The broadcast storm problem in a mobile ad hoc network
Wireless Networks - Selected Papers from Mobicom'99
Tabu Search
A parallel genetic algorithm to solve the set-covering problem
Computers and Operations Research
Approximation algorithms for combinatorial problems
STOC '73 Proceedings of the fifth annual ACM symposium on Theory of computing
Handbook of Approximation Algorithms and Metaheuristics (Chapman & Hall/Crc Computer & Information Science Series)
Power-Efficient and Path-Stable Broadcasting Scheme for Wireless Ad Hoc Networks
AINAW '07 Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02
Analysis of MPR Selection in the OLSR Protocol
AINAW '07 Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02
Mobility Versus Density Metric for OLSR Enhancement
AINTEC '07 Proceedings of the 3rd Asian conference on Internet Engineering: Sustainable Internet
Local search algorithm for unicost set covering problem
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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MultiPoint Relay (MPR) selection algorithm is a flooding technique for propagating a broadcast message inside an ad-hoc network which reduces the number of unnecessary broadcast messages in order to save more energy in the network, minimize the number of packet collisions, and speed up the propagation time. In this paper, we demonstrate that MPR selection is an application of Set Covering Problem (SCP). A few optimization methods are developed in this work to find the optimum solution including Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), and a new greedy algorithm. Extensive simulations are set up to evaluate the developed methods. The new algorithm is named Energy eFficient MPR or EF-MPR in short. The simulation results show that EF-MPR can reduce the number of MPR nodes up to 19%. Moreover, EF-MPR algorithm reduces the power-consumption of network up to 12% and speed up the propagation time by 9%.