Sustainable Computing-Informatics & Systems最新文献

{"title":"Hardware and application aware performance, power and energy models for modern HPC servers with DVFS","authors":"Georges Da Costa","doi":"10.1016/j.suscom.2025.101106","DOIUrl":"10.1016/j.suscom.2025.101106","url":null,"abstract":"<div><div>Energy usage and its ecological impact is now a major concern in High Performance Computing (HPC). To optimize supercomputers efficiency, researchers rely on models, as accessing actual platform is complex and costly. Changing DVFS (Dynamic Voltage and Frequency Scaling) is the most studied method, but it impacts power, performance and energy in a complex way.</div><div>We propose to bridge the gap between the theoretical and the practical approaches. We propose a multi cluster, multi application model accurately describing from a theoretical point of view the power and performance of applications subject to DVFS. We show how to use it on a runtime system with a minimal overhead, using only a few hardware performance counters and RAPL (Running Average Power Limit).</div><div>We validate our models using an extensive dataset, obtained using 18 different clusters and running 9 benchmarks. We also show how such model can be used to optimize the energy-to-solution for HPC workload.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"46 ","pages":"Article 101106"},"PeriodicalIF":3.8,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593211","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}

{"title":"Secured user authentication and data sharing for mobile cloud computing using 2C-Cubehash and PWCC","authors":"Surendar Rama Sitaraman ,&nbsp;Kalyan Gattupalli ,&nbsp;Venkata Surya Bhavana Harish Gollavilli ,&nbsp;Harikumar Nagarajan ,&nbsp;Poovendran Alagarsundaram ,&nbsp;Haris M. Khalid","doi":"10.1016/j.suscom.2025.101107","DOIUrl":"10.1016/j.suscom.2025.101107","url":null,"abstract":"<div><div>To share data securely, existing works use a public key and a private key for transmission. The secured data sharing along with user authentication is necessary for mobile devices. So, proper authorization is needed to access data owners' credential information from cloud computing. Therefore, the paper presents a novel framework for secured data sharing and user authentication. The security-based authorization in data transfer is taken significantly. Initially, DO and DU register to TA and then hashcode is generated using 2C-Cubehash for the login. After login, the data is encrypted by PWCC and then uploaded by the owner into the mobile cloud. Later, with an end-user request, the possessor and permitter verify the user and give PPK and smart contract to the end-user. Using the two PPK, the client downloads the data. The successful transaction in the blockchain is monitored by the proprietor by constructing UUI-MT. The proposed model resulted in 3123 ms processing time, 2941 ms latency, and 98.03 % security level. With the proposed model, secured user-authenticated data sharing is achieved.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"46 ","pages":"Article 101107"},"PeriodicalIF":3.8,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621019","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}

{"title":"FOG computing based energy efficient and secured iot data sharing using SGSOA and GMCC","authors":"Swapna Narla ,&nbsp;Sreekar Peddi ,&nbsp;Dharma Teja Valivarthi ,&nbsp;Sai Sathish Kethu ,&nbsp;Durai Rajesh Natarajan ,&nbsp;Dede Kurniadi","doi":"10.1016/j.suscom.2025.101109","DOIUrl":"10.1016/j.suscom.2025.101109","url":null,"abstract":"<div><div>A Free and open-source Ghost (FOG) computing is a decentralized computing infrastructure, that helps in processing the data efficiently to end-user. None of the existing works concentrated on authorization between source, destination, and intermediate server during the Internet of Things (IoT) sensor data transmission. Therefore, the paper presents the authentication of the servers using Cholesky-HAVAL for secure IoT sensor data transmission. Initially, the IoT sensor devices are registered and logged into the FOG server. Next, the sensor nodes are clustered using Bray Pearson K-Means (BP-KMeans) clustering method. Through the cluster head, the IoT data is sensed, and the attributes are extracted. The sensed data is then secured using Gauss Montgomery Curve Cryptography (GMCC). The secured data is stored in the Hadoop Distributed File System (HDFS) FOG server. Here, the data is mapped using BP-KMeans and then reduced using the Schwefel Group Search Optimization Algorithm (SGSOA). Meanwhile, Merkle Tree (MT) is created using Cholesky-HAVAL regarding the sensor data attributes, IoT sensor ID (Identification), and FOG server ID. Next, to retrieve the sensor data, the user registers and logs into the server. Then, the user gives a query request for accessing the data present in the cloud. The attributes are extracted from the query, and using SGSOA, the query is optimized. Finally, the hashcode verification is done regarding the attributes from sensed data and the query. The IoT data is thus retrieved for the verified hashcodes. Thus, the proposed work clustered the sensor nodes in 4578 ms and generated the hashcode in 1476 ms.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"46 ","pages":"Article 101109"},"PeriodicalIF":3.8,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643835","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}

