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Energy optimization and coverage area optimization of wireless sensor networks (WSN) are two major challenges to accomplish reliability optimization in the field of WSN. Reliability optimization in the field of WSN is directly connected to the performance and efficiency and consistency of the network. In this paper, the authors describe how these challenges can be resolved by designing an efficient WSN with the help of meta-heuristic algorithms. They have configured an optimized route/path using ant colony optimization (ACO) algorithm and deployed static WSN nodes. After configuring an efficient network, if we can maximize the coverage area, then we can ensure that the network is a reliable network. For coverage area optimization, they used a hybrid differential evolution-quantum behaved particle swarm optimization (DE-QPSO) algorithm. The result has been compared with existing literature, and the authors found good results applying those meta-heuristic and hybrid algorithms.

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During the past few years, advances in mobile communication theory have enabled the development and deployment of different wireless technologies, complementary to each other. Hence, their integration can realize a unified wireless system that has the best features of the individual networks. Next-Generation Wireless Systems (NGWS) integrate different wireless systems, each of which is optimized for some specific services and coverage area to provide ubiquitous communications to the mobile users. In this paper, we propose to enhance the handoff performance of mobile IP in wireless IP networks by reducing the false handoff probability in the NGWS handoff management protocol. Based on the information of false handoff probability, we analyze its effect on mobile speed and handoff signaling delay.

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