Optimizing Job Scheduling in Federated Grid System Akshima Aggarwal and Amit Chhabra Abstract Parallel computing is a type of computation in which jobs are executed by the parallel servers. Jobs are further distributed into number of tasks by checking the availability of server. Federated Grid System is a system consists of number of heterogenous clusters which are associated with number of servers. Comparison with existing work on the basis of parameters such as makspan, flow time and energy. The time taken by a single job to accomplish its task is flow time and the time taken by all the jobs to accomplish its task is the makespan of that jobs. DVFS levels are considered in a system to reduce the power consumption during the execution of parallel jobs. In our proposed system we have used DVFS based genetic algorithm so that the job acquired by parallel processors provide optimal results. Keywords Parallel computing ⋅ Makespan ⋅ Flow time ⋅ Federated grid structure 1 Introduction Parallel computing is operating on the principle that large problems can often be divided into smaller ones, which are then solved at the same time. In this type of computation many jobs are performed simultaneously on different servers. There are several types of parallel computing: bit-level, instruction-level, data, and task parallelism. To get high performance computation parallelism is utilized from many years. In our proposed system by using parallel computing we can achieve optimal result in short span of time. It is closely related to concurrent computing—they are frequently used together, and often conflated, though the two are distinct: Paral- A. Aggarwal ( ✉ ) ⋅ A. Chhabra Department of Computer Engineering, Guru Nanak Dev University, Amritsar, India e-mail: akshimaaggarwal2009@gmail.com A. Chhabra e-mail: amit.cse@gndu.ac.in © Springer Nature Singapore Pte Ltd. 2017 H.S. Saini et al. (eds.), Innovations in Computer Science and Engineering, Lecture Notes in Networks and Systems 8, DOI 10.1007/978-981-10-3818-1_11 97