Paper Title
Improved Genetic Algorithm for Load Balancing in Cloud Computing

Cloud computing as a computing paradigm offers a lot of services in-order to reduce the difficulties induced due to on-site computing. These constraints include limited storage, processing power, bandwidth, resources etc. Implementing and providing cloud service face several challenges. One of the main challenges is the task scheduling, which is the mapping of incoming user request to virtual machine (VM). This can be solved using either hard-computing methods or soft-computing methods. In this paper, we propose a method which is based on Genetic algorithm, which can be used to find optimum mapping solution between task and VM. Metrics which can be used to evaluate different strategies are response time, cost, overall execution time etc. Our simulation on cloudsim shows promising results. Keywords - Cloud Computing, Load Balancing, Cloudsim, Genetic Algorithm