Job scheduling algorithm based on Berger model in cloud environment

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Abstract

Considered the commercialization and the virtualization characteristics of cloud computing, the paper proposed for the first time an algorithm of job scheduling based on Berger model. In the job scheduling process, the algorithm establishes dual fairness constraint. The first constraint is to classify user tasks by QoS preferences, and establish the general expectation function in accordance with the classification of tasks to restrain the fairness of the resources in selection process. The second constraint is to define resource fairness justice function to judge the fairness of the resources allocation. We have expanded simulation platform CloudSim, and have implemented the job scheduling algorithm proposed in this paper. The experimental results show that the algorithm can effectively execute the user tasks and manifests better fairness.

Introduction

Cloud computing is the development of grid computing, parallel computing and distributed computing. It is a new pattern of business computing. Compared with grid computing, cloud computing has some new features, such as (1) grid computing is in general the integration of fragmented, heterogeneous distribution resources; cloud computing is the large-scale data center resources which are more concentrated. In addition, virtualization technology hides the heterogeneity of the resources in cloud computing, (2) grid is generally used in science computation, and for solving special-purpose domain problem; cloud computing is user-oriented design which provides varied services to meet the needs of different users. It is more commercialized, and (3) the resources in cloud computing are packed into virtual resources by using virtualization technology. This causes its resource allocation process, the interaction with user tasks and so on are different with grid computation.

The basic mechanism of cloud computing is to dispatch the computing tasks to resource pooling which constitutes by massive computers. It enables a variety of applications to gain computing power, storage and a variety of software services according to their needs [1], [8]. The commercialization and the virtualization technology adopted by cloud computing has poured into new features for cloud architecture. For example, it leaves the job scheduling complexity of cloud computing to the virtual machine layer through resource virtualization. Further, it raised a number of new features for job scheduling, such as cloud computing needs pay more attention to the fairness of resources allocation.

The paper, from the fairness point of view, for the first time proposed and implemented the algorithm of job scheduling based on Berger model in cloud computing.

The paper is organized as follows: Section 2 gives related work. Section 3 gives some background knowledge. Section 4 gives detailed description of the algorithm of job scheduling based on Berger model. Section 5 describes the simulation experiment and experimental results. Section 6 gives the conclusions.

Section snippets

Related work

The relations between resource supply and demand in distributed system are similarities with commodity economy model. The resources provider is equal to the commodity supplier, and it provides a variety of resources for user. The resources users are equivalent to the commodity buyers. Users need to pay a fee in order to achieve the demands of their resources. The basic philosophy of the job scheduling algorithm based on economic models is to establish market mechanisms between resource

Background knowledge

The Berger model of distributive justice is based on expectation states. It is a series of distribution theories of social wealth.

Expectation states formed by a series of theories are used to study actors and evaluate the impact of their behavior. Brief speaking, expectation states theories are to study the follow two issues [9]. First, actor how to generate expectations of itself and other individual’s according to the information (such as status, reward, and performance differences) around

Job scheduling algorithm based on Berger model

In cloud computing, entities are mainly users, resource providers, and scheduling system. The main body that corresponds with them is user tasks, the resources and the scheduling strategy.

As shown in Fig. 2, in order to be able to map the theory of distributive justice in Berger model to resource allocation model in cloud computing, it is need to carry on the task classification, fairness function definition of user tasks, the task and resource parameterization, the task and resource mapping,

Simulation experiment

The paper uses simulation to test and verify the correctness of the job scheduling algorithm presented in this paper. With the optimal completion time of job scheduling algorithms comparative experiment, the results show the algorithm presented in this paper can effectively execute user tasks and manifest better fairness.

Conclusions and questions

In this paper, Berger model theory on distributive justice in the field of social distribution was first introduced into the job scheduling algorithm in cloud computing. Through the expansion of CloudSim platform, job scheduling algorithm based on Berger model is implemented. The validity of the algorithm is verified on the extended simulation platform. By comparing of simulation results with the optimal completion time algorithm, the proposed algorithm in this paper is effective implementation

Acknowledgment

The authors would like to acknowledge Professor Rajkumar Buyya of the University of Melbourne for his very useful suggestions.

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