Computer Communications最新文献

Efficient paths determining strategies in Mobile Crowd-sensing Networks with AI-based sensors forwarding data 基于人工智能传感器转发数据的移动群感网络中的高效路径确定策略

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-03-13 DOI: 10.1016/j.comcom.2025.108138

Jiaoyan Chen , Jin Liu , Zhehao Cheng , Laurence Tianruo Yang , Xianjun Deng , Yihong Chen

{"title":"Efficient paths determining strategies in Mobile Crowd-sensing Networks with AI-based sensors forwarding data","authors":"Jiaoyan Chen , Jin Liu , Zhehao Cheng , Laurence Tianruo Yang , Xianjun Deng , Yihong Chen","doi":"10.1016/j.comcom.2025.108138","DOIUrl":"10.1016/j.comcom.2025.108138","url":null,"abstract":"<div><div>Selecting a sufficient number of mobile users to collect and upload collected data to the server is a critical issue in the Mobile Crowd-sensing Networks (MCN). Previous studies have assumed that mobile users upload collected data over cellular networks, which could cause heavily burden to users. This work focus on how to forward collected data by pre-deployed wireless sensors which can fuse collected data and operate as edge nodes. Specifically, given the reward paid to each mobile user depends on the time he spends on data collection and uploading, this work investigates the problem how to select Points of Interest (PoIs) and edge nodes for participants who already have schedules with the objective of minimizing the total reward paid to all participants. We boil down this problem to the problem of determining path for each participant which connects participant’s initial location to PoI, then to an edge node and finally to participant’s destination. We formulate it as <em>Paths determination with Cost Minimization</em> problem. We can prove that this problem is an NP-Complete problem. Considering that the sensors acted as edge nodes which may be rechargeable or have limited energy, we design three heuristic algorithms: Minimum Cost Algorithm (MCA), Minimum Cost with Energy Consideration Algorithm (MCECA), and Energy Balance Algorithm (EBA) to address this problem. Finally, we conduct extensive simulations to validate the efficiency of the proposed algorithms. The results demonstrate that MCA finds paths for users with lower cost, while EBA effectively balances the energy consumption of edge nodes.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"236 ","pages":"Article 108138"},"PeriodicalIF":4.5,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143628924","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

Target Wake Time in IEEE 802.11 WLANs: Survey, Challenges, and Opportunities

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-03-13 DOI: 10.1016/j.comcom.2025.108127

Shyam Krishnan Venkateswaran, Ching-Lun Tai, Atif Ahmed, Raghupathy Sivakumar

{"title":"Target Wake Time in IEEE 802.11 WLANs: Survey, Challenges, and Opportunities","authors":"Shyam Krishnan Venkateswaran, Ching-Lun Tai, Atif Ahmed, Raghupathy Sivakumar","doi":"10.1016/j.comcom.2025.108127","DOIUrl":"10.1016/j.comcom.2025.108127","url":null,"abstract":"<div><div>Wi-Fi has become the most widely used Wireless Local Area Network (WLAN) technology, but as the density of WLAN deployments and the number of devices per network increase, congestion has become a significant issue. Scheduling features in Wi-Fi have the potential to alleviate these issues by managing medium access more efficiently. While there have been other scheduling features in Wi-Fi in the past, none were widely adopted and were limited in functionality. Target Wake Time (TWT) introduces powerful scheduling capabilities to Wi-Fi as part of Wi-Fi 6, representing a fundamental shift in how Wi-Fi Access Points (APs) manage channel access for Stations (STAs) while improving energy efficiency. TWT is extremely versatile and is poised to play a crucial role in reducing contention and enhancing performance, especially in dense network environments. The potential benefits are particularly valuable for Internet of Things (IoT) scenarios, where low power consumption and efficient medium access are essential due to the large number of connected devices. This paper presents an in-depth survey of the research on TWT, categorizing and analyzing existing literature while identifying practical challenges often overlooked due to idealized assumptions. We introduce comprehensive models of infrastructure-mode APs and STAs to facilitate discussions of current and future work. We provide a detailed analysis of the challenges and issues that must be addressed to fully realize the performance gains promised by TWT. Furthermore, we explore the potential future applications of TWT, particularly in conjunction with upcoming features in IEEE 802.11 such as multi-link operation (MLO) and multi-AP coordination, offering insights into novel uses of TWT for enhancing Wi-Fi performance.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"236 ","pages":"Article 108127"},"PeriodicalIF":4.5,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644297","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

