Journal of Parallel and Distributed Computing最新文献

{"title":"Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues)","authors":"","doi":"10.1016/S0743-7315(24)00182-5","DOIUrl":"10.1016/S0743-7315(24)00182-5","url":null,"abstract":"","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"196 ","pages":"Article 105018"},"PeriodicalIF":3.4,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142745923","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":"Content delivery network solutions for the CMS experiment: The evolution towards HL-LHC","authors":"Carlos Perez Dengra ,&nbsp;Josep Flix ,&nbsp;Anna Sikora ,&nbsp;the CMS Collaboration","doi":"10.1016/j.jpdc.2024.105014","DOIUrl":"10.1016/j.jpdc.2024.105014","url":null,"abstract":"<div><div>The Large Hadron Collider at CERN in Geneva is poised for a transformative upgrade, preparing to enhance both its accelerator and particle detectors. This strategic initiative is driven by the tenfold increase in proton-proton collisions anticipated for the forthcoming high-luminosity phase scheduled to start by 2029. The vital role played by the underlying computational infrastructure, the World-Wide LHC Computing Grid, in processing the data generated during these collisions underlines the need for its expansion and adaptation to meet the demands of the new accelerator phase. The provision of these computational resources by the worldwide community remains essential, all within a constant budgetary framework. While technological advancements offer some relief for the expected increase, numerous research and development projects are underway. Their aim is to bring future resources to manageable levels and provide cost-effective solutions to effectively handle the expanding volume of generated data. In the quest for optimized data access and resource utilization, the LHC community is actively investigating Content Delivery Network (CDN) techniques. These techniques serve as a mechanism for the cost-effective deployment of lightweight storage systems that support both, traditional and opportunistic compute resources. Furthermore, they aim to enhance the performance of executing tasks by facilitating the efficient reading of input data via caching content near the end user. A comprehensive study is presented to assess the benefits of implementing data cache solutions for the Compact Muon Solenoid (CMS) experiment. This in-depth examination serves as a use-case study specifically conducted for the Spanish compute facilities, playing a crucial role in supporting CMS activities. Data access patterns and popularity studies suggest that user analysis tasks benefit the most from CDN techniques. Consequently, a data cache has been introduced in the region to acquire a deeper understanding of these effects. In this paper, the details of the implementation of a data cache system in the PIC Tier-1 compute facility are presented. It includes insights into the developed monitoring tools and discusses the positive impact on CPU usage for analysis tasks executed in the region. The study is augmented by simulations of data caches, with the objective of discerning the most optimal requirements in both size and network connectivity for a data cache serving the Spanish region. Additionally, the study delves into the cost benefits associated with deploying such a solution in a production environment. Furthermore, it investigates the potential impact of incorporating this solution into other regions of the CMS computing infrastructure.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"197 ","pages":"Article 105014"},"PeriodicalIF":3.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142722613","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":"A large-scale study of the impact of node behavior on loosely coupled data dissemination: The case of the distributed Arctic observatory","authors":"Loïc Guégan,&nbsp;Issam Raïs,&nbsp;Otto Anshus","doi":"10.1016/j.jpdc.2024.105013","DOIUrl":"10.1016/j.jpdc.2024.105013","url":null,"abstract":"<div><div>A Cyber-Physical System (CPS) deployed in remote and resource-constrained environments faces multiple challenges. It has, no or limited: network coverage, possibility of energy replenishment, physical access by humans.</div><div>Cyber-physical nodes deployed to observe and interact with the Arctic tundra face these challenges. They are subject to environmental factors such as avalanches, low temperatures, snow, ice, water and wild animals. Without energy supply infrastructures and humans available, nodes must achieve long operational lifetime from a single battery charge. They must be extremely energy-efficient. To reduce energy costs and increase their energy efficiency, cyber-physical nodes sleep most of the time, and avoid to communicate when they are unreachable.</div><div>But, a CPS needs to disseminate data between the nodes for multiple purposes including data reporting to a back-end service, resilient operations, safe-keeping of observational data, and propagating nodes updates. Loosely-coupled data dissemination policies offer this possibility <span><span>[1]</span></span>. Although, investigations should be made on their applicability to large-scale CPS.