Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization in Computer Networks Using Metaheuristics
Multi-Objective Optimization in Computer Networks Using Metaheuristics
ICDCSW '09 Proceedings of the 2009 29th IEEE International Conference on Distributed Computing Systems Workshops
Multi-objective Cross-Layer Algorithm for Routing over Wireless Sensor Networks
SENSORCOMM '09 Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications
Wireless Sensor Networks
ISWPC'10 Proceedings of the 5th IEEE international conference on Wireless pervasive computing
Routing techniques in wireless sensor networks: a survey
IEEE Wireless Communications
APNOMS'07 Proceedings of the 10th Asia-Pacific conference on Network Operations and Management Symposium: managing next generation networks and services
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This paper presents a distributed N-to-1 multipath routing for Wireless Sensor Network (WSN) which addresses as a Multi-objective Optimization Problem (MOP), where three function was optimized with the aim to do an efficient use of the energy in the network and decrease the possibility of packet loss. These functions are: hop count, energy consumption, and free space loss. The simultaneous optimization of these three functions is a NP-complete problem and intends to use a software implementation of Multi-Objective Evolutionary Algorithms (MOEA), specifically the Strength Pareto Evolutionary Algorithm (SPEA2) to solve it.