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Coding Opportunity Aware Backbone Metrics for Broadcast in Wireless Networks

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5 Author(s)
Shuai Wang ; Dept. of Comput. Sci. & Eng., Univ. of Minnesota, Minneapolis, MN, USA ; Guang Tan ; Yunhuai Liu ; Hongbo Jiang
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Reducing transmission redundancy is key to efficient broadcast in wireless networks. A standard approach to achieving this goal is to create a network backbone consisting of a subset of nodes that are responsible for data forwarding, while other nodes act as passive receivers. On top of this, network coding (NC) is often used to further reduce unnecessary transmissions. The main problem with existing backbone and NC combinations is that the backbone construction process is blind of what is needed by NC, thus may produce a structure that limits the power of NC algorithms. To address this problem, we propose Coding Opportunity Aware Backbone (COAB) metrics, which seek to maximize coding opportunities when selecting backbone forwarders. We show that the backbone construction process guided by our metrics leads to significantly increased coding frequency, at the cost of minimal localized information exchange. The highlight of our work is COAB's broad applicability and effectiveness. We integrate the COAB metrics with ten state-of-the-art broadcast algorithms specified in eight publications [1]-[8], and evaluate COAB with a running testbed of 30 MICAz nodes and extensively simulations. The experimental results show that our design outperforms the existing schemes substantially.

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Parallel and Distributed Systems, IEEE Transactions on  (Volume:25 ,  Issue: 8 )