Article
Computer Science, Information Systems
Andrei Palade, Siobhan Clarke
Summary: This article proposes a collaborative approach to engage multiple communities of agents for provisioning QoS-optimal service compositions in mobile environments. New compositions can emerge from local decisions and interactions with agents from diverse communities, improving the diversity and optimality of solutions.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Computer Science, Information Systems
Satish Kumar, Tao Chen, Rami Bahsoon, Rajkumar Buyya
Summary: In this article, we propose DebtCom, a framework that determines whether to trigger recomposition based on the technical debt metaphor and time-series prediction of workload. Our core idea is that recomposition can be unnecessary if the under-/over-utilization only cause temporarily negative effects, and the current composition plan, although carries debt, can generate greater benefit in the long-term. The results confirm that, in contrast to the state-of-the-art, DebtCom achieves better utility while having lower cost and number of recompositions, rendering each composition plan more sustainable.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Information Systems
Deng Zhao, Zhangbing Zhou, Patrick C. K. Hung, Shuiguang Deng, Xiao Xue, Walid Gaaloul
Summary: This article proposes an adaptive composition mechanism leveraging Computation Tree Logic (CTL) specifications to ensure the compatibility of compositions with QoS variations. The composition is formalized as a temporal task, converted to CTL formulae with required functionalities and composite structures, and functional compatibility is interpreted through CTL semantics. A QoS Dependency Graph (QoSDG) is constructed to capture QoS variations, enabling adaptive composition with dynamic QoS satisfactions.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Theory & Methods
Linyuan Liu, Haibin Zhu, Shenglei Chen, Zhiqiu Huang
Summary: This paper discusses the privacy issues in cloud computing and proposes a privacy regulation aware cloud service composition method, the PSSM method, which uses a pre-processed KM algorithm to solve the problem, and validates the effectiveness and efficiency of the method through simulation experiments.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Interdisciplinary Applications
Yen-Ching Chuang, Yee Ming Chen
Summary: Product service systems (PSSs) are transforming the value creation in cloud manufacturing (CMfg) by providing integrated solutions. Cyber-physical systems (CPSs) play a central role in CMfg by integrating cyberspace and dynamic manufacturing physical spaces. Selecting the optimal service combination is crucial in CMfg, and symbiotic simulations are proposed to bridge the gap between cyberspace and physical space.
COMPUTERS IN INDUSTRY
(2022)
Article
Computer Science, Information Systems
Yuben Qu, Dongyu Lu, Haipeng Dai, Haisheng Tan, Shaojie Tang, Fan Wu, Chao Dong
Summary: This paper studies the problem of resilient service provisioning for edge computing, aiming to determine a service placement strategy to maximize overall utility in the presence of uncertain service failures. Two novel solutions are proposed for the general and homogeneous case, respectively, achieving constant approximation ratio within polynomial time and better approximation ratio than previous methods. Extensive simulations and field experiments validate the effectiveness of the proposed algorithms.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Faruk Hasic, Johannes De Smedt, Seppe vanden Broucke, Estefania Serral
Summary: This article presents a method for separating decision modeling from process modeling by using a service-oriented architecture that treats decisions as automated and externalized services. The Decision as a Service (DaaS) mechanism is explained through a formalization of Decision Model and Notation (DMN) constructs and relevant layer elements. The article also evaluates DaaS based on the fundamental characteristics of the service-oriented architecture paradigm and discusses the benefits of the DaaS design on process-decision modeling and mining.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Mathematics
Linyuan Liu, Haibin Zhu, Shenglei Chen
Summary: This paper explores the problem of balancing privacy risk and benefit in multiprovision cloud service composition (MPCSC) and proposes an improved algorithm solution. A series of simulation experiments demonstrate that the proposed approach is both efficient and effective.
Article
Automation & Control Systems
Yankai Wang, Song Gao, Shilong Wang, Roger Zimmermann
Summary: This article introduces a real-life cloud manufacturing paradigm called fog manufacturing (FMfg) based on digital twin models, and proposes a multi-task service composition model. To solve this problem, the article develops an adaptive multi-objective whale optimization algorithm (AMOWOA) and verifies its superiority through numerical experiments and application cases.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Ning Zhao, Peng Shi, Wen Xing, Chee Peng Lim
Summary: This article addresses the event-triggered tracking control and filtering problem for Takagi-Sugeno fuzzy-approximation-based discrete-time nonlinear networked systems subject to the effect of denial-of-service attacks. Two novel resilient adaptive event-triggered mechanisms and an estimator are proposed to overcome the problem of unavailable system mode signal during the trigger interval and improve the stability of the system.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Business
Marika Taishoff, Hans Muehlbacher, Hannele Kauppinen-Ra
Summary: Research shows that the establishment and sustainable development of luxury service ecosystems require joint leadership of private and public actors, a enduring vision, and stable macro-level institutional arrangements. These factors contribute to the adaptation and transformation of service ecosystems in response to ongoing and disruptive socio-historical changes.
