Optimal and Energy Efficient Scheduling Techniques for Resource Management in Public Cloud Networks

Heterogeneous and multi-core server processors are connected across the clouds and cloud data centers in cloud networks. In such a scenario, the overall performance of the cloud system must be optimized for providing fast and effective services by proposing new techniques for load balancing, scheduling, secured storage and effective retrieval. Therefore in this paper, new algorithms are proposed to optimize the power and to improve the performance based on better load distribution using load balancing techniques in cloud networks. These proposed algorithms provide better performance by optimizing the processing speed, time, energy and security level using temporal reasoning. The proposed techniques have been implemented using a public cloud environment and the effectiveness of the proposed techniques are compared with other existing works and it is observed that the storage time and energy are minimized and the security is improved.