</div><div>In this paper, we evaluate and discuss the efficiency in energy, time and number of successful delivery of four data dissemination policies proposed in <span><span>[1]</span></span>. This evaluation is based on flow-level simulations. We study small and large-scale CPS, and evaluate the effects of the number of nodes and the size of the disseminated data on the nodes energy consumption and the dissemination's delivery success. To mitigate negative effects raised on large-scale CPS and large disseminated data sizes, different strategies are proposed and evaluated. We show that energy saving strategies do not always imply energy efficiency, and better data dissemination often comes at a cost. This last result highlights the importance of simulation prior to real CPS deployments in constrained environments.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"197 ","pages":"Article 105013"},"PeriodicalIF":3.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142748597","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":"GPU tabu search: A study on using GPU to solve massive instances of the maximum diversity problem","authors":"Bruno Nogueira ,&nbsp;William Rosendo ,&nbsp;Eduardo Tavares ,&nbsp;Ermeson Andrade","doi":"10.1016/j.jpdc.2024.105012","DOIUrl":"10.1016/j.jpdc.2024.105012","url":null,"abstract":"<div><div>The maximum diversity problem (MDP), a widely studied combinatorial optimization problem due to its broad applications, has seen numerous heuristic methods proposed. However, none of these approaches have addressed the challenges posed by massive instances. Currently, state-of-the-art heuristics are not well-suited for massive instances due to two primary reasons. Firstly, they rely on a matrix-based representation, which proves highly inefficient for sparse instances commonly encountered in massive scenarios. Secondly, as the problem size increases, their local search operators experience a slowdown. This work introduces a GPU-based tabu search algorithm designed to tackle such massive instances. To address the limitations of the state-of-the-art heuristics, our GPU tabu search employs more efficient data structures for sparse instances and leverages GPU parallel capabilities to expedite the local search process. We tested our approach on established small and medium instances, ranging from 2,000 to 5,000 vertices, as well as massive instances with up to 45,000 vertices. In these tests, our approach was compared with a state-of-the-art algorithm. Experimental results demonstrate an up to 30x speedup with of our proposal and its effectiveness on massive instances.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"197 ","pages":"Article 105012"},"PeriodicalIF":3.4,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142748595","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 efficient conference key agreement protocol suited for resource constrained devices","authors":"Manmohan Pundir ,&nbsp;Abhimanyu Kumar","doi":"10.1016/j.jpdc.2024.105011","DOIUrl":"10.1016/j.jpdc.2024.105011","url":null,"abstract":"<div><div>Conference key agreement (CKA) is essential for securing communication in group-oriented scenarios like multi-party messaging and collaborative environments. While elliptic curve cryptography (ECC) offers efficiency and strong security, ECC-based CKA protocols often rely on expensive pairings, making them computationally impractical for deployment over the resource limited devices. This paper introduces a novel CKA approach using ECC without requiring pairing computations, thus addressing scalability and efficiency challenges. The proposed protocol employs scalar point multiplications over a prime field elliptic curve group, enabling secure and efficient CKA operations with reduced computational overhead. Compared to existing ECC-based key agreement protocols, it minimizes user-level computation and enhances performance in computational efficiency, communication overhead, and security strength. Particularly suitable for resource-constrained environments like IoT and edge computing, where computational resources are limited yet secure group communication is crucial.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"196 ","pages":"Article 105011"},"PeriodicalIF":3.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703137","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":"Enabling semi-supervised learning in intrusion detection systems","authors":"Panagis Sarantos ,&nbsp;John Violos ,&nbsp;Aris Leivadeas","doi":"10.1016/j.jpdc.2024.105010","DOIUrl":"10.1016/j.jpdc.2024.105010","url":null,"abstract":"<div><div>Intrusion Detection systems (IDS) are alerting cybersecurity tools that analyze network traffic in order to identify suspicious activity and known threats. State of the art IDS rely on supervised machine learning models which are trained to categorize the network flow with a historical labeled dataset. Nonetheless, next-generation networks are characterized as heterogeneous and dynamic. The heterogeneity can make every network environment to be significantly different and the dynamicity means that new threats are constantly emerging. These two factors raise the research question if a supervised machine learning based IDS can work efficiently in a network environment different from the one that generated its labeled training data. In this paper, we first give an answer to this research question and next try to propose a semi-supervised learning approach that can be generalized sufficiently in a different network environment using unlabeled data, taking into consideration that unlabeled data are much easier and cheap to be collected compared to labeled ones. In order to have a proof of concept we made experiments with two labeled datasets CIC-IDS2017, CIC-IDS2018 which are publicly available and one unlabeled dataset PS-Azure2023 which we constructed for this work and make it also publicly available. The results confirm our assumption and the applicability of the semi-supervised learning paradigm for the design of IDS.