A Parallel Ant Colony Optimization Algorithm for All-Pair Routing in MANETs
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Application-specific protocol architectures for wireless networks
Application-specific protocol architectures for wireless networks
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Cluster-Head Election Using Fuzzy Logic for Wireless Sensor Networks
CNSR '05 Proceedings of the 3rd Annual Communication Networks and Services Research Conference
Compact Genetic Algorithm for Performance Improvement in Hierarchical Sensor Networks Management
ISPAN '05 Proceedings of the 8th International Symposium on Parallel Architectures,Algorithms and Networks
Solar-aware clustering in wireless sensor networks
ISCC '04 Proceedings of the Ninth International Symposium on Computers and Communications 2004 Volume 2 (ISCC"04) - Volume 02
Genetic Algorithm for Energy Efficient Clusters in Wireless Sensor Networks
ITNG '07 Proceedings of the International Conference on Information Technology
Two-Phase Stochastic Optimization to Sensor Network Localization
SENSORCOMM '07 Proceedings of the 2007 International Conference on Sensor Technologies and Applications
Cluster Based Routing Protocol for Mobile Nodes in Wireless Sensor Network
Wireless Personal Communications: An International Journal
Computational Intelligence in Wireless Sensor Networks: A Survey
IEEE Communications Surveys & Tutorials
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
Introduction to Evolutionary Algorithms
Introduction to Evolutionary Algorithms
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In real life scenario for wireless sensor networks (WSNs), energy heterogeneity among the sensor nodes due to uneven terrain, connectivity failure, and packet dropping is a crucial factor that triggered the race for developing robust and reliable routing protocols. Prolonging the time interval before the death of the first sensor node, viz. the stability period, is critical for many applications where the feedback from the WSN must be reliable. Although Low Energy Adaptive Clustering Hierarchy (LEACH) and LEACH-like protocols are fundamental and popular clustering protocols to manage the system's energy and thus to prolong the lifespan of the network, they assume a near to a perfect energy homogeneous system where a node failure, drainage and re-energizing are typically not considered. More recent protocols like Stable Election Protocol (SEP) considers the reverse, i.e., energy heterogeneity, and properly utilizes the extra energy to guarantee a stable and reliable performance of the network system. While paradigms of computational intelligence such as evolutionary algorithms (EAs) have attracted significant attention in recent years to address various WSN's challenges such as nodes deployment and localization, data fusion and aggregation, security and routing, they did not (to the best of our knowledge) explore the possibility of maintaining heterogeneous-aware energy consumption to guarantee a reliable and robust routing protocol design. By this, a new protocol named stable-aware evolutionary routing protocol (SAERP), is proposed in this paper to ensure maximum stability and minimum instability periods for both homogeneous/heterogeneous WSNs. SAERP introduces an evolutionary modeling, where the cluster head election probability becomes more efficient, to well maintain balanced energy consumption in both energy homogeneous and heterogeneous settings. The performance of SAERP over simulation for 90 WSNs is evaluated and compared to well known LEACH and SEP protocols. We found that SAERP is more robust and always ensures longer stability period and shorter instability period.