PROJECT TITLE :
Shadow-Routing Based Dynamic Algorithms for Virtual Machine Placement in a Network Cloud - 2018
We have a tendency to consider a shadow routing based approach to the problem of real-time adaptive placement of virtual machines (VM) in giant information centers (DC) at intervals a network cloud. Such placement in specific has got to respect vector packing constraints on the allocation of VMs to host physical machines (PM) at intervals a DC, because each PM will potentially serve multiple VMs simultaneously. Shadow routing is enticing in that it allows a large variety of system objectives and/or constraints to be treated among a common framework (as long because the underlying optimization downside is convex). Perhaps even additional enticing feature is that the corresponding algorithm is very simple to implement, it runs continuously, and adapts automatically to changes in the VM demand rates, changes in system parameters, etc., without the need to re-solve the underlying optimization downside “from scratch”. In this Project we tend to target the min-max-DC-load drawback. Namely, we propose a combined VM-to-DC routing and VM-to-PM assignment algorithm, referred to as Shadow scheme, which minimizes the utmost of appropriately defined DC utilizations. We have a tendency to prove that the Shadow scheme is asymptotically optimal (joined of its parameters goes to zero). Simulation confirms sensible performance and high adaptivity of the algorithm. Favorable performance is also demonstrated in comparison with a baseline algorithm based on VMware implementation , [eight]. We have a tendency to additionally propose a simplified - “a lot of distributed” - version of the Shadow theme, which performs virtually further in simulations.
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