Dynamic Load Balancing By Scheduling In Computational Grid System (original) (raw)

An Efficient Scheduling Policy for Load Balancing Model for Computational Grid System

Computer Engineering and Intelligent Systems, 2012

Workload and resource management are two essential functions provided at the service level of the Grid system. To improvement in global throughput need, effective and efficient load balancing are fundamentally important. We also check that what type of scheduling policy is used by that algorithm, because an efficient scheduling policy can utilize the computational resources efficiently by allowing multiple independent jobs to run over a network of heterogeneous clusters. In this paper, a dynamic grid model, as a collection of clusters has been proposed. An efficient scheduling policy is used, and its comparison with the other scheduling policy has been presented. 1. INTRODUCTION. In order to fulfil the user expectations in terms of performance and efficiency, the Grid system needs efficient load balancing algorithms for the distribution of tasks [1]. A load balancing algorithm attempts to improve the response time of user's submitted applications by ensuring maximal utilization of available resources. The main goal is to prevent, if possible, the condition where some processors are overloaded with a set of tasks while others are lightly loaded or even idle [2]. Although load balancing problem in conventional distributed systems has been intensively studied, new challenges in Grid computing still make it an interesting topic and many research projects are under way. This is due to the characteristics of Grid computing and the complex nature of the problem itself. Load balancing algorithms in classical distributed systems, which usually run on homogeneous and dedicated resources, cannot work well in the Grid architectures. In this chapter we define the motivation of this research and then identify the research questions. This chapter also discusses overall organization of thesis. 2. CHARACTERISTICS OF GRID

Load Balancing Grid Scheduler for the Computational Grid Environment

International Journal on Computer Sciences and Technologies, 2013

Distributed computing paradigm is a wide spread technology, where computational grid provides huge computation power for the large scale distributed application. One of the challenging issue in computational grid is load balancing. This paper, proposed a new load balancing scheduler algorithm which can not only increases the utilization of the resource and throughput, but also realize the load balancing within the grid environment. The updated topology and load information is acquired dynamically from the resource using the event notification approach. In order to maximize the utilization of resources and to increase the performance of the system application level load balancing is needed for the individual parallel jobs. In many approaches load balancing is done only at the local scheduler level, which is applicable to small application and leads to more communication overhead between the nodes. For the large scale application load balancing at the local scheduler level will not provide the feasible solution. So the novel load balancing algorithm is proposed, which provides the load balancing at the meta scheduler level. To initiate the load balancing triggering policy is used, which determines the appropriate time period time to start the load balancing operation. Triggering policy can be initiated by using two approaches such as threshold and boundary value app oach. These approach increases the performance in the large scale application by submitting the job to the least loaded machine to reduce the elapsed time and waiting time of job, and to maximize the utilization of the resources which are idle or least loaded.

A Hybrid Scheduling Algorithm with Load Balancing for Computational Grid

International Journal of Advanced Science and Technology, 2013

Grid Computing provides seamless and scalable access to wide-area distributed resources. Since, computational grid shares, selects and aggregates wide variety of geographically distributed computing resources and presents them as a single resource for solving large scale computing applications, there is a need for a scheduling algorithm which takes into account the various requirements of grid environment. Hence, this research proposes a new scheduling algorithm for computational grids that considers load balancing, fault tolerance and user satisfaction based on the grid architecture, resource heterogeneity, resource availability and job characteristics such as user deadline. This algorithm reduces the makespan of the schedule along with user satisfaction and balanced load. A simulation is conducted using Grid Simulator Toolkit (GridSim). The simulation results shows that the proposed algorithm has better makespan, hit rate and resource utilization.

Resolving Load Balancing Issue of Grid Computing through Dynamic Approach

Load balancing has been a key concern for traditional multiprocessor systems. The emergence of computational grids extends this challenge to deal with more serious problems, such as scalability, heterogeneity of computing resources and considerable transfer delay. Due to the dynamic property of grid environment, fixed-parameter prediction model cannot exert its forecast capability completely. To improve the global throughput of computational grid, effective and efficient load balancing algorithms are fundamentally important. A computational grid differs from traditional high-performance computing system in the heterogeneity of computing nodes, as well as the communication links that connect the different nodes together. A dynamic and decentralized load balancing algorithm for computationally intensive jobs on a heterogeneous distributed computing platform is required. The time spent by a job in the system is considered as the main issue that needs to be minimized. A resource queue length based solution to the grid load balancing problem has been proposed in this dissertation. An algorithm that is dynamic, decentralized and distributed for load balancing among the aggregated processing elements in the grid has proposed .The proposed algorithm balances the load in the grid based on the queue length of each processing element and transfer the task to the processing element having minimum queue length. The proposed Algorithm is implemented with the help of GridSim toolkit. The Simulations are performed for number of users and processing elements.