{"title":"A hybrid bio-inspired approach for clustering and routing in UWSNs using MPA and HGS","authors":"Haitao Li ,&nbsp;Mohammad Khishe ,&nbsp;Francisco Hernando-Gallego ,&nbsp;Diego Martín","doi":"10.1016/j.suscom.2025.101108","DOIUrl":"10.1016/j.suscom.2025.101108","url":null,"abstract":"<div><div>Underwater Wireless Sensor Networks (UWSNs) encounter serious challenges due to dynamic topology, energy constraints, and high latency underwater communication. Existing methods for clustering and routing often fail to strike an optimal balance between data delivery reliability, energy efficiency, and latency reduction. This paper overcomes these shortcomings by developing a hybrid model that integrates the Hunger Games Search (HGS) and Marine Predator Algorithm (MPA) for improved clustering and routing in UWSNs. The MPA was chosen due to its stability in selecting the first sensors/cluster heads and creating the clusters, drawing inspiration from the foraging strategies of marine predators, which guides it extensively in the balance of exploration and exploitation. Simulations demonstrate that the proposed method achieves significantly better results than classical methods. In particular, the HGS-MPA framework consumes 26.6 % less energy than GWO-PSO, increasing network lifetime by 22.1 % (FINOD) and 15.8 % (HANOD). The packet delivery ratio is improved by 3.1 % against the following best-performing method, reaching 92.4 %. A statistical test performed with ANOVA showed that these improvements are statistically significant at P &lt; 0.001. The results reinforce how the HGS-MPA framework would help improve energy efficiency, network lifetime, and communication reliability in UWSN systems.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"46 ","pages":"Article 101108"},"PeriodicalIF":3.8,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562935","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}

{"title":"Modelling and optimization of a FACTS devices operated multi-objective optimal reactive power dispatch (ORPD) problem minimizing both operational cost and fuel emissions","authors":"Tanmay Das ,&nbsp;Ranjit Roy ,&nbsp;Kamal Krishna Mandal","doi":"10.1016/j.suscom.2025.101104","DOIUrl":"10.1016/j.suscom.2025.101104","url":null,"abstract":"<div><div>The study of modern power systems is complex and multi-dimensional with diverse constraints that are generally considered one at a time for seeking the optimal results for a specific set of goals. However, for a more realistic approach to problem solving, multiple goals are tackled simultaneously, optimizing a multi-objective problem. In this study, a multi-objective (MO) Flexible AC transmission system (FACTS) device incorporated in an optimal reactive power dispatch (ORPD) problem that has been developed considering these distinct objectives concurrently to formulate a ‘MO-ORPD-ELD-Emission-FACTS’ problem—the hourly cost of energy lost in transmission (from ORPD), generation cost (from economic load dispatch), the operational cost of FACTS devices such as static VAR compensator (SVC) and thyristor-controlled series capacitor (TCSC), and emissions of fossil fuel pollutants. The implementation technique is the Arithmetic Optimization Algorithm (AOA), and it is being tested on the standard IEEE 30, IEEE 57, and IEEE 118 bus systems. The fuzzy-based mechanism of Pareto optimality has been employed to determine the Best Compromising Solution (BCS) out of the set of Pareto solutions of the multi-objective problem. A specific case of load uncertainty has also been carried out for the larger IEEE 118 bus system with ten different variations of load demands for the same multi-objective function. The aim was to study the significance of the achieved results under the different loading conditions and compare the voltage profiles. The solutions obtained by AOA were observed to be the best and followed an ideal nature of Pareto optimality compared to the others. The incorporation of FACTS has significantly reduced the cost of economic load dispatch (ELD), the cost of energy loss, and fuel emissions, and with a much healthier voltage profile for all three test bus systems. The power loss has been reduced from 3.1129 MW to 2.8469 MW for the IEEE 30 bus system, from 11.366 MW to 10.0656 MW for the IEEE 57 bus system, and from 73.2977 MW to 64.2368 MW for the IEEE 118 bus system as obtained by the AOA. The IEEE 118 bus system showed the optimal overall operational cost and emission at 77.4 % loading, with a better voltage profile with the incorporation of FACTS devices.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"46 ","pages":"Article 101104"},"PeriodicalIF":3.8,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620888","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}

