Future Generation Computer Systems-The International Journal of Escience最新文献

{"title":"A scalable and modular open-source stack for computing continuum digital twins","authors":"Nikos Filinis,&nbsp;Dimitrios Spatharakis,&nbsp;Ioannis Dimolitsas,&nbsp;Eleni Fotopoulou,&nbsp;Constantinos Vassilakis,&nbsp;Anastasios Zafeiropoulos,&nbsp;Symeon Papavassiliou","doi":"10.1016/j.future.2026.108411","DOIUrl":"10.1016/j.future.2026.108411","url":null,"abstract":"<div><div>The exponential rise of intelligent Internet of Things (IoT) devices and the development of Cyber-Physical Systems (CPS) pose new challenges and requirements for modern applications. These include the need for seamless interconnectivity and interoperable interaction between various physical and virtual elements. The enrichment and transformation of IoT technologies to support such interactions is undergoing, considering the need for convergence with edge and cloud computing technologies and the management of IoT applications across resources in the computing continuum. This broader sense of connectivity is tightly connected with the development of Digital Twins (DT), which take advantage of the development of virtual counterparts of IoT devices and CPS. Novel architectural approaches are required to manage complex DTs’ topologies, collectively forming a Digital Twin Network (DTN) that acts as a middleware to provide advanced communication, efficient orchestration, and autonomous decision-making capabilities. This manuscript presents an architectural approach and a relevant open-source software stack implementation -called VOStack- for developing DTs. VOStack is open and modular by design, while it tackles IoT interoperability and convergence challenges with edge and cloud computing technologies. VOStack is thoroughly evaluated under various deployment schemas, virtualization techniques, and based on the provision of an IoT application in the context of a smart city scenario, demonstrating efficient utilization of resources and high efficiency of Machine Learning (ML)-driven orchestration mechanisms.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"180 ","pages":"Article 108411"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Long integer NTT execution on UPMEM-PIM for 128-bit secure fully homomorphic encryption","authors":"Tathagata Barik ,&nbsp;Priyam Mehta ,&nbsp;Zaira Pindado ,&nbsp;Harshita Gupta ,&nbsp;Mayank Kabra ,&nbsp;Mohammad Sadrosadati ,&nbsp;Onur Mutlu ,&nbsp;Antonio J. Peña","doi":"10.1016/j.future.2026.108386","DOIUrl":"10.1016/j.future.2026.108386","url":null,"abstract":"<div><div>Fully Homomorphic Encryption (FHE) enables secure computations on encrypted data, hence becoming an appealing technology for privacy-preserving data processing. A core kernel in many cryptographic and FHE workloads is the Number Theoretic Transform (NTT). While NTT involves frequent non-contiguous data accesses, limiting overall performance, processing–in–memory (PIM) has the potential to address this limitation. PIM, performing computations close to the data, reduces the need for extensive data transfers between memory and compute units. However, the performance of current PIM solutions is limited by inherent factors related to the integration of processing capabilities within memory modules.</div><div>In this article we analyze the performance trade-offs of NTT kernel designs along with optimized modular multiplication algorithms on PIM systems based on UPMEM hardware. Our results include significant performance improvements of up to 4.3 ×  over baseline approaches on UPMEM-PIM, while preserving, for the first time in the literature, 128-bit security at high precision.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"180 ","pages":"Article 108386"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146014880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"AWTO: A latency-optimized task offloading scheme for LLM-driven agentic workflows on heterogeneous edge","authors":"Peng Yu ,&nbsp;Bo Liu ,&nbsp;Shaomin Tang ,&nbsp;Dongdong Li ,&nbsp;Weiwei Lin","doi":"10.1016/j.future.2026.108415","DOIUrl":"10.1016/j.future.2026.108415","url":null,"abstract":"<div><div>Agentic workflows, driven by Large Language Models (LLMs), present new opportunities for realizing advanced edge intelligence in data-sensitive domains such as finance and healthcare. However, deploying these workflows in private, resource-constrained edge environments poses unique challenges. Unlike public cloud services, these scenarios require computations to be performed locally on dedicated edge clusters to meet strict data compliance and privacy regulations. This restriction, coupled with the limited memory capacity of edge devices relative to the massive size of LLMs, makes dynamic memory management and model loading critical factors. Furthermore, the autoregressive nature of LLMs introduces high dynamic uncertainty in inference latency and memory footprint, fundamentally contradicting the static information assumptions of traditional scheduling methods. To address these challenges, we propose AWTO, a Deep Reinforcement Learning (DRL) offloading scheme designed to minimize the makespan of agentic workflows in isolated edge environments. The core of AWTO is a task-by-task dynamic decision-making mechanism that explicitly handles on-demand model loading and memory contention. We formulate this problem as a Markov Decision Process (MDP) and employ a Proximal Policy Optimization (PPO)-based algorithm. A novel three-module LSTM encoder is designed to capture task dependencies, device heterogeneity, and real-time memory states. Experimental results in heterogeneous environments demonstrate that AWTO reduces the average makespan by 16.99% to 36.36% compared to heuristic baselines. Furthermore, it achieves a 14.00% gain over DRL methods, validating its adaptability to dynamic memory constraints and cache-aware scheduling.