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A Load Distribution Based Resource Allocation Strategy for Bag of Tasks (BoT) in computational grid Environment

WIRELESS PERSONAL COMMUNICATIONS 2024年第1期135卷 47-80页

作者： Sheikh, Sophiya Shahid, Mohammad Sambare, Manas Haidri, Raza Abbas Prakash, Shiv Lovely Profess Univ Sch Comp Applicat Phagwara 144411 Punjab India Aligarh Muslim Univ Dept Commerce Aligarh 202001 Uttar Pradesh India FLAME Univ Dept Data Sci Pune 412115 Maharastra India Khwaja Moinuddin Chishti Language Univ Dept Comp Sci & Informat Technol Lucknow Uttar Pradesh India Univ Allahabad Dept Elect & Commun Allahabad Uttar Pradesh India

In the ever-evolving landscape of computational grid systems, the meticulous selection of resources tailored to specific tasks is a formidable challenge. This paper introduces an efficient load distribution strategy known as Load Distribution Based Resource Allocation (LDRA), one of the foremost goals is to allocate resources to gain enhanced resource utilization and also try to achieve least possible execution time to fulfil the need for grid systems. A comprehensive performance evaluation unfolds to elevate grid efficiency, pitting LDRA against existing heuristics using the ETC Simulation Benchmark. The study expands further on the real-world dataset from the Gaia Cluster Configurations (https://***/systems/gaia/) to verify its significance in the real environment. The LDRA algorithm emerges with superior performance when compared to state-of-the-art such as Max-Min, Opportunistic Load Balancing, AlgHybrid_LB, and Resource Aware Load Balancing for resource utilization, makespan, flowtime, and energy efficiency in the majority of the cases in experimental evaluation. In some cases, the experimental results show that LDRA's usage of the grid resources is remarkable, reaching over 99% in four cases and approaching 98% in two cases of the ETC simulation benchmark. These accomplishments are further mirrored in the evaluation against real datasets, where LDRA's performance among peers is nothing short of exemplary in the cases under study.

关键词： computational grid Resource Allocation Scheduling Load Distribution Scheme Resource Utilization

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A job scheduling algorithm based on parallel workload prediction on computational grid

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2023年 171卷 88-97页

作者： Tang, Xiaoyong Liu, Yi Deng, Tan Zeng, Zexin Huang, Haowei Wei, Qiyu Li, Xiaorong Yang, Li Changsha Univ Sci & Technol Sch Comp & Commun Engn Changsha 410114 Peoples R China Shanghai Univ Sch Microelect Shanghai 201800 Peoples R China Singapore Inst Technol Infocomm Technol Cluster Singapore Singapore

Generally, the computational grid consists of a large number of computing nodes, some of them are idle due to the uneven geographical distribution of computing requirements. This may cause workload unbalancing problems, which affect the performance of large-scale computational grids. In order to balance the computing requirements and computing nodes, we propose a job scheduling algorithm based on the workload prediction of computing nodes. We first analyze the causes of workload imbalance and the feasibility of reallocating computing resources. Secondly, we design an application and workload -aware scheduling algorithm (AWAS) by combining the previously designed workload prediction model. To reduce the complexity of the AWAS algorithm, we propose a parallel job scheduling method based on computing node workload prediction. The experiments show that the AWAS algorithm can balance the workload among different computing nodes on the real-world dataset. In addition, we propose the parallelism of workload prediction model from the perspective of internal structure and data set to make AWAS apply to more computing nodes of the large-scale computing grids. Experimental results show that the combination of the two can achieve satisfactory acceleration efficiency.(c) 2022 Elsevier Inc. All rights reserved.

关键词： Job scheduling Workload balancing Neural network computational grid Parallel

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Dynamic energy efficient load balancing strategy for computational grid

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2022年第1期34卷

作者： Nazir, Babar Ahmad, Zulfiqar Pak Austria Fachhsch Inst Appl Sci & Technol Dept Informat Technol & Comp Sci Haripur Khyber Pakhtunk Pakistan Hazara Univ Dept Comp Sci & Informat Technol Mansehra Khyber Pakhtunk Pakistan

computational grid is a pool of computational resources that is used by various organizations for storage purposes and execution of a large number of tasks. Load balancing and energy consumption are two core performance parameters in the computational grid. Since, performance of a computational grid is highly dependable to variations in load and energy consumption, therefore, it is important to pay attention to these aspects in grid. Therefore, we proposed an energy-aware dynamic load balancing strategy for tasks scheduling in grid referred to as dynamic energy efficient load balancing strategy (DEEL) for computational grid. DEEL combined energy efficiency and load balancing paradigms in order to improve the utilization and reduce the energy consumption of resources. Simulations were performed by using gridSim. Simulation results were compared with published strategy IEGDC with respect to performance indices: finished gridlets, unfinished gridlets, resubmitted times, and response time. The simulation results were evaluated through performance metrics that is, (a) cost, (b) energy consumption, and (c) energy saved. As per simulation results, DEEL outperformed the published method IEGDC by reducing the execution time of finished gridlets up to 28%, minimizing the execution and resource cost up to 35%, and saving the energy consumption up to 38%.

