Computer Communications最新文献_第9页

Energy consumption optimization in UAV-assisted multi-layer mobile edge computing with active transmissive RIS 基于主动传输RIS的无人机辅助多层移动边缘计算能耗优化

IF 4.3 3区计算机科学

Computer Communications Pub Date : 2025-11-01 Epub Date: 2025-09-19 DOI: 10.1016/j.comcom.2025.108320

Kexin Yang, Yaxi Liu, Boxin He, Jiahao Huo, Wei Huangfu

{"title":"Energy consumption optimization in UAV-assisted multi-layer mobile edge computing with active transmissive RIS","authors":"Kexin Yang, Yaxi Liu, Boxin He, Jiahao Huo, Wei Huangfu","doi":"10.1016/j.comcom.2025.108320","DOIUrl":"10.1016/j.comcom.2025.108320","url":null,"abstract":"<div><div>Unmanned Aerial Vehicle (UAV)-assisted edge computing provides low-latency and low-energy consumption computing capabilities for sparsely distributed Internet of Things (IoT) networks. In addition, the assisted UAVs provide line-of-sight links to further improve communication quality. However, the existing offloading strategies have low efficiency and high costs. Motivated by this, we propose a novel UAV-assisted multi-layer mobile edge computing network with active transmissive reconfigurable intelligent surface (RIS). The introduced an active transmissive RIS not only receives data from UAVs but also performs computing functionality. We establish an optimization to minimize the total system energy consumption under delay constraints by jointly planning UAV positions and allocating computing bits, sub-carriers, time slots, transmission power, and RIS transmission coefficient. To tackle this problem, we first use the block coordinate descent (BCD) algorithm to decouple it into four sub-problems. Then, we solve them by adopting successive convex approximation (SCA), difference-convex (DC) programming, and introducing slack variables. Experimental results demonstrate that the proposed network is superior to the other five baselines concerning energy consumption reduction. Also, the influences of system parameters are verified, including the number of IoT devices, the number of RIS elements, and the delay threshold.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"243 ","pages":"Article 108320"},"PeriodicalIF":4.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145120973","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

Channel-hopping sequence generation for blind rendezvous in cognitive radio-enabled internet of vehicles: A multi-agent twin delayed deep deterministic policy gradient-based method 基于认知无线电的车联网盲交会跳信道序列生成：基于多智能体双延迟深度确定性策略梯度的方法

IF 4.3 3区计算机科学

Computer Communications Pub Date : 2025-11-01 Epub Date: 2025-09-19 DOI: 10.1016/j.comcom.2025.108318

Mehri Asadi Vasfi, Behrouz Shahgholi Ghahfarokhi

{"title":"Channel-hopping sequence generation for blind rendezvous in cognitive radio-enabled internet of vehicles: A multi-agent twin delayed deep deterministic policy gradient-based method","authors":"Mehri Asadi Vasfi, Behrouz Shahgholi Ghahfarokhi","doi":"10.1016/j.comcom.2025.108318","DOIUrl":"10.1016/j.comcom.2025.108318","url":null,"abstract":"<div><div>Efficient spectrum utilization is a major challenge in highly dynamic vehicular environments due to the scarcity of spectrum resources. Cognitive Radio (CR) has emerged as a solution to improve spectrum utilization by enabling opportunistic access in IoV. In this context, channel-hopping based blind rendezvous offers a practical approach for decentralized spectrum access in CR-enabled IoV (CR-IoV). This paper presents a novel Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3PG)-based strategy for generating channel sequences in channel-hopping-based blind rendezvous. Unlike existing methods that overlook the quality of licensed spectrum, our approach ensures spectrum efficiency and QoS awareness in dynamic channel sequence generation. We formulate the channel sequence selection problem as a multi-objective optimization, aiming to maximize spectrum efficiency and minimize Time-To-Rendezvous (TTR) while meeting stringent latency and reliability requirements for vehicular communications. Each vehicle independently generates a channel-hopping sequence using a learning agent, which considers key channel quality metrics such as availability, reliability, and capacity. The generated sequences are employed in an asynchronous and asymmetric blind rendezvous process, enhancing adaptability to dynamic network conditions. Simulation results demonstrate that the proposed method significantly outperforms existing approaches, including Enhanced Jump-Stay (EJS), Single-radio Sunflower Set (SSS), Zero-type, One-type, and S-type (ZOS), Multi-Agent Q-Learning based Rendezvous (MAQLR), Exponential-weight algorithm for Exploration and Exploitation (Exp3), and Reinforcement Learning-based Channel-Hopping Rendezvous (RLCH) in terms of Expected TTR (ETTR), Maximum TTR (MTTR), delay, capacity, and reliability.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"243 ","pages":"Article 108318"},"PeriodicalIF":4.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160256","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

