Efficient Computation Offloading and Resource Allocation Scheme for Opportunistic Access Fog-Cloud Computing Networks

Fog-cloud computing is one of cores techniques in wireless networks, where fog and cloud nodes provide high-speed and large-scale computing services to mobile users through a collaborative method. For the conventional fog-cloud computing schemes, the computing abilities of nodes and the computation...

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Bibliographic Details
Published in:IEEE transactions on cognitive communications and networking 2023-04, Vol.9 (2), p.1-1
Main Authors: Sun, Wen-Bin, Xie, Jian, Yang, Xin, Wang, Ling, Meng, Wei-Xiao
Format: Article
Language:English
Subjects:
Cloud computing
Computation offloading
Computer architecture
Data transmission
Edge computing
Energy consumption
fog-cloud computing network
Iterative algorithms
Iterative methods
Mobile computing
Network latency
Nodes
opportunistic access
Optimization
Quality of service
Resource allocation
Resource management
Task analysis
Wireless networks
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Summary:Fog-cloud computing is one of cores techniques in wireless networks, where fog and cloud nodes provide high-speed and large-scale computing services to mobile users through a collaborative method. For the conventional fog-cloud computing schemes, the computing abilities of nodes and the computation task offloading methods are the main factors affecting the latency and energy consumption. However, when computing abilities of nodes reach saturation, the latency and energy consumption caused by task data transmission are approximate to those caused by computation. In order to reduce latency and energy consumption of data transmission and computation, this paper proposes an opportunistic access fog-cloud computing network (OFCN), where each mobile user selects fog node through opportunistic access method. Then, we formulate an optimization problem, considering both resource allocation and computation offloading under the constraints of users' quality of service (QoS) requirements. Due to the difficulty of solving, we divide the original problem into four suboptimal problems and develop an iterative algorithm to approach the global optimal solution. Numerical results show that the proposed OFCN can achieve lower latency and energy consumption than the conventional fog-cloud computing networks.
ISSN:2332-7731
2332-7731
DOI:10.1109/TCCN.2023.3234290