Task Allocation Mechanism for Cable Real-Time Online Monitoring Business Based on Edge Computing

Shao, Sujie; Zhang, Qinghang; Guo, Shaoyong; Qi, Feng

doi:10.1109/jsyst.2020.2988266

Cited by 12 publications

(1 citation statement)

References 35 publications

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“…The particularity of this work is that the energy consumed by the fronthaul links (between users and relays) and the backhaul links (between relays and edge servers) is considered in the design of fitness function. Recently, different PSO variants are proposed in the literature for task allocation, e.g., improved discrete PSO algorithms in [128], [129], a hybrid scheme based on PSO and cat swarm optimization in [130], and two slow-movement PSO schemes in [131].…”

Section: B Computation Offloadingmentioning

confidence: 99%

Swarm Intelligence for Next-Generation Wireless Networks: Recent Advances and Applications

Pham¹,

Nguyen²,

Mirjalili³

et al. 2020

Preprint

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Due to the proliferation of smart devices and emerging applications, many next-generation technologies have been paid for the development of wireless networks. Even though commercial 5G has just been widely deployed in some countries, there have been initial efforts from academia and industrial communities for 6G systems. In such a network, a very large number of devices and applications are emerged, along with heterogeneity of technologies, architectures, mobile data, etc., and optimizing such a network is of utmost importance. Besides convex optimization and game theory, swarm intelligence (SI) has recently appeared as a promising optimization tool for wireless networks. As a new subdivision of artificial intelligence, SI is inspired by the collective behaviors of societies of biological species. In SI, simple agents with limited capabilities would achieve intelligent strategies for high-dimensional and challenging problems, so it has recently found many applications in nextgeneration wireless networks (NGN). However, researchers may not be completely aware of the full potential of SI techniques. In this work, our primary focus will be the integration of these two domains: NGN and SI. Firstly, we provide an overview of SI techniques from fundamental concepts to well-known optimizers. Secondly, we review the applications of SI to settle emerging issues in NGN, including spectrum management and resource allocation, wireless caching and edge computing, network security, and several other miscellaneous issues. Finally, we highlight open challenges and issues in the literature, and introduce some interesting directions for future research.

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