Beyond performance comparing the costs of applying Deep and Shallow Learning 除了性能比较应用深度学习和浅学习的成本

IF 4.3 3区计算机科学

Computer Communications Pub Date : 2025-11-01 Epub Date: 2025-09-22 DOI: 10.1016/j.comcom.2025.108312

Rafael Teixeira, Leonardo Almeida, Pedro Rodrigues, Mário Antunes, Diogo Gomes, Rui L. Aguiar

{"title":"Beyond performance comparing the costs of applying Deep and Shallow Learning","authors":"Rafael Teixeira, Leonardo Almeida, Pedro Rodrigues, Mário Antunes, Diogo Gomes, Rui L. Aguiar","doi":"10.1016/j.comcom.2025.108312","DOIUrl":"10.1016/j.comcom.2025.108312","url":null,"abstract":"<div><div>The rapid growth of mobile network traffic and the emergence of complex applications, such as self-driving cars and augmented reality, demand ultra-low latency, high throughput, and massive device connectivity, which traditional network design approaches struggle to meet. These issues were initially addressed in Fifth-Generation (5G) and Beyond-5G (B5G) networks, where Artificial Intelligence (AI), particularly Deep Learning (DL), is proposed to optimize the network and to meet these demanding requirements. However, the resource constraints and time limitations inherent in telecommunication networks raise questions about the practicality of deploying large Deep Neural Networks (DNNs) in these contexts. This paper analyzes the costs of implementing DNNs by comparing them with shallow ML models across multiple datasets and evaluating factors such as execution time and model interpretability. Our findings demonstrate that shallow ML models offer comparable performance to DNNs, with significantly reduced training and inference times, achieving up to 90% acceleration. Moreover, shallow models are more interpretable, as explainability metrics struggle to agree on feature importance values even for high-performing DNNs.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"243 ","pages":"Article 108312"},"PeriodicalIF":4.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160257","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

A preemptive task unloading scheme based on second optional unloading in cloud-fog collaborative networks 云雾协同网络中一种基于二次可选卸载的抢占式任务卸载方案

IF 4.3 3区计算机科学

Computer Communications Pub Date : 2025-11-01 Epub Date: 2025-09-16 DOI: 10.1016/j.comcom.2025.108315

Yuan Zhao , Hongmin Gao , Shuaihua Liu

{"title":"A preemptive task unloading scheme based on second optional unloading in cloud-fog collaborative networks","authors":"Yuan Zhao , Hongmin Gao , Shuaihua Liu","doi":"10.1016/j.comcom.2025.108315","DOIUrl":"10.1016/j.comcom.2025.108315","url":null,"abstract":"<div><div>Long-distance data transmission between Internet of Things (IoT) devices and remote cloud center often leads to unacceptable latency for certain tasks. Fog computing has emerged as a promising solution for low-latency tasks. Consequently, the concept of cloud-fog collaborative networks has garnered significant attention. However, existing research primarily focuses on heterogeneous tasks, overlooking the crucial aspect of considering both task priority and second unloading. To address this gap, this paper proposes a novel task unloading scheme that concurrently takes preemptive priority and second optional unloading into account. In this scheme, delay-sensitive tasks (DSTs) are given preemptive priority over delay-tolerant tasks (DTTs). Furthermore, some DTTs may undergo preprocessing in the fog layer to optimize resource utilization. Moreover, tasks encountering blocking or preemption in the fog layer can also be secondarily unloaded to the cloud layer. In this framework, we devise a four-dimensional Markov chain (4DMC) to model and analyze this process. Through numerical experiments, we assess performance indicators under various parameters. Ultimately, our proposed strategy is compared with the unloading scheme that does not incorporate second unloading through both numerical analysis and simulation validation. The results indicate that our scheme notably enhances the throughput of DTTs, albeit at a marginal performance trade-off.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"243 ","pages":"Article 108315"},"PeriodicalIF":4.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109055","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

