Skewed Prognostic Load Prediction Strategy in Mobile Cloud Computing

In Mobile Cloud Computing (MCC), load balancing is essential to distribute the local workload evenly across all the nodes either statically or dynamically. A high level of user satisfaction and resource utilization ratio can be achieved by ensuring an efficient and fair allocation of all computing resources. In the absence of proper load balancing strategy/technique the growth of MCC will never go as per predictions. The appropriate load balancing helps in minimizing resource consumption, implementing fail-over, enabling scalability, avoiding bottlenecks. We introduce the concept of "skewness" to measure the unevent utilization of a server. By minimizing skewness, we can improve the overall utilization of servers in the face of multi-dimensional resource constraints. We design a load prediction algorithm that can capture the future resource usages of applications accurately without looking inside the VMs. The algorithm can capture the rising trend of resource usage patterns and help reduce the placement churn significantly.