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SSRN 2022年

作者： Cioppa, Antonio Della De Falco, Ivanoe Koutny, Tomas Scafuri, Umberto Ubl, Martin Tarantino, Ernesto NCLab DIEM University of Salerno SA Fisciano84084 Italy Institute of High Performance Computing and Networking National Research Council of Italy Naples80131 Italy DCSE Department of Computer Science Engineering University of West Bohemia Pilsen306 14 Czech Republic NTIS New Technologies for the Information Society University of West Bohemia Pilsen306 14 Czech Republic

Diabetes mellitus is a metabolic disease involving high blood glucose levels that can lead to serious medical consequences. Hence, for diabetic patients the prediction of future glucose levels is essential in the management of the *** of the forecasting approaches in the literature evaluate the effectiveness of glucose predictors only with numerical *** approaches are limited because they evenly treat all the errors without considering their different clinical impact that could involve lethal effects in dangerous situations such as hypo- or hyperglycemia. To overcome such a limitation, this paper aims to devise models for reducing high-risk glucose forecasting errors for Type 1 diabetic *** this purpose, we exploit a Grammatical Evolution algorithm to induce personalized and interpretable forecasting glucose models assessed with a novel, composite metric to satisfy both clinical and numerical requirements of the estimated *** assess the effectiveness of the proposed approach, a real-world data set widely used in literature, consisting of data from several patients suffering from Type 1 diabetes, has been adopted. The experimental findings show that the induced models are interpretable and capable of assuring predictions with a good tradeoff between medical quality and numerical accuracy. Furthermore, their performance is better than or comparable to that of other state–of–the–art methods. © 2022, The Authors. All rights reserved.

关键词： Forecasting

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A systematic literature review: the role of assistive technology in supporting elderly social interaction with their online community

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Journal of Ambient Intelligence and Humanized Computing 2020年第7期12卷 7427-7440页

作者： Embarak, Farhat Ismail, Nor Azman Othman, Salem School of Computing Faculty of Engineering University Teknologi Malaysia (UTM) Johor Bahru Malaysia Department of Computer Science Faculty of Computing and Information Technology University of Ajdabiya Ajdabiya Libya Department of Computer Science and Networking Wentworth Institute of Technology Boston USA

Social integration through communication with family and friends can fulfill human’s desires of being cherished and respected. Such communications are very important for the elderly people, especially for those who have retired. Online social communities can help with this and provide positive effect on elderly people. But the elderly are quite reluctant to work with new technologies and hence, researchers have tried to implement specially designed social media application in easy user-interface devices for the elderly. In this paper, we conduct a Systematic Literature Review (SLR) method to collect and review studies to understand the different user-interaction devices used for the elderly to promote social connection. 33 literature papers were identified within the years 2013–2019 following a review procedure, which presents research on online social communities for elders. The papers are analyzed and classified further to understand the current state-of-the-art focus. This study further offers related discussion and conclusions.

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Vehicular network slicing for reliable access and deadline-constrained data offloading: A multi-agent on-device learning approach

arXiv

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arXiv 2020年

作者： Pervej, Md Ferdous Lin, Shih-Chun Intelligent Wireless Networking Laboratory Department of Electrical and Computer Engineering North Carolina State University RaleighNC27695 United States

Efficient data offloading plays a pivotal role in computational-intensive platforms as data rate over wireless channels is fundamentally limited. On top of that, high mobility adds an extra burden in vehicular edge networks (VENs), bolstering the desire for efficient user-centric solutions. Therefore, unlike the legacy inflexible network-centric approach, this paper exploits a software-defined flexible, open, and programmable networking platform for an efficient user-centric, fast, reliable, and deadline-constrained offloading solution in VENs. In the proposed model, each active vehicle user (VU) is served from multiple low-powered access points (APs) by creating a noble virtual cell (VC). A joint node association, power allocation, and distributed resource allocation problem is formulated. As centralized learning is not practical in many real-world problems, following the distributed nature of autonomous VUs, each VU is considered an edge learning agent. To that end, considering practical location-aware node associations, a joint radio and power resource allocation non-cooperative stochastic game is formulated. Leveraging reinforcement learning’s (RL) efficacy, a multi-agent RL (MARL) solution is proposed where the edge learners aim to learn the Nash equilibrium (NE) strategies to solve the game efficiently. Besides, real-world map data, with a practical microscopic mobility model, are used for the simulation. Results suggest that the proposed user-centric approach can deliver remarkable performances in VENs. Moreover, the proposed MARL solution delivers near-optimal performances with ≈ 3% collision probabilities in case of distributed random access in the uplink. © 2020, CC BY.

