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Oata Grid provides transparent access to grid user. The grid data stored across distributed storage resources whilst fulfilling the Confidentiality, Integrity, Availability (C,I,A). The stored data is replicated in data grid to increase the availability. Replica Manager uses replica replacement algorithm to decide which replica to be replaced for the new replica when there is not enough space for...
Grid technology is the structure of technology that provides highly efficient performance in the grid environment. Design of an efficient and reliable task scheduling algorithm is one of the challenging issues in grid computing. A novel improvised scheduling algorithm (IDSA) with deadline limitation for efficient job execution is proposed in this paper. This algorithm is compared with renowned task...
Web-based service-oriented grid computing refers to a distributed computing system comprising a collection of interconnected and virtual computers that provides web-based services via the Internet. These services are based on Service Level Agreements (SLAs) established by negotiation between service providers and consumers. SLAs are contractual obligations that define the mutually agreed understandings...
The necessity of making a system robust to the uncertainties of the different measures taken from the computing infrastructure is one of the Grid Computing research challenges. In particular, taking relevant information to tasks scheduling from a set of heterogeneous sources and dynamic behavior has been the focus of a significant number of studies. Considering this background, this paper aims to...
A great challenge faced by many organizations refers to translating their large computing infrastructure into an effective tool to support their productive chain. In this paper, we introduce a modular single point of access middleware approach focused on integrating distributed and heterogeneous computing resources, coined as Dédalo. Since its design, which follows a software product line (SPL) paradigm,...
Agents and agent systems are becoming more and more important in the development of a variety of fields such as ubiquitous computing, ambient intelligence, autonomous computing, intelligent systems and intelligent robotics. In this paper, we analyze how agent technology is presented in mathematical models of computation demonstrating how these models are used in the novel distributed intelligent managed...
Grid computing is a collection of computer resources from multiple locations to reach a common goal. Grid computing distinguishes from conventional high performance computing systems that are heterogeneous and geographically dispersed than cluster computer. One of the major issues in grid computing is load balancing. Classification of load balancing is: Static - Dynamic, Centralized - Decentralized,...
As communication was the major perspective of traditional networks, grid computing focuses on figuring the problems by using unprocessed CPU cycles that cannot be resolved by stand-alone computers. Grid being an earthly distributed network of computers provides a clear, coordinated, consistent and reliable computing medium to various applications. Owing to the heterogeneity of resources in a grid...
This paper discusses a method that can be used for efficiency increasing of distributed computing by using dynamic parameters redefinition of the executed tasks. The method based on idea that we can variate the complexity of tasks by changing their parameters. Using hybrid modelling we determine optimization possibility for the procedure of application running as well as estimate the number of necessary...
With the ever increasing technology integration, the analysis, operation and control of power system is becoming more and more complicated. Grid Computing is one of the solutions for integrating such a large and complicated system. Grid Computing integrates computational resources from various geographical and administrative locations to accomplish a common task. This paper presents a review on the...
Rapid growth of internet and other technologies seems more challenging to develop the high speed networks with powerful capabilities in lower computational cost. To cover the above problem grid computing has emerged rapidly. The previous technologies such as distributed computing cluster computing, parallel computing, etc., facing the problem of space utilization. Using Grid Computing technologies...
Workload information management and resource management are two key aspects in grid computing to provide the better services to grid environment users. Grid computing also faced other challenging areas like heterogeneous nature of resources, huge number of computing elements, independency of computing resources, different processing capacities of the nodes, different types of load conditions, overloading...
Computational Grids are high performance computing systems used to solve large scale computational demands. Because scheduling workflow applications in a distributed environment is a NP-Complete problem, meta-heuristics are introduced to solve this issue. In this paper, we propose an Energy-Aware algorithm based on Discrete Particle Swarm Optimization (DPSO) called EA-DPSO. Our aim is to minimize...
As we come to terms with various big data challenges, one vital issue remains largely untouched. That is service level agreement (SLA) management to deliver strong Quality of Service (QoS) guarantees for big data analytics applications (BDAA) sharing the same underlying infrastructure, for example, a public cloud platform. Although SLA and QoS are not new concepts as they originated much before the...
Desktop Grid (DG) systems use a combination of geographically heterogeneous distributed resources to execute jobs from science and engineering projects. Organization of the distributed resources are administrated by scheduling policies. To evaluate and prove the effectiveness of DG scheduling policy, a simulator is necessary since DG is an unpredictable and unrepeatable environment. Hence, the goal...
Over the decades people have seen a change from large mainframe computing to commodity, off-the-shelf clusters of high performance computers. Currently data centers have thousands or tens of thousands of high performance computers that provides services as well as computation for tens or hundreds of thousands of users. Traditional IT challenges such as scheduling, resource allocation and now data...
Grid computing is considered as the upcoming phase of distributed computing. Grid focuses on maximizing the resource utilization of an organization by sharing them across application. Ingrid computing, job scheduling is an important task. Load balancing and resource allocation are vital issues that must be considered in a grid computing environment. Load balancing is the technique which distributes...
A mortal finding out proteins logs into a pc and uses a complete network of computers to investigate knowledge. A man of affairs accesses his company's network through a personal organizer so as to forecast the long run of a selected stock. a military official accesses and coordinates pc resources on 3 completely different military networks to formulate a battle strategy. All of those situations have...
Grid computing creates the illusion of a simple but large and powerful self-managing virtual computer out of a large collection of connected heterogeneous systems sharing various combinations of resources which leads to the problem of load balance. In this paper, two techniques such as MMS and EMS are proposed for job scheduling in grid. The objective of the scheduling process is to map each job with...
In the standard firefly algorithm, every firefly has same parameter settings and its value changes from iteration to iteration. The solutions keeps on changing as the optima are approaching which results that it may fall into local optimum. Furthermore, the underlying strength of the algorithm lies in the attractiveness of less brighter firefly towards the brighter firefly which has an impact on the...
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