Article
Computer Science, Information Systems
Chinmaya Kumar Dehury, Prasan Kumar Sahoo
Summary: This article introduces a failure-aware semi-centralized VNE algorithm to reduce the impact of resource failures on cloud computing users, and demonstrates the superiority of this algorithm through simulation experiments.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Computer Science, Information Systems
Hong-Yen Lo, Wanjiun Liao
Summary: The study focuses on survivability of virtual data centers and proposes the CALM algorithm to minimize network resource usage and ensure survivability after hardware failures.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2021)
Article
Computer Science, Hardware & Architecture
Yang Yang, Songtao Guo, Guiyan Liu, Lin Yi
Summary: This paper proposes two fine granularity models and multiple efficient embedding algorithms to solve the virtual data center embedding problem. Comparing with existing methods, our algorithms can find sub-optimal solutions in polynomial time and outperform existing methods in terms of acceptance ratio, revenue, and utilization.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2021)
Article
Green & Sustainable Science & Technology
Halimjon Khujamatov, Khaleel Ahmad, Nargiza Usmanova, Jamshid Khoshimov, Mai Alduailij, Mona Alduailij
Summary: The development of Internet technologies has led to the collection and analysis of vast amounts of data, with fog computing offering a flexible and advantageous solution for big data processing.
Article
Computer Science, Information Systems
Long Chen, Xiaoping Li, Yucheng Guo, Ruben Ruiz
Summary: This paper addresses the issue of workflow scheduling with both reserved and on-demand instances in cloud computing, aiming to minimize the total rental cost under deadline constraints through mathematical modeling and optimization algorithms. Experimental results show that the proposed algorithm can achieve considerable cost savings compared to other algorithms.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2021)
Article
Computer Science, Interdisciplinary Applications
Daniel G. Lago, Rodrigo A. C. da Silva, Edmundo R. M. Madeira, Nelson L. S. da Fonseca, Deep Medhi
Summary: The paper addresses the difficulty in validating new solutions in hybrid cloud evaluation and presents SinergyCloud simulator for data center assessment, demonstrating its accuracy and scalability. The simulator features easy-to-use code and fine granularity of abstraction, suitable for handling various cloud scenarios and device consumption simulation.
SIMULATION MODELLING PRACTICE AND THEORY
(2021)
Article
Chemistry, Multidisciplinary
Abdul Saboor, Mohd Fadzil Hassan, Rehan Akbar, Syed Nasir Mehmood Shah, Farrukh Hassan, Saeed Ahmed Magsi, Muhammad Aadil Siddiqui
Summary: Cloud computing is a rapidly growing paradigm with the importance of cloud data centers expanding dramatically. This study proposes a conceptual framework for efficient management of microservices execution in order to reduce response time, energy consumption, and execution costs. The suggested framework was partially evaluated using a simulation environment, demonstrating improved performance and reduced energy consumption and carbon emissions.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Information Systems
A. Poobalan, P. Shanthakumar, M. Robinson Joel
Summary: Cloud data centers play a crucial role in providing services to customers based on demand and pay-per-use strategy. VM consolidation is a key issue in virtualized data centers, as it improves performance and reduces costs. This research proposes an effective strategy that combines optimization-enabled VM scaling and load distribution to address the problem of overloading. The proposed model achieves superior results in terms of load, power, energy consumption, and latency.
Article
Computer Science, Information Systems
Paolo Bellavista, Antonio Corradi, Andy Edmonds, Luca Foschini, Alessandro Zanni, Thomas Michael Bohnert
Summary: This paper presents novel solutions to achieve cost-effective elastic provisioning of telco services over heterogeneous and federated cloud providers, focusing on supporting extreme quality levels demanded by traditional telco infrastructures. Through automation and leveraging industry-mature orchestration technologies and cloud management frameworks, the proposed state migration model and procedure were experimented successfully for 5G services, showing technical feasibility under different load conditions.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2021)
Article
Computer Science, Information Systems
Thomas Weripuo Gyeera, Anthony J. H. Simons, Mike Stannett
Summary: Cloud data centers aim to optimize resource provision and investigate predictive algorithms for proactive monitoring and adaptation. The Boosted Decision Tree (BDT) regression algorithm achieved high accuracy in predicting KPI data and outperformed other approaches.
IEEE TRANSACTIONS ON BIG DATA
(2023)
Article
Computer Science, Information Systems
Jiachen Zu, Guyu Hu, Jiajie Yan, Siqi Tang
Summary: This paper studies the online placement and migration problem of virtual network functions in data centers considering user service function chains, and designs an online two-stage heuristic algorithm to optimize the placement of SFC. It is proven that the joint online heuristic algorithm can make intelligent predictions based on historical traffic and provide good performance guarantees.
