Balanced Scheduling Algorithm Considering Availability in Mobile Grid

Author(s):  
JongHyuk Lee ◽  
SungJin Song ◽  
JoonMin Gil ◽  
KwangSik Chung ◽  
Taeweon Suh ◽  
...  
2014 ◽  
Vol 29 (4) ◽  
pp. 409-432 ◽  
Author(s):  
Jonghyuk Lee ◽  
Sungjin Choi ◽  
Taeweon Suh ◽  
Heonchang Yu

AbstractThe emerging Grid is extending the scope of resources to mobile devices and sensors that are connected through loosely connected networks. Nowadays, the number of mobile device users is increasing dramatically and the mobile devices provide various capabilities such as location awareness that are not normally incorporated in fixed Grid resources. Nevertheless, mobile devices exhibit inferior characteristics such as poor performance, limited battery life, and unreliable communication, compared with fixed Grid resources. Especially, the intermittent disconnection from network owing to users’ movements adversely affects performance, and this characteristic makes it inefficient and troublesome to adopt the synchronous message delivery in mobile Grid. This paper presents a mobile Grid system architecture based on mobile agents that support the location management and the asynchronous message delivery in a multi-domain proxy environment. We propose a novel balanced scheduling algorithm that takes users’ mobility into account in scheduling. We analyzed users mobility patterns to quantitatively measure the resource availability, which is classified into three types: full availability, partial availability, and unavailability. We also propose an adaptive load-balancing technique by classifying mobile devices into nine groups depending on availability and by utilizing adaptability based on the multi-level feedback queue to handle the job type change. The experimental results show that our scheduling algorithm provides a superior performance in terms of execution times to the one without considering mobility and adaptive load-balancing.


2010 ◽  
Vol 6 (2) ◽  
pp. 193-211 ◽  
Author(s):  
Chunlin Li ◽  
Layuan Li

Energy efficient computing has recently become hot research area. Many works have been carried out on conserving energy, but considering energy efficiency in grid computing is few. This paper proposes energy efficient resource management in mobile grid. The objective of energy efficient resource management in mobile grid is to maximize the utility of the mobile grid which is denoted as the sum of grid application utility. The utility function models benefits of application and system. By using nonlinear optimization theory, energy efficient resource management in mobile grid can be formulated as multi objective optimization problem. In order to derive a distributed algorithm to solve global optimization problem in mobile grid, we decompose the problem into the sub problems. The proposed energy efficient resource management algorithm decomposes the optimization problem via iterative method. To test the performance of the proposed algorithm, the simulations are conducted to compare proposed energy efficient resource management algorithm with other energy aware scheduling algorithm.


2014 ◽  
Vol 8 (5) ◽  
pp. 847-857 ◽  
Author(s):  
JongHyuk Lee ◽  
SungJin Choi ◽  
JoonMin Gil ◽  
Taeweon Suh ◽  
HeonChang Yu

Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.


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