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Channel allocation and medium access control for wireless sensor networks

✍ Scribed by Kaushik R. Chowdhury; Nagesh Nandiraju; Pritam Chanda; Dharma P. Agrawal; Qing-An Zeng


Publisher
Elsevier Science
Year
2009
Tongue
English
Weight
389 KB
Volume
7
Category
Article
ISSN
1570-8705

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✦ Synopsis


Recent developments in sensor technology, as seen in Berkeley's Mica2 Mote, Rockwell's WINS nodes and the IEEE 802.15.4 Zigbee, have enabled support for single-transceiver, multi-channel communication. The task of channel assignment with minimum interference, also named as the 2-hop coloring problem, allows repetition of colors occurs only if the nodes are separated by more than 2 hops. Being NP complete, development of efficient heuristics for this coloring problem is an open research area and this paper proposes the Dynamic Channel Allocation (DCA) algorithm as a novel solution. Once channels are assigned, a Medium Access Control protocol must be devised so that channel selection, arbitration and scheduling occur with maximum energy savings and reduced message overhead, both critical considerations for sensor networks. The contribution of this paper is twofold: (1) development and analysis of the DCA algorithm that assigns optimally minimum channels in a distributed manner in order to make subsequent communication free from both primary and secondary interference and (2) proposing CMAC, a fully desynchronized multi-channel MAC protocol with minimum hardware requirements. CMAC takes into account the fundamental energy constraint in sensor nodes by placing them in a default sleep mode as far as possible, enables spatial channel re-use and ensures nearly collision free communication. Simulation results reveal that the DCA consumes significantly less energy while giving a legal distributed coloring. CMAC, our MAC protocol that leverages this coloring, has been thoroughly evaluated with various modes in SMAC, a recent protocol that achieves energy savings through coordinated sleeping. Results show that CMAC obtains nearly 200% reduction in energy consumption, significantly improved throughput, and end-to-end delay values that are 50-150% better than SMAC for our simulated topologies.


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