A cooperative resource allocation model for IoT applications in mobile edge computing

2021 ◽  
Author(s):  
Xianwei Li ◽  
Liang Zhao ◽  
Keping Yu ◽  
Moayad Aloqaily ◽  
Yaser Jararweh
Keyword(s):  
Resource Allocation ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Allocation Model ◽  
Iot Applications ◽  
Resource Allocation Model ◽  
Cooperative Resource Allocation

scholarly journals Resource Allocation in Wireless-Powered Mobile Edge Computing Systems for Internet of Things Applications

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 206 ◽  
Author(s):  
Bingjie Liu ◽  
Haitao Xu ◽  
Xianwei Zhou
Keyword(s):  
Resource Allocation ◽  
Internet Of Things ◽  
Wireless Power Transfer ◽  
Edge Computing ◽  
Game Model ◽  
Mobile Edge Computing ◽  
Power Transfer ◽  
Wireless Devices ◽  
Wireless Power ◽  
Iot Applications

Wireless devices in Internet of Things (IoT) applications, such as wireless sensors and Radio Frequency Identifications (RFIDs), are faced with challenges of heavy computation tasks and limited energy, which can be solved by the importation of mobile edge computing (MEC) and wireless power transfer (WPT) techniques. As MEC can effectively enhance computation capability, and the wireless power transfer can ensure a sustainable supply of energy, it has drawn significant research interest in IoT applications. In this paper, we will study the resource allocation problem in the wireless-powered MEC system for IoT applications with one access point (AP) and many other wireless devices, and propose a Stackelberg dynamic game model to obtain the optimal allocated resource for the nodes in the IoT environment. The AP is a wireless power source that can charge wireless devices based on wireless power transfer techniques. The AP is also integrated with a MEC server that can carry out computation tasks that offload from wireless devices. The wireless devices can use the harvested energy to execute and offload computation tasks to the AP. Based on the proposed game model, the AP and wireless devices can control their optimal transmit power for energy transfer, and computation tasks offloading to the AP, respectively. The numerical simulation results show the correctness and effectiveness of the proposed model.

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