关键词： computational grid energy efficiency execution time gridSim load balancing

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computational grid scheduling architecture using MapReduce model-based non-dominated sorting genetic algorithm

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SOFT COMPUTING 2019年第18期23卷 8335-8347页

作者： Rajeswari, D. Prakash, M. Suresh, J. SRM Inst Sci & Technol Dept Comp Sci & Engn Kancheepuram Tamil Nadu India CK Coll Engn & Technol Dept Comp Sci & Engn Cuddalore Tamil Nadu India

computational grid (CG) environment has a group of autonomous dissimilar distributed computing systems to provide service to user tasks. To attain the auspicious usefulness of CG resources, basically best scheduling algorithms are important. The CG service users are very cautious in time needed for task completion. To meet multiple requirements of the user, the job allocation problem in CG is designed as a multi-objective problem. Evolutionary algorithms have an efficient meta-heuristic technique for optimization problem solving. This work introduces a MapReduce model for non-dominated sorting genetic algorithm (NSGA-II) for independent job scheduling in a CG. This research work attempts to find the optimal schedules by considering makespan and flowtime minimization. A fuzzy membership function is used to analyze the efficiency of the schedule. Set of benchmark instances is used to test the algorithm. Experimental results show that MapReduce model-based NSGA-II generated finer solutions in less time than the MapReduce model-based weighted sum multi-objective genetic algorithm (WMOGA) which is also implemented in this paper.

关键词： computational grid MapReduce Multi-objective Task scheduling Non-dominated sorting Genetic algorithm

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A fault-tolerant hybrid resource allocation model for dynamic computational grid

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JOURNAL OF computational SCIENCE 2021年 48卷 101268-101268页

作者： Sheikh, Sophiya Nagaraju, A. Shahid, Mohammad Cent Univ Rajasthan Dept Comp Sci NH-8 Bandarsindri 305817 Ajmer India Aligarh Muslim Univ Dept Commerce Aligarh 202002 Uttar Pradesh India

Effectual allocation of resources with fault tolerance is one of the key targets in any computational grid environment to accomplish the task execution on time. In this paper, a Fault Tolerant Hybrid Resource allocation Model (FTHRM) has been proposed to minimize the Turnaround Time (TAT) for the batch of tasks while ensuring fault tolerance in a dynamic grid environment. The model uses the prior reservation mechanism to allocate the resources to tasks for guaranteed task execution. Furthermore, resources are reserved in advance for time slots with resource configuration as required by the batch of tasks. Alternate resources are provided by the system in the case of resource failures. Here, the resource with the least previous workload and lowest execution time will prefer over other resources for task accomplishment. The performance evaluation of FTHRM has been carried out by comparing it with Minimum Completion Time (MCT). The simulation study reveals that the proposed model viz. FTHRM outperforms MCT on considered parameters under study. Statistical testing has been conducted to test the level of significance using SPSS 20, which also confirms the conclusions drawn in the simulation.

关键词： computational grid Resource allocation Fault-tolerance Advance reservation Minimum completion time

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Dynamic task scheduling with advance reservation of resources to minimize turnaround time for computational grid

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International Journal of Information Technology (Singapore) 2020年第2期12卷 625-633页

作者： Sheikh, Sophiya Nagaraju, Aitha Department of Computer Science Central University of Rajasthan NH-8 Banadarsindri Kishangarh Ajmer India

It is a vital necessity of a heterogeneous environment to schedule the resources efficiently among applications to optimize the execution time to provide well-regulated services to the users. The system is said to be effective only if it supplies the resources on time and assures smooth task execution. This paper introduces a dynamic task scheduling with advance reservation (DTSAR) of resources to optimize turnaround time (TAT). A task will be dynamically allocated to the resource in an advance manner that takes meanest execution time. More parameters are considered for performance comparison viz. flow time, average utilization and processing cost. Simulation results acknowledge the preferable achievements of the proposed scheduling schemes on the comparison of another state of art in literature. The experimental assessments and obtained results show that DTSAR is preferable than other considered heuristics in terms of TAT and other QoS parameters. © 2020, Bharati Vidyapeeth's Institute of Computer Applications and Management.

关键词： Advance reservation computational grid Dynamic task scheduling Execution time QoS parameters Turnaround time

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A reliable, TOPSIS-based multi-criteria, and hierarchical load balancing method for computational grid

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第4期22卷 1085-1106页

作者： Abdullah, Aref M. Ali, Hesham A. Haikal, Amira Y. Taiz Univ Taizi Yemen Mansoura Univ Al Daqhaliya Egypt Mansoura Univ Fac Engn Comp Engn Control Sys Dept Al Daqhaliya Egypt

