Hybrid Electro Search with Ant Colony Optimization Algorithm for Task Scheduling in a Sensor Cloud Environment for Agriculture Irrigation Control System

Integrating cloud computing with wireless sensor networks creates a (WSN). Some real-time applications, such as agricultural irrigation control systems, use cloud. The battery life in clouds is constrained. data center’s computers consume lot of energy to offer storage the emerging technology-enabled virtualization. Using virtual environment has many advantages. However, different resource requirements and task execution cause substantial performance parameter optimization issues computing. In this study, we proposed hybrid electro search ant colony (HES-ACO) technique enhance behavior scheduling, for those considering parameters total time, cost execution, makespan center consumption like throughput, response utilization rejection ratio, deadline constraint multicloud. Electro algorithm are combined method. Compared HESGA, HPSOGA, AC-PSO, PSO-COGENT algorithms, created HES-ACO was simulated at CloudSim found optimize all parameters.