Energy efficient LEO satellite communications: Traffic-aware payload switch-off techniques 高能效低地轨道卫星通信：流量感知有效载荷开关技术

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-03-12 DOI: 10.1016/j.comcom.2025.108122

Vaibhav Kumar Gupta , Hayder Al-Hraishawi , Eva Lagunas , Symeon Chatzinotas

{"title":"Energy efficient LEO satellite communications: Traffic-aware payload switch-off techniques","authors":"Vaibhav Kumar Gupta , Hayder Al-Hraishawi , Eva Lagunas , Symeon Chatzinotas","doi":"10.1016/j.comcom.2025.108122","DOIUrl":"10.1016/j.comcom.2025.108122","url":null,"abstract":"<div><div>Low Earth orbit (LEO) satellite constellations have a pivotal role in shaping the future of communication networks by providing extensive global coverage. However, ensuring the long-term viability of LEO constellations relies on addressing significant challenges, particularly in the domains of energy efficiency and maximizing the lifespan of satellites. This paper introduces a novel approach that considers user traffic demands to optimize power consumption. By implementing a traffic-aware strategy, redundant satellites can be intelligently switched-off, resulting in significant power savings within the LEO constellation. To accomplish this objective, we formulate the problem of joint satellite beam assignment and beam power allocation as a mixed binary integer optimization problem while carefully considering the constraints imposed by satellite-user visibility and the need to fulfill the data traffic requirements of all ground users. To tackle the formulated problem, we employ a framework called the Difference of Convex Programming and Multiplier Penalty (DCMP) based convexification approach, which ensures convergence to a local optimum. The reformulated convex problem is solved using the low-complexity iterative algorithm, Successive Convex Approximation (SCA). Additionally, we propose a heuristic algorithm based on slant distance, which offers a simplified and efficient solution to the joint problem. To corroborate the effectiveness and validity of the proposed techniques, we assess and compare their performance via simulations, considering practical constellation patterns and realistic user traffic distribution. It has been shown that approximately 43% of the satellite nodes can be switched-off for energy saving, and thus, extending the constellation lifetime and reducing the aggregated interference from multi-beam satellites.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"236 ","pages":"Article 108122"},"PeriodicalIF":4.5,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620518","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

AI-Powered Resilience: A Dual-Approach for Outage Management in Dense Cellular Networks

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-03-12 DOI: 10.1016/j.comcom.2025.108129

Waseem Raza , Muhammad Umar Bin Farooq , Aneeqa Ijaz , Marvin Manalastas , Ali Imran

{"title":"AI-Powered Resilience: A Dual-Approach for Outage Management in Dense Cellular Networks","authors":"Waseem Raza , Muhammad Umar Bin Farooq , Aneeqa Ijaz , Marvin Manalastas , Ali Imran","doi":"10.1016/j.comcom.2025.108129","DOIUrl":"10.1016/j.comcom.2025.108129","url":null,"abstract":"<div><div>As 5G evolves to 6G, network management faces growing challenges with increasing base station density, leading to more frequent outages. To address this, we introduce a robust, automated two-tier framework for outage management. The first tier involves an artificial intelligence-based outage detection scheme using an enhanced XGBoost model (Impv-XGBoost), which incorporates autoencoder outputs for hyperparameter tuning. The analysis shows Impv-XGBoost’s superior performance in high shadowing conditions and with sparse data, outperforming existing methods. The second tier adopts an actor–critic reinforcement learning strategy for outage compensation by adjusting the tilt of the neighboring base station and power. To prevent service declines to connected user equipment, our compensation scheme accounts for both outage-affected users and those connected to compensating base stations. We design a reward scheme that combines Jain’s fairness index and the geometric mean of the reference signal received power to ensure fairness and enhance convergence. Performance evaluations for single and multiple base station failures show coverage improvements for outage-affected users without compromising the coverage of the users in compensating base stations.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"236 ","pages":"Article 108129"},"PeriodicalIF":4.5,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642705","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

IoT edge network interoperability

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-03-11 DOI: 10.1016/j.comcom.2025.108125

