Article
Engineering, Electrical & Electronic
Minghao Ye, Yang Hu, Junjie Zhang, Zehua Guo, H. Jonathan Chao
Summary: This paper proposes a destination-based TE solution called FlexEntry, which uses reinforcement learning and linear programming to reduce time complexity, decrease forwarding entry updates, and improve network performance.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Jing Yang, Xu Yang, Zhang-Bing Zhou, Zhi-Yong Liu
Summary: This paper proposes a fast normalized cut-based graph matching method that introduces discrete constraints and constructs an objective function during the optimization process to solve the graph matching problem. Experiments have validated the effectiveness of this method.
PATTERN RECOGNITION
(2022)
Article
Computer Science, Theory & Methods
Ankur O. Bang, Udai Pratap Rao, Pallavi Kaliyar, Mauro Conti
Summary: This article investigates the routing security issues in RPL-based IoT networks and provides a comprehensive survey of security threats and countermeasures. A novel classification scheme is proposed based on the study, along with an in-depth statistical analysis. The article also highlights some open challenges and future research opportunities.
ACM COMPUTING SURVEYS
(2023)
Article
Computer Science, Information Systems
Bing Su, Ling Tong
Summary: This paper proposes a geographic routing strategy based on trusted nodes to deliver Emergency Messages (EMs) in Vehicle Ad Hoc Networks (VANETs). The strategy evaluates the reliability of link quality and node quality, and has significant performance improvements in message delivery rate, end-to-end delay, and network throughput. It can also detect and identify malicious nodes in the network.
Article
Computer Science, Artificial Intelligence
Qian Li, YuFeng Xie, XinHong Wu, Yunpeng Xiao
Summary: Traditional prediction models of rumor forwarding based solely on explicit network topology are not effective due to the lack of consideration for homogeneity and antagonism among multi-type rumor messages. This study proposes a user behavior prediction model based on implicit links and multi-type rumor messages to address these problems. By considering user interactions and similarities comprehensively, implicit links among non-friends are mined using the K-dimension-tree algorithm to improve the network topology. The advantages of graph convolutional networks (GCNs) model in network representation are utilized to fully represent rumor information, user characteristics, and network structure, resulting in improved generalization ability of the proposed model.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Lei Jiao, Zhihong Peng, Lele Xi, Miao Guo, Shuxin Ding, Yue Wei
Summary: This paper proposes a multi-stage vehicle routing algorithm based on task grouping for the rescue vehicle routing problem with energy constraint in disasters. The algorithm includes a novel K-means algorithm, a problem-specific genetic algorithm, and various heuristics for route adjustment. The effectiveness of each stage in the algorithm has been verified in several scenarios, and the proposed algorithm outperforms other algorithms for VRPEC.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Multidisciplinary
M. Khalid Diaa, I. Samer Mohamed, M. Ayman Hassan
Summary: This paper presents an obstacle prediction-based routing protocol for Vehicular Ad-hoc Networks (VANETs) that utilizes vehicle kinematics and mobility prediction to achieve reliable communication and data transmission in the network.
AIN SHAMS ENGINEERING JOURNAL
(2023)
Article
Computer Science, Information Systems
Pingakshya Goswami, Dinesh Bhatia
Summary: Design closure in VLSI and FPGA physical design flows, especially in routing, is important and time-consuming. Accurate congestion estimation can help alleviate routing-related issues during the design flow. This paper introduces a machine learning-based prediction model for FPGA routing congestion, which shows significant improvements in accuracy and prediction time through experiments.
Article
Engineering, Civil
Md Mostafizur Rahman Komol, Mohammed Elhenawy, Mahmoud Masoud, Andry Rakotonirainy, Sebastien Glaser, Merle Wood, David Alderson
Summary: This paper presents an early prediction framework to classify drivers' intended intersection movements in a connected vehicle environment. The accurate perception of drivers' intended movements at intersections is required for advanced red-light or turning warnings for vulnerable road users. Early prediction of intersection movement and adequate warning assistance will ensure road users' safety at the intersection.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Jinhao Zhang, Mi Xiao, Liang Gao
Summary: The paper introduces a new RBDO method based on local updates, using Kriging metamodels to approximate objective and constraint functions, and applying sequential optimization and reliability assessment. The method includes two local update strategies for constraint and objective functions, refining the Kriging metamodels in local regions to improve accuracy and efficiency.
ENGINEERING WITH COMPUTERS
(2021)
Article
Computer Science, Interdisciplinary Applications
Mustafa Kucuk, Seyda Topaloglu Yildiz
Summary: This study presents constraint programming-based solution approaches for the 3l-CVRP in distribution logistics. The developed decomposed models outperformed the previous mixed-integer programming models for small-size problems. The results of computational study show improvement in 36 out of 93 benchmark problems.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Chemistry, Analytical
Lei Nie, Junjie Zhang, Haizhou Bao, Yiming Huo
Summary: This study proposes a vehicular safety message routing method based on heuristic path search and multi-attribute decision-making (HMDR). The method is capable of selecting the globally optimal transmission path and comprehensively considers multiple metrics and their relationships when evaluating relays, thus improving the performance of vehicular safety message transmission.
