A Multicast Routing Algorithm Using Movement Prediction for Mobile Ad Hoc Networks

1. A Multicast Routing Algorithm Using Movement Prediction for Mobile Ad Hoc Networks Huei-Wen Ferng, Ph.D. Assistant Professor Department of Computer Science and Information Engineering (CSIE) Nation Taiwan University of Science and Technology (NTUST) Wireless Communications and Networking Engineering (WCANE) Lab E-mail: hwferng@mail.ntust.edu.tw URL: http://mail.ntust.edu.tw/~hwferng

2. Introduction Description of the proposed protocol Numerical examples and discussions Conclusions Outline NTUST/WCANE Lab

3. Introduction (1/2) • The multicast communication is a challenging issue in MANETs because of frequent topology changes. • Approaches to update states of neighbors • Soft state approach vs. Hard state approach • Two categories of multicast algorithms • Mesh-based vs. Tree-based • A few routing algorithms in MANETs • Ad-hoc On-demand Distance Vector (AODV) • On Demand Multicast Routing Protocol (ODMRP) NTUST/WCANE Lab

4. Introduction (2/2) • Goal • To propose a tree-based routing algorithm with hard state update called Tree-based Multicast Routing Algorithm with Movement Prediction (TMRAMP) • Features • Less overhead • Prediction-based • Local path search and recovery NTUST/WCANE Lab

5. Introduction Description of the proposed protocol Numerical examples and discussions Conclusions Outline NTUST/WCANE Lab

6. TMRAMP • The algorithm is composed of three parts • Movement prediction • Routing protocol • Local path search and recovery NTUST/WCANE Lab

7. Movement Prediction • Assume that the moving speeds, coordinates, and directions of two mobile nodes, say node 1 and node 2, are given, then we can calculate the connection time Dtusing the following equation (by Su, Lee, and Gerla) • where NTUST/WCANE Lab

8. Routing Protocol • The source first broadcasts a Join Request packet which includes the necessary information. • A node upon receiving a Join Request packet determines if it is a duplicate. • If it is not duplicate and the Hop Count (HP) is still smaller a pre-specified threshold, movement prediction is applied to estimate the link connection time (LCT) between this node and its upstream node. • Set RCT=min( LCT, RCT), where RCT stands for Route Connection Time. • The modified packet is broadcasted to neighbors. NTUST/WCANE Lab

9. Routing Protocol • For a group member, it further chooses the path with the largest RCT since multiple Join Request packets may be received from different paths. • Of course, a member routing table is maintained at each node such that Join Reply packets sent by group members are able to return back to the sender along the chosen paths. NTUST/WCANE Lab

10. Local Path Search and Recovery • We assume that all necessary information is available and is put into packets so as to make GPS work. • By setting a threshold BeginHandoff, a node canestimate the time when the link will terminate. • When the estimated connection time falls below the threshold, the node will issue the Rejoin packet to its neighbors. NTUST/WCANE Lab

11. Local Path Search and Recovery • A neighboring node upon receiving the packet first checks • Duplicate? On-treenode? • If it is not duplicate and an on-tree node, a Reply Rejoin (with estimated connection life time) is sent; otherwise, Rejoin packet is broadcasted to neighbors. • For the disconnected node, a path with the longest life time is chosen as a new path. • If no path can be found, the disconnected node tries repeatedly to contact any on-tree node with scope one hop larger until at least one is found. NTUST/WCANE Lab

12. Local Path Search and Recovery NTUST/WCANE Lab

13. Introduction Description of the proposed protocol Numerical examples and discussions Conclusions Outline NTUST/WCANE Lab

14. Simulation Arrangements NTUST/WCANE Lab

15. Performance Metrics • (Data) packet delivery ratio • Number of control packets transmitted per data packet received -> reflect overhead • Number of data packets received per data packet transmitted -> represent routing efficiency NTUST/WCANE Lab

16. Simulation Results TMRAMP outperforms ODMRP by reducing 20% to 60% of overhead. NTUST/WCANE Lab

17. Simulation Results TMRAMP performs better by gaining 10% to 15% more routing efficiency than ODMRP. NTUST/WCANE Lab

18. Simulation Results TMRAMP outperforms ODMRP by reducing 10% to 30% of overhead. In general, about 40% improvement can be achieved by TMRAMP as compared to ODMRP. NTUST/WCANE Lab

19. Introduction Description of the proposed protocol Numerical examples and discussions Conclusions Outline NTUST/WCANE Lab

20. Conclusions • TMRAMP is about 20% to 60% higher under various moving speeds and 10% to 30% higher under various group sizes than ODMRP in overhead. • TMRAMP outperforms ODMRP in routing efficiency by 10% to 15% under various moving speeds and up to 40% under various group sizes. • A scheme using tree-based routing is more suitable than that using mesh-base routing when applied to an environment with a large group. • Hence, we suggest TMRAMP to be used in MANETs. NTUST/WCANE Lab

21. Thank You! NTUST/WCANE Lab