A Feedback Control-Based Crowd Dynamics Management in IoT System

Kawamoto, Yuichi; Yamada, Naoto; Nishiyama, Hiroki; Kato, Nei; Shimizu, Yoshitaka; Zheng, Yao

doi:10.1109/jiot.2017.2724642

Cited by 63 publications

(10 citation statements)

References 27 publications

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“…where ( > 0) denotes the number of cycles needed for computing each single data bit 1 . Consequently, the energy consumption of local computing at TN k is given by…”

Section: Computation Modelsmentioning

confidence: 99%

Energy-Efficient Task Offloading in Massive MIMO-Aided Multi-Pair Fog-Computing Networks

Wang

Zhou

et al. 2021

IEEE Trans. Commun.

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The energy-efficient task offloading problem of a massive multiple-input multiple-output (MIMO)-aided fog computing system is solved, where multiple task nodes offload their computational tasks to be solved via a massive MIMO-aided fog access node to multiple processing nodes in the fog for execution. By considering realistic imperfect channel state information (CSI), we formulate a joint task offloading and power allocation problem for minimizing the total energy consumption, including both computation and communication power consumptions. We solve the resultant non-convex optimization problem in two steps. First, we solve the computational task allocation and computational resource allocation for a given power allocation. Then, we conceive a sequential optimization framework for determining the specific power allocation decision that minimizes the total energy consumption of the fog access node. Given the computational tasks, the computational resources, and the power allocation, we propose an iterative algorithm for the system optimization. The simulation results show that the proposed scheme significantly reduces the total energy consumption compared to the benchmark schemes.Index Terms-Fog computing, massive MIMO, computational task offloading, energy efficiency, fog access node. I. INTRODUCTIONGiven the rapid development of the Internet of Things (IoT), more and more intelligent things and smart objects are being connected to the network [1], [2]. Meanwhile, the improved The work of K.

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“…where ( > 0) denotes the number of cycles needed for computing each single data bit 1 . Consequently, the energy consumption of local computing at TN k is given by…”

Section: Computation Modelsmentioning

confidence: 99%

Energy-Efficient Task Offloading in Massive MIMO-Aided Multi-Pair Fog-Computing Networks

Wang

Zhou

et al. 2021

IEEE Trans. Commun.

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“…With the rapid development of Internet of things (IoT) technologies, various intelligent terminals (devices) have penetrated into our daily lives and works. As is well known, the traditional cloud computing system has some inherent limitations, namely real-time control incompetence [1], heavy network traffic, cloud data privacy insecurity, and so on. Luckily for us, the edge computing paradigm can also meet the key industrial requirements (such as instant links, real-time business, low latency and jitter, data security and privacy protection, and so on) by building small edge data centers [2].…”

Section: Introductionmentioning

confidence: 99%

Clustering Based Physical-Layer Authentication in Edge Computing Systems with Asymmetric Resources

Chen

Hong

et al. 2019

Sensors

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In this paper, we propose a clustering based physical-layer authentication scheme (CPAS) to overcome the drawback of traditional cipher-based authentication schemes that suffer from heavy costs and are limited by energy-constrained intelligent devices. CPAS is a novel cross-layer secure authentication approach for edge computing system with asymmetric resources. The CPAS scheme combines clustering and lightweight symmetric cipher with physical-layer channel state information to provide two-way authentication between terminals and edge devices. By taking advantage of temporal and spatial uniqueness in physical layer channel responses, the non-cryptographic physical layer authentication techniques can achieve fast authentication. The lightweight symmetric cipher initiates user authentication at the start of a session to establish the trust connection. Based on theoretical analysis, the CPAS scheme is secure and simple, but there is no trusted party, while it can also resist small integer attacks, replay attacks, and spoofing attacks. Besides, experimental results show that the proposed scheme can boost the total success rate of access authentication and decrease the data frame loss rate, without notable increase in authentication latencies.

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“…The same goes for power systems. As we know, traditional power cloud computing system has some inherent limitations [1] that it can't satisfy the demand of real-time control. Especially, for a large number of intelligent electrical power unit (EPU), traditional digital signatures is not suitable for rapid access authentication due to the intensive computation involved in signature verification [2,3].…”

Section: Introductionmentioning

confidence: 99%

A Lightweight Mutual Authentication Scheme for Power Edge Computing System

Chen¹,

Xu²,

Chen³

et al. 2019

dteees

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Because of heavy cost, using of the traditional Public Key Infrastructure (PKI) authentication schemes is limited for the energy-constrained intelligent devices such as the power edge computing system, in which lightweight secure authentication schemes are urgent needed. In this paper, we propose a lightweight mutual authentication scheme supported by the edge computing, which is a novel cross-layer secure authentication program with asymmetric resources. The novel scheme combines lightweight symmetric cipher and physical-layer Channel State Information (CSI) to provide two-way authentication between terminals and edge devices. Experimental results show that the proposed scheme can significantly reduce the access authentication latency compared with the traditional PKI authentication scheme.

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A Feedback Control-Based Crowd Dynamics Management in IoT System

Cited by 63 publications

References 27 publications

Energy-Efficient Task Offloading in Massive MIMO-Aided Multi-Pair Fog-Computing Networks

Energy-Efficient Task Offloading in Massive MIMO-Aided Multi-Pair Fog-Computing Networks

Clustering Based Physical-Layer Authentication in Edge Computing Systems with Asymmetric Resources

A Lightweight Mutual Authentication Scheme for Power Edge Computing System

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