JOURNAL OF BUSINESS RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Xuhuan Xie, Songlin Hu, Yonggui Liu, Qinxue Li
Summary: This article proposes a resilient adaptive event-triggered H-infinity fuzzy filtering scheme for interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy-model-based cyber-physical systems (CPSs) under stochastic sampling and energy-constrained, nonperiodic denial-of-service (DoS) attacks. The proposed scheme uses a resilient switched IT2 T-S fuzzy filter and applies a codesign algorithm for the fuzzy filter and resilient adaptive event-triggered scheme (AETS). The effectiveness of the proposed strategy is demonstrated through numerical examples.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Mathematics, Applied
Xin Li, Guoliang Wei, Derui Ding
Summary: This article studies the problem of distributed interval estimation for sensor networks under DoS attacks and AETP. A method utilizing local and neighboring information is proposed to estimate system states effectively, and its effectiveness is demonstrated through simulation.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Computer Science, Information Systems
Parminder Singh, Avinash Kaur, Gagangeet Singh Aujla, Ranbir Singh Batth, Salil Kanhere
Summary: This article introduces the Dew Computing as a Service (DaaS) for intelligent intrusion detection in Edge of Things (EoT) ecosystems. It uses a deep learning-based classifier to design an intelligent alarm filtration mechanism. The experimentation in a simulated environment shows lower response time, improved classification accuracy, and reduced workload of cloud servers compared to edge IDS.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Linan Huang, Quanyan Zhu
Summary: This work identifies and defines a new type of proactive attentional attacks called Informational Denial-of-Service (IDoS) attacks. The researchers develop a Resilient and Adaptive Data-driven alert and Attention Management Strategy (RADAMS) to assist human operators in identifying and addressing real attacks while dismissing feint attacks.
COMPUTERS & SECURITY
(2022)
Article
Computer Science, Information Systems
Sajib Mistry, Sheik Mohammad Mostakim Fattah, Athman Bouguettaya
Summary: The study introduces a novel IaaS composition framework that selects an optimal set of consumer requests based on provider's preferences, and uses temporal conditional preference networks and global preference ranking algorithm for optimization.
ACM TRANSACTIONS ON THE WEB
(2021)
Review
Computer Science, Hardware & Architecture
Athman Bouguettaya, Quan Z. Sheng, Boualem Benatallah, Azadeh Ghari Neiat, Sajib Mistry, Aditya Ghose, Surya Nepal, Lina Yao
COMMUNICATIONS OF THE ACM
(2021)
Article
Computer Science, Information Systems
Sajib Mistry, Lie Qu, Athman Bouguettaya
Summary: This study proposes a novel generic reputation bootstrapping framework for evaluating the reputation of composite services. By considering multiple reputation-related indicators and using a deep learning model, the reputation of component services can be predicted and evaluated.
ACM TRANSACTIONS ON INTERNET TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Sheik Mohammad Mostakim Fattah, Athman Bouguettaya, Sajib Mistry
Summary: A novel framework is proposed to select IaaS providers based on a consumer's long-term performance requirements. The framework utilizes free short-term trials to discover the unknown QoS performance of IaaS providers and employs past trial experiences for long-term performance prediction.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Computer Science, Information Systems
Sajib Mistry, Athman Bouguettaya
Summary: This research proposes a novel framework to bootstrap the reputation of on-demand service compositions. It addresses the limitations of existing methods by considering the topology of the composition and relationships among reputation-related factors. The proposed approach, which uses Conditional Preference Networks (CP-nets), demonstrates its efficiency through experimental results.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Computer Science, Information Systems
Atish Kumar Dipongkor, Md. Saiful Islam, Ishtiaque Hussain, Sira Yongchareon, Sajib Mistry
Summary: Automated bug report assignment is crucial for large-scale software projects. Researchers have proposed machine learning and deep learning-based techniques to improve the performance of these assignments. In this paper, a novel deep learning approach is proposed that utilizes two sets of features from the textual data of reported bugs. Extensive experiments on real-world software projects demonstrate that the proposed approach outperforms previous models and improves automated bug report assignment. All source code is published for future researchers to contribute to this problem.
