Job scheduling algorithm based on Berger model in cloud environment
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.
References (18)
- et al.
A Comparison of eleven static heuristics for mapping a class of independent tasks onto heterogeneous distributed computing system
J Parallel Dist Comput
(2001) - et al.
Maximizing business value by optimal assignment of jobs to resources in grid computing
Eur J Oper Res
(2009) - Liu Peng, the definition of cloud computing and characteristics,...
A futures market in computer time
Commun ACM
(1968)- et al.
Microeconomic algorithms for load balancing in distributed computer systems
- et al.
Towards a micro-economic model for resource allocation in grid computing systems
- et al.
Market-Based resource allocation for grid computing: a model and simulation
- et al.
The popcorn market – An online market for computational resources
- Buyya R. Economic-Based distributed resource management and scheduling for grid computing, Ph.D. Thesis. Melbourne:...
Cited by (149)
Cost-aware scheduling systems for real-time workflows in cloud: An approach based on Genetic Algorithm and Deep Reinforcement Learning
2023, Expert Systems with ApplicationsNeural network inspired differential evolution based task scheduling for cloud infrastructure
2023, Alexandria Engineering JournalResource scheduling methods for cloud computing environment: The role of meta-heuristics and artificial intelligence
2022, Engineering Applications of Artificial IntelligenceA systematic literature review on soft computing techniques in cloud load balancing network
2024, International Journal of System Assurance Engineering and ManagementABLA: Application-Based Load-Balanced Approach for Adaptive Mapping of Datacenter Networks
2023, Electronics (Switzerland)Network Aware Resource Optimization Using Nature Inspired Optimization Algorithm for Task Scheduling in Cloud Infrastructure
2023, Journal of Circuits, Systems and Computers