Abstract: The cloud environment provides a cluster of interconnected virtualized systems which are progressively provisioned and recognized as pooled computing resources. The primary objective of job scheduling in cloud is to accomplish a framework that achieve foremost system throughput. The adequacy of cloud environment is to great extent depends upon the proficiency of its scheduler. The cloud service provider implement a scheduler that designates the optimal job scheduling by effectively distributing and executing cloud user jobs on available resources in such a manner as to limit execution time, reduce energy consumption, overall cost and various other factors that can dominate the performance in cloud environment. So, keeping in mind these performance parameters we analyzed and implemented a smarter multi queue job scheduling algorithm for cloud computing. This algorithm accommodate to virtualization trait of cloud computing, vary from traditional job scheduling algorithms character-concentrate on energy efficiency and maintain optimal resource fairness under the cloud computing. To assess the performance of the proposed algorithm we compared it with efficient multi queue job scheduling technique which is presented by researcher in recent past. Through, the experiments, the smarter multi queue scheduling algorithm has demonstrated that it can intensify the performance by effectively reducing the energy consumption by 41.22%. Finally, the comparative simulations and numeral results of both strategies on different number of user jobs indicates that our recommended smarter MQS approach is much more oriented towards energy saving and to some extent reduce execution time in cloud environment.