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FakeSens: A Social Sensing Approach to COVID-19 Misinformation Detection on Social Media 17

FakeSens: A Social Sensing Approach to COVID-19 Misinformati...

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17th Annual ieee international conference on distributed computing in sensor systems (ieee dcoss)

作者： Kou, Ziyi Shang, Lanyu Zhang, Yang Youn, Christina Wang, Dong Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

ISBN: (纸本)9781665439299

Social sensing is emerging as an effective and pervasive sensing paradigm to collect timely data and observations from human sensors. This paper focuses on the problem of COVID-19 misinformation detection on social media. Our work is motivated by the lack of COVID-specific knowledge in current misinformation detection solutions, which is critical to assess the truthfulness of social media claims about the emerging COVID19 disease. In this paper, we leverage human intelligence on a crowdsourcing platform to obtain essential knowledge facts for detecting the COVID-19 misinformation on social media. Two critical challenges exist in solving our problem: i) how to efficiently acquire accurate and timely knowledge that is both inclusive and specific to COVID-19? ii) How to effectively coordinate the efforts from both expert and non-expert workers to detect COVID-19 misinformation? To address these challenges, we develop FakeSens, a social sensing based crowd knowledge graph approach that explicitly explores the knowledge facts specific to COVID-19 and models the reliability of different types of crowd workers to capture the misleading COVID-19 claims Evaluation results on a real-world dataset show that FakeSens significantly outperforms state-of-the-art baselines in accurately detecting misleading claims of COVID-19 on social media.

关键词： COVID-19 Knowledge engineering Social networking (online) Human intelligence Performance gain sensor systems Graph neural networks

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Large Scale Global Optimization Algorithms for IoT Networks: A Comparative Study 17

Large Scale Global Optimization Algorithms for IoT Networks:...

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17th Annual ieee international conference on distributed computing in sensor systems (ieee dcoss)

作者： Goudos, Sotirios K. Boursianis, Achilles D. Mohamed, Ali Wagdy Wan, Shaohua Sarigiannidis, Panagiotis Karagiannidis, George K. Suganthan, Ponnuthurai N. Aristotle Univ Thessaloniki Sch Phys ELEDIA AUTH Thessaloniki Greece Cairo Univ Fac Grad Studies Stat Res Operat Res Dept Giza Egypt Nile Univ Wireless Intelligent Networks Ctr WINC Sch Engn & Appl Sci Giza Egypt Zhongnan Univ Econ & Law Sch Informat & Safety Engn Wuhan Peoples R China Univ Western Macedonia Dept Informat & Telecommun Engn Kozani Greece Aristotle Univ Thessaloniki Sch Elect & Comp Engn Thessaloniki Greece Nanyang Technol Univ Sch Elect Elect Engn Singapore Singapore

ISBN: (纸本)9781665439299

The advent of Internet of Things (IoT) has bring a new era in communication technology by expanding the current inter-networking services and enabling the machine-to-machine communication. IoT massive deployments will create the problem of optimal power allocation. The objective of the optimization problem is to obtain a feasible solution that minimizes the total power consumption of the WSN, when the error probability at the fusion center meets certain criteria. This work studies the optimization of a wireless sensor network (WNS) at higher dimensions by focusing to the power allocation of decentralized detection. More specifically, we apply and compare four algorithms designed to tackle Large scale global optimization (LSGO) problems. These are the memetic linear population size reduction and semi-parameter adaptation (MLSHADE-SPA), the contribution-based cooperative coevolution recursive differential grouping (CBCC-RDG3), the differential grouping with spectral clustering-differential evolution cooperative coevolution (DGSC-DECC), and the enhanced adaptive differential evolution (EADE). To the best of the authors knowledge, this is the first time that LSGO algorithms are applied to the optimal power allocation problem in IoT networks. We evaluate the algorithms performance in several different cases by applying them in cases with 300, 600 and 800 dimensions.

关键词： Internet of Things optimal power allocation wireless sensor network large scale global optimization

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HeteroSAS: A Heterogeneous Resource Management Framework for "All-in-the-Air" Social Airborne Sensing in Disaster Response 17

HeteroSAS: A Heterogeneous Resource Management Framework for...