{"title":"New approach of computing task offloading for IOV based on sparrow search optimization strategy","authors":"Degan Zhang ,&nbsp;Xiaoyang Wang ,&nbsp;Jie Zhang ,&nbsp;Ting Zhang ,&nbsp;Lu Chen ,&nbsp;Hongtao Chen ,&nbsp;E. Honglin ,&nbsp;Member, IEEE","doi":"10.1016/j.suscom.2025.101099","DOIUrl":"10.1016/j.suscom.2025.101099","url":null,"abstract":"<div><div>With the rapid development of the Internet of Vehicles (IoV), the computation and communication demands of vehicles are increasing. The traditional centralized computing model can no longer meet these demands. Consequently, task offloading techniques have become crucial for enhancing computational performance and reducing vehicle load in IoV. In this paper, we propose a new method of task offloading for IoV computing based on the sparrow search optimization strategy. Specifically, we address the multifactorial influences on task offloading. Firstly, we design an offloading model that integrates multiple optimization objectives, such as delay and energy consumption. Secondly, we develop a fitness function that balances delay and energy consumption to evaluate and select task offloading strategies. Additionally, we design a network access model to maintain network access stability. Finally, we conduct an iterative optimization search for the offloading strategy using an improved sparrow search optimization algorithm. Through extensive simulation experiments and real-world scenario tests, we validated the effectiveness and performance advantages of the proposed method. The experimental results demonstrate that our new IoV task offloading method, based on the improved sparrow search optimization algorithm, enhances computational performance while reducing vehicle load, showing great potential for applications in the field of IoV task offloading.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"46 ","pages":"Article 101099"},"PeriodicalIF":3.8,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593210","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}

{"title":"A hybrid learning technique for intrusion detection system for smart grid","authors":"Najet Hamdi","doi":"10.1016/j.suscom.2025.101102","DOIUrl":"10.1016/j.suscom.2025.101102","url":null,"abstract":"<div><div>Smart grid is becoming more interconnected with external networks as a result of integrating IoT technologies, making its supervisory control and data acquisition (SCADA) vulnerable to serious cyberattacks. Therefore, early detection of suspicious activities is of utmost importance to safeguard SCADA systems. Machine learning (ML) algorithms are effective methods for developing intrusion detection systems. However, developing an efficient and reliable detection system for smart grids remains challenging: Most suggested ML-based intrusion detection methods are based on centralized learning, in which data is collected from smart meters and transferred to a central server for training. Transferring sensitive data adds another burden to safeguarding smart grids, since it may result in significant privacy breaches and data leaks in the event of attacking the central server. In contrast to centralized learning, federated learning (FL) offers data privacy protection. FL is an emerging cooperative learning that enables training between smart devices (clients) using local datasets which are kept on the clients’ sides. The resilience of FL-based detection systems in real-world situations, however, has not yet been examined, as clients may encounter various assaults, resulting in their local datasets having more or fewer attacks than others participating in the learning process. Motivated by this concern, we propose a FL-based intrusion detection for SCADA systems where clients have different attacks. We examine the impact of having missing attacks in local datasets on the performance of FL-based classifier. The experimental findings demonstrate a significant performance degradation of the FL-based model. As a remedy, we suggest a novel learning method – hybrid learning – that combines centralized and federated learning. The experimental results show that the hybrid learning classifier succeeds in identifying unseen attacks.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"46 ","pages":"Article 101102"},"PeriodicalIF":3.8,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143519514","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}

{"title":"An extensible lightweight framework for distributed telemetry of microservices","authors":"Manuel Otero ,&nbsp;José María García ,&nbsp;Pablo Fernandez","doi":"10.1016/j.suscom.2025.101100","DOIUrl":"10.1016/j.suscom.2025.101100","url":null,"abstract":"<div><div>Microservice architectures have become the standard for developing scalable distributed systems that offer significant benefits in managing the integration and evolution of complex applications. However, they face challenges in effectively diagnosing and resolving performance and reliability issues. Traditional centralized telemetry models and cloud-based monitoring platforms often require complex or costly configurations and are not optimized for RESTful microservices. In fact, although the OpenAPI Specification (OAS) has become a key standard for describing microservice APIs, existing telemetry tools do not leverage this information to enhance service analysis and diagnostics. This paper introduces a lightweight and distributed approach to telemetry that uses OAS-based API information, offering an automated, configuration-free system that enables developers and operations teams to perform root cause analysis more efficiently. Moreover, we propose a plugin system to incorporate intelligent behavior into the telemetry system, such as an adaptive proactive alert mechanism when response-time anomalies are detected. By incorporating this extensibility mechanism, the framework paves the way to address issues such as energy consumption and performance, allowing the system to dynamically adjust its monitoring activities to optimize resource usage and minimize the carbon footprint of microservice deployment and execution. This adaptability reduces operational overhead and supports sustainable computing practices. To validate our approach, we present a proof-of-concept in the form of a ready-to-use package for the NodeJS ecosystem, demonstrating that this distributed telemetry model can operate with minimal impact on system performance and resource usage, proving its effectiveness to support more robust and sustainable IT systems.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"46 ","pages":"Article 101100"},"PeriodicalIF":3.8,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552705","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}

