A DNN inference acceleration algorithm combining model partition and task allocation in heterogeneous edge computing system

2021 ◽  
Author(s):  
Lei Shi ◽  
Zhigang Xu ◽  
Yabo Sun ◽  
Yi Shi ◽  
Yuqi Fan ◽  
...  
Keyword(s):  
Task Allocation ◽  
Computing System ◽  
Edge Computing ◽  
And Task

scholarly journals Cloudlet Placement and Task Allocation in Mobile Edge Computing

2019 ◽  
Vol 6 (3) ◽  
pp. 5853-5863 ◽  
Author(s):  
Song Yang ◽  
Fan Li ◽  
Meng Shen ◽  
Xu Chen ◽  
Xiaoming Fu ◽  
...  
Keyword(s):  
Task Allocation ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
And Task

scholarly journals Server Placement and Task Allocation for Load Balancing in Edge-Computing Networks

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 138200-138208
Author(s):  
Ping-Chun Huang ◽  
Tai-Lin Chin ◽  
Tzu-Yi Chuang
Keyword(s):  
Load Balancing ◽  
Task Allocation ◽  
Edge Computing ◽  
Server Placement ◽  
And Task

Division of labor

2018 ◽  
Author(s):  
Phanish Puranam
Keyword(s):  
Division Of Labor ◽  
Task Allocation ◽  
Task Structure ◽  
Heuristic Approaches ◽  
Object Based ◽  
The Creation ◽  
Task Division ◽  
And Task

Division of labor involves task division and task allocation. An extremely important consequence of task division and allocation is the creation of interdependence between agents. In fact, division of labor can be seen as a process that converts interdependence between tasks into interdependence between agents. While there are many ways in which the task structure can be chunked and divided among agents, two important heuristic approaches involve division of labor by activity vs. object. I show that a choice between these two forms of division of labor only arises when the task structure is non-decomposable, but the product itself is decomposable. When the choice arises, a key criterion for selection between activity vs. object-based division of labor is the gain from specialization relative to the gain from customization.

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