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Ongoing Projects

  1. Bio-Inspired QoS Aware Load Balancing in Heterogeneous Cloud Computing Environment

    Load balancing is the major concern in the cloud computing environment. Cloud comprises of many hardware and software resources and managing these will play an important role in executing a client's request. Now a day's clients from different parts of the world are demanding for the various services in a rapid rate. In this present situation the load balancing algorithms built should be very efficient in allocating the request and also ensuring the usage of the resources in an intelligent way so that underutilization of the resources will not occur in the cloud environment. Clients demands for different cloud resources w.r.t Service Level Agreements (SLAs) in a seamless manner, therefore resource allocation and management plays an important role in load balancing of cloud environment.

  2. Energy Efficient Resource Management at Cloud Data Center

    Due to the increasing demand of cloud services, the size of the data center is exponentially increasing and more servers are needed to full-fill this demand. Hence, the Data center generates more heat, and therefore more cooling devices are required to keep the Data center at a specified temperature resulting in more energy consumption and CO2 emission. The energy efficient resources allocation problem is an important and challenging research issue since most of the modern data centers are hosting variety of time dependent services like e-commerce, large data set processing, etc. Therefore managing time dependent services and maintaining QOS w.r.t. SLA need energy efficient resources allocation in response to the time varying workload. The resource allocation in the form of VMs on PMs at the data center is an NP hard problem in nature. Bio inspired algorithm such as PSO, CSO, GA deals with optimization problem and gives an optimal solution in polynomial time. During our research work we implemented some bio inspired algorithm like GA, PSO, CSO in heterogeneous environments and compared their solutions with other greedy approaches like Bin-Packing, First-Fit, Fist -Fit decreasing, Best Fit.

  3. Software Aging and Rejuvenation Analysis of server Consolidation Systems

    The primary objective of this research work is to establish the aging trend in the server virtualized system. The secondary objective is to study the seasonal trend, if any, of the system variables which gives a detailed idea of the rejunation mechanism in-built in the system. The third objective is to identify the aging based workload on the server. This involves the classification of the workload running on the server and based on that the workload characterisation will be done. The final objective of the work is to find an optimum rejunation schedule based on the analysis done.