Proceedings Paper
Computer Science, Interdisciplinary Applications
Babar Shahzaad, Athman Bouguettaya
Summary: This study proposes a novel service-oriented architecture for drone-based multi-package delivery and introduces a graph-based heuristic algorithm for optimizing service selection. Experimental results demonstrate the efficiency and effectiveness of this approach in terms of execution time and delivery time.
2022 IEEE INTERNATIONAL CONFERENCE ON WEB SERVICES (IEEE ICWS 2022)
(2022)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Yuval Berman, Sajib Mistry, Joby Mathew, Aneesh Krishna
Summary: This study proposes a novel network metric and entropy-based live soccer analytic framework (NMELSA) that can identify the opponent team's tactics by observing the events in a live soccer match. It also designs a live game replacement model that recommends substitute players based on the on-field players' live game ratings.
2022 IEEE INTERNATIONAL CONFERENCE ON WEB SERVICES (IEEE ICWS 2022)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Jermaine Janszen, Babar Shahzaad, Balsam Alkouz, Athman Bouguettaya
Summary: Drones are being used in delivery services, and this article demonstrates the use of drones in a skyway network that utilizes the service paradigm. The experiments conducted with Crazyflie drones collected data on drone positions, wind speed, wind direction, and battery consumption. Various flight patterns, including linear, rectangular, and triangular shapes, were tested.
SERVICE-ORIENTED COMPUTING, ICSOC 2021 WORKSHOPS
(2022)
Proceedings Paper
Computer Science, Information Systems
Xijing Liu, Kevin Lam, Balsam Alkouz, Babar Shahzaad, Athman Bouguettaya
Summary: Drone swarms can deliver multiple packages simultaneously by leveraging formation flying to conserve energy and increase flight range. An adaptive formation allows the swarm to adjust to constraints and change formation patterns during flight. Utilizing existing building rooftops and a line-of-sight skyway network in a city ensures safe operation of the swarms. The route planning of the drone swarm in the skyway network is accomplished using a heuristic-based A* algorithm.
2022 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS WORKSHOPS AND OTHER AFFILIATED EVENTS (PERCOM WORKSHOPS)
(2022)
Article
Computer Science, Information Systems
Abdallah Lakhdari, Athman Bouguettaya, Sajib Mistry, Azadeh Ghari Ghari Neiat
Summary: We propose a novel framework for composing crowdsourced wireless energy services in a crowdsourced IoT environment to meet users' energy requirements. We design a new energy service model and propose a composability model that considers the spatio-temporal aspects and usage patterns of IoT devices. We develop a multiple local knapsack-based approach to select an optimal set of energy services and propose a heuristic-based composition approach. Experimental results demonstrate the effectiveness and efficiency of the proposed approach.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Proceedings Paper
Computer Science, Information Systems
Abdallah Lakhdari, Athman Bouguettaya, Sajib Mistry, Azadeh Ghari Ghari Neiat, Basem Suleiman
Summary: The study introduces a novel elastic composition framework for service provision in fluctuating IoT energy settings by utilizing crowdsourced IoT energy, with the concepts of soft and hard deadlines as key criteria, and conducts experiments on real-world datasets to evaluate efficiency.
PROCEEDINGS OF THE 17TH EAI INTERNATIONAL CONFERENCE ON MOBILE AND UBIQUITOUS SYSTEMS: COMPUTING, NETWORKING AND SERVICES (MOBIQUITOUS 2020)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Balsam Alkouz, Babar Shahzaad, Athman Bouguettaya
Summary: The paragraph discusses the major paradigm shift in service delivery due to fast advances in drone technologies and increased customer expectations and competition. It proposes a novel service-oriented approach for ubiquitous package delivery in a drone-operated skyway network, while also covering the benefits, framework, contemporary approaches, open challenges, and future directions of service-based drone deliveries.
