Energy-Efficient Context-Aware Resource Allocation for Edge-Computing-Empowered Industrial IoT

2020 ◽  
pp. 69-88
Author(s):  
Zhenyu Zhou ◽  
Zheng Chang ◽  
Haijun Liao
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Edge Computing ◽  
Context Aware ◽  
Industrial Iot

scholarly journals Learning-Based Context-Aware Resource Allocation for Edge-Computing-Empowered Industrial IoT

2020 ◽  
Vol 7 (5) ◽  
pp. 4260-4277 ◽  
Author(s):  
Haijun Liao ◽  
Zhenyu Zhou ◽  
Xiongwen Zhao ◽  
Lei Zhang ◽  
Shahid Mumtaz ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Edge Computing ◽  
Context Aware ◽  
Industrial Iot

Energy-Efficient Joint Task Offloading and Resource Allocation in OFDMA-based Collaborative Edge Computing

2021 ◽  
pp. 1-1
Author(s):  
Lin Tan ◽  
Zhufang Kuang ◽  
Lian Zhao ◽  
Anfeng Liu
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Edge Computing ◽  
Joint Task ◽  
Task Offloading

Stable-Matching-Based Energy-Efficient Context-Aware Resource Allocation for Ultra-Dense Small Cells

2017 ◽  
pp. 29-57
Author(s):  
Zhenyu Zhou ◽  
Zheng Chang ◽  
Chen Xu ◽  
Tapani Ristaniemi
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Small Cells ◽  
Context Aware ◽  
Delay Sensitive ◽  
Optimum Energy ◽  
Significant Performance ◽  
Promising Solution ◽  
Nonlinear Fractional Programming ◽  
Efficient Matching

Implementing caching to ultra-densely deployed small cells provides a promising solution for satisfying the stringent quality of service (QoS) requirements of delay-sensitive applications with limited backhaul capacity. With the rapidly increasing energy consumption, in this chapter, the authors investigate the NP-hard energy-efficient context-aware resource allocation problem and formulate it as a one-to-one matching problem. The preference lists in the matching are modeled based on the optimum energy efficiency (EE) under specified matching, which can be obtained by using an iterative power allocation algorithm based on nonlinear fractional programming and Lagrange dual decomposition. Next, on account of the Gale-Shapley algorithm, an energy-efficient matching algorithm is proposed. Some properties of the proposed algorithm are discussed and analyzed in detail. Moreover, the authors extend the algorithm to the matching with indifferent and incomplete preference lists. Finally, the significant performance gain of the proposed algorithm is demonstrated through simulation results.

scholarly journals Energy-Efficient Resource Allocation for Secure NOMA-Enabled Mobile Edge Computing Networks

2020 ◽  
Vol 68 (1) ◽  
pp. 493-505 ◽  
Author(s):  
Wei Wu ◽  
Fuhui Zhou ◽  
Rose Qingyang Hu ◽  
Baoyun Wang
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Efficient Resource ◽  
Energy Efficient Resource Allocation

Energy-Efficient Offloading and Resource Allocation for Multi-Access Edge Computing

2019 ◽  
Author(s):  
Zhiqian Xu ◽  
Yao Zhang ◽  
Xu Qiao ◽  
Haotong Cao ◽  
Longxiang Yang
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Edge Computing ◽  
Multi Access

scholarly journals Energy Efficient Resource Allocation in UAV-Enabled Mobile Edge Computing Networks

2019 ◽  
Vol 18 (9) ◽  
pp. 4576-4589 ◽  
Author(s):  
Zhaohui Yang ◽  
Cunhua Pan ◽  
Kezhi Wang ◽  
Mohammad Shikh-Bahaei
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Efficient Resource ◽  
Energy Efficient Resource Allocation

scholarly journals Energy-Efficient Resource Allocation for Latency-Sensitive Mobile Edge Computing

2020 ◽  
Vol 69 (2) ◽  
pp. 2246-2262 ◽  
Author(s):  
Xihan Chen ◽  
Yunlong Cai ◽  
Liyan Li ◽  
Minjian Zhao ◽  
Benoit Champagne ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Efficient Resource ◽  
Energy Efficient Resource Allocation
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