IEEE Systems Journal最新文献_第7页

An Adaptive Synchronous Lightweight AKA Protocol With Authority Management for Wireless Medical Sensor Networks 无线医疗传感器网络中具有权限管理的自适应同步轻量级AKA协议

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-12-31 DOI: 10.1109/JSYST.2024.3519516

Lei Zhang;Ting Wu;Jianwei Liu;Zhenyu Guan;Xiaodong Yin

{"title":"An Adaptive Synchronous Lightweight AKA Protocol With Authority Management for Wireless Medical Sensor Networks","authors":"Lei Zhang;Ting Wu;Jianwei Liu;Zhenyu Guan;Xiaodong Yin","doi":"10.1109/JSYST.2024.3519516","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3519516","url":null,"abstract":"The advancement of wireless network technology has propelled wireless medical sensor networks (WMSNs) to transform healthcare, offering efficient communication for enhanced quality of life. These networks employ sensitive and resource-efficient sensors to monitor and transmit patients' vital health data to medical professionals through wireless channels. However, the openness of these channels risks unauthorized access and data tampering, jeopardizing patient privacy and treatment efficacy. Ensuring the integrity and confidentiality of health data is crucial. Current authentication and key agreement (AKA) protocols have limitations, including susceptibility to sensor information disclosure and security flaws due to excessive user authority and mismatched pseudorandom identities. Given the resource constraints of WMSNs, traditional cryptographic methods are not always suitable. To overcome these challenges, a lightweight AKA protocol with self-adaptive synchronization and authority management is proposed. Formal verification through the real-or-random model, BAN logic, and ProVerif tool confirms its security and availability, while informal analysis demonstrates its robust security features. Comparative analysis with recent schemes also highlights its superiority and fitness for WMSNs.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 1","pages":"200-211"},"PeriodicalIF":4.0,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AoI-Aware Resource Allocation for Smart Multi-QoS Provisioning 基于aoi感知的多qos智能资源分配

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-12-27 DOI: 10.1109/JSYST.2024.3519536

Jingqing Wang;Wenchi Cheng;Wei Zhang

{"title":"AoI-Aware Resource Allocation for Smart Multi-QoS Provisioning","authors":"Jingqing Wang;Wenchi Cheng;Wei Zhang","doi":"10.1109/JSYST.2024.3519536","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3519536","url":null,"abstract":"The age of information (AoI) has recently gained recognition as a critical quality-of-service (QoS) metric for quantifying the freshness of status updates, playing a crucial role in supporting massive ultrareliable and low-latency communications (mURLLCs). In mURLLC scenarios, status updates generally involve the transmission through applying finite blocklength coding (FBC) to efficiently encode small update packets while meeting stringent error-rate and latency-bounded QoS constraints. However, due to inherent system dynamics and varying environmental conditions, optimizing AoI under such multi-QoS constraints often results in nonconvex and computationally intractable problems. Motivated by the demonstrated efficacy of deep reinforcement learning (DRL) in addressing large-scale networking challenges, this work aims to apply DRL techniques to derive optimal resource allocation solutions in real time. Despite its potential, the effective integration of FBC in DRL-based AoI optimization remains underexplored, especially in addressing the challenge of simultaneously upper bounding both delay and error rate. To address these challenges, we propose a DRL-based framework for AoI-aware optimal resource allocation in mURLLC-driven multi-QoS schemes, leveraging AoI as a core metric within the finite blocklength regime. First, we design a wireless communication architecture and AoI-based modeling framework that incorporates FBC. Second, we proceed by deriving upper bounded peak AoI and delay violation probabilities using stochastic network calculus. Subsequently, we formulate an optimization problem aimed at minimizing the peak AoI violation probability through FBC. Third, we develop DRL algorithms to determine optimal resource allocation policies that meet statistical delay and error-rate requirements for mURLLC. Finally, to validate the effectiveness of the developed schemes, we have executed a series of simulations.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 1","pages":"305-316"},"PeriodicalIF":4.0,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143645183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Edge Server and Service Deployment Considering Profit With Improved PSO in IoV 基于改进粒子群的车联网边缘服务器和服务部署