ScaleIP: A hybrid autoscaling of VoIP services based on deep reinforcement learning ScaleIP：基于深度强化学习的VoIP服务混合自动扩展

IF 4.3 3区计算机科学

Computer Communications Pub Date : 2025-11-01 Epub Date: 2025-09-19 DOI: 10.1016/j.comcom.2025.108314

Zahra Najafabadi Samani , Juan Aznar Poveda , Dominik Gratz , Rene Hueber , Philipp Kalb , Thomas Fahringer

{"title":"ScaleIP: A hybrid autoscaling of VoIP services based on deep reinforcement learning","authors":"Zahra Najafabadi Samani , Juan Aznar Poveda , Dominik Gratz , Rene Hueber , Philipp Kalb , Thomas Fahringer","doi":"10.1016/j.comcom.2025.108314","DOIUrl":"10.1016/j.comcom.2025.108314","url":null,"abstract":"<div><div>Adaptive resource provisioning has become crucial for cloud-based applications, especially those managing real-time traffic like Voice over IP (VoIP), which experience rapidly fluctuating workloads. Traditional static provisioning methods often fall short in these dynamic environments, leading to inefficiencies and potential service disruptions. Existing solutions struggle to maintain performance under varying traffic conditions, particularly for time-sensitive applications. This paper introduces ScaleIP, a hybrid autoscaling solution for containerized VoIP services that offers real-time adaptability and efficient resource management. ScaleIP leverages Deep Reinforcement Learning to make dynamic and efficient scaling decisions, improving call latency, increasing the number of successfully routed calls, and maximizing resource utilization. We evaluated ScaleIP through extensive experiments conducted on a real testbed utilizing the customer Call Detail Record (CDR) from 2023 provided by World Direct, encompassing over 89 million calls. The results show that ScaleIP consistently maintains call latency below 2s, increases the number of successfully routed calls by 3.26×, and increases the resource utilization up to 60% compared to state-of-the-art autoscaling methods.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"243 ","pages":"Article 108314"},"PeriodicalIF":4.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145120974","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

RIS-assisted LoRa networks with diversity: Impact of hardware impairments and phase noise 具有多样性的ris辅助LoRa网络：硬件损伤和相位噪声的影响

IF 4.3 3区计算机科学

Computer Communications Pub Date : 2025-11-01 Epub Date: 2025-09-20 DOI: 10.1016/j.comcom.2025.108319

Thi-Phuong-Anh Hoang , Thien Huynh-The , Tien Hoa Nguyen , Trong-Thua Huynh , Nguyen-Son Vo , Lam-Thanh Tu

{"title":"RIS-assisted LoRa networks with diversity: Impact of hardware impairments and phase noise","authors":"Thi-Phuong-Anh Hoang , Thien Huynh-The , Tien Hoa Nguyen , Trong-Thua Huynh , Nguyen-Son Vo , Lam-Thanh Tu","doi":"10.1016/j.comcom.2025.108319","DOIUrl":"10.1016/j.comcom.2025.108319","url":null,"abstract":"<div><div>This paper investigates the performance of downlink LoRa networks assisted by reconfigurable intelligent surfaces (RIS) and diversity techniques. We derive closed-form expressions for the coverage probability (Pcov) under four scenarios: phase noise at the RIS only, hardware impairments at both the gateway and end devices (EDs), the combined effect of both impairments, and an ideal benchmark case. The analysis is carried out within a unified framework that is valid for any number of RIS elements, providing key insights into the influence of hardware impairment levels, gateway transmit power, and the diversity order as the number of RIS elements grows large. The results reveal that coverage probability improves with transmit power but deteriorates under more severe hardware impairments, while the diversity order scales directly with the number of RIS elements. Monte Carlo simulations validate the analytical findings and confirm that the ideal scenario achieves the best performance, followed in order by the phase noise, hardware impairment, and combined impairment cases.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"243 ","pages":"Article 108319"},"PeriodicalIF":4.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145222639","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

