IEEE Transactions on Sustainable Computing最新文献

2024 Reviewers List* 2024审稿人名单*

IF 3 3区计算机科学

IEEE Transactions on Sustainable Computing Pub Date : 2025-02-05 DOI: 10.1109/TSUSC.2025.3526402

引用次数: 0

Energy-Efficient Shop Scheduling Using Space-Cooperation Multi-Objective Optimization 基于空间协同多目标优化的节能车间调度

IF 3 3区计算机科学

IEEE Transactions on Sustainable Computing Pub Date : 2024-12-11 DOI: 10.1109/TSUSC.2024.3506822

Jiepin Ding;Jun Xia;Yaning Yang;Junlong Zhou;Mingsong Chen;Keqin Li

{"title":"Energy-Efficient Shop Scheduling Using Space-Cooperation Multi-Objective Optimization","authors":"Jiepin Ding;Jun Xia;Yaning Yang;Junlong Zhou;Mingsong Chen;Keqin Li","doi":"10.1109/TSUSC.2024.3506822","DOIUrl":"https://doi.org/10.1109/TSUSC.2024.3506822","url":null,"abstract":"Since Industry 5.0 emphasizes that manufacturing enterprises should raise awareness of social contribution to achieve sustainable development, more and more meta-heuristic algorithms are investigated to save energy in manufacturing systems. Although non-dominated sorting-based meta-heuristics have been recognized as promising multi-objective optimization methods for solving the energy-efficient flexible job shop scheduling problem (EFJSP), it is hard to guarantee the quality of the Pareto front (e.g., total energy consumption, makespan) due to the lack of population diversity. This is mainly because an improper individual comparison inevitably reduces population diversity, thus limiting exploration and exploitation abilities during population updates. To achieve efficient population evolution, this paper introduces a novel space-cooperation multi-objective optimization (SCMO) method that can effectively solve EFJSP to obtain scheduling schemes with better trade-offs. By cooperatively evaluating the similarity among individuals in both the decision space and objective space, we propose a space-cooperation population update method based on a three-vector representation that can accurately eliminate repetitive individuals to derive higher-quality Pareto solutions. To further improve search efficiency, we propose a difference-driven local search, which selectively changes the positions of operations with higher differences to search for neighbors effectively. Based on the Taguchi method, we conduct experiments to obtain a suitable parameter combination of SCMO. Comprehensive experimental results show that, compared to state-of-the-art methods, our SCMO method achieves the highest HV and NR and the lowest IGD, with an average of 0.990, 0.952, and 0.001, respectively. Meanwhile, compared to traditional local search approaches, our difference-driven local search obtains twice the HV on instance Mk12 and reduces the solving time from 1521 s to 475 s.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"10 3","pages":"601-615"},"PeriodicalIF":3.0,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219630","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 and Minimum Connected Dominating Set Based Confident Information Coverage Reliability Evaluation for IoT 基于张量和最小连通支配集的物联网可信信息覆盖可靠性评估

IF 3 3区计算机科学

IEEE Transactions on Sustainable Computing Pub Date : 2024-11-25 DOI: 10.1109/TSUSC.2024.3503712

Ziheng Xiao;Chenlu Zhu;Wei Feng;Shenghao Liu;Xianjun Deng;Hongwei Lu;Laurence T. Yang;Jong Hyuk Park

{"title":"Tensor and Minimum Connected Dominating Set Based Confident Information Coverage Reliability Evaluation for IoT","authors":"Ziheng Xiao;Chenlu Zhu;Wei Feng;Shenghao Liu;Xianjun Deng;Hongwei Lu;Laurence T. Yang;Jong Hyuk Park","doi":"10.1109/TSUSC.2024.3503712","DOIUrl":"https://doi.org/10.1109/TSUSC.2024.3503712","url":null,"abstract":"Internet of Things (IoT) reliability evaluation contributes to the sustainable computing and enhanced stability of the network. Previous algorithms usually evaluate the reliability of IoT by enumenating the states of nodes and networks, which are difficult to handle IoT with hundreds of nodes because the computational cost. In this paper, a novel algorithm, TMCRA, is proposed to evaluate the reliability of IoT in complex network environment, which consider both coverage and connectivity. For coverage, TMCRA employs the Confident Information Coverage (CIC) model to divide the target area into independent grids and calculates the coverage rate. In terms of connectivity, TMCRA forming the Virtual Backbone Network (VBN) based on two proposed methods: TMA and MGIN, and evaluate connectivity by analyzing the VBN rather than the whole network. The TMA and MGIN are two algorithms for constructing Minimum Connected Dominant Sets (MCDS), which are suitable for different scale networks. Finally, based on the data of coverage and connectivity, TMCRA utilizes tensors for the unified modeling and representation of network structure, and calculates IoT reliability based on the tensors. Simulations are carried out for various sizes of IoT to show the advantages and effectiveness of the proposed approach in reliability evaluation.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"10 3","pages":"547-561"},"PeriodicalIF":3.0,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219804","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

