Dynamic Dependent Tasks Assignment for Grid Computing

2011 ◽  
Vol 3 (2) ◽  
pp. 44-58 ◽  
Author(s):  
Meriem Meddeber ◽  
Belabbas Yagoubi
Keyword(s):  
Resource Management ◽  
Grid Computing ◽  
Large Scale ◽  
Task Assignment ◽  
Considerable Effect ◽  
Distributed Applications ◽  
Grid Middleware ◽  
Assignment Strategy ◽  
Transfer Cost ◽  
Dependent Tasks

A computational grid is a widespread computing environment that provides huge computational power for large-scale distributed applications. One of the most important issues in such an environment is resource management. Task assignment as a part of resource management has a considerable effect on the grid middleware performance. In grid computing, task execution time is dependent on the machine to which it is assigned, and task precedence constraints are represented by a directed acyclic graph. This paper proposes a hybrid assignment strategy of dependent tasks in Grids which integrate static and dynamic assignment technologies. Grid computing is considered a set of clusters formed by a set of computing elements and a cluster manager. The main objective is to arrive at a method of task assignment that could achieve minimum response time and reduce the transfer cost, inducing by the tasks transfer respecting the dependency constraints.

Dynamic Dependent Tasks Assignment for Grid Computing

2013 ◽  
pp. 58-73
Author(s):  
Meriem Meddeber ◽  
Belabbas Yagoubi
Keyword(s):  
Resource Management ◽  
Grid Computing ◽  
Large Scale ◽  
Task Assignment ◽  
Considerable Effect ◽  
Distributed Applications ◽  
Grid Middleware ◽  
Assignment Strategy ◽  
Transfer Cost ◽  
Dependent Tasks

A computational grid is a widespread computing environment that provides huge computational power for large-scale distributed applications. One of the most important issues in such an environment is resource management. Task assignment as a part of resource management has a considerable effect on the grid middleware performance. In grid computing, task execution time is dependent on the machine to which it is assigned, and task precedence constraints are represented by a directed acyclic graph. This paper proposes a hybrid assignment strategy of dependent tasks in Grids which integrate static and dynamic assignment technologies. Grid computing is considered a set of clusters formed by a set of computing elements and a cluster manager. The main objective is to arrive at a method of task assignment that could achieve minimum response time and reduce the transfer cost, inducing by the tasks transfer respecting the dependency constraints.

Dynamic Dependent Tasks Assignment for Grid Computing

2012 ◽  
pp. 551-565
Author(s):  
Meriem Meddeber ◽  
Belabbas Yagoubi
Keyword(s):  
Resource Management ◽  
Grid Computing ◽  
Large Scale ◽  
Task Assignment ◽  
Considerable Effect ◽  
Distributed Applications ◽  
Grid Middleware ◽  
Assignment Strategy ◽  
Transfer Cost ◽  
Dependent Tasks

A computational grid is a widespread computing environment that provides huge computational power for large-scale distributed applications. One of the most important issues in such an environment is resource management. Task assignment as a part of resource management has a considerable effect on the grid middleware performance. In grid computing, task execution time is dependent on the machine to which it is assigned, and task precedence constraints are represented by a directed acyclic graph. This paper proposes a hybrid assignment strategy of dependent tasks in Grids which integrate static and dynamic assignment technologies. Grid computing is considered a set of clusters formed by a set of computing elements and a cluster manager. The main objective is to arrive at a method of task assignment that could achieve minimum response time and reduce the transfer cost, inducing by the tasks transfer respecting the dependency constraints.

scholarly journals Massively multi-user online platform for large-scale applications

2021 ◽  
Author(s):  
Allen Yen-Cheng Yu
Keyword(s):  
Grid Computing ◽  
High Performance ◽  
Large Scale ◽  
Distributed Applications ◽  
Service Architecture ◽  
Online Application ◽  
Online Platform ◽  
Massively Multiplayer Online Game ◽  
And Performance

Many large-scale online applications enable thousands of users to access their services simultaneously. However, the overall service quality of an online application usually degrades when the number of users increases because, traditionally, centralized server architecture does not scale well. In order to provide better Quality of Service (QoS), service architecture such as Grid computing can be used. This type of architecture offers service scalability by utilizing heterogeneous hardware resources. In this thesis, a novel design of Grid computing middleware, Massively Multi-user Online Platform (MMOP), which integrates the Peer-to-Peer (P2P) structured overlays, is proposed. The objectives of this proposed design are to offer scalability and system design flexibility, simplify development processes of distributed applications, and improve QoS by following specified policy rules. A Massively Multiplayer Online Game (MMOG) has been created to validate the functionality and performance of MMOP. The simulation results have demonstrated that MMOP is a high performance and scalable servicing and computing middleware.