2021 IEEE 7TH INTERNATIONAL CONFERENCE ON COLLABORATION AND INTERNET COMPUTING (CIC 2021)
(2021)
Editorial Material
Computer Science, Theory & Methods
Kiho Lim, Christian Esposito, Tian Wang, Chang Choi
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Editorial Material
Computer Science, Theory & Methods
Jesus Carretero, Dagmar Krefting
Summary: Computational methods play a crucial role in bioinformatics and biomedicine, especially in managing large-scale data and simulating complex models. This special issue focuses on security and performance aspects in infrastructure, optimization for popular applications, and the integration of machine learning and data processing platforms to improve the efficiency and accuracy of bioinformatics.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Renhao Lu, Weizhe Zhang, Qiong Li, Hui He, Xiaoxiong Zhong, Hongwei Yang, Desheng Wang, Zenglin Xu, Mamoun Alazab
Summary: Federated Learning allows collaborative training of AI models with local data, and our proposed FedAAM scheme improves convergence speed and training efficiency through an adaptive weight allocation strategy and asynchronous global update rules.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Qiangqiang Jiang, Xu Xin, Libo Yao, Bo Chen
Summary: This paper proposes a multi-objective energy-efficient task scheduling technique (METSM) for edge heterogeneous multiprocessor systems. A mathematical model is established for the task scheduling problem, and a problem-specific algorithm (IMO) is designed for optimizing task scheduling and resource allocation. Experimental results show that the proposed algorithm can achieve optimal Pareto fronts and significantly save time and power consumption.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Editorial Material
Computer Science, Theory & Methods
Weimin Li, Lu Liu, Kevin I. K. Wang, Qun Jin
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Mohammed Riyadh Abdmeziem, Amina Ahmed Nacer, Nawfel Moundji Deroues
Summary: Internet of Things (IoT) devices have become ubiquitous and brought the need for group communications. However, security in group communications is challenging due to the asynchronous nature of IoT devices. This paper introduces an innovative approach using blockchain technology and smart contracts to ensure secure and scalable group communications.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Robert Sajina, Nikola Tankovic, Ivo Ipsic
Summary: This paper presents and evaluates a novel approach that utilizes an encoder-only transformer model to enable collaboration between agents learning two distinct NLP tasks. The evaluation results demonstrate that collaboration among agents, even when working towards separate objectives, can result in mutual benefits.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Hebert Cabane, Kleinner Farias
Summary: Event-driven architecture has been widely adopted in the software industry for its benefits in software modularity and performance. However, there is a lack of empirical evidence to support its impact on performance. This study compares the performance of an event-driven application with a monolithic application and finds that the monolithic architecture consumes fewer computational resources and has better response times.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Haroon Wahab, Irfan Mehmood, Hassan Ugail, Javier Del Ser, Khan Muhammad
Summary: Wireless capsule endoscopy (WCE) is a revolutionary diagnostic method for small bowel pathology. However, the manual analysis of WCE videos is cumbersome and the privacy concerns of WCE data hinder the adoption of AI-based diagnoses. This study proposes a federated learning framework for collaborative learning from multiple data centers, demonstrating improved anomaly classification performance while preserving data privacy.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Maruf Monem, Md Tamjid Hossain, Md. Golam Rabiul Alam, Md. Shirajum Munir, Md. Mahbubur Rahman, Salman A. AlQahtani, Samah Almutlaq, Mohammad Mehedi Hassan
Summary: Bitcoin, the largest cryptocurrency, faces challenges in broader adaption due to long verification times and high transaction fees. To tackle these issues, researchers propose a learning framework that uses machine learning to predict the ideal block size in each block generation cycle. This model significantly improves the block size, transaction fees, and transaction approval rate of Bitcoin, addressing the long wait time and broader adaption problem.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Rafael Duque, Crescencio Bravo, Santos Bringas, Daniel Postigo
Summary: This paper introduces the importance of user interfaces for digital twins and presents a technique called ADD for modeling requirements of Human-DT interaction. A study is conducted to assess the feasibility and utility of ADD in designing user interfaces, using the virtualization of a natural space as a case study.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Xiulin Li, Li Pan, Wei Song, Shijun Liu, Xiangxu Meng
Summary: This article proposes a novel multiclass multi-pool analytical model for optimizing the quality of composite service applications deployed in the cloud. By considering embarrassingly parallel services and using differentiated parallel processing mechanisms, the model provides accurate prediction results and significantly reduces job response time.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Seongwan Park, Woojin Jeong, Yunyoung Lee, Bumho Son, Huisu Jang, Jaewook Lee
Summary: In this paper, a novel MEV detection model called ArbiNet is proposed, which offers a low-cost and accurate solution for MEV detection without requiring knowledge of smart contract code or ABIs.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Sacheendra Talluri, Nikolas Herbst, Cristina Abad, Tiziano De Matteis, Alexandru Iosup
Summary: Serverless computing is increasingly used in data-processing applications. This paper presents ExDe, a framework for systematically exploring the design space of scheduling architectures and mechanisms, to help system designers tackle complexity.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Chao Wang, Hui Xia, Shuo Xu, Hao Chi, Rui Zhang, Chunqiang Hu
Summary: This paper introduces a Federated Learning framework called FedBnR to address the issue of potential data heterogeneity in distributed entities. By breaking up the original task into multiple subtasks and reconstructing the representation using feature extractors, the framework improves the learning performance on heterogeneous datasets.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