关键词： Resource allocation

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An Out-of-Sample Extension for Wireless Multipoint Channel Charting 14th

An Out-of-Sample Extension for Wireless Multipoint Channel C...

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14th EAI International Conference on Cognitive Radio-Oriented Wireless Networks, CROWNCOM 2019

作者： Ponnada, Tushara Al-Tous, Hanan Tirkkonen, Olav Studer, Christoph Department of Communications and Networking Aalto University Espoo Finland School of Electrical and Computer Engineering Cornell University IthacaNY United States

ISBN: (纸本)9783030257477

Channel-charting (CC) is a machine learning technique for learning a multi-cell radio map, which can be used for cognitive radio-resource-management (RRM) problems. Each base-station (BS) extracts features from the channel-state-information samples (CSI) from transmissions of user-equipment (UE) at different unknown locations. The multi-path channel components are estimated and used to construct a dissimilarity matrix between CSI samples at each BS. A fusion center combines the dissimilarity matrices of all base-stations, performs dimensional reduction based on manifold learning, constructing a Multipoint-CC (MPCC). The MPCC is a two dimension map, where the spatial difference between any pair of UEs closely approximates the distance between the clustered features. MPCC provides a mapping for any given trained UE location. To use MPCC for cognitive RRM tasks, CSI measurements for new UEs would be acquired, and these UEs would be placed on the radio map. Repeating the MPCC procedure for out-of-sample CSI measurements is computationally expensive. For this, extensions of MPCC to out-of-sample UE CSIs are investigated in this paper, when Laplacian-Eigenmaps (LE) is used for dimensional reduction. Simulation results are used to show the merits of the proposed approach. © 2019, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Channel state information

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Q-Learning Based D2D Offloading for Statistical QoS Provisioning over 5G Multimedia Edge-Computing Wireless Networks

Q-Learning Based D2D Offloading for Statistical QoS Provisio...

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2019 INFOCOM IEEE Conference on computer Communications Workshops, INFOCOM WKSHPS 2019

作者： Wang, Jingqing Zhang, Xi Networking and Information Systems Laboratory Department of Electrical and Computer Engineering Texas AandM University College StationTX77843 United States

ISBN: (纸本)9781728118789

With the increasing demand for the wireless multimedia services over 5G multimedia edge-computing wireless networks, the statistical quality-of-service (QoS) provisioning has been proven to be able to effectively guarantee the multimedia data transmissions over time-varying wireless channels. On the other hand, the collaborative device-to-device (D2D) based offloading scheme, where the mobile users share the popular multimedia files within a D2D communication group instead of downloading from the remote backhaul networks, has been proposed as one of the 5G promising candidate techniques to meet the statistical delaybounded QoS requirements as well as address the data explosion problem introduced by 5G multimedia edge-computing wireless networks. However, due to the dynamically changing environment and various demands for each mobile user, it is challenging to design an efficient offloading algorithm for choosing the optimal D2D offloading strategy. To overcome the aforementioned problems, in this paper we propose the machine-learning based framework for the collaborative D2D offloading scheme through repeatedly interacting with the networking environment while satisfying the statistical delay-bounded QoS constraints. In particular, we derive and analyze the collaborative D2D communication model and the interference based constraints. Under the statistical delaybounded QoS requirements, we formulate and solve the effectivecapacity optimization problem for the collaborative D2D offloading scheme by using Q-learning technique over 5G multimedia edgecomputing wireless networks. Also conducted is a set of simulations which evaluate the system performance and show that our proposed collaborative D2D offloading scheme outperforms the other existing schemes under the statistical delay-bounded QoS constraints over 5G multimedia edge-computing wireless networks. © 2019 IEEE.

