Paper Info
Title
Energy-Efficient Differentiated Coverage Of Dynamic Objects Using An Improved Evolutionary Multi-Objective Optimization Algorithm With Fuzzy-Dominance
Abstract
We present an energy efficient sensor manager for differentiated coverage of dynamic object group changing their positions with time. The information about the location of the object group is provided to the sensor manager. The manager invokes optimization algorithm whenever the obtained coverage falls below a threshold to sleep schedule the sensor network. Multi-objective Optimization (MO) algorithms help in finding a better trade-off among energy consumption, lifetime, and coverage. Here the motion of the particle is modeled to follow a polynomial variation and with a constant acceleration. We formulate the scheduling problem as a combinatorial, constrained and multi-objective optimization problem with energy and non-coverage as the two objectives to be minimized. The proposed scheme uses a recent variant of a powerful MO algorithm known as Decomposition based Multi-Objective Evolutionary Algorithm (MOEA/D). Systematic comparison with the original MOEA/D and another well-known MO algorithm, NSGA-II (Non-dominated Sorting Genetic Algorithm) quantifies the superiority of the proposed approach.
Year
DOI
Venue
2012
10.1109/CEC.2012.6256541
2012 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
Keywords
Field
DocType
Wireless sensor networks, differentiated coverage, node deployment, density control, evolutionary multi-objective optimization
Mathematical optimization,Job shop scheduling,Evolutionary algorithm,Computer science,Efficient energy use,Algorithm,Evolutionary computation,Sorting,Multi-objective optimization,Optimization problem,Genetic algorithm
Conference
Citations 
PageRank 
References 
4
0.42
15
Authors
5
Name
Order
Citations
PageRank
Soumyadip Sengupta121110.08
Swagatam Das26026276.66
Md Nasir31234.75
Athanasios V. Vasilakos412735523.55
W. Pedrycz5139661005.85