Cloud infrastructure resource management

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Cloud computing is a common name in IT industry. However increase in Cloud computing usage also comes with increased complexity. Efficient resource management for best utilization with minimal cost is a crucial task. The scope of this work is under IaaS service module, which handles infrastructure resources (Virtual Machines, Servers, Storage, and Network) allocation. Resource management offers the following benefits: elasticity/scalability, QoS, optimal utility, reduced overhead, improved throughput, reduced latency, cost effectiveness and simplified interface. VM migration is one of the most popular way to manage resources, and Live VM migration is the most used technique to reload or rearrange the resources in datacenter to keep the delivered services available. Statistics shows 70% of datacenters resources is not utilized. Therefore, reduction in number of servers and hardware will not only reduce its capital costs, but will also reduce its running and maintenance cost. In addition, Live VM migration will facilitate load balancing and energy management as part of resource management. VM migration consists of optimally selecting VM to be migrated, which physical server must be chosen to move this VM, when to start migration process, and duration of migration process. The goals for VM Selection techniques are to reduce power consumption, increase load balancing, and increase fault tolerance, which eventually will increase the cloud services availability and throughput/efficiency. The increased efficiency reduces the overall operation costs, pollution (green datacenters), and hardware maintenance. Migration Process itself targets moving the VM in minimum time to avoid any interruption of services. In this research proposal, in collaboration with Cistech Ltd, we consider investigating solutions to decrease the migration process time and optimally selecting VMs for live migration. Our project goal is to develop smart algorithms that will evaluate the available running resources for load balancing, server consolidation, network bandwidth, VMs shrinking or expanding and fault tolerance. Our project will drive the energy saving and the cost saving in running the IT datacenters.