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"180 ","pages":"Article 108415"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Maximizing the benefits of in-network aggregation with joint job placement and routing control","authors":"Shouxi Luo ,&nbsp;Xiaoyu Yu ,&nbsp;Huanlai Xing ,&nbsp;Ke Li ,&nbsp;Bo Peng","doi":"10.1016/j.future.2026.108416","DOIUrl":"10.1016/j.future.2026.108416","url":null,"abstract":"<div><div>As recent studies have shown, in-network aggregation (INA) is excellent in relieving the communication bottleneck faced by the gradient uploading of parameter server (PS) based data-parallel training. In such systems, INA-aware routing optimization is crucial to release the power of deployed aggregators to improve the throughput, since correlated flows can be aggregated into a single one only if they go through the same aggregator. However, only optimizing routing is not enough, since the placement of the PS and training workers (i.e., jobs) determines where the traffic enters and leaves the network, thus limiting the space that routing optimizations can explore.</div><div>In this article, we examine the problem of how to maximize the benefits of deployed aggregators by jointly optimizing job placement and routing paths. We not only find that such a joint scheduling problem can be converted to conducting INA-aware routing optimization with resource constraints on an augmented topology, thus abundant existing INA-aware routing optimization designs might help, but also propose ARO+, a case study of achieving theory-guided optimal (or near-optimal) joint optimization for Clos-based clusters, by extending the state-of-the-art INA-aware routing optimization proposal of ARO. To reduce the solving time, ARO+ employs a novel model simplification scheme by taking advantage of the problem structure. Performance studies show that the joint optimization of ARO+ does markedly increase the throughput of gradient uploading, and our model simplification could accelerate its solving up to an order of magnitude.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"180 ","pages":"Article 108416"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Dynamic task transmission control and improved greedy strategy for vehicular edge computing","authors":"Sheng Cai ,&nbsp;Jianmao Xiao ,&nbsp;Yuanlong Cao ,&nbsp;Qinghang Gao ,&nbsp;Zhiyong Feng ,&nbsp;Shuiguang Deng","doi":"10.1016/j.future.2026.108369","DOIUrl":"10.1016/j.future.2026.108369","url":null,"abstract":"<div><div>With the rapid development of on-board applications, edge computing is now widely used in Internet of vehicles, enabling vehicles with limited resources to offload tasks to the edge for execution via computation offloading. However, current research methods are often hard to adapt to dynamic scenarios due to model training costs and vehicle mobility and also lack consideration for load balancing in high-load situations. To improve the quality of experience of users and balance the load of edge servers simultaneously, this paper proposes an improved greedy strategy method for computation offloading. First, to mitigate potential communication overload during peak hours, this study analyzes the relationship between transmission scheduling and execution queues, and investigates a dynamic task transmission control method. Second, explicit modeling of round-trip communication reliability in mobile environments is provided to extend the vehicle interconnection model. Subsequently, by analyzing the structure of the optimal solution for total latency optimization, the priority of offloaded tasks is classified. A multi-perspective analysis of task offloading is then conducted, and a greedy strategy is adopted to ensure both the quality of user experience and load balancing at the edge. Finally, comparative experiments on real-world datasets validate the efficiency of the proposed method and model under high-mobility and high-load experimental scenarios.