Srikanth Sundarrajan

Grouping genetic algorithm for solving the serverconsolidation problem with conflicts

The advent of virtualization technologies encourages organizations to undertake server consolidation exercises for improving the overall server utilization and for minimizing the capacity redundancy within data-centers. Identifying complimentary workload patterns is a key to the success of server consolidation exercises and for enabling multi-tenancy within data-centers. Existing works either do not consider incompatibility constraints or performs poorly on the disjointed conflict graphs. The algorithm proposed in the current work overcomes the limitations posed by the existing solutions. The current work models the server consolidation problem as a vector packing problem with conflicts (VPC) and tries to minimize the number of servers used for hosting applications within datacenters and maximizes the packing efficiency of the servers utilized. This paper solves the problem using techniques inspired from grouping genetic algorithm (GGA) - a variant of the traditional Genetic Algorithm (GA). The algorithm is tested over varying scenarios which show encouraging results.

Optimizing Migration of Virtual Machines across Data-Centers

Managing virtual machines (VM) in large scale enterprise grid scenarios, commonly encountered in data centers, is extremely challenging. Currently, live VM migration is based on QoS non-conformance events; migration of a VM is initiated as soon as the aggregate resource (CPU and memory) requirements of the VMs on the physical machine (PM) exceed the capacity available on the PM. However, this paper establishes that, such ‘event-based’ migration can be extremely myopic. To overcome the limitations posed by the ‘event-based’ VM migration, this paper, proposes a new migration strategy based on ‘time-windows’. The paper outlines a mixed integer linear programming (MILP) model and a heuristic solution for generating near-optimal rearrangements of the VMs on the PMs. The paper evaluates the solutions on various VM scenarios which show encouraging results.

Nova: an approach to on-demand virtual execution environments for grids

The technique of using virtual machines for grid jobs as trusted execution environments has been hampered by the overheads involved creating the virtual machines. This paper attempts to reduce the overheads of dynamically creating and destroying the virtual environments for secure job execution. It broaches a grid architecture which we call Nova, consisting of extremely minuscule, pre-created virtual machines whose configurations could be altered with respect to the application executed within it. The benefits of the architecture are supported by experimental claims.