Name
Abstract | ||
|---|---|---|
Opportunistic routing is widely known to have substantially better performance than traditional unicast routing in wireless networks with lossy links. However, wireless sensor networks are heavily duty-cycled, i.e. they frequently enter deep sleep states to ensure long network life-time. This renders existing opportunistic routing schemes impractical, as they assume that nodes are always awake and can overhear other transmissions. In this paper, we introduce a novel opportunistic routing metric that takes duty cycling into account. By analytical performance modeling and simulations, we show that our routing scheme results in significantly reduced delay and improved energy efficiency compared to traditional unicast routing. The method is based on a new metric, EDC, that reflects the expected number of duty cycled wakeups that are required to successfully deliver a packet from source to destination. We devise distributed algorithms that find the EDC-optimal forwarding, i.e. the optimal subset of neighbors that each node should permit to forward its packets. We compare the performance of the new routing with ETX-optimal single path routing in both simulations and testbed-based experiments. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/SECON.2012.6275795 | Sensor, Mesh and Ad Hoc Communications and Networks |
Keywords | Field | DocType |
telecommunication network routing,wireless sensor networks,EDC-optimal forwarding,ETX-optimal single path routing,duty cycled wireless sensor networks,lossy links,network life-time,opportunistic routing,optimal subset,unicast routing | Multipath routing,Equal-cost multi-path routing,Link-state routing protocol,Dynamic Source Routing,Static routing,Computer science,Policy-based routing,Computer network,Wireless Routing Protocol,Geographic routing,Distributed computing | Conference |
ISSN | ISBN | Citations |
2155-5486 E-ISBN : 978-1-4673-1903-4 | 978-1-4673-1903-4 | 12 |
PageRank | References | Authors |
0.63 | 12 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Euhanna Ghadimi | 1 | 275 | 13.75 |
| Olaf Landsiedel | 2 | 562 | 43.33 |
| Pablo Soldati | 3 | 364 | 30.34 |
| mikael johansson | 4 | 1612 | 147.94 |