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-12-18 DOI: 10.1109/JSYST.2024.3512871

Junhui Zhao;Yuwen Huang;Qingmiao Zhang;Dongming Wang;Wei Xu

{"title":"Edge Server and Service Deployment Considering Profit With Improved PSO in IoV","authors":"Junhui Zhao;Yuwen Huang;Qingmiao Zhang;Dongming Wang;Wei Xu","doi":"10.1109/JSYST.2024.3512871","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3512871","url":null,"abstract":"Mobile edge computing (MEC) plays a pivotal role in the Internet of Vehicles and the Internet of Things. Edge server deployment is the initial step in establishing edge computing systems, which impact the overall system performance significantly. Besides, the performance of an edge computing system is also contingent upon the type of service deployed on servers, in the case of the same server deployment, different deployment of services will bring different profits. Most current studies concentrate solely on the former aspect, neglecting the optimization of service deployment in MEC system. In this article, we proposed a two-step method KPSOP for edge server and edge service deployment, aiming to reduce time delay, balance load, and improve the profit of MEC system, and KPSOP includes clustering algorithm and heuristic algorithm. We considered the location distribution of base stations, the task requests of vehicle users, the resource limitations of edge servers, etc. First, the edge server deployment was completed with the goal of minimizing time delay and load balancing. Second, the service deployment was completed with the goal of maximizing edge server profit. The experiments were based on real world base station information. The simulation results validate that our algorithm is more stable and converges faster. In addition, compared to other algorithms, it performs better in load balance and increasing profit.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 1","pages":"55-64"},"PeriodicalIF":4.0,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Output Feedback Tracking Consensus of Switched Stochastic Uncertain Multiagent Systems via Event-Triggered Control 基于事件触发控制的切换随机不确定多智能体系统输出反馈跟踪一致性

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-12-17 DOI: 10.1109/JSYST.2024.3511914

Jiayi Cai;Chengbo Yi;Xue Luo;Canrong Xiao

{"title":"Output Feedback Tracking Consensus of Switched Stochastic Uncertain Multiagent Systems via Event-Triggered Control","authors":"Jiayi Cai;Chengbo Yi;Xue Luo;Canrong Xiao","doi":"10.1109/JSYST.2024.3511914","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3511914","url":null,"abstract":"This article explores the adaptive event-triggered output consensus control problem for a class of switched stochastic multiagent systems (MASs) with unmeasured states and unknown nonlinearity. First, in order to overcome the limitations facing the average dwell-time method of consensus for switched MASs proposed in the existing works, the adaptive control protocol within the framework of mode-dependent average dwell time (MDADT) is introduced to expand the scope of applications. Furthermore, through a novel gain-scheduled state observer, the fuzzy logic systems are applied to approximate the unknown nonlinear functions. The dynamic surface design method is used to remove the need for derivative calculations of the constructed virtual controls, significantly the complexity of calculations. In addition, under the framework of backstepping design, the switching threshold event-triggered control strategy is developed to effectively decrease the communication load and balance the performance of MASs. The proposed control protocol ensures that all signals within the closed-loop systems are ultimately bounded under the MDADT switching property. Finally, the simulation results are obtained to validate the proposed control mechanism.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 1","pages":"130-141"},"PeriodicalIF":4.0,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distributed $mathcal {H}_{infty }$ Resilient Bipartite Control of Multiagent Systems With Semi-Markov Switching 半马尔可夫交换多智能体系统的分布式$mathcal {H}_{infty }$弹性二部控制

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-12-13 DOI: 10.1109/JSYST.2024.3506812