Article
Computer Science, Information Systems
Zheheng Rao, Yanyan Xu, Shaoming Pan
Summary: Routing services in next generation networks require good transmission quality and differentiated performance for different applications. However, existing deep learning-based algorithms cannot meet specific performance requirements. Therefore, researchers propose a deep learning-based constrained intelligent routing method, which combines the advantages of solving constrained problems and deep learning methods to adapt to network environments and meet user performance requirements.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2021)
Article
Computer Science, Theory & Methods
Hassan Zivarifard, Matthieu R. Bloch, Aria Nosratinia
Summary: This paper analyzes secrecy rates for a channel in which two transmitters simultaneously multicast to two receivers in the presence of an eavesdropper. Achievable rates are calculated and inner and outer bounds are derived, showcasing the minimal randomness necessary to achieve secrecy in different channel scenarios.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2021)
Article
Environmental Sciences
Yuguo Yang, Tianhe Xu, Zhangzhen Sun, Wenfeng Nie, Zhenlong Fang
Summary: In this study, a new UT1-UTC prediction model based on polynomial curve fitting, weighted least squares, and autoregressive model was proposed. Experimental results show that this model can predict UT1-UTC more accurately in the mid and long term, with an improvement of 33.2% compared to existing models.
Article
Computer Science, Theory & Methods
Jasenka Dizdarevic, Francisco Carpio, Admela Jukan, Xavi Masip-Bruin
ACM COMPUTING SURVEYS
(2019)
Article
Thermodynamics
X. Masip, A. Cazorla-Marin, Carla Montagud-Montalva, J. Marchante, F. Barcelo, J. M. Corberan
APPLIED THERMAL ENGINEERING
(2019)
Article
Computer Science, Theory & Methods
Zeineb Rejiba, Xavier Masip-Bruin, Eva Marin-Tordera
ACM COMPUTING SURVEYS
(2019)
Article
Computer Science, Hardware & Architecture
Admela Jukan, Francisco Carpio, Xavi Masip, Ana Juan Ferrer, Nicole Kemper, Birgit U. Stetina
Article
Engineering, Electrical & Electronic
Souvik Sengupta, Jordi Garcia, Xavi Masip-Bruin
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
(2020)
Article
Computer Science, Theory & Methods
A. Asensio, X. Masip-Bruin, R. J. Duran, I de Miguel, G. Ren, S. Daijavad, A. Jukan
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2020)
Article
Computer Science, Theory & Methods
Zeineb Rejiba, Xavier Masip-Bruin, Eva Marin-Tordera
Summary: This study introduces a block-based FN selection scheme and a greedy selection approach to tackle the issues of uncertainty and dynamics in fog computing environments. Simulation results demonstrate the significant improvement in FN selection performance using both methods.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Computer Science, Theory & Methods
A. Asensio, X. Masip-Bruin, J. Garcia, S. Sanchez
Summary: This paper discusses the advantages of leveraging cloud and edge computing resources in smart environments, and proposes the Concurrent Container Clusters Scheduling problem (C3S) to optimize the deployment of containers in heterogeneous node clusters. Using Integer Linear Programming, the objective is to minimize the number of rejected applications and computing nodes.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Chemistry, Analytical
Xavi Masip-Bruin, Eva Marin-Tordera, Sergi Sanchez-Lopez, Jordi Garcia, Admela Jukan, Ana Juan Ferrer, Anna Queralt, Antonio Salis, Andrea Bartoli, Matija Cankar, Cristovao Cordeiro, Jens Jensen, John Kennedy
Summary: The cloud continuum, formed by the combination of fog computing, edge computing, and cloud computing, requires novel management strategies to coordinate and efficiently manage resources from the edge to the cloud. This management framework design poses various research challenges and has spurred many global initiatives.
Review
Chemistry, Analytical
Xavi Masip-Bruin, Eva Marin-Tordera, Jose Ruiz, Admela Jukan, Panagiotis Trakadas, Ales Cernivec, Antonio Lioy, Diego Lopez, Henrique Santos, Antonis Gonos, Ana Silva, Jose Soriano, Grigorios Kalogiannis
Summary: Building supply chains on large and complex IoT systems require a coordinated framework for cyber resilience provisioning to ensure trusted ICT systems. The proposed solution in this paper addresses security and privacy functionalities related to risks and vulnerabilities management, accountability, and mitigation strategies. The FISHY architecture leverages programmable networks and IT infrastructure to orchestrate security services in real-time and proactively.
Article
Computer Science, Theory & Methods
Jordi Garcia, Francesc Aguilo, Adria Asensio, Ester Simo, Marisa Zaragoza, Xavi Masip-Bruin
Summary: A new model is proposed for offloading task execution in heterogeneous environments, considering nodes computing capacity, network bandwidth, and geographical location. Two optimization strategies are suggested, and the simulation results show that the staged model provides the optimal solution in most scenarios.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Chemistry, Analytical
Panagiotis Trakadas, Xavi Masip-Bruin, Federico M. Facca, Sotirios T. Spantideas, Anastasios E. Giannopoulos, Nikolaos C. Kapsalis, Rui Martins, Enrica Bosani, Joan Ramon, Raul Gonzalez Prats, George Ntroulias, Dimitrios Lyridis
Summary: This paper presents a reference architecture of a meta-operating system (RAMOS) for edge computing and explores its potential in key applications, focusing on distributed intelligence, privacy preservation principles, and environmental footprint minimization.
Proceedings Paper
Computer Science, Information Systems
Sarang Kahvazadeh, Xavi Masip-Bruin, Pau Marcer, Eva Marin-Tordera
COMPUTER SECURITY: ESORICS 2019 INTERNATIONAL WORKSHOPS, IOSEC, MSTEC, AND FINSEC
(2020)
Article
Computer Science, Information Systems
Azin Moradbeikie, Kamal Jamshidi, Ali Bohlooli, Jordi Garcia, Xavi Masip-Bruin
Proceedings Paper
Computer Science, Hardware & Architecture
Xavi Masip-Bruin, Sergi Sanchez-Lopez, Alejandro Jurnet, Eva Marin-Tordera, Admela Jukan, Guang-Jie Ren
PROCEEDING OF THE 2019 IEEE 8TH INTERNATIONAL CONFERENCE ON CLOUD NETWORKING (CLOUDNET)
(2019)