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17th Annual ieee international conference on distributed computing in sensor systems (ieee dcoss)

作者： Rashid, Md Tahmid Zhang, Daniel (Yue) Wang, Dong Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

ISBN: (纸本)9781665439299

Social airborne sensing (SAS) is emerging as a new sensing paradigm that leverages the complementary aspects of social sensing and airborne sensing (i.e., UAVs) for reliable information collection. In this paper, we present HeteroSAS, a heterogeneous resource management framework for "all-in-the-air" SAS in disaster response applications. Current SAS approaches use UAVs to only capture data, but carry out computation on ground-based processing nodes that may be unavailable in disaster scenarios and thus consider a single model of UAV along with only one type of task (i.e., data capture). In this paper, we explore the opportunity to exploit the complementary strengths of different UAV models to accomplish all stages of sensing tasks (i.e., data capturing, maneuvering, and computation) exclusively "in-the-air". However, several challenges exist in developing such a resource management framework: i) handling the uncertain social signals in presence of the heterogeneity of UAVs and tasks;and ii) adapting to constantly changing cyber-physical-social environments. The HeteroSAS framework addresses these challenges by building a novel resource management framework that observes the environment and learns the optimal strategy for each UAV using techniques from multi-agent reinforcement learning, game theory, and ensemble learning. The evaluation with a real-world case study shows that HeteroSAS outperforms the state-of-the-art in terms of detection effectiveness, deadline hit rate, and robustness on heterogeneity.

关键词： Social networking (online) Computational modeling Reinforcement learning Robustness Data models sensor systems sensors

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CoEdge: A Cooperative Edge System for distributed Real-Time Deep Learning Tasks 22

CoEdge: A Cooperative Edge System for Distributed Real-Time ...

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22nd ACM/ieee international conference on Information Processing in sensor Networks (IPSN)

作者： Jiang, Zhehao Ling, Neiwen Huang, Xuan Shi, Shuyao Wu, Chenhao Zhao, Xiaoguang Yan, Zhenyu Xing, Guoliang Chinese Univ Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9798400701184

Recent years have witnessed the emergence of a new class of cooperative edge systems in which a large number of edge nodes can collaborate through local peer-to-peer connectivity. In this paper, we propose CoEdge, a novel cooperative edge system that can support concurrent data/compute-intensive deep learning (DL) models for distributed real-time applications such as city-scale traffic monitoring and autonomous driving. first, CoEdge includes a hierarchical DL task scheduling framework that dispatches DL tasks to edge nodes based on their computational profiles, communication overhead, and real-time requirements. Second, CoEdge can dramatically increase the execution efficiency of DL models by batching sensor data and aggregating the inferences of the same model. Finally, we propose a new edge containerization approach that enables an edge node to execute concurrent DL tasks by partitioning the CPU and GPU workloads into different containers. We extensively evaluate CoEdge on a self-deployed smart lamppost testbed on a university campus. Our results show that CoEdge can achieve up to 82.32% reduction on deadline missing rate compared to baselines.

关键词： Smart City Edge computing distributed Deep Learning System Real-time Scheduling Edge Containerization

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BRB-based distributed fault diagnosis for consensus of heterogeneous multi-agent systems 23

BRB-based distributed fault diagnosis for consensus of heter...

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23rd ieee international conference on High Performance computing and Communications, 7th ieee international conference on Data Science and systems, 19th ieee international conference on Smart City and 7th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Yang, Ruohan Feng, Zhichao School of Electronics and Information Northwestern Polytechnical University Xi'an China High-Tech Institute of Xi'an Xi'an China Harbin Institute of Technology Harbin China

ISBN: (纸本)9781665494571

This paper studies the belief rule base (BRB) expert system based distributed fault diagnosis problem for a group of heterogeneous multi-agent systems (MASs) subject to unpredictable disturbances. first, a novel distributed consensus protocol is developed based on the feedforward approach and internal reference model under directed topology. It is shown that under the proposed consensus protocol, the MASs without fault could achieve bounded consensus asymptotically. Then, novel distributed fault diagnosis models based on BRB are developed for each agent by using the output information of neighbor agents. It should be noted that BRB can handle the information with uncertainty and ambiguity that can address the unpredictable interference in engineering practice. Thus, the proposed BRB based distributed fault diagnosis models for MASs can diagnose the fault and meanwhile eliminate the influence of the unpredictable interference in engineering practice. Finally, a simulation example is provided to illustrate the effectiveness of the approach proposed in this paper. © 2021 ieee.

