infocom06-lof - Learn on the Fly Data-driven Link...

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Unformatted text preview: Learn on the Fly: Data-driven Link Estimation and Routing in Sensor Network Backbones Hongwei Zhang Anish Arora Prasun Sinha Computer Science and Engineering The Ohio State University, USA { zhangho, anish, prasun } @cse.ohio-state.edu Abstract — In the context of IEEE 802.11b network testbeds, we examine the differences between unicast and broadcast link properties, and we show the inherent difficulties in precisely estimating unicast link properties via those of broadcast beacons even if we make the length and transmission rate of beacons be the same as those of data packets. To circumvent the difficulties in link estimation, we propose to estimate unicast link properties directly via data traffic itself without using periodic beacons. To this end, we design a data-driven routing protocol Learn on the Fly (LOF). LOF estimates link quality based on data traffic, and it chooses routes by way of a locally measurable metric ELD, the expected MAC latency per unit-distance to the destination . Using a realistic sensor network traffic trace and an 802.11b testbed of 195 Stargates, we experimentally compare the performance of LOF with that of existing protocols, represented by the geography-unaware ETX and the geography-based PRD. We find that LOF reduces end-to-end MAC latency by a factor of 3 and enhances energy efficiency by a factor up to 2.37, which demonstrate the feasibility as well as potential benefits of data- driven link estimation and routing. I. INTRODUCTION Wireless sensor networks are envisioned to be of large scale, comprising thousands to millions of nodes. To guarantee real- time and reliable end-to-end packet delivery in such networks, they usually require a high-bandwidth network backbone to process and relay data generated by the low-end sensor nodes such as motes [3]. This architecture has been demonstrated in the sensor network field experiment ExScal [6], where 203 Stargates and 985 XSM motes were deployed in an area of 1260 meters by 288 meters. Each Stargate is equipped with a 802.11b radio, and the 203 Stargates form the backbone network of ExScal to support reliable and real-time communi- cation among the motes for target detection, classification, and tracking. Similar 802.11 based sensor networks (or network backbones) have also been explored in other projects such as MASE [1] and CodeBlue [2]. In this paper, we study how to perform routing in such 802.11 based wireless sensor network backbones. As the quality of wireless links, for instance, packet delivery rate, varies both temporally and spatially in a complex manner [7], [19], [28], estimating link quality is an important aspect of routing in wireless networks. Existing routing protocols [11], [12], [13], [23], [25] periodically exchange broadcast beacons between peers for link quality estimation. Nevertheless, link quality for broadcast beacons differs significantly from that for unicast data, because broadcast beacons and unicast data differ in packet size, transmission rate, and coordination method at...
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infocom06-lof - Learn on the Fly Data-driven Link...

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