关键词： Wireless networks

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Joint optimization for secure ambient backscatter communication in NOMA-enabled IoT networks

arXiv

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arXiv 2021年

作者： Khan, Wali Ullah Jameel, Furqan Ihsan, Asim Waqar, Omer Ahmed, Manzoor University of Luxembourg Luxembourg City1855 Luxembourg Department of Communications and Networking Aalto University Espoo02150 Finland Department of Communication and Information Engineering Shanghai Jiao Tong University Shanghai200240 China BC Canada College of Computer Science and Technology Qingdao University Qingdao266071 China

Non-orthogonal multiple access (NOMA) has emerged as a novel air interface technology for massive connectivity in sixth-generation (6G) era. The recent integration of NOMA in backscatter communication (BC) has triggered significant research interest due to its applications in low-powered Internet of Things (IoT) networks. However, the link security aspect of these networks has not been well investigated. This article provides a new optimization framework for improving the physical layer security of the NOMA ambient BC system. Our system model takes into account the simultaneous operation of NOMA IoT users and the backscatter node (BN) in the presence of multiple eavesdroppers (EDs). The EDs in the surrounding area can overhear the communication of base station (BS) and BN due to the wireless broadcast transmission. Thus, the main objective is to enhance the link security by optimizing the BN reflection coefficient and BS transmit power. To gauge the performance of the proposed scheme, we also present the suboptimal NOMA and conventional orthogonal multiple access as benchmark schemes. Monte Carlo simulation results demonstrate the superiority of the NOMA BC scheme over the pure NOMA scheme without BC and conventional orthogonal multiple access scheme in terms of system secrecy rate. Copyright © 2021, The Authors. All rights reserved.

关键词： Internet of things

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Energy-Constrained Computation Offloading in Space-Air-Ground Integrated Networks using Distributionally Robust Optimization

arXiv

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arXiv 2022年

作者： Chen, Yali Ai, Bo Niu, Yong Zhang, Hongliang Han, Zhu The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-Speed Railway System Beijing Jiaotong University Beijing100044 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen China The National Mobile Communications Research Laboratory Southeast University Nanjing211189 China The Department of Electrical Engineering Princeton University PrincetonNJ08544 United States The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of

With the rapid development of connecting massive devices to the Internet, especially for remote areas without cellular network infrastructures, space-air-ground integrated networks (SAGINs) emerge and offload computation-intensive tasks. In this paper, we consider a SAGIN, where multiple low-earthorbit (LEO) satellites providing connections to the cloud server, an unmanned aerial vehicle (UAV), and nearby base stations (BSs) providing edge computing services are included. The UAV flies along a fixed trajectory to collect tasks generated by Internet of Things (IoT) devices, and forwards these tasks to a BS or the cloud server for further processing. To facilitate efficient processing, the UAV needs to decide where to offload as well as the proportion of offloaded tasks. However, in practice, due to the variability of environment and actual demand, the amount of arrival tasks is uncertain. If the deterministic optimization is utilized to develop offloading strategy, unnecessary system overhead or higher task drop rate may occur, which severely damages the system robustness. To address this issue, we characterize the uncertainty with a data-driven approach, and formulate a distributionally robust optimization problem to minimize the expected energy-constrained system latency under the worst-case probability distribution. Furthermore, the distributionally robust latency optimization algorithm is proposed to reach the suboptimal solution. Finally, we perform simulations on the realworld data set, and compare with other benchmark schemes to verify the efficiency and robustness of our proposed algorithm. Copyright © 2022, The Authors. All rights reserved.

关键词： Probability distributions

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A QUIC Simulation Model for INET and its Application to the Acknowledgment Ratio Issue

A QUIC Simulation Model for INET and its Application to the ...

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IFIP networking Conference

作者： Timo Völker Ekaterina Volodina Michael Tüxen Erwin P. Rathgeb Department of Electrical Engineering and Computer Science FH Müunster University of Applied Sciences Steinfurt Germany Computer Networking Technology Group University of Duisburg-Essen Essen Germany

ISBN: (数字)9783903176287

ISBN: (纸本)9781728167107

Quick UDP Internet Connections (QUIC) is a novel transport protocol introducing known features in a new protocol design. To investigate these features and the design, we developed a QUIC implementation in the INET simulation model suite. In this paper, we describe that implementation, its validation and a result achieved using the simulation model. The result shows the negative impact on throughput, when raising the acknowledgment ratio. We propose a solution and describe how it solves the issue.