{"title":"Fuzzy fair efficiency assessment in network data envelopment analysis models for complex system: An application in sustainable supply chain management","authors":"Mohammad Tavassoli","doi":"10.1016/j.suscom.2025.101105","DOIUrl":"10.1016/j.suscom.2025.101105","url":null,"abstract":"<div><div>Network data envelopment analysis (NDEA) is a common mathematical technique to evaluate the performance of a set of homogeneous decision-making units (DMUs) with a network structure. In an open-series system with a multi-stage structure, it is crucial to determine fair efficiency for each stage when multiple optimal weights exist, so that the stages have incentives to cooperate with each other to achieve the highest possible performance of the entire system. This study suggests a novel approach based on the NDEA model to assess the fair efficiency of an open-series system with a multi-stage structure. Then, to deal with qualitative data and uncertainty in the values of some variables, the suggested NDEA model is developed in a fuzzy setting, using linguistic terms parameterized through fuzzy sets. The proposed method in this study has the following features that cannot be found in previous studies. <em>First</em>, the proposed method can provide a unique and fair efficiency decomposition for the stages of a system at any level of uncertainty while the overall efficiency of the system remains unchanged. <em>Second</em>, the proposed methodology proves that the achieved efficiency decomposition shows a fair trade-off among the stages. <em>Third</em>, the proposed method can provide fair efficiency decomposition in multi-stage systems in the presence of undesirable intermediate outputs, in which undesirable intermediate output can be reused as input after processing. The application of the proposed methodology is justified by two real-case studies that include performance evaluations of 9 tomato paste producer supply chains and 22 home appliance supply chains.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"46 ","pages":"Article 101105"},"PeriodicalIF":3.8,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143519513","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}

{"title":"Simulation and real-time implementation of a combined control strategy-based shunt active power filter in microgrid","authors":"Prasanta Kumar Barik ,&nbsp;Gauri Shankar ,&nbsp;Pradeepta Kumar Sahoo ,&nbsp;Sarita Samal","doi":"10.1016/j.suscom.2025.101103","DOIUrl":"10.1016/j.suscom.2025.101103","url":null,"abstract":"<div><div>Renewable energy is rapidly being employed in power networks to meet energy demands, changing the traditional power distribution system into a microgrid (MG)-based system. Additionally, nonlinear loads in the MG system have a tendency to produce undesirable power quality (PQ) problems that need to be properly addressed. In the present work, the MG system is designed using solar PV, wind energy, and fuel cell-based distributed generations, and the PQ concerns of the MG system are addressed in the presence of a combined control technique-based shunt active power filter (SAPF). The combined control technique used for the generation of compensating current of SAPF consists of a negative feedback phase locked loop (NFPLL) based modified synchronous reference frame (MSRF) technique for improving the synchronization performance of SAPF, fuzzy inverted error deviation (FIED) based dc-link voltage controller and adaptive fuzzy hysteresis current controller (AFHCC) based switching pulse generation. The conventional MSRF method, HCC methodology, and fuzzy logic controller (FLC) approach are used by the majority of SAPFs to generate the compensating current for SAPF, but these methods do not completely eliminate harmonics. Hence, in this work, a FIED based control approach is used to improve the performance of SAPF by controlling the <span><math><msub><mrow><mi>V</mi></mrow><mrow><mi>D</mi><mi>C</mi></mrow></msub></math></span>under load changing condition. Apart from FIED technique, NFPLL based MSRF technique is used for quickly and accurately extracts the reference signal during load perturbations and AFHCC scheme is used for switching pulse generation. The suggested combined control strategy (NFPLL-MSRF-FIED-AFHCC) is first evaluated on the MATLAB/Simulink environment and then validated on the OPAL-RT 4510 real-time digital simulator platform. The simulation and real-time outcomes show that the proposed technique works effectively in different scenarios.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"46 ","pages":"Article 101103"},"PeriodicalIF":3.8,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143511000","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}