Designing an energy-efficient routing makes the Wireless Sensor Networks (WSN) more effective and attractive for different applications. The WSN communication system power consumption mainly depends on three aspects such as routing cost computation, signal interference, and routing
distance. All three factors are equally important in order to improve the network performance. The system reliability and deployment cost depends on the energy efficiency of the WSN. The energy related cost assignment and shortest paths identification are used in existing routing techniques.
In the existing routing techniques maximum achievable lifetime and optimal link cost are low. Hence greatest possible performance can be achieved in distributed routing algorithm by finding shortest path. Maximum lifetime and best cost link can be generally obtained using distributed shortest
path routing algorithm. In this paper high speed reconfigurable distributed Lifetime-Efficient Routing algorithm is designed to provide route selection outline with low complexity and obtain better performance compared to existing routing algorithm.
Objective: Energy efficiency aspect in wireless sensor networks (WSN) can be achieved by small sized rechargeable and easily replaceable batteries. The lifetime of wireless sensor network can be improved by identifying the efficient and reliable nodes as a cluster heads using Hybrid Simulated Annealing algorithm. The proposed algorithm identifies cluster head to reduce overhead and is capable of handling high volume of nodes with minimum node death rate. Methods: This study proposed initialization of population vectors using the opposite point procedure, self-adaptive control approach by node mutation rate, crossover rate, node capacity and cluster head allocation Methods. Findings: A case study in the proposed work is found to be better in throughput, accuracy, efficiency, energy utilization, batteries recharge ability and replacement procedures compared to the conventional methods. By the analysis and comparison of the proposed method with existing methods, it is identified that the reduction of the number of dead nodes gradually increases the throughput and lifetime of the nodes with respect to the number of iterations. Novelty: To overcome the limitations of conventional Low Energy Adaptive Clustering Hierarchy (LEACH), harmony search algorithm (HSA), modified HSA and differential evolution, we propose a hybrid optimal model using simulated annealing algorithm which includes a node capability function. It is used to improve the network lifetime of the cluster heads and sensor nodes. The proposed method have capability of batteries recharge ability and replacement option to improve network throughput and reliability of network.
Security is a very important issue when designing or deploying any network or protocol. The nature of large, ad-hoc, wireless sensor networks presents significant challenges in designing security schemes. One or several sensors then collect the detection results from other sensors. The collected data must be processed by the sensor to reduce the transmission burden before they are transmitted to the base station. This process is called data fusion. Data fusion Nodes will fuses the collected data from nearby sensor nodes before they are sent to the base station. If a fusion node is compromised, then the base station cannot ensure the correctness of the fusion data sent to it. Various methods are proposed, that deal with providing an assured data transfer to the Base Station.In this paper a novel power-efficient data fusion assurance scheme has been proposed using silent negative voting mechanism. The proposed scheme has been compared with the direct voting based fusion assurance scheme. The proposed scheme produced very well with better power efficiency and lower network overhead.
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