关键词： Protocols Receivers Internet Analytical models Dictionaries Generators Computational modeling

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Assistive Technical Communication of Montenegrin eServices: a Case Study

Assistive Technical Communication of Montenegrin eServices: ...

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International Scientific-Professional Conference on Information Technology (IT)

作者： Aniko Simon Luka Laković Pavle Kovačević Peter A. Kara Ivana Ognjanović Ramo Šendelj Christoph Reich Milovan Roganović John Mantas Laszlo Bokor Sigma Technology 1093 Budapest Hungary Faculty for Information Systems and Technologies University of Donja Gorica 81000 Podgorica Montenegro Budapest University of Technology and Economics 1111 Budapest Hungary Department of Networked Systems and Services Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics 1111 Budapest Hungary Department of Computer Science School of Computer Science and Mathematics Faculty of Science Engineering and Computing Wireless Multimedia and Networking Research Group Kingston University London KT1 2EE UK Humanistic Studies University of Donja Gorica 81000 Podgorica Montenegro Institute of Data Science Cloud Computing and IT Security Furtwangen University 78120 Furtwangen Germany Clinic for Neurology Clinical Centre of Montenegro 81000 Podgorica Montenegro Faculty of Nursing School of Health Sciences National and Kapodistrian University of Athens 11527 Goudi Greece

With the advancement of information technology in the recent decades, digital and online services have become essential components of everyday life in Europe. Montenegro is no different in this regard. However, as digital literacy in the country is still in a developing phase in comparison with most countries of the EU, a higher portion of its citizens may rely on assistive technical communication. In this paper, we provide a case study on the assistive technical communication of Montenegrin eServices. The work addresses the sectors of online banking, healthcare services, higher education, national administrative services, and utilities. Our findings highlight the diversity in terms of implemented assistive technical communication, and distinguish usage contexts on the level of adequacy. Yet as the functionalities of Montenegrin eServices are expected to gradually expand in the upcoming years, assistive technical communication must aim to handle the higher extents of service complexity.

关键词： Online banking Education Europe Medical services Complexity theory Information technology

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Evaluation of the Montenegrin Academic Digital Innovation Hub

Evaluation of the Montenegrin Academic Digital Innovation Hu...

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International Scientific-Professional Conference on Information Technology (IT)

作者： Luka Laković Peter A. Kara Ivana Ognjanović Laszlo Bokor Ramo Šendelj Christoph Reich Milovan Roganović Emmanouil Zoulias Jevto Eraković Tanja Radusinović Nada Rakočević Aniko Simon Faculty for Information Systems and Technologies University of Donja Gorica 81000 Podgorica Montenegro Department of Networked Systems and Services Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics 1111 Budapest Hungary Department of Computer Science School of Computer Science and Mathematics Wireless Multimedia and Networking Research Group Faculty of Science Engineering and Computing Kingston University London KT1 2EE UK Humanistic Studies University of Donja Gorica 81000 Podgorica Montenegro Institute of Data Science Cloud Computing and IT Security Furtwangen University 78120 Furtwangen Germany Clinic for Neurology Clinical Centre of Montenegro 81000 Podgorica Montenegro Faculty of Nursing School of Health Sciences National and Kapodistrian University of Athens 11527 Goudi Greece Chamber of Economy of Montenegro 81000 Podgorica Montenegro Sigma Technology 1093 Budapest Hungary

In the era of global digitalization, digital innovation hubs have become essential, as they function as transforming forces. In this paper, we provide an analysis of the Montenegrin Academic Digital Innovation Hub by applying multi-criteria qualitative evaluation over several criteria: process flow of fully digitized operations of the Hub (with aspects of the innovation life-cycle, ethics, and security), resource management, strategic goals, and feasibility. The paper also proposes a model of comprehensive resource management via the perspective of smart specialization priorities of Montenegro.

关键词： Technological innovation Ethics Resource management Security Information technology

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