A reformed task scheduling algorithm for heterogeneous distributed systems with energy consumption constraints

2019 ◽  
Vol 32 (10) ◽  
pp. 5681-5693
Author(s):  
Yikun Hu ◽  
Jinghong Li ◽  
Ligang He
Keyword(s):  
Energy Consumption ◽  
Distributed Systems ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Task Scheduling Algorithm ◽  
Heterogeneous Distributed Systems ◽  
Consumption Constraints

Enhanced Parallel Application Scheduling Algorithm with Energy Consumption Constraint in Heterogeneous Distributed Systems

2019 ◽  
Vol 28 (11) ◽  
pp. 1950190 ◽  
Author(s):  
Jinghong Li ◽  
Guoqi Xie ◽  
Keqin Li ◽  
Zhuo Tang
Keyword(s):  
Energy Consumption ◽  
Distributed Systems ◽  
Gaussian Elimination ◽  
Scheduling Algorithm ◽  
Parallel Applications ◽  
Parallel Application ◽  
Heterogeneous Distributed Systems ◽  
Dynamic Voltage ◽  
Cluster Computer Systems ◽  
Consumption Constraints

Energy consumption has always been one of the main design problems in heterogeneous distributed systems, whether for large cluster computer systems or small handheld terminal devices. And as energy consumption explodes for complex performance, many efforts and work are focused on minimizing the schedule length of parallel applications that meet the energy consumption constraints currently. In prior studies, a pre-allocation method based on dynamic voltage and frequency scaling (DVFS) technology allocates unassigned tasks with minimal energy consumption. However, this approach does not necessarily result in minimal scheduling length. In this paper, we propose an enhanced scheduling algorithm, which allocates the same energy consumption for each task by selecting a relatively intermediate value among the unequal allocations. Based on the two real-world applications (Fast Fourier transform and Gaussian elimination) and the randomly generated parallel application, experiments show that the proposed algorithm not only achieves better scheduling length while meeting the energy consumption constraints, but also has better performance than the existing parallel algorithms.

scholarly journals A New Task Scheduling Algorithm for Maximizing the Distributed Systems Efficiency

2015 ◽  
Vol 110 (9) ◽  
pp. 9-16
Author(s):  
Amal El-Nattat ◽  
Nirmeen A. El-Bahnasawy ◽  
Ayman El-Sayed
Keyword(s):  
Distributed Systems ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Task Scheduling Algorithm

scholarly journals An Improved Min-Min Task Scheduling Algorithm with Grid Utilization and Minimized Makespan

2015 ◽  
Vol 14 (8) ◽  
pp. 5960-5966 ◽  
Author(s):  
Lalla Singh ◽  
Neha Agarwal
Keyword(s):  
Distributed Systems ◽  
Load Balancing ◽  
Grid Computing ◽  
Task Scheduling ◽  
Completion Time ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Basic Algorithm ◽  
Software Infrastructure ◽  
Task Scheduling Algorithm

Grid computing is hardware and software infrastructure which offers a economical, distributable, coordinated and credible access to strong computational abilities [1]. For optimal use of the abilities of large distributed systems, necessitate for successful and proficient scheduling algorithms is enforced. For diminution of total completion time and improvement of load balancing, many algorithms have been executed. In this paper, our goal is to propose new scheduling algorithm based on well known task scheduling algorithm i.e. Min-Min[1]. The proposed algorithm tries to use the advantages of this basic algorithm and excludes its drawbacks with better grid utilization and minimized makespan. In comparison to existing algorithms like Min-Min and improved Min-Min algorithm[1], our proposed algorithm is achieving better results for considered parameters.

Task Scheduling Algorithm based on Resources Segregation in Cloud Environment

2018 ◽  
pp. 96-101
Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey
Keyword(s):  
Load Balancing ◽  
Task Scheduling ◽  
Waiting Time ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Task Scheduling Algorithm ◽  
Machine Utilization ◽  
Independent Tasks ◽  
Optimal Machine

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.

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