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@article{144332,
        author = {Srividhya R and Uma Maheswari K },
        title = {Workload Aware Load Balancing For Cloud Data Center},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {10},
        pages = {200-204},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=144332},
        abstract = {Cloud computing is emerging as a new standard for manipulating, configuring, and accessing large scale distributed computing applications over the network. Load balancing is the main Challenges in cloud computing which is required to distribute the workload evenly across all the nodes. Load is a measure of the work that a computation system performs which can be classified as CPU load and memory. The concept of load balancing used in cloud computing is to evenly distribute data to underutilized virtual machines in the data center for effectively scheduling. The challenge faced during the load balancing is to balance the load in single Data Center which allocates the resources overloaded in each Virtual Machines and the algorithm used two parameter namely processing power and computer loading, which is less efficient when user login multiple times. The proposed system is to perform load balancing in cloud based on the workload of the cloud data center and to create multiple data centers for single 

server so that when a particular Virtual Machines overloads tasks will automatically allocated to other available data center (which contains Virtual Machines) by using three parameters - number of task/jobs, workload of each Virtual Machines or threshold and computing power, which balances both data center and Virtual Machines efficiently, thereby increasing the performance. This technique that helps resources by providing a Maximum throughput with minimum response time. So that there will less time for allocating workload, thereby increases the performance.},
        keywords = {Cloud computing, cloud data center, load balancing, processing power, virtual machines.},
        month = {},
        }