Scalability of efficient and dynamic workload distribution in autonomic cloud computing

The expectations of human desire on the technology are unlimited, so we need much more scalable system that manage themselves and fulfills our desire automatically. The current state of cloud computing infrastructure is not fully industrialized. To provide good quality of service (QOS) through cloud, the autonomic cloud computing, offers self- management properties of Autonomic Computing. With this technique, we scale up workload distribution dynamically and efficiently for cloud environment. With traditional system, centralized approach exists which are inefficient to scale up and proper workload distribution can be complex which required extra cost for large operation. In this paper, we integrate autonomic computing principals for automatic workload distribution through distributed decision in cloud. We will demonstrate the entire scenario based on cloud computing where individual resource allocated to the users (consumers) processes.