Paper Title
Recommendation Based Genetic Algorithm For Independent Task In Cloud Computing Environment

Cloud computing environments provide virtualized resources that can be utilized dynamically. Cloud computing, also known as utility based computing, encourage researchers to utilize resources virtually via electronic medium. Small and medium-sized enterprises (SMEs) are gaining interest in cloud computing because of their easier services, convenience and ability to use across multiple platforms at low cost. Availability of virtualized resources has increased the demand of scheduling for resource optimization. Scheduling problem of independent task on distributed computing system (DCs) deals with the allocation of task on available resources with greater recommendation value and higher trust worthiness (TW) values. Due to complex nature of scheduling, scheduling is interesting field of research. In this paper we used Genetic Algorithm approach to map tasks onto best available resources. Recommendation and TW of resources are the important factors for task assignment. Recommendation value, TW value, Cost, Minimum Completion Time (MCT) factors are considered here to find optimal solution for independent task scheduling.