Tanzima Azad , M.A. Hakim Newton , Jarrod Trevathan , Abdul Sattar

{"title":"IoT edge network interoperability","authors":"Tanzima Azad , M.A. Hakim Newton , Jarrod Trevathan , Abdul Sattar","doi":"10.1016/j.comcom.2025.108125","DOIUrl":"10.1016/j.comcom.2025.108125","url":null,"abstract":"<div><div>Network interoperability is crucial for achieving seamless communication across Internet of Things (IoT) environments. IoT comprises heterogeneous devices and systems supporting diverse technologies, protocols, and manufacturers. Enabling devices to communicate and exchange data effectively, regardless of underlying protocols, is key to building cohesive and integrated IoT networks. IoT has transformed multiple sectors ranging from home automation to healthcare—by harnessing a vast array of sensors and actuators that communicate through cloud, fog, and edge layers. However, the variety in device manufacturing and communication standards demands interoperable interfaces, and most current solutions depend on cloud-based centralised architectures. These architectures introduce latency and scalability challenges, particularly for resource-constrained IoT devices that often struggle to communicate with the cloud due to limited resources. This paper addresses network interoperability at the IoT edge level, focusing on resource-efficient communication by integrating Wi-Fi and Bluetooth, two commonly used protocols in IoT ecosystems. We have implemented a network edge interoperability solution that supports effective data exchange between devices operating on these distinct protocols, enhancing the overall efficiency, flexibility, and scalability of IoT systems. Our approach allows devices interoperate by addressing network latency and bandwidth limitations, incorporating an integrated controller to facilitate broader applications and enhance performance across IoT networks. Our findings illustrate how bridging protocol differences can foster more resilient and adaptable IoT solutions, advancing the deployment of IoT applications across various domains and use cases.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"236 ","pages":"Article 108125"},"PeriodicalIF":4.5,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Resiliency focused proactive lifecycle management for stateful microservices in multi-cluster containerized environments

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-03-08 DOI: 10.1016/j.comcom.2025.108111

Abd Elghani Meliani, Mohamed Mekki, Adlen Ksentini

引用次数: 0

A defense mechanism for federated learning in AIoT through critical gradient dimension extraction

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-03-05 DOI: 10.1016/j.comcom.2025.108114

Jian Xu , Bing Guo , Fei Chen , Yan Shen , Shengxin Dai , Cheng Dai , Yuchuan Hu

{"title":"A defense mechanism for federated learning in AIoT through critical gradient dimension extraction","authors":"Jian Xu , Bing Guo , Fei Chen , Yan Shen , Shengxin Dai , Cheng Dai , Yuchuan Hu","doi":"10.1016/j.comcom.2025.108114","DOIUrl":"10.1016/j.comcom.2025.108114","url":null,"abstract":"<div><div>Leveraging the distributed nature of the Internet of Things (IoT), Federated Learning (FL) facilitates knowledge transfer among heterogeneous IoT devices, enhancing the capabilities of Artificial Intelligence of Things (AIoT) while preserving data privacy. However, FL is susceptible to poisoning attacks such as label flipping, Gaussian, and backdoor attacks. Most existing defense strategies rely on robust aggregation algorithms that use the statistical properties of gradient vectors to counteract poisoning attacks, however, they often overlook the non-independent and identically distributed (non-iid) nature of client data, limiting their effectiveness in the IoT. We propose a method that combines cross-node Top-k gradient vector compression and Principal Component Analysis (PCA) dimensionality reduction to extract critical gradient dimensions. By clustering these essential dimensions and performing filtering, our approach effectively distinguishes malicious from benign clients in non-iid data scenarios. Additionally, we introduce a client trust-score assessment mechanism that continuously monitors client behavior and applies secondary filtering, further improving the identification of malicious clients. Experimental results on the CIFAR-10, MNIST, DomainNet, and Flowers102 datasets demonstrate that our method achieves higher model accuracy and robustness in non-iid data settings compared to existing defense strategies.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"236 ","pages":"Article 108114"},"PeriodicalIF":4.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611555","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

SQID: A deep learning and network design synergy for next-generation IoT resource allocation management

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-03-05 DOI: 10.1016/j.comcom.2025.108128