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"180 ","pages":"Article 108369"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145947955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Towards real-time sensor-based human activity recognition: a re-parameterized multidimensional feature communication fusion framework","authors":"Hao Zheng,&nbsp;Hongji Xu,&nbsp;Yupeng Duan,&nbsp;Yonghui Yu,&nbsp;Fei Gao,&nbsp;Yu Qiao","doi":"10.1016/j.future.2025.108364","DOIUrl":"10.1016/j.future.2025.108364","url":null,"abstract":"<div><div>Sensor-based human activity recognition (HAR) has become a research hotspot due to its far-reaching applications including health monitoring, smart home, and sports tracking. Deep learning, particularly convolutional neural networks (CNNs) with automatic feature extraction capabilities, has demonstrated outstanding recognition accuracy. However, some current deep learning-based HAR methods require substantial parameters and computation resources to pursue high accuracy, resulting in expensive resource and time costs. To handle the challenge, we propose a lightweight one-dimensional re-parameterization multidimensional feature communication fusion (ORepMFCF) framework for HAR, achieving an impressive trade-off between recognition accuracy and speed. The one-dimensional re-parameterization VGG (ORV) block is developed to decouple the trained multi-branch structure into a single path to improve the inference speed without compromising accuracy. The time-dependent information channel shuffle (TDICS) module is proposed to strengthen feature extraction and communication ability. The channel attention feature fusion (CAFF) module is presented to improve multidimensional feature fusion. The ORepMFCF achieves the accuracy of 98.60% on the WISDM, 89.38% on the UniMiB-SHAR, 86.43% on the OPPORTUNITY, and 96.26% on the MobiACT, respectively. The ORepMFCF requires fewer parameters and incurs less computational overhead with better recognition performance, which significantly surpasses the recent state-of-the-art HAR networks. The real-world inference time of the ORepMFCF is evaluated on a Raspberry Pi and a smartphone, demonstrating its effectiveness and practicality.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"180 ","pages":"Article 108364"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145893751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 coclustering and computational intelligence-based approach for internet-of-things services composition","authors":"Nawel Atmani ,&nbsp;Mohamed Essaid Khanouche ,&nbsp;Ahror Belaid ,&nbsp;Abdelghani Chibani","doi":"10.1016/j.future.2026.108381","DOIUrl":"10.1016/j.future.2026.108381","url":null,"abstract":"<div><div>The Internet of Things (IoT) paradigm aims at interconnecting heterogeneous devices, called <em>smart objects</em> and seamlessly offering a multitude of services tailored to the user requirements. With the extremely rapid growth of the number of connected objects, the IoT services composition process becomes an NP-hard challenge due to the very high increase of the number of services offering similar functionalities but that may differ in their Quality of Service (QoS) parameter values. Various approaches have been proposed in the literature to obtain compositions with suboptimal QoS in a reasonable computation time. However, when the number of services and QoS parameters increases, the performance of these approaches is limited in terms of the composition time and/or the QoS utility of the composition. To address these limitations, a coclustering-based approach for QoS-constrained services composition (CoQSC) is proposed to reduce the composition space and improve the composition time as well as the composition utility. Unlike existing services composition algorithms where the composition space is reduced only in terms of the number of candidate services, the CoQSC approach exploits a coclustering method to reduce both the number of candidate services and the number of QoS parameters to be considered in the composition process. This reduction allows the composition process to find suboptimal compositions in a reduced computation time using eight among the most representative and recent computational intelligence (CI) techniques in the literature separately. The formulation of the CoQSC approach is complemented by a complexity analysis. Simulation scenarios show that the CoQSC approach significantly improves the QoS utility of composition and substantially decreases the composition time compared to recent and representative state-of-the-art composition approaches, making it suitable for large-scale IoT service environments.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"180 ","pages":"Article 108381"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146000901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Quantum-resistant blockchain architecture for secure vehicular networks: A ML-KEM-enabled approach with PoA and PoP consensus","authors":"Muhammad Asim ,&nbsp;Wu Junsheng ,&nbsp;Li Weigang ,&nbsp;Lin Zhijun ,&nbsp;Zhang Peng ,&nbsp;He Hao ,&nbsp;Wei Dong ,&nbsp;Ghulam Mohi-ud-Din","doi":"10.1016/j.future.2026.108391","DOIUrl":"10.1016/j.future.2026.108391","url":null,"abstract":"<div><div>The increasing interconnectivity within modern transportation ecosystems, a cornerstone of Intelligent Transportation Systems (ITS), creates critical vulnerabilities, demanding stronger security measures to prevent unauthorized access to vehicles and private data. Existing blockchain implementations for Vehicular Ad Hoc Networks (VANETs) are fundamentally flawed, exhibiting inefficiency with traditional consensus mechanisms, vulnerability to quantum attacks, or often both. To overcome these critical limitations, this study introduces a novel Quantum-Resistant Blockchain Architecture. The core objectives are to achieve highly efficient vehicular