关键词： Fault diagnosis Uncertainty Smart cities Interference Consensus protocol Topology Feedforward systems

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Precise Wireless Charging in Complicated Environments 42

Precise Wireless Charging in Complicated Environments

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42nd ieee international conference on distributed computing systems (ICDCS)

作者： Yang, Wei Lin, Chi Dai, Haipeng Ren, Jiankang Wang, Pengfei Wang, Lei Wu, Guowei Zhang, Qiang Dalian Univ Technol Sch Software Technol Dalian 116024 Peoples R China Xidian Univ State Key Lab Integrated Serv Networks Xian 710000 Peoples R China Key Lab Ubiquitous Network & Serv Software Liaoni Dalian 116621 Peoples R China Nanjing Univ State Key Lab Novel Software Technol Nanjing 210023 Jiangsu Peoples R China Dalian Univ Technol Sch Comp Sci & Technol Dalian 116024 Peoples R China

ISBN: (数字)9781665471770

ISBN: (纸本)9781665471770

Wireless Rechargeable sensor Networks (WRSNs) have become an important research issue as it can overcome the energy bottleneck problem of wireless sensor networks. However, inaccurate discretization methods and imprecise charging models yield a huge gap between theoretical results and practical applications, making it difficult for wide adoptions. In this paper, we focus on designing a precise charging method for maximizing charging utility when line-of-sight (LOS) and none-line-of-sight (NLOS) charging cases exist in complicated environments. first, we design discretization methods for charging area and charging orientation for precisely constructing the charging model. Then, we develop a novel electromagnetic wave reflection model to describe the signal propagation model in the presence of obstacles. We formalize the mobile charging problem into a submodular function maximization problem which can be solved by a proposed algorithm with an approximation guarantee. Finally, extensive experiments and simulations demonstrate that our schemes outperform comparison algorithms by 31.45% on average in charging utility in complicated environments.

关键词： Wireless communication Wireless sensor networks Inductive charging Line-of-sight propagation Directional antennas Directive antennas Approximation algorithms

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distributed Service Placement in Ultra-Dense Edge computing: A Game-Theoretical Approach 23

Distributed Service Placement in Ultra-Dense Edge Computing:...

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作者： He, Junyi Zhang, Di Li, Xishuo Zhou, Yuezhi Zhang, Yaoxue School of Software Engineering Beijing Jiaotong University China School of Science and Engineering The Chinese University of Hong Kong Shenzhen China School of Computer Science and Engineering Beihang University China Tsinghua University Department of Computer Science and Technology China

ISBN: (纸本)9781665494571

Ultra-dense mobile edge computing (MEC) is expected as an effective approach to provide services with ultra-low latency and massive connectivity, which is extremely important for delay-sensitive applications. In this paper, we study service instance (SI) placement for delay-sensitive applications in ultra-dense MEC, which decides where to place applications and the required data (programming codes and datasets). In general, the SI placement problem is a combinatorial optimization and usually does not have low-complexity optimal solutions. Existing centralized policies are difficult to implement due to the high complexity, especially when edge servers are densely deployed in the ultra-dense network (UDN). To design an approach that can make SI placement decisions quickly and efficiently, this paper investigates a distributed strategy for multi-user multi-server edge systems in UDN. We first formulate the SI placement problem as a non-linear combinatorial optimization, which is proven to be NP-hard to compute a centralized optimal solution. Then, we propose an uncooperative game to design a low-complexity distributed algorithm. We further analyze the properties of the game and prove the existence of pure strategy Nash Equilibrium. A polynomial-complexity distributed algorithm is proposed to get the Nash Equilibrium. Theoretical analysis shows the algorithm's convergence and the bound of the price of anarchy (PoA), which serves as a performance guarantee in the worst-case scenarios compared to the global optimum. Numerical results validate the convergence and near-optimal performance of the proposed distributed algorithm. © 2021 ieee.

关键词： Performance evaluation Games Reinforcement learning Nash equilibrium Servers distributed algorithms Ultra-dense networks

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False Data Injection Attacks Against High Voltage Transmission systems

False Data Injection Attacks Against High Voltage Transmissi...