Revisiting the problem of optimizing spreading factor allocations in LoRaWAN: From theory to practice 再论LoRaWAN中扩散因子分配的优化问题：从理论到实践

IF 4.3 3区计算机科学

Computer Communications Pub Date : 2025-11-01 Epub Date: 2025-09-23 DOI: 10.1016/j.comcom.2025.108321

Dimitrios Zorbas , Aruzhan Sabyrbek , Luigi Di Puglia Pugliese

{"title":"Revisiting the problem of optimizing spreading factor allocations in LoRaWAN: From theory to practice","authors":"Dimitrios Zorbas , Aruzhan Sabyrbek , Luigi Di Puglia Pugliese","doi":"10.1016/j.comcom.2025.108321","DOIUrl":"10.1016/j.comcom.2025.108321","url":null,"abstract":"<div><div>This paper revisits the problem of optimizing LoRa network success probability by proposing an optimized allocation strategy for Spreading Factors (SFs) under both uniform and Gaussian network deployments with a single or multiple gateways. More specifically, we solve the problem of finding the best SF allocations in dense network deployments whose EDs are first assigned with the minimum SF. Theoretical models are developed to quantify the success probability of transmissions, considering the capture effect as well as intra- and inter-SF interference. A mathematical optimization framework is introduced to determine the optimal SF distribution that maximizes the average probability of packet reception. The problem is solved using Mixed Integer Linear Programming (MILP), and then evaluated using simulations. Even though optimal SF allocation strategies have been proposed in the literature, no practical insights have been discovered and no real-world deployments have been considered. To this extent, the practical benefits of using improved or optimal SF settings are discovered in this paper. Simulation results confirm the theoretical findings while they demonstrate an up to 10 percentage points improvements in Packet Reception Ratio (PRR) in the real-world use-case.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"243 ","pages":"Article 108321"},"PeriodicalIF":4.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160150","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

Tensor-based task allocation using multi-objective optimization in GECC environment GECC环境下基于张量的多目标优化任务分配

IF 4.3 3区计算机科学

Computer Communications Pub Date : 2025-11-01 Epub Date: 2025-09-15 DOI: 10.1016/j.comcom.2025.108316

Huazhong Liu, Longtao Huang, Yuan Tian, Jihong Ding, Xiaoxue Yin, Guangshun Zhang

{"title":"Tensor-based task allocation using multi-objective optimization in GECC environment","authors":"Huazhong Liu, Longtao Huang, Yuan Tian, Jihong Ding, Xiaoxue Yin, Guangshun Zhang","doi":"10.1016/j.comcom.2025.108316","DOIUrl":"10.1016/j.comcom.2025.108316","url":null,"abstract":"<div><div>Green Edge-Cloud Computing (GECC) has emerged as a promising paradigm to meet the diverse requirements of modern applications by integrating edge and cloud resources. Existing task allocation strategies in GECC environment often fail to adequately address the problems of low resource utilization and high economic cost in multi-objective conflicts. Therefore, this paper proposes a tensor-based task allocation scheme using multi-objective optimization in GECC environment. We first extend the task allocation problem in GECC environment to a multi-objective optimization problem and construct five optimization models, i.e., energy, system reliability, quality of experience, economic cost, and latency. Then, to address the complex relationship among these objectives, we develop a tensor-based representation and calculation model for task allocation across cloud, edge service, and edge device platforms. Furthermore, we propose a tensor-based multi-objective beetle swarm optimization algorithm combined speed limiting and dynamic step strategies (TMOBSO-SLDS) that dynamically adjusts the step size and limit speed to improve the global search efficiency and the diversity of solution set. Extensive experimental results in various task allocation scenarios demonstrate that our proposed TMOBSO-SLDS algorithm outperforms existing approaches, as measured by the HV value. It can significantly enhance the diversity of the solution set and improve resource utilization.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"243 ","pages":"Article 108316"},"PeriodicalIF":4.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160253","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