COMPUTER COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Bowen Fei, Xiaomin Zhu, Daqian Liu, Junjie Chen, Weidong Bao, Ling Liu
Summary: This article proposes a method of elastic resource provisioning using data clustering in a cloud service platform. The method effectively meets the demands of different types of tasks through tasks clustering, prediction of the amount of tasks, and dynamic resource provisioning.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
E. G. Radhika, G. Sudha Sadasivam
Summary: Among different deployment models, hybrid cloud is the preferred choice for maximizing cost savings and performance for customers. However, the challenge lies in evaluating and discovering the best fit Cloud Service Provider for efficient Virtual Machine provisioning. The proposed VM Provisioning framework utilizes a Multi Criteria Decision-Making model to select the most suitable CSP for VM provisioning in hybrid cloud.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Miguel Caballer, Marica Antonacci, Zdenek Sustr, Michele Perniola, German Molto
Summary: This paper introduces an architecture of open-source components that can deploy virtual elastic clusters across multiple cloud sites for large-scale computing. These hybrid virtual elastic clusters can be automatically deployed and configured, supporting automated tunneling of communications across cluster nodes.
JOURNAL OF GRID COMPUTING
(2021)
Article
Engineering, Manufacturing
Yong Liang, Mengshi Lu, Zuo-Jun Max Shen, Runyu Tang
Summary: This study formulates a mathematical programming model to minimize total operating cost and service delay penalty, while optimizing data center location, footprint allocation, and resource provisioning decisions. By employing a queueing model and Lagrangian relaxation methods, significant cost reductions and improvements in service quality are achieved compared to hierarchical approaches. The proposed solution methods outperform state-of-the-art commercial software in terms of computational efficiency, selecting data centers chosen by major cloud computing infrastructure providers.
PRODUCTION AND OPERATIONS MANAGEMENT
(2021)
Review
Computer Science, Artificial Intelligence
Victor Chang, Lian Liu, Qianwen Xu, Taiyu Li, Ching-Hsien Hsu
Summary: This article proposes a heuristic model for sentiment analysis on luxury hotel reviews to explore marketing insights. It contributes to visual and multimedia analytics by building on information analytics, geospatial analytics, statistical analytics, and data management. The study analyzes large heterogeneous data generated by hotel customers to improve luxury hotels' service quality. It is expected to be utilized in practice to gain more insights through integrated analytics in social media. The model performs well and provides essential features for future adjustments. Rating: 8/10.
Article
Computer Science, Information Systems
Weiwei Lin, Haojun Xu, Jianzhuo Li, Ziming Wu, Zhengyang Hu, Victor Chang, James Z. Wang
Summary: This paper proposes a neural network-based model for extracting profile attributes, which utilizes the characteristics of recurrent neural networks to extract features and contextual representations of entities. Experimental results demonstrate that the model performs well on large-scale training data.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Xiaoting Dai, Jie Zhang, Victor Chang
Summary: This study proposes an agent-based artificial stock market to investigate the influence of social networks on financial markets. The results show that when information is exogenous, social networks can increase market volatility and trading volume, while reducing price distortion and bid-ask spread. However, when information is endogenous, the effects are reversed.
ENTERPRISE INFORMATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Victor Chang, Jozeene Bailey, Qianwen Ariel Xu, Zhili Sun
Summary: This paper proposes an e-diagnosis system based on machine learning algorithms for diagnosing diabetes in the Internet of Medical Things environment. It explores the use of three interpretable supervised ML models and analyzes their performance to determine the best algorithm for accuracy and precision. The decision process is also assessed and improved.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Automation & Control Systems
Bo Chen, Kang Xu, Yongxin Zhu, Li Tian, Victor Chang
Summary: In this article, a physics law-informed federated learning method is proposed to improve the screening of synchrotron X-ray microdiffraction images while protecting data privacy.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Victor Chang, Jagpreet Sidhu, Sarbjeet Singh, Rajinder Sandhu
Summary: Fog computing extends cloud computing to provide storage, computing facilities, and applications with less latency for latency-sensitive smart applications. A multi-dimensional trust model is proposed to enable smart application clients to determine the trustworthiness of Fog service providers. The model includes application evaluations, peer evaluations, and Fog auditor evaluations, which can be used to determine the reliability of Fog service providers in a Fog computing environment. Our work can assist users in choosing Fog service providers fairly and systematically.
JOURNAL OF GRID COMPUTING
(2023)
Article
Business
Victor Chang, Le Minh Thao Doan, Qianwen Ariel Xu, Karl Hall, Yuanyuan Anna Wang, Muhammad Mustafa Kamal
Summary: The prevalence of IoT has enhanced healthcare business quality and customer experience, while omnichannel services have integrated online and offline channels to increase customer engagement. Healthcare wearable devices play a crucial role in connecting providers and patients in the omnichannel environment. However, ethical concerns and lack of studies on wearables in hospital supply chain management hinder market expansion. This study addresses these gaps by proposing a framework that integrates traditional statistical and machine learning approaches for data analysis and management of omnichannel healthcare supply chain businesses.
