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Home / programming language / Online Dotnet Projects / Dynamic Bin Packing for On-Demand Cloud Resource Allocation
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Dotnet Project - Cloud Computing, Final Year Project
  • Dotnet Project - Cloud Computing, Final Year Project

Dynamic Bin Packing for On-Demand Cloud Resource Allocation

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SKU: PROJ7381 Categories: 2017 Projects, Cloud Computing Projects, Online Dotnet Projects Tags: Android Project, Asp.Net Project, C# Project, Computer Engineering Final Year Projects, Computer Science Final Year Projects, Electronics Projects Engineering Students Final Year, Engineering Student Project Ideas, Final Semester Projects, Final Year Project Center, Final Year Projects, ieee ECE Projects, ieee EEE Projects, ieee Final Year Projects, IEEE Projects, ieee Projects Networking, Image Processing Projects, J2EE Project, Java Project, Java Project Code, Matlab Project, PHP Project, Students Projects
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Dynamic Bin Packing for On-Demand
Cloud Resource Allocation

Abstract— Dynamic Bin Packing (DBP) is a variant of classical bin packing, which assumes that items may arrive and depart at arbitrary times. Existing works on DBP generally aim to minimize the maximum number of bins ever used in the packing. In this paper, we consider a new version of the DBP problem, namely, the MinTotal DBP problem which targets at minimizing the total cost of the bins used over time. It is motivated by the request dispatching problem arising from cloud gaming systems. We analyze the competitive ratios of the modified versions of the commonly used First Fit, Best Fit, and Any Fit packing (the family of packing algorithms that open a new bin only when no currently open bin can accommodate the item to be packed) algorithms for the MinTotal DBP problem. We show that the competitive ratio of Any Fit packing cannot be better than m þ 1, where m is the ratio of the maximum item duration to the minimum item duration. The competitive ratio of Best Fit packing is not bounded for any given m. For First Fit packing, if all the item sizes are smaller than 1 b of the bin capacity (b > 1 is a constant), the competitive ratio has an upper bound of b b1  m þ 3b b1 þ 1. For the general case, the competitive ratio of First Fit packing has an upper bound of 2m þ 7. We also propose a Hybrid First Fit packing algorithm that can achieve a competitive ratio no larger than 5 4m þ 19 4 when m is not known and can achieve a competitive ratio no larger
than m þ 5 when m is known.< final year projects >

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