scholarly journals Massively multi-user online platform for large-scale applications

2021 ◽  
Author(s):  
Allen Yen-Cheng Yu
Keyword(s):  
Grid Computing ◽  
High Performance ◽  
Large Scale ◽  
Distributed Applications ◽  
Service Architecture ◽  
Online Application ◽  
Online Platform ◽  
Massively Multiplayer Online Game ◽  
And Performance

Many large-scale online applications enable thousands of users to access their services simultaneously. However, the overall service quality of an online application usually degrades when the number of users increases because, traditionally, centralized server architecture does not scale well. In order to provide better Quality of Service (QoS), service architecture such as Grid computing can be used. This type of architecture offers service scalability by utilizing heterogeneous hardware resources. In this thesis, a novel design of Grid computing middleware, Massively Multi-user Online Platform (MMOP), which integrates the Peer-to-Peer (P2P) structured overlays, is proposed. The objectives of this proposed design are to offer scalability and system design flexibility, simplify development processes of distributed applications, and improve QoS by following specified policy rules. A Massively Multiplayer Online Game (MMOG) has been created to validate the functionality and performance of MMOP. The simulation results have demonstrated that MMOP is a high performance and scalable servicing and computing middleware.

scholarly journals Hierarchical Task Assignment Strategy for Heterogeneous Multi-UAV System in Large-Scale Search and Rescue Scenarios

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Jie Chen ◽  
Kai Xiao ◽  
Kai You ◽  
Xianguo Qing ◽  
Fang Ye ◽  
...  
Keyword(s):  
Large Scale ◽  
Cluster Head ◽  
Task Assignment ◽  
Search And Rescue ◽  
Small Scale ◽  
Assignment Strategy ◽  
Negotiation Mechanism ◽  
Decoupling Algorithm ◽  
Task Assignment Problem ◽  
Multi Uav

For the large-scale search and rescue (S&R) scenarios, the centralized and distributed multi-UAV multitask assignment algorithms for multi-UAV systems have the problems of heavy computational load and massive communication burden, which make it hard to guarantee the effectiveness and convergence speed of their task assignment results. To address this issue, this paper proposes a hierarchical task assignment strategy. Firstly, a model decoupling algorithm based on density clustering and negotiation mechanism is raised to decompose the large-scale task assignment problem into several nonintersection and complete small-scale task assignment problems, which effectively reduces the required computational amount and communication cost. Then, a cluster head selection method based on multiattribute decision is put forward to select the cluster head for each UAV team. These cluster heads will communicate with the central control station about the latest assignment information to guarantee the completion of S&R mission. At last, considering that a few targets cannot be effectively allocated due to UAVs’ limited and unbalanced resources, an auction-based task sharing scheme among UAV teams is presented to guarantee the mission coverage of the multi-UAV system. Simulation results and analyses comprehensively verify the feasibility and effectiveness of the proposed hierarchical task assignment strategy in large-scale S&R scenarios with dispersed clustering targets.

Grid Computing Based Middleware for Labor and Social Security Data Storage Resources Discovery

2011 ◽  
Vol 148-149 ◽  
pp. 1425-1428
Author(s):  
Jian Yu
Keyword(s):  
Social Security ◽  
Grid Computing ◽  
Data Storage ◽  
Social Insurance ◽  
Large Scale ◽  
Data Grid ◽  
Dynamic Management ◽  
Grid Middleware ◽  
Large Scale Data ◽  
Large Groups

Labor and social security social insurance and employment related to large groups of services. The labor security department of information technology often combined with computational grid computing systems. This paper presents a new kind of data grid middleware for data storage resources discovery and dynamic management in labor and social security resources environment. The architecture of grid storage resources discovery and dynamic management is presented for discovering data storage resources from the different computer organizational structure. The middleware can realize the necessary functions for the ultra large-scale application in data grid environment. It could be applied to the ultra large-scale data storage management in grid computing in next generation labor and social security resources environment.

scholarly journals Trust Management for Grid Systems

2010 ◽  
pp. 149-178
Author(s):  
Benjamin Aziz ◽  
Alvaro Arenas ◽  
Fabio Martinelli ◽  
Paolo Mori ◽  
Marinella Petrocchi
Keyword(s):  
Grid Computing ◽  
Trust Management ◽  
Large Scale ◽  
Distributed Computation ◽  
Shared Resources ◽  
Grid Systems ◽  
Grid Middleware ◽  
Grid Environments ◽  
Administrative Domains ◽  
Heterogeneous Resources

