Genetic-fuzzy based load balanced protocol for WSNs

Abstract

<p><span>Recent advancement in wireless sensor networks primarily depends upon energy constraint. Clustering is the most effective energy-efficient technique to provide robust, fault-tolerant and also enhance network lifetime and coverage. Selection of optimal number of cluster heads and balancing the load of cluster heads are most challenging issues. Evolutionary based approach and soft computing approach are best suitable for counter the above problems rather than mathematical approach. In this paper we propose hybrid technique where Genetic algorithm is used for the selection of optimal number of cluster heads and their fitness value of chromosome to give optimal number of cluster head and minimizing the energy consumption is provided with the help of fuzzy logic approach. Finally cluster heads uses multi-hop routing based on A*(A-star) algorithm to send aggregated data to base station which additionally balance the load. Comparative study among LEACH, CHEF, LEACH-ERE, GAEEP shows that our proposed algorithm outperform in the area of total energy consumption with various rounds and network lifetime, number of node alive versus rounds and packet delivery or packet drop ratio over the rounds, also able to balances the load at cluster head.</span></p>

An energy consumption minimization approach in wireless sensor networks

“…The bunch heads are gatherings of the sensor hubs that have been chosen among all sensor hubs in WSN. In this way, the proposed ACHS calculation covers significant components that are dismissed by the other LEACH conventions [24,25]. These components think about the leftover vitality of every sensor hub, the quantity of sensor hub chosen as a CH, the separation between CH hubs with the base station, the quantity of neighbor hubs, and the normal vitality of sensor hubs in the current round.…”

Simulation model of PID for DC-DC converter by using MATLAB

“…The current work provides how to develop a design for Buck boost adapter with PWM in addition to a control unit of the type PID [18]- [20]. PID is one of the most important traditional control systems that works to control and is widely used and noticeable in the industry as it is characterized by being simple and easy to implement and applicable [21]- [23]. PID provides acceptable performance with linear systems of the first degree, the process of controlling the controller have two tasks that include setting a simple and powerful algorithm it works under suitable conditions [24]- [26].…”

Adaptive Chaotic Ant Colony Optimization for Energy Optimization in Smart Sensor Networks

“…Taking energy optimization as the starting point, this paper studies and designs a clustering algorithm based on ACACO to reduce the energy consumption of smart sensor single-round communication as much as possible. To verify the effectiveness of the algorithm, we compare it with two heuristic artificial intelligence algorithms, which are GA [10,11] and PSO [12]. The contributions of this research are as follows:…”