Ali. M.A. Ibrahim , Zhigang Chen , Yijie Wang , Hala A. Eljailany

{"title":"SQID: A deep learning and network design synergy for next-generation IoT resource allocation management","authors":"Ali. M.A. Ibrahim , Zhigang Chen , Yijie Wang , Hala A. Eljailany","doi":"10.1016/j.comcom.2025.108128","DOIUrl":"10.1016/j.comcom.2025.108128","url":null,"abstract":"<div><div>The exponential growth of mobile broadband and Internet of Things (IoT) devices has pushed traditional IoT models to their operational limits, necessitating more efficient data management strategies. This research introduces the SQID framework, a solution that integrates advanced techniques, including Sierpinski triangle design (STD) for network optimization, quantum density peak clustering (QDPC) for intelligent device clustering, and improved deep deterministic policy gradient (IDDPG) for deep learning-driven traffic prediction. By utilizing STD to optimize device communication, the framework applies the QDPC algorithm to efficiently cluster devices, ensuring balanced packet distribution and minimizing latency. Additionally, IDDPG enhances network performance by enabling accurate traffic prediction and resource allocation, optimizing data transmission. Extensive simulations reveal that SQID outperforms existing methods in critical metrics such as time efficiency, latency reduction, throughput maximization, and packet loss. These results indicate that SQID has the potential to significantly improve data management in IoT networks, paving the way for next-generation IoT advancements.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"236 ","pages":"Article 108128"},"PeriodicalIF":4.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611556","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

Optimizing UAV delivery for pervasive systems through blockchain integration and adversarial machine learning

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-03-03 DOI: 10.1016/j.comcom.2025.108113

Chengzu Dong , Shantanu Pal , Aiting Yao , Frank Jiang , Shiping Chen , Xiao Liu

{"title":"Optimizing UAV delivery for pervasive systems through blockchain integration and adversarial machine learning","authors":"Chengzu Dong , Shantanu Pal , Aiting Yao , Frank Jiang , Shiping Chen , Xiao Liu","doi":"10.1016/j.comcom.2025.108113","DOIUrl":"10.1016/j.comcom.2025.108113","url":null,"abstract":"<div><div>Unmanned Aerial Vehicles (UAVs), play a significant role in the advancement of pervasive systems by providing efficient, scalable, and innovative solutions in various sectors, such as smart cities or location-based services. However, the current UAV delivery scenario presents various challenges for recipients, including lengthy identity verification processes, privacy concerns, and risks of fraud and theft. In response to these issues, this paper proposes an innovative system that leverages Blockchain technology and Adversarial Machine Learning (AML) to tackle these problems effectively. The proposed system streamlines the verification process, enhances privacy safeguards, and reduces fraud risks. The integration of AML is crucial as it enables users to have greater control over their personal data, boosting privacy and security. AML also plays a critical role in this system by creating test scenarios that reinforce the machine learning model against adversarial threats, ensuring its precision and dependability in the face of malicious manipulations. The paper also provides details on the practical implementation and evaluation of this system in real-life adversarial situations. The evaluation results demonstrate superior performance on selected metrics, highlighting the potential of this system as an effective solution for verifying recipients in UAV delivery.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"236 ","pages":"Article 108113"},"PeriodicalIF":4.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards green networking: Efficient dynamic radio resource management in Open-RAN slicing using deep reinforcement learning and transfer learning

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-03-01 DOI: 10.1016/j.comcom.2025.108126

Heba Sherif, Eman Ahmed, Amira M. Kotb

{"title":"Towards green networking: Efficient dynamic radio resource management in Open-RAN slicing using deep reinforcement learning and transfer learning","authors":"Heba Sherif, Eman Ahmed, Amira M. Kotb","doi":"10.1016/j.comcom.2025.108126","DOIUrl":"10.1016/j.comcom.2025.108126","url":null,"abstract":"<div><div>Next Generation Wireless Networks (NGWNs) are characterized by agility and flexibility. It introduces new technologies such as network slicing (NS) and Open Radio Access Network (O-RAN). NS supports multiple services with different requirements whereas O-RAN supports different network suppliers and provides Mobile Network Operators (MNOs) more intelligent control. Deep Reinforcement Learning (DRL) techniques have been presented to address resource management and other problems in NGWNs in recent years. However, instability and lateness in convergence are the main obstacles against their adoption in live networks. Moreover, deep learning models consume lots of energy and emit significant amounts of carbon dioxide which badly impacts climate. This paper addresses solving the dynamic radio resource management (RRM) problem in O-RAN slicing with DRL and Transfer Learning (TL), focusing on proposing a green model that minimizes power and energy consumption, decreasing the carbon footprint. A new latency-and-reliability-based reward function is designed. Then, a variable threshold action filtration mechanism is proposed, and a policy TL approach is proposed to accelerate the performance in commercial networks. Compared with the state-of-the-art, this work significantly improved exploration stability, convergence speed, Quality of Service (QoS) satisfaction, power and energy consumption, and emitted carbon footprint.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"236 ","pages":"Article 108126"},"PeriodicalIF":4.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143628923","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