Grid computing is a paradigm for distributed computation on shared resources. It uses a large-scale, highly decentralized infrastructure, in which a huge number of participants share heterogeneous resources for a given purpose. Each participant both provides their own resources and exploits others’ resources, combining them to solve their own problems. Trust management is a major issue in the shared Grid environment because Grid participants are usually unknown to each other and usually belong to separate administrative domains, with little or no common trust in the security of opposite infrastructures. The standard security support provided by the most common Grid middleware may be regarded as one means through which such common trust may be established. However, such security solutions are insufficient to exhaustively address all the trust requirements of Grid environments. In this chapter, the authors survey proposals for enhancing trust management in Grid systems.

Task Assignment for Multiple-Application Workload with Streaming Ones in MPSoC Using Shared Memory

2012 ◽  
Vol 263-266 ◽  
pp. 1781-1785
Author(s):  
Qi Zuo
Keyword(s):  
Shared Memory ◽  
Large Scale ◽  
Task Assignment ◽  
Streaming Application ◽  
Streaming Applications ◽  
Multiple Application ◽  
Memory Contention ◽  
Assignment Strategy ◽  
Overall Performance ◽  
On Chip

Large scale Multi-Processor System-on-a-chip (MPSoC) based on Network on Chip (NoC) can support multiple applications running simultaneously. When the multiple-application workload includes streaming applications processing massive data, the communication concentrated on shared memory can't be ignored. In this paper, we propose a task assignment strategy for multiple-application workload which includes one streaming application on a NoC-based MPSoC. The proposed algorithm first assigns the streaming application centering the multi-port shared memory, and then assigns the other applications minimizing external communication congestion. By adopting the proposed algorithm, the memory-contention tasks are assigned to the PEs close to the shared memory and the overall congestion is minimized. This allows the system to provide better overall performance.

A Combined Approach for Implementation of Broadcast Operation in Grid Computing

2013 ◽  
Vol 5 (1) ◽  
pp. 25-36
Author(s):  
Ghalem Belalem ◽  
Mohammed Ilyes Kara Mostefa
Keyword(s):  
Grid Computing ◽  
Large Scale ◽  
Distributed Applications ◽  
Scheduling Problems ◽  
Distributed Environment ◽  
Hybrid Strategy ◽  
Large Scale Systems ◽  
Information Power ◽  
Grid Simulation ◽  
Collective Communications

In distributed computing, the collective communications scheduling is among the most important scheduling problems related to intensive applications executed over heterogeneous platforms. The optimization of collective operations allows the improvement of parallel and distributed applications performance by reducing the completion time of these operations. In this paper, the authors are particularly interested by the optimization of broadcast operation executed over large scale distributed environment such as grid computing. For this aim, we combined the two levels approach implemented in MagPIe library proposed for the hierarchical large scale systems with the ECEF (Earliest Completion Edge First) heuristic proposed for the IPG (Information Power Grid). Simulation results show the advantage of our proposed hybrid strategy compared to the classical ECEF heuristic.

scholarly journals Trust Management for Grid Systems

2012 ◽  
pp. 1033-1061
Author(s):  
Benjamin Aziz ◽  
Alvaro Arenas ◽  
Fabio Martinelli ◽  
Paolo Mori ◽  
Marinella Petrocchi ◽  
...  
Keyword(s):  
Grid Computing ◽  
Trust Management ◽  
Large Scale ◽  
Distributed Computation ◽  
Shared Resources ◽  
Grid Systems ◽  
Grid Middleware ◽  
Grid Environments ◽  
Administrative Domains ◽  
Heterogeneous Resources

Grid computing is a paradigm for distributed computation on shared resources. It uses a large-scale, highly decentralized infrastructure, in which a huge number of participants share heterogeneous resources for a given purpose. Each participant both provides their own resources and exploits others’ resources, combining them to solve their own problems. Trust management is a major issue in the shared Grid environment because Grid participants are usually unknown to each other and usually belong to separate administrative domains, with little or no common trust in the security of opposite infrastructures. The standard security support provided by the most common Grid middleware may be regarded as one means through which such common trust may be established. However, such security solutions are insufficient to exhaustively address all the trust requirements of Grid environments. In this chapter, the authors survey proposals for enhancing trust management in Grid systems.

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