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"196 ","pages":"Article 105010"},"PeriodicalIF":3.4,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142652811","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":"Fault-tolerance in biswapped multiprocessor interconnection networks","authors":"Basem Assiri ,&nbsp;Muhammad Faisal Nadeem ,&nbsp;Waqar Ali ,&nbsp;Ali Ahmad","doi":"10.1016/j.jpdc.2024.105009","DOIUrl":"10.1016/j.jpdc.2024.105009","url":null,"abstract":"<div><div>Interconnection networks play a vital role in connecting many sets of processor memories, known as processing vertices. Recently, multiprocessor interconnection networks have obtained much attention due to their cost-effectiveness and wide applications in parallel multi-processor systems connecting processors and memory modules. A locating set in a computer network is to select certain nodes, called the locating set, whose positions determine the positions of all other nodes in the network. The locating number is defined as the minimum size of the locating set needed to identify all network vertices. Since, if any single node fails within the locating set, that set is no longer able to identify all the nodes within the network, if the remaining nodes in the locating set can still locate all other network nodes, then it is termed a fault-tolerant locating set. The fault tolerance becomes highly essential in multiprocessor networks, wherein every processor is subject to an absolute failure, to guarantee the system is at full capacity in case one or more components fail. In this study, we determine the fault-tolerant locating number of biswapped networks by considering different classes of networks as base clusters.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"196 ","pages":"Article 105009"},"PeriodicalIF":3.4,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592959","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":"Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues)","authors":"","doi":"10.1016/S0743-7315(24)00167-9","DOIUrl":"10.1016/S0743-7315(24)00167-9","url":null,"abstract":"","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"195 ","pages":"Article 105003"},"PeriodicalIF":3.4,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572923","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":"Design and experimental evaluation of algorithms for optimizing the throughput of dispersed computing","authors":"Xiangchen Zhao ,&nbsp;Diyi Hu,&nbsp;Bhaskar Krishnamachari","doi":"10.1016/j.jpdc.2024.104999","DOIUrl":"10.1016/j.jpdc.2024.104999","url":null,"abstract":"<div><div>We introduce three optimized scheduling algorithms for dispersed computing and present JupiterTP, a real-world system built on k8s and the prior Jupiter system, enabling end-to-end computation on distributed clusters. Distinguishing itself from traditional throughput optimization approaches that focus on theory and simulations, our work is the first implementation of such an end-to-end system capable of handling arbitrary DAGs across diverse computing networks, including public clouds, IoT systems, and edge networks. Beyond mere scheduling, JupiterTP integrates profilers, execution, and orchestration engines, offering unified interfaces for additional scheduling algorithm integrations. The system's performance is tested on real clusters and real applications, compared to prior work that relied on simulations alone. We make JupiterTP available to the community as open-source software at <span><span>https://github.com/ANRGUSC/JupiterTP</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"196 ","pages":"Article 104999"},"PeriodicalIF":3.4,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578882","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":"Hands-on parallel & distributed computing with Raspberry Pi devices and clusters","authors":"Elizabeth Shoop ,&nbsp;Suzanne J. Matthews ,&nbsp;Richard Brown ,&nbsp;Joel C. Adams","doi":"10.1016/j.jpdc.2024.104996","DOIUrl":"10.1016/j.jpdc.2024.104996","url":null,"abstract":"<div><div>Parallel and distributed computing (PDC) concepts are now required topics for accredited undergraduate computer science programs. However, introducing PDC into the CS curriculum is challenging for several reasons, including an instructor's lack of PDC knowledge and difficulties in accessing PDC hardware. This paper addresses both of these challenges by presenting free, interactive, web-based PDC teaching modules using inexpensive Raspberry Pi single board computers (SBCs). Our materials include a free disk image that makes it possible for instructors to build Raspberry Pi clusters in minutes and use our software in a variety of curricular contexts. Our multi-year assessment of these materials on students and faculty members indicates that: (i) our materials increased students' confidence regarding important PDC concepts and motivated them to study PDC further; and (ii) our materials increased faculty members' confidence and preparedness in teaching key PDC concepts at their own institutions.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"196 ","pages":"Article 104996"},"PeriodicalIF":3.4,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578881","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}