Modeling of the resource allocation in cloud computing centers

Modeling of the resource allocation in cloud computing centers

ژورنال:Computer Networks

سال: November 2015

قیمت اصلی:35.95$

Abstract

Cloud computing offers on-demand network access to the computing resources through virtualization. This paradigm shifts the computer resources to the cloud, which results in cost savings as the users leasing instead of owning these resources. Clouds will also provide power constrained mobile users accessibility to the computing resources. In this paper, we develop performance models of these systems. We assume that jobs arrive to the system according to a Poisson process and they may have quite general service time distributions. Each job may consist of multiple numbers of tasks with each task requiring a virtual machine (VM) for its execution. The size of a job is determined by the number of its tasks, which may be a constant or a variable. The jobs with variable sizes may generate new tasks during their service times. In the case of constant job size, we allow different classes of jobs, with each class being determined through their arrival and service rates and number of tasks in a job. In the variable case a job generates randomly new tasks during its service time. The latter requires dynamic assignment of VMs to a job, which will be needed in providing service to mobile users. We model the systems with both constant and variable size jobs using birth–death processes. In the case of constant job size, we determined joint probability distribution of the number of jobs from each class in the system, job blocking probabilities and distribution of the utilization of resources for systems with both homogeneous and heterogeneous types of VMs. We have also analyzed tradeoffs for turning idle servers off for power saving. In the case of variable job sizes, we have determined distribution of the number of jobs in the system and average service time of a job for systems with both infinite and finite amount of resources. We have presented numerical results and any approximations are verified by simulation. The results of the paper may be used in the dimensioning of cloud computing centers.

KeywordsCloud computing, Queuing systems, Resource allocation, Markov process

ISI Paper: Service Centers Location Problem Considering Service Diversity within Queuing Framework

مقاله ISI چاپ شده در مجله علمی ساینتیا ایرانیکا (Scientia Iranica), شماره 105، چاپ سال 2015

In this paper, a new model is developed considering diversity of service in service centers location problem. It is assumed that different services can be provided at each service center. The model has three objective functions including: minimizing the sum of customers’ travel time and waiting time in service centers, balancing service loads among the given centers, and minimizing the total establishment costs of service centers and assignment costs of servers. Different number of servers can be assigned to each service center. Regarding the allocation of customers to the centers, each customer patronizes with respect to the distance to the service center, the attractiveness of each service center’s site for the customer and the number of located servers at the service center. Since the proposed model is of nonlinear integer programming type and is of high complexity on solving, two meta-heuristic based heuristics using particle swarm optimization (PSO) and variable neighborhood search (VNS) are proposed to solve the problem. Different sizes of numerical examples are designed and solved in order to compare the efficiency of the heuristics.

Authors: Fezzeh Partovi, Mehdi Seifbarghy

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