Service‐level agreement–aware scheduling and load balancing of tasks in cloud

Cloud computing is an innovative computing paradigm designed to provide a flexible and low‐cost way to deliver information technology services on demand over the Internet. Proper scheduling and load balancing of the resources are required for the efficient operations in the distributed cloud environment. Since cloud computing is growing rapidly and customers are demanding better performance and more services, scheduling and load balancing of the cloud resources have become very interesting and important area of research. As more and more consumers assign their tasks to cloud, service‐level agreements (SLAs) between consumers and providers are emerging as an important aspect. The proposed prediction model is based on the past usage pattern and aims to provide optimal resource management without the violations of the agreed service‐level conditions in cloud data centers. It considers SLA in both the initial scheduling stage and in the load balancing stage, and it looks into different objectives to achieve the minimum makespan, the minimum degree of imbalance, and the minimum number of SLA violations. The experimental results show the effectiveness of the proposed system compared with other state‐of‐the‐art algorithms.

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