A Novel hybrid heuristic-metaheuristic Load balancing algorithm for Resource allocationin IaaS-cloud computing

Cloud networks have used for secured data processing during the transmission of data to authorized persons. Cloud computing consists of a group of clients that spatially distributed and dedicated to monitoring the external user, managing, and recording information. Load balancing is an important parameter utilized. In this paper, a hybrid heuristic mathematic algorithm (HHMA) has proposed for the IaaS computing network, which solves the resource allocation problem cloud network. To obtain a faster design and reduce the file download time, the cluster divided into small chunks using improved K-means clustering technique (heuristic). Then cockroach swarm optimization (MCSO) algorithm proposed to measure the load ratio of a computed node by different constraints which realize the real-time load. After MCSO algorithm performance, the optimal comprehensive evaluation value is established for assigning the master node to storage node. Optimal processing has been obtained using two algorithms to dedicate the request data to the reasonable nodes. Hence way, resource utilization has achieved high performance and improvement over other techniques. The simulation result shows that the proposed method has reduced the network overhead, average response time, and memory load. As a result, the proposed heuristic scheme is a promising and well-constructed scheme for cloud computing investors.