JOURNAL OF BUSINESS RESEARCH
(2023)
Article
Computer Science, Information Systems
Victor Chang, Dan Lawrence, Le Minh Thao Doan, Ariel Qianwen Xu, Ben S. C. Liu
Summary: This paper introduces Aboleth, a tool for rapid prototyping. We propose enhancing the API framework and provide details on the design process and implementation of the project. The prototype is developed using Computer-Assisted Designs and Xamarin, integrating software engineering into game design to improve Human-Computer Interaction and user experiences. Additionally, we discuss the relevance of using this tool for rapid prototyping in enterprise mobile applications and Metaverse, and explore opportunities to improve the project design.
ENTERPRISE INFORMATION SYSTEMS
(2023)
Review
Computer Science, Information Systems
Victor Chang, Lewis Golightly, Qianwen Ariel Xu, Thanaporn Boonmee, Ben S. S. Liu
Summary: This paper discusses cybersecurity issues for children, especially teenagers, with a focus on the impact of social media. Many social media users lack awareness of cybersecurity and digital privacy, and fail to understand the importance of developing privacy measures. The paper identifies seven categories of hacking motivations through multimedia platforms, and explores various hacking methods, such as sexting and influence on buying advertisements. The findings highlight the importance of understanding the digital footprint and its consequences for protection.
ENTERPRISE INFORMATION SYSTEMS
(2023)
Article
Automation & Control Systems
Mohamed Abdel-Basset, Hossam Hawash, Victor Chang
Summary: This article proposes a novel fully volumetric segmentation network called FV-Seg-Net, which effectively addresses the precise segmentation of small-size lesions in CT scans. The network utilizes a computationally efficient recalibrated anisotropic convolution module and a multilevel multiscale pyramid aggregation module to capture local and global spatial information. The introduction of stacked data augmentation further improves the generalizability of FV-Seg-Net. Experimental results show that FV-Seg-Net achieves excellent segmentation performance, outperforming current cutting-edge studies.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Yang Yang, Chunming Rong, Xianghan Zheng, Hongju Cheng, Victor Chang, Xiangyang Luo, Zuoyong Li
Summary: In this article, a new concept called time controlled expressive predicate query with accountable anonymity is proposed, which allows for time controlled data query and accountable anonymity for users. The system is based on techniques such as anonymous credential, Pederson commitment, and non-interactive zero-knowledge proof. An efficient expressive predicate query scheme is designed and a concrete system instantiation is presented, which is proven secure and accountable.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Interdisciplinary Applications
Harleen Kaur, Roshan Jameel, M. Afshar Alam, Bhavya Alankar, Victor Chang
Summary: The purpose of this paper is to ensure the anonymity and security of health data and improve the integrity and authenticity among patients, doctors, and insurance providers. Simulation and validation algorithms are proposed in this work to ensure the proper implementation of the distributed system to secure and manage healthcare data. The author also aims to examine the methodology of Wireless Body Area Networks and how it contributes to the health monitoring system.
JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
Muhidin Mohamed, Mourad Oussalah, Victor Chang
Summary: Query-focused multi-document summarization (Qf-MDS) is a sub-task of automatic text summarization that aims to extract a substitute summary from a document cluster of the same topic and based on a user query. In this work, a semantic diversity feature based query-focused extractive summarizer (SDbQfSum) is proposed to address the challenges of query-relevance, centrality, redundancy and diversity. The summarizer combines semantically parsed document text with knowledge-based vectorial representation to extract effective sentence importance and query-relevance features. Evaluation results on the DUC2006 dataset show that the proposed summarizer outperforms most state-of-the-art approaches on ROUGE measures.
Article
Computer Science, Artificial Intelligence
Peichao Lai, Feiyang Ye, Yanggeng Fu, Zhiwei Chen, Yingjie Wu, Yilei Wang, Victor Chang
Summary: The study proposes a CogNLG framework based on the dual-process theory in cognitive science for KG-to-text generation tasks, which shows excellent performance in both explainability and capability.
Article
Business
Vitor Jesus, Balraj Bains, Victor Chang
Summary: Cyber threat intelligence (CTI) is important but often limited to large organizations, creating barriers to effective sharing. This article reviews the challenges of open, crowd-sourced CTI and analyzes the confidentiality threat in existing sharing architectures. By proposing a reference architecture and addressing key requirements, the article aims to strengthen the case for open, crowd-based sharing of CTI and mitigate confidentiality concerns.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2023)
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)