Title
Optimizing Resources Allocation for Fog Computing-Based Internet of Things Networks.
Abstract
In the wireless Internet of Things (IoT) networks with resource-constrained devices, fog computing has been introduced to deal with the computation-intensive applications at the edges of the networks. While fog computing decreases the computation delay and fronthaul traffic data, it also brings the severe challenge on complex resource allocation of the available computation and communication resources under the stringent quality of service (QoS) requirements. In this paper, we investigate the problem of tasks scheduling and heterogeneous resource allocation for multiple devices in the wireless IoT networks. The IoT devices that collect a massive amount of data need to make proper offoading decision to transfer the data to the fog computing nodes (FNs). Moreover, to support a massive number of device connections and transfer a huge amount of data with low latency and limited resource, we consider the deployment of non-orthogonal multiple access (NOMA) in IoT networks, which enables multiple IoT devices to simultaneously transmit data to the same FN at the same time, frequency, and code domain. We jointly optimize the allocation of resource blocks and transmit power of multiple IoT devices, subject to the respective QoS requirements. Furthermore, the optimization problem is formulated as a mixed-integer nonlinear programming problem to minimize the system energy consumption. Since it is an NP-hard problem, we introduce an improved genetic algorithm (IGA) to solve it. The simulation results show that the proposed scheme achieves good performance in throughput, delay, outage probability, and energy consumption.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2917557
IEEE ACCESS
Keywords
Field
DocType
Fog computing,Internet of things,non-orthogonal multiple access,resource allocation,energy consumption
Computer science,Internet of Things,Computer network,Fog computing
Journal
Volume
ISSN
Citations 
7
2169-3536
1
PageRank 
References 
Authors
0.35
0
5
Name
Order
Citations
PageRank
Xi Li115419.69
Liu Yiming27316.37
Hong Ji381578.32
Heli Zhang48319.75
Victor C. M. Leung59717759.02