AEECA for Reliable Communication to Enhance the Network Life Time for WSN

Nowadays,wireless sensor networks play a vital role in our day to day life.Wireless communication is preferred for many sensing applications due its convenience,flexibility and effectiveness.The sensors to sense the environmental factor are versatile and send sensed data to central station wirelessly.The cluster based protocols are provided an optimal solution for enhancing the lifetime of the sensor networks.In this paper,modified K-means++algorithm is used to form the cluster and cluster head in an efficient way and the Advanced Energy-Efficient Cluster head selection Algorithm(AEECA)is used to calculate the weighted fac-tor of the transmission path and effective data collection using gateway node.The experimental results show the proposed algorithm outperforms the existing routing algorithms.

Router and gateway node placement in wireless mesh networks for emergency rescue scenarios

The focus of this paper is on base functionalities required for UAV-based rapid deployment of an ad hoc communication infrastructure in the initial phases of rescue operations.The main idea is to use heterogeneous teams of UAVs to deploy communication kits that include routers,and are used in the generation of ad hoc Wireless Mesh Networks(WMN).Several fundamental problems are considered and algorithms are proposed to solve these problems.The Router Node Placement problem(RNP)and a generalization of it that takes into account additional constraints arising in actual field usage is considered first.The RNP problem tries to determine how to optimally place routers in a WMN.A new algorithm,the RRT-WMN algorithm,is proposed to solve this problem.It is based in part on a novel use of the Rapidly Exploring Random Trees(RRT)algorithm used in motion planning.A comparative empirical evaluation between the RRT-WMN algorithm and existing techniques such as the Covariance Matrix Adaptation Evolution Strategy(CMA-ES)and Particle Swarm Optimization(PSO),shows that the RRT-WMN algorithm has far better performance both in amount of time taken and regional coverage as the generalized RNP problem scales to realistic scenarios.The Gateway Node Placement Problem(GNP)tries to determine how to locate a minimal number of gateway nodes in a WMN backbone network while satisfying a number of Quality of Service(QoS)constraints.Two alternatives are proposed for solving the combined RNP-GNP problem.The first approach combines the RRT-WMN algorithm with a preexisting graph clustering algorithm.The second approach,WMNbyAreaDecomposition,proposes a novel divide-and-conquer algorithm that recursively partitions a target deployment area into a set of disjoint regions,thus creating a number of simpler RNP problems that are then solved concurrently.Both algorithms are evaluated on real-world GIS models of different size and complexity.WMNbyAreaDecomposition is shown to outperform existing algorithms using 73%to 92%fewer router nodes while at the same time satisfying all QoS requirements.