy efficiency

15. IPDPS 2007 03/28/07 15 Simulation Results – Varying Beacon Interval PDR decreases with less beaconing

16. IPDPS 2007 03/28/07 16 Simulation Results – Varying Beacon Interval Energy consumption per packet delivered increases due to decrease in number of packets delivered.

17. IPDPS 2007 03/28/07 17 Simulation Results – Varying Node Mobility Low packet delivery with high dynamicity ODMRP has high PDR due to redundant routes

18. IPDPS 2007 03/28/07 18 Simulation Results – Varying Node Mobility SS-SPST-E leads to energy-efficiency ODMRP has high overhead to generate redundant routes SS-SPST-FC has higher energy-consumption than SS-SPST-E

19. IPDPS 2007 03/28/07 19 Simulation Results - Varying Multicast Group Size Self-stabilizing protocols scale better. MAODV has highest delay due to reactive tree construction

20. IPDPS 2007 03/28/07 20 Simulation Results - Varying Multicast Group Size ODMRP leads to high control overhead and less PDR.

21. IPDPS 2007 03/28/07 21 Conclusions & Future Work SS-SPST-E provides energy-efficiency and action localization.  High adaptability to topological changes. SS-SPST-FC further increases packet delivery.  Decreases stabilization latency. SS-SPST-E and SS-SPST-FC lead to group-scalability. Energy wastage in beaconing if less or no multicast traffic. Future Work  Optimizing periodic beacon transmission.  Applying adaptive localization to other energy-efficient multicast (BIP/MIP etc.).

22. IPDPS 2007 03/28/07 22 References Internet Engineering Task Force (IETF) Mobile Ad Hoc Networks (MANET) Working Group Charter. http://www.ietf.org/html.charters/manet-charter.html. http://www.ietf.org/html.charters/manet-charter.html Q. Zhao, L. Tong. Energy Efficiency of Large-Scale Wireless Networks: Proactive Versus Reactive Networking. IEEE Journal on Selected Areas in Communications, Vol. 23, No. 5, May, 2005. E. W. Dijkstra, “Self Stabilizing systems in spite of distributed control”, In Proc. Communications of the ACM, November 1974. S. K. S. Gupta and P. K. Srimani. “Self-Stabilizing Multicast Protocols for Ad Hoc Networks”. Journal of Parallel and Distributed Computing, 2003. E. Royer and C. E. Perkins. ”Multicast operation of the ad-hoc on-demand distance vector routing protocol”. In Proc. Of the 5th ACM/IEEE Annual Conf. On Mobile Computing and Networking, August 1999. S. Meguerdichian, S. Slijepcevic, V. Karayan, M. Potkonjak. “Localized Algorithms In Wireless Ad-Hoc Networks: Location Discovery And Sensor Exposure”. In 2nd ACM International Symposium on Mobile Ad Hoc Networking & Computing. 2001 M. Gerla, S. J. Lee and C. C. Chang. ”On-Demand multicast routing protocol (ODMRP) for ad hoc networks”. In Proc. Of IEEE Wireless Communications and Networking Conference 1999, LA, September 1999. S. Vaudevan, C. Zhang, D. Goeckel, D. Towsley. “Optimal Power Allocation in Wireless Networks with Transmitter-Receiver Power Tradeoff Proc. INFOCOM’06, 2006.

23. IPDPS 2007 03/28/07 23 Questions ???