An effective method for Data Aggregation Point placement in LoRaWAN network for smart metering service 一种用于智能计量服务的LoRaWAN网络数据汇聚点的有效布置方法

IF 4.3 3区计算机科学

Computer Communications Pub Date : 2025-11-01 Epub Date: 2025-10-09 DOI: 10.1016/j.comcom.2025.108335

Thiago A.R. da Silva , Geraldo A. Sarmento N. , Luís H. de O. Mendes , Pedro F. de Abreu , Artur F. da S. Veloso , Fernando J.V. Santos , José Valdemir dos R. Júnior

{"title":"An effective method for Data Aggregation Point placement in LoRaWAN network for smart metering service","authors":"Thiago A.R. da Silva , Geraldo A. Sarmento N. , Luís H. de O. Mendes , Pedro F. de Abreu , Artur F. da S. Veloso , Fernando J.V. Santos , José Valdemir dos R. Júnior","doi":"10.1016/j.comcom.2025.108335","DOIUrl":"10.1016/j.comcom.2025.108335","url":null,"abstract":"<div><div>Electric grids have been restructured with Smart Grids (SGs), and the deployment of Advanced Metering Infrastructure (AMI) systems is a fundamental part of this process. An AMI system consists of Smart Meters (SMs) that collect energy consumption data and send it to the utility company through Data Aggregation Points (DAPs). Thus, methods to determine the appropriate quantity and positions of DAPs become necessary. In this context, this paper proposes a method called DAP Placement (DPlace), which determines the minimum number of DAPs and applies the Fuzzy C-Means algorithm to position the DAPs at coordinates that enhance the successful reception of packets, ensuring that smart metering applications can adequately transmit data through a Long Range Wide-Area Network (LoRaWAN) network. The proposed method is compared to three state-of-the-art solutions through simulations, and the results show that the DPlace method reduces the required number of DAPs by up to 37.04% while achieving communication performance – evaluated through metrics such as packet delivery ratio and delay – similar to related methods, even with less DAPs.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"243 ","pages":"Article 108335"},"PeriodicalIF":4.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269673","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

Requirement-driven multi-workflow scheduling based on improved evolutionary multitasking embedded bi-level optimization 基于改进进化多任务嵌入式双级优化的需求驱动多工作流调度

IF 4.3 3区计算机科学

Computer Communications Pub Date : 2025-11-01 Epub Date: 2025-10-06 DOI: 10.1016/j.comcom.2025.108334

Mengxia Li , Linjie Wu , Yan Zhang , Xingjuan Cai

{"title":"Requirement-driven multi-workflow scheduling based on improved evolutionary multitasking embedded bi-level optimization","authors":"Mengxia Li , Linjie Wu , Yan Zhang , Xingjuan Cai","doi":"10.1016/j.comcom.2025.108334","DOIUrl":"10.1016/j.comcom.2025.108334","url":null,"abstract":"<div><div>When multiple users share the same cloud service resources, cloud computing makes it more difficult for workflow applications to schedule tasks. Therefore, it is important to design an appropriate scheme that benefits both users and cloud service providers. We create a bi-level optimization model to explain cloud client cooperation in order to address this issue. In order to ensure fairness while vying for resources across several processes, users combine execution time and cost as a goal for user satisfaction. They also coordinate resource allocation to minimize the error between the time and cost of a single workflow execution. Cloud service providers maximize their profits by rationally and dynamically adjusting prices. In the solution method to maintain the diversity of the population in the optimization process, adaptive cross-variance probability and population local replacement strategy are proposed, which reduces the poorly adapted individuals to play the game and accelerates the convergence of the population. The experimental findings demonstrate that the model’s algorithm’s validity is confirmed by various datasets and that the user’s service quality and the cloud service provider’s interests are balanced.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"243 ","pages":"Article 108334"},"PeriodicalIF":4.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145325768","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