Novel Approach of Vehicular Cooperative Communication Based on Strategy of Interval Type-2 Fuzzy Logic and Cooperative Game 基于区间2型模糊逻辑和合作博弈策略的车辆协同通信新方法

IF 3 3区计算机科学

IEEE Transactions on Sustainable Computing Pub Date : 2024-11-21 DOI: 10.1109/TSUSC.2024.3503580

Jie Zhang;Zhihao Zhang;Degan Zhang;Chenhao Ni;Ting Zhang;Xingru Jiang

{"title":"Novel Approach of Vehicular Cooperative Communication Based on Strategy of Interval Type-2 Fuzzy Logic and Cooperative Game","authors":"Jie Zhang;Zhihao Zhang;Degan Zhang;Chenhao Ni;Ting Zhang;Xingru Jiang","doi":"10.1109/TSUSC.2024.3503580","DOIUrl":"https://doi.org/10.1109/TSUSC.2024.3503580","url":null,"abstract":"As an important branch of the Internet of Things (IoT), vehicular networks play a crucial role in the construction of intelligent transportation systems. However, due to the rapid movement of vehicles and signal obstruction, achieving high- quality and low-latency communication in vehicular networks remains a significant challenge. To address this issue, this paper proposes a novel data communication method based on interval type-2 fuzzy logic and cooperative game theory. Firstly, interval type-2 fuzzy logic is utilized to infer vehicle stability, thereby selecting high-quality backbone nodes. Concurrently, the memory and forgetfulness functions of the Gated Recurrent Unit are employed to retain critical data packets. Subsequently, a greedy algorithm and cooperative game theory model are used to describe the behavior of vehicles in Roadside-to-Vehicle (R2V) communication and Vehicle-to- Vehicle (V2V) communication, respectively. This approach encourages backbone nodes to cooperate and serve other vehicles based on a benefit function. Experimental results demonstrate that the proposed method excels in terms of transmission delay, coverage range, and data packet delivery success rate.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"10 3","pages":"588-600"},"PeriodicalIF":3.0,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219581","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

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting 移动网络中的联邦学习：流量预测的综合案例研究

IF 3 3区计算机科学

IEEE Transactions on Sustainable Computing Pub Date : 2024-11-21 DOI: 10.1109/TSUSC.2024.3504242

Nikolaos Pavlidis;Vasileios Perifanis;Selim F. Yilmaz;Francesc Wilhelmi;Marco Miozzo;Pavlos S. Efraimidis;Remous-Aris Koutsiamanis;Pavol Mulinka;Paolo Dini

{"title":"Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting","authors":"Nikolaos Pavlidis;Vasileios Perifanis;Selim F. Yilmaz;Francesc Wilhelmi;Marco Miozzo;Pavlos S. Efraimidis;Remous-Aris Koutsiamanis;Pavol Mulinka;Paolo Dini","doi":"10.1109/TSUSC.2024.3504242","DOIUrl":"https://doi.org/10.1109/TSUSC.2024.3504242","url":null,"abstract":"The increasing demand for efficient resource allocation in mobile networks has catalyzed the exploration of innovative solutions that could enhance the task of real-time cellular traffic prediction. Under these circumstances, federated learning (FL) stands out as a distributed and privacy-preserving solution to foster collaboration among different sites, thus enabling responsive near-the-edge solutions. In this paper, we comprehensively study the potential benefits of FL in telecommunications through a case study on federated traffic forecasting using real-world data from base stations (BSs) in Barcelona (Spain). Our study encompasses relevant aspects within the federated experience, including model aggregation techniques, outlier management, the impact of individual clients, personalized learning, and the integration of exogenous sources of data. The performed evaluation is based on both prediction accuracy and sustainability, thus showcasing the environmental impact of employed FL algorithms in various settings. The findings from our study highlight FL as a promising and robust solution for mobile traffic prediction, emphasizing its twin merits as a privacy-conscious and environmentally sustainable approach, while also demonstrating its capability to overcome data heterogeneity and ensure high-quality predictions, marking a significant stride towards its integration in mobile traffic management systems.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"10 3","pages":"576-587"},"PeriodicalIF":3.0,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219807","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

ChestBox: Enabling Fast State Sharing for Stateful Serverless Computing With State Functions ChestBox：使用状态函数为有状态无服务器计算启用快速状态共享

