Abstract
Routing optimization is a promising platform in wireless sensor network (WSN) for many researchers to work on various problems related to the balancing of performance parameters required by an application. In a sensor network, multipath routing protocol design is influenced by many factors, which includes hardware constraints, scalability, operating environment, reliability, topology, fault tolerance, transmission media, and power consumption which are addressed by many researchers. Balancing of these factors plays vital role in designing a routing protocol because they are application specific and vary from one application to another. All these performance metrics which are considered as application requirement must be measurable, independent and comparable. This paper focuses on designing a framework that balances the various performance metrics to get near optimal solution for multipath routing in WSNs. This framework is a hybrid approach that combines the dynamic programming model of DNA sequence algorithm with the existing Multipath routing algorithms to get the optimized routing sequence to balance the real time traffic and non-real time traffic on the multiple paths with improved energy and throughput parameters. Simulation results confirms the significant improvement in throughput performance and packet delivery ratio, substantial reduction in energy consumption against standard Multipath routing protocols.
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