Cross-layer Optimal Decision Policies for Spatial Diversity Forwarding in Wireless Ad Hoc Networks

1. Cross-layer Optimal Decision Policies for Spatial Diversity Forwarding in Wireless Ad Hoc Networks Rensselaer Polytechnic Institute Prof. Alhussein Abouzeid Joint work with Jing Ai & Zhenzhen Ye

2. Jing Ai Hussein Abouzeid Zhenzhen Ye (if we were here)

3. Outline • Spatial Diversity Forwarding • Motivation • Related work • Problem formulation of Optimal Stopping Relaying • Implementation of OSR • Evaluations of OSR • Analytical results • Simulation results • Summary

4. Spatial Diversity Forwarding: Motivation & Related Work • Motivation: Exploiting spatial diversity inherent in multi-hop wireless networks • Observation: There naturally exist alternate next-hop relays with high probability that one of them has favorable channel condition at any given instant! • The key challenge is design of strategy for next-hop selection. Prior work can be classified into two classes: • FSR (First Stopping Relaying) [JD05, WZF04, etc.] • Selects the first relay that replies to the forwarding node. (Problem: though minimum overheads incurred, the selected relay may be poor in quality.) • LSR (Last Stopping Relaying) [SM05] • Collecting CSI from all candidate relays and then selecting the best one. (Problem: though the selected relay might be (if CSI is not outdated) the best, it incurs the maximum delay.) • We propose OSR: Exploiting the range between these extreme cases.

5. Problem formulation of optimal stopping relaying (OSR) • Optimal stopping relaying: investigate and design spatial-diversity forwarding policies based on a formally defined stochastic decision framework. • Mapping next-hop selection problem to a sequential optimal stopping problem • The Decision maker: the forwarding node which has a packet to be forwarded • Every time step, the decision maker observes a random variable which is the state (e.g. channel quality) of the next available candidate. It also computes the reward up to that point in time. • Action: whether to “stop” at a candidate next-hop relay and forward the packet to it, or “continue” observing other candidates • Policy:The goal of the problem is to derive an optimal policy (i.e. a rule for deciding which action to take at every decision instant) in order to maximize the expected reward.

6. A B Problem formulation of OSR (cont.) • A “conceptual” decision making procedure of OSR Channel Quality: 2 Channel Quality? 2 Channel Quality? Channel Quality: 7 7 2 is low, continue! 7 is good enough, stop! Channel Quality: 8

7. Problem formulation of OSR (cont.) • Given:a forwarding node ns which intends to forward a packet toward its destination and a set of L candidate next-hop relays {n1, n2, . . . , nL} known at the routing layer, which can be characterized by L independent discrete random variables (rewards) {Θ1,Θ2, . . . ,ΘL}. • Problem: what is the optimal policy at the forwarding node ns to select the next-hop relay to which the packet is to be forwarded so as to maximize the expected reward E{Θ}? • Θ is defined as d*Rdata, a generalization of Information Efficiency (IE) • Solution: the optimal policyis a threshold-based policy • easy to implement

8. Implementation of OSR • Physical layer: rayleigh fading channels • determined the channel quality statistics if known long-term average • MAC layer: an extended MAC anycast scheme based on IEEE 802.11 • perform the “optimal stopping” decision-making procedure • Network layer: Greedy geographic routing [BMSU99,BK00] • take charge of selecting a set of candidate next-hop relays at a forwarding node

9. MAC layer anycast • Motivation • transform “costly” sequential decision-making procedure at the forwarding node to a relatively “cheap” parallel decision-making procedure on the relay side. • MRTS-CTS dialogue • Multicast RTS (MRTS) carries the threshold-based policy • CTS comes from the relay selected by the optimal stopping policy • Feedbacks collision resolution • it is possible that more than one candidate next-hop relay qualified to relay the packet by performing the threshold-based policy issued by the forwarding node • prioritized the responses of relays in an order pre-assigned by the forwarding node • with CSMA, the response of a higher-priority relay can suppress the responses of lower-priority relays

10. MAC layer anycast (cont.) • A sample timeline of the OSR scheme for three candidate next-hop relays

11. OSR v.s. FSR: Analytical Results • Scenario • X-axis represents the average SNR • Y-axis represents the gain OSR over FSR in terms of IE • L homogenous candidate next-hop relays • Main observation • FSR can not utilize more than two candidate relays as efficiently as OSR, especially when channels quality is average

12. LSR v.s. OSR: Simulation Results (Qualnet) • Comparison of end-to-end performance metrics in Qualnet [QUA] • Grid topology (8X8 grid), a single TCP flow • throughput • Random topology, multiple TCP flows (not included due to space limit) • Static random topology, multiple UDP flows • packet delivery ratio • end-to-end delay • jitter • Mobile topology, multiple UDP flows (not included due to space limit)

13. Impact of Fading Velocity (vm) on Average FTP Throughput • Note: M is a protocol parameter in geographic routing that specifies the maximum order of spatial diversity that can be utilized by a forwarding node • Observation: In OSR, larger M means better performance (which is what we want). Not true for LSR (due to overheads)

14. Impact of Traffic Load on CBR flows

15. Summary & Future Work • Formulated the next-hop relay selection problem as a sequential decision problem and derived the Optimal Stopping Relaying (OSR) policies for improving spatial diversity gain in wireless ad hoc networks • Implement OSR in a realistic protocol stack • Both analytical and simulation results reveal that OSR outperforms FSR and LSR in terms of IE/end-to-end performance metrics • Enable nodes to learn the fading channel characteristics online instead of relying on a channel model • Extend such a decision framework to flow/service differentiation schemes.

16. References • [BK00] B. Karp and H T. Kung, “GPSR: greedy perimeter stateless routing for wireless networks,” in Proc. ACM/IEEE Mobicom 2000. • [BMSU99] Prosenjit Bose, Pat Morin, Ivan Stojmenovic and Jorge Urrutia, “Routing with guaranteed delivery in ad hoc wireless networks,” in Proc. DIALM, 1999. • [JD05] S. Jain and S. R. Das, “Exploiting path diversity in the link layer in wireless ad hoc networks,” in Proc. IEEE WoWMoM, 2005. • [JZF04] J. Wang, H. Zhai and Y. Fang, “Reliable and efficient packet forwarding by utilizing path diversity in wireless ad hoc networks,” in Proc. IEEE Milcom, 2004. • [QUA] “Qualnet 3.7 user’s guide.” http://www.scalable-networks.com/. • [SM05] M. R. Souryal and N. Moayeri, “Channel-adaptive relaying in mobile ad hoc networks with fading,” in Proc. IEEE SECON, 2005.

17. Thank You! • Questions? abouza@rpi.edu