IF 3 3区计算机科学

IEEE Transactions on Sustainable Computing Pub Date : 2024-11-13 DOI: 10.1109/TSUSC.2024.3497326

Xinmin Zhang;Song Wu;Lin Gu;Qiang He;Hai Jin

{"title":"ChestBox: Enabling Fast State Sharing for Stateful Serverless Computing With State Functions","authors":"Xinmin Zhang;Song Wu;Lin Gu;Qiang He;Hai Jin","doi":"10.1109/TSUSC.2024.3497326","DOIUrl":"https://doi.org/10.1109/TSUSC.2024.3497326","url":null,"abstract":"This paper presents ChestBox, a novel approach that utilizes <italic>state functions</i> to facilitate low-latency state sharing for stateful serverless computing. When an <italic>application function</i> needs to share a state, the state function creates a memory space with Linux's shared memory object to store the state. Other application functions can then read the state directly from the shared memory. ChestBox enables fast state sharing that avoids excessive memory overhead without compromising on-demand resource allocation compared to existing solutions. This effectively reduces the energy consumption of serverless computing and promotes sustainable computing. The implementation of ChestBox on Apache OpenWhisk unearths two major implementation challenges, which we address with respective optimization techniques, i.e., state function channel and state swapping. The evaluation of ChestBox with four real-world applications shows that compared with the state-of-the-art approach, it can reduce state-sharing latency by up to 99.71%, while reducing execution costs by 24.59% and storage costs by 99.76%.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"10 3","pages":"491-502"},"PeriodicalIF":3.0,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10752406","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219803","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

Distributed Energy Bank Optimization Towards Outage Aware Sustainable Cellular Networks 面向停电感知可持续蜂窝网络的分布式能源银行优化

IF 3 3区计算机科学

IEEE Transactions on Sustainable Computing Pub Date : 2024-10-28 DOI: 10.1109/TSUSC.2024.3486976

Ashutosh Balakrishnan;Swades De;Li-Chun Wang

{"title":"Distributed Energy Bank Optimization Towards Outage Aware Sustainable Cellular Networks","authors":"Ashutosh Balakrishnan;Swades De;Li-Chun Wang","doi":"10.1109/TSUSC.2024.3486976","DOIUrl":"https://doi.org/10.1109/TSUSC.2024.3486976","url":null,"abstract":"Grid connected and solar powered base stations (BSs) acting as distributed energy sources are increasingly becoming a popular solution to mobile operators. These networks experience double stochasticity due to the space-time variations in energy harvest and BS traffic. Hence, accurate and efficient green energy outage estimation in such networks is a challenging task. In this work, we propose a complutationally efficient cooperative energy transfer based distributed energy bank strategy to alleviate green energy outage and design energy sustainable networks. We first develop low-complexity Markovian frameworks to estimate green energy outage in a standalone BS without energy cooperation (WEC) and a multi-BS energy-cooperative (EC) setting, respectively. For the WEC system, we present a computationally efficient three-state discrete time Markovian statistical model, while the multi-BS EC framework is characterized by a two-state Markov model. The energy outage is studied as a function of capital expenditure (CAPEX), manifesting engineering insights from a service provider's perspective. Subsequently for the EC framework, we formulate a CAPEX optimization problem by jointly optimizing the BS cluster size and solar provisioning on individual BSs. Our results demonstrate that the proposed EC framework alleviates the green energy outage significantly, providing computational efficiency gains and CAPEX savings over the state-of-art approaches.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"10 3","pages":"503-514"},"PeriodicalIF":3.0,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219757","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

Analysis of Transceiver RF Impairments on Artificial Noise Suppression in Frequency-Hopping Systems 跳频系统中人工噪声抑制对收发器射频损伤的影响分析

IF 3 3区计算机科学

IEEE Transactions on Sustainable Computing Pub Date : 2024-10-07 DOI: 10.1109/TSUSC.2024.3475576

