Published on Aug 1, 2015
Wisam Abduladheem Kamil1
Estimated H-index: 1
Shahrudin Awang Nor6
Estimated H-index: 6
Raaid Alubady4
Estimated H-index: 4
Nowadays, the electronic resources are available almost in every institution or facility. These electronic resources could be CPU, memory, electrical devices and so on. Most of these resources are wasted or not completely utilized. Hence, the role of Computational Grid comes. Grid Computing focuses on computing resources (such as CPU), in order to achieve a huge task in a short time. Due to the high heterogeneity in Grid environment, proposing an optimal resource allocation mechanism that can work in all scenarios is a dilemma. This paper presents a critical review about some of the most widely known and recently proposed mechanisms in Grid Computing. Thus, it will give the researchers an idea about the features of the most recent and used resource allocation mechanisms in Grid.
馃摉 Papers frequently viewed together
2 Citations
2007HiPC: IEEE International Conference on High Performance Computing, Data, and Analytics
1 Citations
#1Muhammad Bilal Qureshi (CUI: COMSATS Institute of Information Technology)H-Index: 8
#2Maryam Mehri Dehnavi (MIT: Massachusetts Institute of Technology)H-Index: 9
Last. Albert Y. Zomaya (USYD: University of Sydney)H-Index: 81
view all 11 authors...
Grid is a distributed high performance computing paradigm that offers various types of resources (like computing, storage, communication) to resource-intensive user tasks. These tasks are scheduled to allocate available Grid resources efficiently to achieve high system throughput and to satisfy user requirements. The task scheduling problem has become more complex with the ever increasing size of Grid systems. Even though selecting an efficient resource allocation strategy for a particular task ...
55 CitationsSource
#1Joanna KolodziejH-Index: 30
#2Samee U. Khan (NDSU: North Dakota State University)H-Index: 69
Last. Cheng-Zhong Xu (WSU: Wayne State University)H-Index: 60
view all 8 authors...
Distributed Cyber Physical Systems (DCPSs) are networks of computing systems that utilize information from their physical surroundings to provide important services, such as smart health, energy efficient grid and cloud computing, and smart security-aware grids. Ensuring the energy efficiency, thermal safety, and long term uninterrupted computing operation increases the scalability and sustainability of these infrastructures. Achieving this goal often requires researchers to harness an understan...
44 CitationsSource
#1R. Manimala (Kongu Engineering College)H-Index: 1
#2P. Suresh (Kongu Engineering College)H-Index: 4
Grid computing is a way of combining computers across a network to form a distributed supercomputer to perform complex computations. In the commercial world, grid aims to maximize the utilization of an organization's computing resources by making them shareable across applications. A grid environment can be classified into two types: Computing grids and data grids. In computing grid, job scheduling is an important task. Load Balancing is a technique which is used to distribute the workload equal...
7 CitationsSource
Jun 1, 2012 in GRID (Grid Computing)
#1Ahmed I. Saleh (Mansoura University)H-Index: 14
#2Amany Sarhan (Tanta University)H-Index: 9
Last. Amr M. Hamed (Mansoura University)H-Index: 2
view all 3 authors...
Computational Grids (CGs) have become an appealing research area. They suggest a suitable environment for developing large scale parallel applications. CGs integrate a huge mount of distributed heterogeneous resources for constituting a powerful virtual supercomputer. Scheduling is the most important issue for enhancing the performance of CGs. Various strategies have been introduced, including static and dynamic behaviors. The former maps tasks to resources at submission time, while the latter o...
10 CitationsSource
1 Citations
Apr 23, 2010 in JSSPP (Job Scheduling Strategies for Parallel Processing)
#1Ding Ding (Beijing Jiaotong University)H-Index: 5
#2Siwei Luo (Beijing Jiaotong University)H-Index: 6
Last. Zhan Gao (Beijing Jiaotong University)H-Index: 6
view all 3 authors...
To improve the resource utilization and satisfy more users, a Greedy Double Auction Mechanism(GDAM) is proposed to allocate resources in grid environments. GDAM trades resources at discriminatory price instead of uniform price, reflecting the variance in requirements for profits and quantities. Moreover, GDAM applies different auction rules to different cases, over-demand, over-supply and equilibrium of demand and supply. As a new mechanism for grid resource allocation, GDAM is proved to be stra...
7 CitationsSource
#1E. Saravanakumar (Adhiyamaan College of Engineering)H-Index: 1
#2Gomathy Prathima (Adhiyamaan College of Engineering)H-Index: 1
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 a...
18 CitationsSource
#1Jesse S. A. Bridgewater (UCLA: University of California, Los Angeles)H-Index: 5
Last. Vwani P. Roychowdhury (UCLA: University of California, Los Angeles)H-Index: 53
view all 3 authors...
We present a novel framework, called balanced overlay networks (BON), that provides scalable, decentralized load balancing for distributed computing using large-scale pools of heterogeneous computers. Fundamentally, BON encodes the information about each node's available computational resources in the structure of the links connecting the nodes in the network. This distributed encoding is self-organized, with each node managing its in-degree and local connectivity via random-walk sampling. Assig...
24 CitationsSource
#1Leila Ismail (United Arab Emirates University)H-Index: 13
Grid computing is an emerging paradigm to enable scalable computational environment through efficient resource utilization. In this context, resource allocation is one of the major challenges in grid environment. Currently, several approaches were proposed to solve this problem. However, most of the approaches rely on administrators' intervention for proper allocation. In this paper, we propose dynamic resource allocation mechanisms of computations using a combination of best fit algorithm and p...
8 CitationsSource
#1Chun-tian Cheng (DUT: Dalian University of Technology)H-Index: 1
#2Zhi-jie Li (DUT: Dalian University of Technology)H-Index: 1
This paper presents a proportional sharing resource allocation strategy based on Nash equilibrium in grid computing. Given perfect information, the problem of resource allocation can be formulated as a multi-player game with the players being users purchasing computational service from a common resource. A computable Nash equilibrium for parallel tasks is derived to determine a grid user's bidding strategy. In particular, by introducing maximum entropy method, the initial Nash equilibrium proble...
8 CitationsSource
Cited By2
Nov 1, 2017 in TENCON (IEEE Region 10 Conference)
#1Omar Dakkak (UUM: Universiti Utara Malaysia)H-Index: 2
#2Shahrudin Awang Nor (UUM: Universiti Utara Malaysia)H-Index: 6
Last. Suki Arif (UUM: Universiti Utara Malaysia)H-Index: 5
view all 3 authors...
To tackle complex and massive number of jobs sent by end users, a powerful and dedicated computational resources are required. Grid computing provides such environment in which applications may run for a quite long time. Therefore, efficient scheduling policy is indispensable. In our previous work, a mechanism named Swift Gap followed by developed completion time rule is introduced. This paper deeply analysis the interactions between the introduced mechanism with the simulated workloads and the ...
1 CitationsSource
#1Omar DakkakH-Index: 2
Last. Suki ArifH-Index: 5
view all 3 authors...
Due to the heterogeneity and complexity in grid computing, classical algorithms may not be able to deal with dynamic jobs properly. In the dynamic mode, incoming jobs reach the scheduler arbitrary. Therefore, scheduling the jobs using simple policy alone deteriorates the performance of the scheduler. Thus, a policy that can handle the dynamicity efficiently is indispensable. This paper presents the Swift Gap mechanism (SG), which is a hybridization of the Best Gap mechanism, alongside with Tabu ...
1 CitationsSource