Multiprocessor task scheduling in multistage hybrid flow-shops: A parallel greedy algorithm approach. Applied Soft Computing, 10(4):1293-1300, 2010.Serifoglu, F. Sivrikaya,Ulusoy, G.Multiprocessor task schedulin
This paper presents the solution quality analysis of a parallel tabu search algorithm for the task scheduling problem on heterogeneous processors under precedence constraints. We evaluate the achieved makespan reduction of different parallel applications, relatively to the results obtained by the best greed...
Kumar, A.S., Venkatesan, M.: Task scheduling in a cloud computing environment using HGPSO algorithm. Clust. Comput. 22(1), 2179–2185 (2019) Article Google Scholar Oyelade, O.N., et al.: Ebola optimization search algorithm: a new nature-inspired metaheuristic optimization algorithm. IEE...
The above recursive greedy algorithm can be expressed in an iterative manner. In task scheduling, we repeat the same process again and again, so iteration of the same process is computationally efficient. In this case, we have two tasks, s is set of all the tasks, and f is the set of...
The result shows that it can reduce about 40% of the energy consumption of the non-power-aware data center and reduce 1.7% energy consumption of the greedy scheduling algorithm in data center scheduling area [18]. Lin et al. used TD-error reinforcement learning to reduce the energy ...
And an efficient collaborative greedy task scheduling algorithm was designed to achieve the optimization objective. However, little attention has been paid to the relationship between energy consumption and system performance in a UAV-assisted multi-clouds computing system. So we concentrate on the ...
Overall, these types of problems underlie many day-to-day cognitive tasks such as shopping, bin packing, way-finding and task scheduling4,5. We tested human performance in the Boolean satisfiability problem (3SAT) and the traveling salesperson problem (TSP), and compared these results to those...
Collision-free path planning and task scheduling optimization in multi-region operations of autonomous agricultural robots present a complex coupled problem. In addition to considering task access sequences and collision-free path planning, multiple fact
Pham et al.[114]presented a taskscheduling algorithmin the Fog-Cloud environment. The proposed algorithm performs the scheduling by specifying the priorities of tasks, and determining which node to execute tasks. The obtained results show that the proposed algorithm provides an efficient balance betwee...
Evolutionary Many-Objective Algorithm NSGAIII Tasks scheduling Cloud Optimization 1. Introduction Cloud computing can be defined as an economic and technological revolution where Information Technologies (IT) resources (CPU, Memory, Storage, etc.) are provided as a service via a secure Internet connectio...