MIPSOE–Markov Integrated PSO Encryption Algorithm for Secure Data Aggregation

Various clustering algorithm exists in Wireless Sensor Networks concerned on balancing energy utilization. Many research issues deviate towards the formation of clusters based on energy, distance, and another sensor node’s resource parameters. In this article, the proposed protocol is composed of two phases. In the first phase, clusters are formed based on Particle Swarm Optimization and Markov’s Random Field mathematical calculation. The second phase generates a key, where the secret key is used for encryption technique. The proposed protocol is implemented in the NS2 simulator. When comparing the existing protocol with the proposed MIPSOE protocol it is inferred that there is an improvement in terms of network lifetime, throughput, delay, and packet delivery ratio

Improved Particle Swarm Optimization Algorithm Based on Last-Eliminated Principle and Enhanced Information Sharing

In this study, an improved eliminate particle swarm optimization (IEPSO) is proposed on the basis of the last-eliminated principle to solve optimization problems in engineering design. During optimization, the IEPSO enhances information communication among populations and maintains population diversity to overcome the limitations of classical optimization algorithms in solving multiparameter, strong coupling, and nonlinear engineering optimization problems. These limitations include advanced convergence and the tendency to easily fall into local optimization. The parameters involved in the imported “local-global information sharing” term are analyzed, and the principle of parameter selection for performance is determined. The performances of the IEPSO and classical optimization algorithms are then tested by using multiple sets of classical functions to verify the global search performance of the IEPSO. The simulation test results and those of the improved classical optimization algorithms are compared and analyzed to verify the advanced performance of the IEPSO algorithm