Static Thermal-Aware Task Assignment and Scheduling for Makespan Minimization in Heterogeneous Real-Time MPSoCs

2016 ◽  
Author(s):  
Kun Cao ◽  
Junlong Zhou ◽  
Min Yin ◽  
Tongquan Wei ◽  
Mingsong Chen
Keyword(s):  
Real Time ◽  
Task Assignment ◽  
Makespan Minimization

scholarly journals A Real-Time Framework for Task Assignment in Hyperlocal Spatial Crowdsourcing

2018 ◽  
Vol 9 (3) ◽  
pp. 1-26 ◽  
Author(s):  
Luan Tran ◽  
Hien To ◽  
Liyue Fan ◽  
Cyrus Shahabi
Keyword(s):  
Real Time ◽  
Task Assignment ◽  
Spatial Crowdsourcing

scholarly journals An Improved SOM-Based Method for Multi-Robot Task Assignment and Cooperative Search in Unknown Dynamic Environments

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3296
Author(s):  
Hongwei Tang ◽  
Anping Lin ◽  
Wei Sun ◽  
Shuqi Shi
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Task Assignment ◽  
Dynamic Environments ◽  
Self Organizing Map ◽  
Cooperative Search ◽  
Dynamic Task ◽  
Locking Mechanism ◽  
Som Neural Network ◽  
Multi Robot

The methods of task assignment and path planning have been reported by many researchers, but they are mainly focused on environments with prior information. In unknown dynamic environments, in which the real-time acquisition of the location information of obstacles is required, an integrated multi-robot dynamic task assignment and cooperative search method is proposed by combining an improved self-organizing map (SOM) neural network and the adaptive dynamic window approach (DWA). To avoid the robot oscillation and hovering issue that occurs with the SOM-based algorithm, an SOM neural network with a locking mechanism is developed to better realize task assignment. Then, in order to solve the obstacle avoidance problem and the speed jump problem, the weights of the winner of the SOM are updated by using an adaptive DWA. In addition, the proposed method can search dynamic multi-target in unknown dynamic environment, it can reassign tasks and re-plan searching paths in real time when the location of the targets and obstacle changes. The simulation results and comparative testing demonstrate the effectiveness and efficiency of the proposed method.

scholarly journals A new load balancing strategy by task allocation in edge computing based on intermediary nodes

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Guangshun Li ◽  
Yonghui Yao ◽  
Junhua Wu ◽  
Xiaoxiao Liu ◽  
Xiaofei Sheng ◽  
...  
Keyword(s):  
Load Balancing ◽  
Real Time ◽  
Task Allocation ◽  
Normal Load ◽  
Task Assignment ◽  
Edge Computing ◽  
Heavy Load ◽  
Light Load ◽  
Assignment Model ◽  
Classification Evaluation

AbstractThe latency of cloud computing is high for the reason that it is far from terminal users. Edge computing can transfer computing from the center to the network edge. However, the problem of load balancing among different edge nodes still needs to be solved. In this paper, we propose a load balancing strategy by task allocation in edge computing based on intermediary nodes. The intermediary node is used to monitor the global information to obtain the real-time attributes of the edge nodes and complete the classification evaluation. First, edge nodes can be classified to three categories (light-load, normal-load, and heavy-load), according to their inherent attributes and real-time attributes. Then, we propose a task assignment model and allocate new tasks to the relatively lightest load node. Experiments show that our method can balance load among edge nodes and reduce the completion time of tasks.

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