Changqing Song;Hongzhi Zhao;Yong Yu;Zhuo Li;Shihai Shao

{"title":"Analysis of Transceiver RF Impairments on Artificial Noise Suppression in Frequency-Hopping Systems","authors":"Changqing Song;Hongzhi Zhao;Yong Yu;Zhuo Li;Shihai Shao","doi":"10.1109/TSUSC.2024.3475576","DOIUrl":"https://doi.org/10.1109/TSUSC.2024.3475576","url":null,"abstract":"The artificial noise shielded frequency-hopping (AN-FH) architecture can secure wireless communications against interference and eavesdropping. However, the AN suppression performance is highly sensitive to the radio frequency (RF) impairments, and the transceiver in-phase and quadrature (IQ) imbalances and phase noise in FH systems are more severe for the wide FH bandwidth. In this study, the AN-FH transceivers under RF impairments are mathematically modeled. Subsequently, distortions for transceiver phase noise are represented by the common phase error, distortions for transceiver IQ imbalances are represented by the mirror image component, and closed-form expressions for their respective power are derived and compared with the thermal noise power. Finally, the AN suppression capability is evaluated via the AN suppression ratio (ANSR), defined as the ratio of the AN-plus-noise power before and after suppression. It is found that when only phase noise exists, shortening the channel compensation cycle can enhance ANSR and reduce ANSR degradation; when the distortions’ power is smaller than the thermal noise power, it is also recommended to enhance the transmitting power and the power ratio of AN to information signals. When only IQ imbalances exist, increasing the power ratio of AN to information signals is suggested; when the distortions’ power is smaller than the thermal noise power, enhancing the transmitting power is also suggested.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"10 3","pages":"475-490"},"PeriodicalIF":3.0,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219808","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

Let Robots Watch Grass Grow: Optimal Task Assignment for Automatic Plant Factory 让机器人看草：自动化工厂的最佳任务分配

IF 3 3区计算机科学

IEEE Transactions on Sustainable Computing Pub Date : 2024-09-17 DOI: 10.1109/TSUSC.2024.3462447

Zhengzhe Xiang;Xizi Xue;Yuanyi Chen;Schahram Dustdar;Minyi Guo

{"title":"Let Robots Watch Grass Grow: Optimal Task Assignment for Automatic Plant Factory","authors":"Zhengzhe Xiang;Xizi Xue;Yuanyi Chen;Schahram Dustdar;Minyi Guo","doi":"10.1109/TSUSC.2024.3462447","DOIUrl":"https://doi.org/10.1109/TSUSC.2024.3462447","url":null,"abstract":"Modularized plant factories, characterized by machines executing intelligent control requests to automatically take care of crops, have emerged as a sustainable agricultural paradigm, garnering the attention of Internet-of-Things and agricultural researchers for their production stability and energy efficiency. However, the diversity and pluralism of the plant factory components make it difficult to cooperate and produce crops with better qualities. Therefore, appropriate resource allocation and task scheduling strategies become the key points to optimize the quality of production in the factories by immediately telling which component is more suitable to do what in taking care of the crops. To address this challenge, this paper investigates how the machines of the factory can use their unique services and resource to help improve the crops’ quality and model the machine cooperation as an online decision-making problem. An <inline-formula><tex-math>$alpha$</tex-math></inline-formula>-competitive approach called <inline-formula><tex-math>$textsc {OnATS}$</tex-math></inline-formula> is designed based on the transformation of the original problem, and the experiments show that the proposed algorithm is superior to the baselines. Additionally, this paper explores the impact of different system configurations on the proposed method and shows that the proposed approach has broad applicability.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"10 3","pages":"464-474"},"PeriodicalIF":3.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219809","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

Workload Pattern Learning-Based Cloud Resource Management Models: Concepts and Meta-Analysis 基于工作量模式学习的云资源管理模型：概念和元分析

IF 3 3区计算机科学

IEEE Transactions on Sustainable Computing Pub Date : 2024-09-09 DOI: 10.1109/TSUSC.2024.3456429

Deepika Saxena;Ashutosh Kumar Singh

{"title":"Workload Pattern Learning-Based Cloud Resource Management Models: Concepts and Meta-Analysis","authors":"Deepika Saxena;Ashutosh Kumar Singh","doi":"10.1109/TSUSC.2024.3456429","DOIUrl":"https://doi.org/10.1109/TSUSC.2024.3456429","url":null,"abstract":"Workload pattern learning-based resource management is crucial for cloud computing environments for achieving higher performance, sustainability, fault-tolerance, and quality of service. The existing literature lacks a comprehensive discussion and meta-analysis of workload pattern learning centered cloud resource management. In this context, this paper presents a first comprehensive study about five pattern learning and analysis-driven techniques applied for achieving higher efficiency and performance during multi-constrained cloud resource management. The paper manifests utility and significance of workload pattern learning-based resource management as compared with traditional resource management. The five principle techniques are thoroughly discussed with coherent depiction of intended concept alongwith numerical illustration. The most prominent state-of-the-art models belonging to each technique are further distinguished based on distinct objectives conferring an extensive survey and comparison. Besides, conceptual and theoretical analysis, the leading models underlying the major resource management techniques are implemented on a common platform and thoroughly examined using real-world Google Cluster workload traces. Based on the all-inclusive study and performance evaluation, trade-off discussion among these techniques are capsuled to put forward imperative concluding remarks with concrete open issues and insightful future research directions.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"10 3","pages":"418-438"},"PeriodicalIF":3.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219810","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