scholarly journals Energy-aware strategies for reliability-oriented real-time task allocation on heterogeneous platforms

2020 ◽  
Author(s):  
Li Han ◽  
Yiqin Gao ◽  
Jing Liu ◽  
Yves Robert ◽  
Frédéric Vivien
Keyword(s):  
Real Time ◽  
Task Allocation ◽  
Energy Aware ◽  
Heterogeneous Platforms ◽  
Time Task

scholarly journals Contention & Energy-Aware Real-Time Task Mapping on NoC Based Heterogeneous MPSoCs

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 75110-75123 ◽  
Author(s):  
Haider Ali ◽  
Umair Ullah Tariq ◽  
Yongjun Zheng ◽  
Xiaojun Zhai ◽  
Lu Liu
Keyword(s):  
Real Time ◽  
Task Mapping ◽  
Energy Aware ◽  
Time Task

scholarly journals A mutual-selecting market-based mechanism for dynamic coalition formation

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141875584 ◽  
Author(s):  
Bing Xie ◽  
Shaofei Chen ◽  
Jing Chen ◽  
LinCheng Shen
Keyword(s):  
Real Time ◽  
Coalition Formation ◽  
Task Allocation ◽  
Completion Rate ◽  
Utilization Rate ◽  
Task Completion ◽  
Distributed Agents ◽  
Time Task ◽  
Comparable Performance ◽  
Negotiation Mechanism

This article presents a novel market-based mechanism for a dynamic coalition formation problem backgrounded under real-time task allocation. Specifically, we first analyze the main factors of the real-time task allocation problem, and formulate the problem based on the coalition game theory. Then, we employ a social network for communication among distributed agents in this problem, and propose a negotiation mechanism for agents forming coalitions on timely emerging tasks. In this mechanism, we utilize an auction algorithm for real-time agent assignment on coalitions, and then design a mutual-selecting method to acquire better performance on agent utilization rate and task completion rate. And finally, our experimental results demonstrate that our market-based mechanism has a comparable performance in task completion rate to a decentralized approach (within 25% better on average) and a centralized dynamic coalition formation method (within 10% less on average performance).

scholarly journals Energy-Aware Real-Time Task Scheduling for Heterogeneous Multiprocessors with Particle Swarm Optimization Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Weizhe Zhang ◽  
Hucheng Xie ◽  
Boran Cao ◽  
Albert M. K. Cheng
Keyword(s):  
Particle Swarm Optimization ◽  
Energy Consumption ◽  
Real Time ◽  
Task Scheduling ◽  
Particle Swarm ◽  
Energy Aware ◽  
Swarm Optimization ◽  
Heterogeneous Multiprocessors ◽  
Time Task ◽  
Feasible Solutions

Energy consumption in computer systems has become a more and more important issue. High energy consumption has already damaged the environment to some extent, especially in heterogeneous multiprocessors. In this paper, we first formulate and describe the energy-aware real-time task scheduling problem in heterogeneous multiprocessors. Then we propose a particle swarm optimization (PSO) based algorithm, which can successfully reduce the energy cost and the time for searching feasible solutions. Experimental results show that the PSO-based energy-aware metaheuristic uses 40%–50% less energy than the GA-based and SFLA-based algorithms and spends 10% less time than the SFLA-based algorithm in finding the solutions. Besides, it can also find 19% more feasible solutions than the SFLA-based algorithm.

Triple Speed: Energy-Aware Real-Time Task Synchronization in Homogeneous Multi-Core Systems

2016 ◽  
Vol 65 (4) ◽  
pp. 1297-1309 ◽  
Author(s):  
Ting-Hao Tsai ◽  
Lin-Fong Fan ◽  
Ya-Shu Chen ◽  
Tien-Shun Yao
Keyword(s):  
Real Time ◽  
Energy Aware ◽  
Time Task
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