Optimization of Dynamic Resource Scheduling Algorithm in Grid Computing Environment

International Journal of Computer Sciences and Engineering , 2018

Resource supervision and task scheduling are very important and complex problems in grid computing environment. Handle of such resources we need job scheduling and load balancing techniques which are responsible for efficient use of the grid resources, reduce job waiting time, access latency in a wise manner. After comprehensive investigation of an existing grid which involves a large number of CPU cluster, we observe that grid scheduling decisions can be significantly improved computation time if the characteristics of current usage patterns are understood. In this paper a new job scheduling algorithm, called Improved Dynamic Load Balancing (IDLB) is proposed. In the proposed algorithm the current scheduling is denoted as S* so the runtime delay is reduced by using Actual Latest Finish Time (ALFT). Finally, in this research the algorithm was simulated with the aid of OptorSim simulator and it was proved that our proposed algorithm provid an effective solution for resource management grid scheduling.

A Comparative Study of Load Balancing Algorithms in Computational Grid Environment

2013 Fifth International Conference on Computational Intelligence, Modelling and Simulation, 2013

Grids are a form of distributed computing whereby a 'super virtual computer' is composed of many networked loosely coupled computers acting together to perform very large tasks. This technology has been applied to computationally intensive scientific, mathematical and academic problems through volunteer computing, and it is used in commercial enterprises for many diverse applications. Computational grid provides resource sharing through multiinstitutional virtual organizations for dynamic problem solving. Load balancing is an important property in grid computing as the load scenarios of individual grid resources are dynamic in nature. In order to make computational grids more effective and reliable, balanced load across the grid is necessary. The objective of this paper is to review different existing load balancing algorithms or techniques applicable in grid computing. This paper also proposes an algorithm to solve the prevailing problem of dynamic load balancing with respect to deadline of job submitted by the clients.

A novel Load Balancing algorithm for computational Grid

2010 International Conference on Innovative Computing Technologies (ICICT), 2010

The Grid computing environment is a cooperation of distributed computer systems where user jobs can be executed on either local or remote computer. Many problems exist in grid environment. Not only the computational nodes are heterogeneous but also the underlying networks connecting them are heterogeneous. The network bandwidth varies and the network topology among resources is also not fixed. Thus with this multitude of heterogeneous resources, a proper scheduling and efficient load balancing across the Grid is required for improving performance of the system. The load balancing is done by migrating jobs to the buddy processors, a set of processors to which a processor is directly connected. An algorithm, Load Balancing on Arrival (LBA) is proposed for small-scale (intraGrid) systems. It is efficient in minimizing the response time for small-scale grid environment. When a job arrives LBA computes system parameters and expected finish time on buddy processors and the job is migrated immediately. This algorithm estimates system parameters such as job arrival rate, CPU processing rate and load on each processor to make migration decision. This algorithm also considers job transfer cost, resource heterogeneity and network heterogeneity while making migration decision.

Modified Hierarchical Load Balancing Algorithm for Scheduling in Grid Computing

Grid computing provides a large reliable framework for execution of large scale applications. Grid is a collection of huge number of resources which are heterogeneous in nature. And it also provides access to those resources for reliable execution of the problem. Computation and data grid are two types of grid. This paper considers computational grid. In computational grid, Scheduling of resources is the main challenge. Resources are of different types and dynamic in nature, so load on resource changes randomly. The previous scheduling optimization algorithms consider either economic factor or time factor along with load balancing. This paper proposed a system that considers both economic and time factor with load balancing and provides a reliable framework that is client efficient algorithm. Experimental results show that modified hierarchical load balancing algorithm (mHLBA) provides a better framework for allocation of resources.

A Novel Load Balancing Algorithms in Grid Computing

2014

The Grid is emerging as a wide-scale distributed computing infrastructure that promises to support resource sharing and coordinated problem solving in dynamic multi-institutional Virtual Organizations. The idea is similar to the former Meta Computing where the focus was limited to computation resources, whereas Grid computing takes a broader approach. On one hand, Grid computing provides the user with access to locally unavailable resource types. On the other hand, there is the expectation that a large number of resources are available. A computational Grid is the cooperation of distributed computer systems where user jobs can be executed on either local or remote computer systems. The main aim of the paper is to design an architectural framework to propose decentralized, scalable, adaptive, and distributed algorithms for load balancing across resources for data-intensive computations on Grid environments using job migration algorithms which is Load Balancing Algorithm. KeywordsGrid...

Comparative Analysis of Job Scheduling for Grid Environment

Grid computing is a continuous growing technology that alleviates the executions of largescale resource intensive applications on geographically distributed computing resources. For a computational grid environment, there are number of scheduling policies available to address the scheduling and load balancing problem. Scheduling techniques applied in grid systems are primarily based on the concept of queuing systems, and deals with the allocation of job to computing node. The scheduler, that schedules the incoming job can be based on global vs. local i.e. what information will be used to make a load balancing decision, centralized vs. de-centralized i.e. where load balancing decisions are made, and static vs. dynamic i.e. when the distribution of load is made. The primary objective of all load balancing algorithm is minimization of the makespan value, maximum load balanced and to gain more desirable performance. In this paper, we present the various load balancing strategies of job scheduling for grid computing environment. We also analyze the efficiency and limitations of the various approaches