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Cloud computing, which helps in sharing resources through networks, has become one of the most widely used technologies in recent years. Vast numbers of organizations are moving to the cloud since it is more cost-effective and easy to maintain. An increase in the number of consumers using the cloud, however, results in increased traffic, which leads to the problem of balancing tasks on the loads. Numerous dynamic algorithms [1] have been proposed and implemented to handle these loads in different ways. The performance of these dynamic algorithms are scaled with different parameters, such as response time, throughput, utilization, efficiency, etc. The weighted round-robin algorithm is one of the most widely used load balancing algorithms. The proposed algorithm is an improvement of the weighted round-robin algorithm, which considers the priority of every task before assigning the tasks to different virtual machines (VMs). The proposed algorithm uses the priority of tasks to decide to which VMs the tasks should be assigned dynamically. The same process is used to migrate the tasks from overloaded VMs to under-loaded VMs. The simulations are conducted using CloudSim by varying cloud resources. Simulation results show that the proposed algorithm performs equivalent to the dynamic weighted round robin algorithm in all the QoS factors, but it shows significant improvement in handling high-priority tasks. 

Cloud computing has become an emerging trend for the software industry with the requirement of large infrastructure and resources. The future success of cloud computing depends on the effectiveness of instantiation of the infrastructure and utilization of available resources. Load Balancing ensures the fulfillment of these conditions to improve the cloud environment for the users. Load Balancing dynamically distributes the workload among the nodes in such a way that no single resource is either overwhelmed with tasks or underutilized. In this paper we propose a threshold based load balancing algorithm to ensure the equal distribution of the workload among the nodes. The main objective of the algorithms is to stop the VMs in the cloud being overloaded with tasks or being idle for lack allocation of tasks, when there are active tasks. We have simulated our proposed algorithm in the Cloudanalyst simulator with real world data scenarios. Simulation results shows that our proposed threshold based algorithm can provide a better response time for the task/requests and data processing time for the datacenters compared to the existing algorithms such as First Come First Serve (FCFS), Round Robin(RR) and Equally Spread Current Execution Load Balancing algorithm(ESCELB).