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international conference on distributed computing in sensor systems (dcoss)

作者： Panagiotis Radoglou-Grammatikis Magda Zafeiropoulou Maria Atanasova Pencho Zlatev Sofia Giannakidou Thomas Lagkas Vasileios Argyriou Evangelos K. Markakis Ioannis Moscholios Panagiotis Sarigiannidis Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Innovative Energy and Information Technologies LTD (IEIT BIC-IZOT Sofia Bulgaria K3Y Ltd Sofia Bulgaria Department of Computer Science International Hellenic University Kavala Campus Greece Department of Networks and Digital Media Kingston University London Surrey UK Department of Electrical and Computer Engineering Hellenic Mediterranean University Crete Greece Department of Informatics & Telecommunications University of Peloponnese Tripolis Greece

The digitisation of the smart electrical grid provides several advantages and valuable services, such as self-monitoring, pervasive control and smart healing. However, despite the benefits of this progression, critical cybersecurity and privacy issues are raised due to the vulnerabilities of legacy Electrical Power and Energy systems (EPES) and the evolution of stealthy cyberthreats and malware. In this paper, we give emphasis to False Data Injection Attacks (FDIAs) that can affect the EPES State Estimation (SE). In particular, we investigate two FDIA categories, namely: (a) Global Positioning System (GPS) Spoofing Attacks and (b) ieee C37.118 FDIAs against an actual testbed emulating a high-voltage ieee 9-Bus transmission grid. Finally, we provide a relevant Intrusion Detection System (IDS) capable of detecting the aforementioned FDIAs. The evaluation analysis demonstrates the impact of the above FDIAs and the efficiency of the proposed IDS.

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Are You Really Charging Me? 42

Are You Really Charging Me?

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42nd ieee international conference on distributed computing systems (ICDCS)

作者： Lin, Chi Yang, Ziwei Ren, Jiankang Wang, Lei Zhong, Wei Wu, Guowei Zhang, Qiang Dalian Univ Technol Sch Software Technol Dalian Peoples R China Xidian Univ State Key Lab Integrated Serv Networks Xian Peoples R China Key Lab Ubiquitous Network & Serv Software Liaoni Dalian Peoples R China Dalian Univ Technol Sch Comp Sci & Technol Dalian Peoples R China Dalian Univ Technol DUT RU Int Sch Informat Sci & Engn Dalian Peoples R China

ISBN: (数字)9781665471770

ISBN: (纸本)9781665471770

Wireless rechargeable sensor networks (WRSNs), which benefit from recent breakthroughs in Wireless Power Transfer (WPT) technology, emerge as very promising for network lifetime extension. Traditional methods concentrate on system performance improvement while little attention has been paid to security, making them vulnerable to novel attacks. In this paper, we develop a novel Charging Spoofing Attack (CSA), in which a mobile charger (MC) is charging a node intuitively. Nevertheless, it is launching an attack based on the nonlinear superposition principle of electromagnetic waves, causing the target node to be unable to receive any energy and finally exhausted in vain. first, we explain and model the nonlinear superposition effect through experiments, which points out the potential of launching such a novel attack. Second, we formalize the attacking problem as a charging uTility optimization problem with key noDe timE window constraints (TIDE). Then, we propose an approximation algorithm termed CSA to solve the TIDE problem with a bounded performance guarantee. Theoretical analyses are presented to exploit the feature of CSA. Finally, to demonstrate the outperformed features of our scheme, extensive simulations and test-bed experiments are conducted, revealing that CSA can exhaust at least 80% of key nodes without being detected.

关键词： Wireless communication Wireless sensor networks System performance Wireless power transfer Programming Approximation algorithms Time factors

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6th ieee international Workshop on Wireless Communications and Networking in Extreme Environments (WCNEE) Message from the Workshop Chairs

Proceedings - 18th Annual International Conference on Distri...

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Proceedings - 18th Annual international conference on distributed computing in sensor systems, dcoss 2022 2022年 XX页

作者： Balasubramaniam, Sasitharan Demirors, Emrecan Guan, Zhangyu Sklivanitis, George University of Nebraska-Lincoln United States Northeastern University United States University at Buffalo United States Florida Atlantic University United States

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