Opportunity-based Topology Control in Wireless Sensor Networks

1. Opportunity-based Topology Control in Wireless Sensor Networks IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS |||| Date: 2009.12.30 Speaker: Chang, Chien-Yang

2. Outline • Introduction • Related Work • System Model • CONREAP • Performance Evaluation • Conclusion

3. Introduction • Topology control is an effective method to improve the energy efficiency of wireless sensor networks (WSNs) • connectivity-based topology control • reliable links • opportunity-based topology control • lossy link • reliable links

4. Related Work • Connectivity-based topology control • Cone-Based Topology Control (CBTC)

5. System Model • Assumptions • individual link reachability is available • the link reachability is fixed • the link reach ability is pretty stable (not asymmetric) • the node is stationary • only sink-to-sensors communications • Without consideration • do not consider the node failure • no node sleeping is considered in this work. • no congestion or packet collision is considered either.

6. Motivation

7. Problems • Reachability Preserving Problem (RPP) • data-critical applications • to minimize the energy cost while guaranteeing that the network reachability is no less than a given threshold • Energy Preserving Problem • long-term monitoring • to maximize the network reachability while guaranteeing that the network energy cost is no greater than a given threshold • Efficiency Maximization Problem • no constraint on energy or network reachability • to maximize the reachability-energy ratio

8. Basic Idea • Reachability Preserving Problem • Greedy algorithm

9. CONREAP • Initially, v broadcasts a “Hello” message and initials its neighbor set Nbv

10. CONREAP • Step2. from the known λTi(u), v selects a node ui that provides v the highest tree reachability λTi(v) as its parent node in the tree 0.8 0.4 0.2 0.9

11. CONREAP • Step3. node v selects the tree with the highest λTi (v) to join, denoted as and

12. CONREAP • Step4. Upon receiving the Nbv node reachability, v updates avg(˜λGR(v)) Until

13. Performance Evaluation • Experiment parameters • 50 Berkeley Mica2 nodes • uniformly deployed • transmission power: -10dbm • maximal distance: 5 hops • link reachability is measured using 1000 “Hello” messages • receivers continuously measure the link quality and piggyback the results to senders

14. Performance Evaluation • Experiment results

15. Performance Evaluation • Simulation parameters • evaluate CONREAP in a large scale of 200 nodes • fixed-size field of 300m × 300m • 1/9 of the simulated wireless links are reliable • the other 8/9 are lossy links

16. Performance Evaluation • Simulation results

17. Conclusion • We propose a novel opportunity-based topology control • We focus on the reachability preserving problem • this problem is NP-hard • we propose CONREAP algorithm by exploring reliability theory • we prove that CONREAP has the guaranteed network reachability and the energy cost can be significantly reduced • the worst running time is O(|E|) and the space requirement is O(d)