Load balancing is a very important and complex problem in computational grids. In load balancing, jobs should be effectively distributed among resources in order to minimize the average completion time and maximize the utilization of all resources even those with low reliabilities and capacities. However, using the less reliable and slow resources implies worse completion time, whereas always selecting the powerful and reliable resources undermines the utilization of other resources. So, it is essential to develop an efficient load balancing method which makes a good tradeoff between these criteria in a way that satisfies the quality of service of jobs and fairly distributes jobs between resources based on their reliabilities and capacities. This paper proposes an efficient multicriteria load balancing method using technique for order preference by similarity to ideal solution which treats load balancing as a multi criteria decision making problem. Also, an effective weighting mechanism is proposed, which adaptively adjusts the weights of the considered criteria according to the system's current state and jobs' characteristics. This mechanism can make an efficient tradeoff between the considered criteria and accurately reflect the importance of each one. By simulation, the proposed method was evaluated and compared with other approaches from the literature. In the range of examined parameters' values, the simulation results show that proposed method minimizes the average completion time by 8.7-15.7%, increases the throughput ratio up to 15.8-19.4%, and maximizes the load balancing level by 7.68-20.1%.

关键词： computational grid grid scheduling Load balancing Fault tolerance Distributed system

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Job Scheduling in computational grid Using a Hybrid Algorithm Based on Particle Swarm Optimization and Extremal Optimization

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JOURNAL OF INFORMATION TECHNOLOGY RESEARCH 2018年第4期11卷 72-86页

作者： Ghosh, Tarun Kumar Das, Sanjoy Haldia Inst Technol Dept Comp Sci & Engn Haldia W Bengal India Kalyani Univ Dept Engn & Technol Studies Kalyani W Bengal India

grid computing has been used as a new paradigm for solving large and complex scientific problems using resource sharing mechanism through many distributed administrative domains. One of the most challenging issues in computational grid is efficient scheduling of jobs, because of distributed heterogeneous nature of resources. In other words, the job scheduling in computational grid is an NP hard problem. Thus, the use of meta-heuristic is more appropriate option in obtaining optimal results. In this article, the authors propose a novel hybrid scheduling algorithm which combines intelligently the exploration ability of Particle Swarm Optimization (PSO) with the exploitation ability of Extremal Optimization (EO) which is a recently developed local-search heuristic method. The hybrid PSO-EO reduces the schedule makespan, processing cost, and job failure rate and improves resource utilization. The proposed hybrid algorithm is compared with the standard PSO, population-based EO (PEO) and standard Genetic Algorithm (GA) methods on all these parameters. The comparison results exhibit that the proposed algorithm outperforms other three algorithms.

关键词： computational grid EO Job Scheduling Makespan PSO Resource Utilization

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A hybrid heuristic resource allocation model for computational grid for optimal energy usage

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INTERNATIONAL JOURNAL OF grid AND UTILITY COMPUTING 2018年第1期9卷 51-74页

作者： Kaushik, Achal Vidyarthi, Deo Prakash GGSIP Univ Bhagwan Parshuram Inst Technol Dept Comp Sci Engn New Delhi India Jawaharlal Nehru Univ Sch Comp & Syst Sci New Delhi India

computational grid helps in faster execution of compute intensive jobs. The resource allocation for the job execution in computational grid demands a lot of characteristic parameters to be optimised but in the process the green aspect is ignored. Reducing the energy consumption in computational grid is a major recent issue among researchers. The conventional systems, which offer energy efficient scheduling strategies, ignore other quality of service parameters while scheduling the jobs. The proposed work tries to optimise the energy for resource allocation and at the same time makes no compromise on other related characteristic parameters. A hybrid model, that uses genetic algorithm and graph theory concept has been proposed for this purpose. In this model, an energy saving mechanism is implemented using a dynamic threshold method followed by genetic algorithm to further consolidate the saving. Eventually, a graph theory concept of Minimum Spanning Tree (MST) is applied. The performance of the proposed model has been studied by its simulation. The result reveals the benefits achieved with the proposed model for optimal energy with resource allocation in the grid.

关键词： computational grid green energy resource allocation genetic algorithm MST minimum spanning tree QoS quality of service

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Dynamic Load Balancing with Advanced Reservation of Resources for computational grid

Dynamic Load Balancing with Advanced Reservation of Resource...

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International Conference on Computing, Analytics and Networking (ICCAN)

作者： Sheikh, Sophiya Nagaraju, Aitha Shahid, Mohammad Cent Univ Rajasthan Dept Comp Sci Kishangarh Ajmer India Aligarh Muslim Univ Dept Commerce Aligarh Uttar Pradesh India

ISBN: (纸本)9789811078712;9789811078705

The primary requirement of heterogeneous computing is minimization of task waiting time in order to well regulate services to the users with efficient resource utilization. In this paper, we propose a dynamic load balancing with advanced reservation (DLBAR) of resources that commits advanced reservation of resources to tasks to minimize load imbalance on nodes with optimum makespan. The objective of this work is to allocate and calculate load earlier in advance on each resource before task execution started to efficiently distribute load among available resources, and other parameters like makespan are computed for performance evaluation. In order to show the effectiveness of proposed model, an unbiased comparative performance analysis is carried out with other well-known load balancing heuristic approach available in the literature. The simulation study reveals the motivation of algorithm with the superior performance of the proposed algorithm on account of all considered parameters under study.

关键词： computational grid Dynamic load balancing Waiting time Advanced reservation

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