Impact of interference on multi-hop wireless network performance
Proceedings of the 9th annual international conference on Mobile computing and networking
All maximal independent sets and dynamic dominance for sparse graphs
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Fundamentals of wireless communication
Fundamentals of wireless communication
Wireless Communications & Mobile Computing - Medium Access Control Protocols for Wireless Ad Hoc Networks
ICNC '08 Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 01
Lifetime-resource tradeoff for multicast traffic in wireless sensor networks
IEEE Transactions on Wireless Communications
An Improved Independent Set Ordering Algorithm for Solving Large-Scale Sparse Linear Systems
IHMSC '10 Proceedings of the 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics - Volume 01
Network coding-aware routing in wireless networks
IEEE/ACM Transactions on Networking (TON)
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In wireless ad hoc networks, one of the most important issues impacting performance is wireless interference between adjacent nodes. Such interference problem has often been approached to find independent sets in a topological graph. In general, the topological graph have exponentially many independent sets and and thus it is very difficult to find the optimal independent sets for high performance. It is known that this problem belongs to the class of NP-hard problems. To deal with this problem, heuristic methods such as greedy algorithm, local search and genetic algorithm have been usually used. Such heuristics are useful to speed up the process of finding a satisfactory solution, however they do not guarantee the optimality of the solution found. In this paper, we develop a linearization technique to transform the nonlinear equations into linear ones. Then, we propose a novel integer linear programming (ILP)-based optimization design not only to properly find the optimal independent sets, but also to appropriately schedule wireless nodes for high performance. Based on the priority of the multiple objectives, our design is presented as a two-stage problem and optimizes the system sequentially. Numerical results demonstrate the effectiveness of the proposed optimization design.