data storage, ensure robust confidentiality through post-quantum cryptography, and automate secure transactions. The proposed methodology employs a dual-blockchain structure: a Registration Blockchain (RBC) using Proof-of-Authority (PoA) for secure identity management, and a Message Blockchain (MBC) using Proof-of-Position (PoP) for low-latency message dissemination. A key innovation is the integration of smart contracts with the NIST-approved Module Lattice-Based Key Encapsulation Mechanism (ML-KEM) to automate and secure all processes. The framework is rigorously evaluated using a realistic 5G-VANET Multi-access Edge Computing(MEC) dataset, which includes key parameters like vehicle ID, speed, and location. The results are compelling, demonstrating an Average Block Processing Time of 0.0326 s and a Transactional Throughput of 30.64 TPS, significantly outperforming RSA and AES benchmarks. This research’s primary contribution is a comprehensive framework that substantially improves data security and scalability while future-proofing VANETs against the imminent and evolving threat of quantum computing.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"180 ","pages":"Article 108391"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 message-driven system for processing highly skewed graphs","authors":"Bibrak Qamar Chandio,&nbsp;Maciej Brodowicz,&nbsp;Thomas Sterling","doi":"10.1016/j.future.2026.108394","DOIUrl":"10.1016/j.future.2026.108394","url":null,"abstract":"<div><div>The paper provides a unified co-design of: 1) a non-Von Neumann architecture for fine-grain irregular memory computations, 2) a programming and execution model that allows spawning tasks from within the graph vertex data at runtime, 3) language constructs for <em>actions</em> that send work to where the data resides, combining parallel expressiveness of local control objects (LCOs) to implement asynchronous graph processing primitives, 4) and an innovative vertex-centric data-structure, using the concept of Rhizomes, that parallelizes both the out and in-degree load of vertex objects across many cores and yet provides a single programming abstraction to the vertex objects. The data structure hierarchically parallelizes the out-degree load of vertices and the in-degree load laterally. The rhizomes internally communicate and remain consistent, using event-driven synchronization mechanisms, to provide a unified and correct view of the vertex.</div><div>Simulated experimental results show performance gains for BFS, SSSP, and Page Rank on large chip sizes for the tested input graph datasets containing highly skewed degree distributions. The improvements come from the ability to express and create fine-grain dynamic computing task in the form of <em>actions</em>, language constructs that aid the compiler to generate code that the runtime system uses to optimally schedule tasks, and the data structure that shares both in and out-degree compute workload among memory-processing elements.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"180 ","pages":"Article 108394"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"LOTL-hunter: Detecting multi-stage living-off-the-land attacks in cyber-physical systems using decision fusion techniques with digital twins","authors":"Carol Lo ,&nbsp;Thu Yein Win ,&nbsp;Zeinab Rezaeifar ,&nbsp;Zaheer Khan ,&nbsp;Phil Legg","doi":"10.1016/j.future.2026.108382","DOIUrl":"10.1016/j.future.2026.108382","url":null,"abstract":"<div><div>The integration of smart sensors and actuators in industrial environments has expanded the cyber-physical attack surface, making it increasingly difficult to distinguish anomalies caused by cyberattacks from those due to mechanical or electrical faults. This challenge is exacerbated by stealthy, multi-stage attacks leveraging Living off the Land (LOTL) techniques, which often evade conventional anomaly detection or intrusion detection systems (IDS).</div><div>This study presents a Digital Twin-based testbed for safe, repeatable simulation of multi-stage cyber-physical attacks targeting Cyber-Physical Systems (CPS) and Industrial Control Systems (ICS). We propose a two-level decision fusion method that aggregates and aligns anomalies across network, process, and host domains in synchronized 1-minute intervals. The first-level fusion improves OT-layer detection by applying confidence-aware decision logic to outputs combined from (a) a supervised deep learning model (LSTM-FCN) for process anomalies, (b) an unsupervised model (Isolation Forest) for OPC UA network anomalies, and (c) process alarm signals. The second-level fusion integrates these results with host-based anomalies, computed through point-based scoring of Wazuh alerts, to provide comprehensive IT/OT situational awareness. Experimental results demonstrate improved detection of stealthy, multi-stage APT attack behaviours. Additionally, Large Language Models (LLM) provide summarization of the integrated IT/OT anomaly logs into human-readable insights, enhancing interpretability and supporting cyber threat hunting.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"180 ","pages":"Article 108382"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146014879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}