Lin Sun;Mingming Wang;Chong Wu;Yuan Ping;Juntong Qi

{"title":"Distributed $mathcal {H}_{infty }$ Resilient Bipartite Control of Multiagent Systems With Semi-Markov Switching","authors":"Lin Sun;Mingming Wang;Chong Wu;Yuan Ping;Juntong Qi","doi":"10.1109/JSYST.2024.3506812","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3506812","url":null,"abstract":"When information interaction occurs among agents, the communication network could be attacked or the signal interrupted, culminating in systemic instability and mission failure. Therefore, this article proposes <inline-formula><tex-math>$mathcal {H}_{infty }$</tex-math></inline-formula> resilient bipartite control method to address the security problem of network information interaction among agents within competitive and cooperative multiagent systems. When the communication networks among agents are subject to a replay attack, the system model integrating multisensor weight fusion with an unknown input leader is established first. Then, a detection fusion algorithm is proposed to simultaneously uncover attacker behavior and identify tampered sensors. Considering the intermittent or interrupted communication resulting from the time variability of topology switching among agents, the switching topology is modeled by a semi-Markov process within a signed graph having positive and negative interaction weights. Subsequently, a distributed observer is designed to estimate the unknown input leader, utilizing the semi-Markov interactions among agents and incorporating an adaptive update mechanism to eliminate the dependency on global topology information. Ulteriorly, by solving convex optimization problems, a distributed resilient bipartite controller relying on the observer state is formulated, and achieves the expected <inline-formula><tex-math>$mathcal {H}_{infty }$</tex-math></inline-formula> performance while remaining resilient against replay attacks. Finally, the superiority of the proposed method is validated through comparative examples.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 1","pages":"152-163"},"PeriodicalIF":4.0,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

2024 Index IEEE Systems Journal Vol. 18 2024索引IEEE系统学报第18卷

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-12-12 DOI: 10.1109/JSYST.2024.3514272

引用次数: 0

AP Working Mode Selection and Blocklength Optimization for Industrial URLLC in Network-Assisted Full-Duplex Cell-Free Massive MIMO Systems 网络辅助全双工无小区大规模MIMO系统中工业URLLC的AP工作模式选择和块长度优化

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-12-11 DOI: 10.1109/JSYST.2024.3507049

Zheng Sheng;Pengcheng Zhu;Peng Hao;Feng Shu;Fu-Chun Zheng

{"title":"AP Working Mode Selection and Blocklength Optimization for Industrial URLLC in Network-Assisted Full-Duplex Cell-Free Massive MIMO Systems","authors":"Zheng Sheng;Pengcheng Zhu;Peng Hao;Feng Shu;Fu-Chun Zheng","doi":"10.1109/JSYST.2024.3507049","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3507049","url":null,"abstract":"Network-assisted full-duplex (NAFD) cell-free massive multiple-input–multiple-output (MIMO) systems, which virtually achieve FD transmission by employing half-duplex access points (APs) to simultaneously serve uplink (UL) and downlink (DL) users on the same frequency bands, can decrease latency and enhance reliability since self-interference cancellation is unnecessary and macrodiversity is provided, thus helping industrial ultrareliable low-latency communication applications. In this article, we consider a monitoring scenario of industrial automation in NAFD cell-free systems using finite blocklength codewords and analyze UL and DL signals, end-to-end (E2E) delay, and E2E decoding error probability (DEP). Then, an optimization problem is formulated to minimize the maximum E2E DEP among all actuators by jointly designing AP working mode, UL and DL blocklengths under the E2E delay constraint. We propose the estimation of distribution algorithm-differential evolution (EDA-DE) method with low complexity to obtain a near-optimal solution, where the block coordinate descent is used to divide this problem into two parts. The first AP working mode selection is solved by EDA, and the second UL and DL blocklengths are designed by DE. Simulation results indicate that the performance of our proposed EDA-DE method is close to that of exhaustive search with lower computational complexity.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 1","pages":"188-199"},"PeriodicalIF":4.0,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prescribed-Time Target Enclosing and Tracking With Motion and Visibility Constraints 带有运动和可见性约束的规定时间目标封闭和跟踪

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-12-09 DOI: 10.1109/JSYST.2024.3506560

Jiayi Zheng;Shulong Zhao;Xiangke Wang

引用次数: 0

IEEE Systems Council Information IEEE系统委员会信息

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-12-04 DOI: 10.1109/JSYST.2024.3486435

引用次数: 0

IEEE Systems Journal Publication Information IEEE系统期刊出版信息

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-12-04 DOI: 10.1109/JSYST.2024.3486431

引用次数: 0