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Research on the Security of Beyond-the-Sight Services Based on Blockchain 3rd

Research on the Security of Beyond-the-Sight Services Based ...

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3rd international conference on Blockchain and Trustworthy Systems, Blocksys 2021

作者： Duan, Xuefei Lu, Hua Bai, Lejin Guo, Zixuan GuangDong Communications and Networks Institute Huangpu District Guangdong Province Guangzhou City China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9789811679926

In 2008, blockchain was proposed as the basic technology of Bitcoin, and it is essentially a decentralized database. This technology is widely used in financial industry, data storage, edge computing and other scenarios. With the rapid increase of the number of devices connected to the Internet of Things (IoT), the traditional centralized cloud computing system is unable to satisfy the Quality of Service (QoS) of many IoT applications, especially for areas with real-time. IoT services based on Mobile Edge computing (MEC) are gradually becoming popular, and the characteristics of the distributed accounting and consensus mechanism of the blockchain can ensure the security of MEC-based IoT services. In this paper, we first summarize the existing blockchain and MEC related technologies, and then propose a future-oriented Internet of Vehicles (IoV) service: beyond-the-sight service. At last, we specifically discuss how the blockchain can ensure the security of beyond-the-sight service in terms of terminal equipment identification and data transmission. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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A Global Opinion-influencing Consensus Model based on the DeGroot

A Global Opinion-influencing Consensus Model based on the De...

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IEEE international Symposium on Parallel and distributed Processing with Applications and IEEE international conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Yuntian Zhang Xiaoliang Chen Zexia Huang Xianyong Li Yajun Du School of Computer and Software Engineering Xihua University Chengdu China College of Science Xihua University Chengdu China

Social networks have become an important platform for transmitting and sharing information due to the rapid development of online social networks. Opinion dynamics have been examined through the consensus-reaching process (CRP) in social networks, which aims to model the evolution of opinions in social networks so that agents can reach a consensus. Many researchers have solved the CRP problem by improving the DeGroot model, which models divide agents into two categories, leaders and followers, and change the network structure or the values of the agents’ opinions to bring the network to a consensus. However, all of them require the construction of leaders who can influence the entire network. Consensus cannot be achieved without the leaders. This paper proposes a global opinion-influencing consensus model (GOCM) to solve the CRP problem. A network agent refers not only to the opinion of its neighbors but also to the average opinion of the entire network. The numerical analysis indicates that our proposed GOCM can significantly accelerate the achievement of an expected consensus.

关键词： Analytical models Social networking (online) Numerical analysis Computational modeling Ubiquitous computing Numerical models

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Deep quantile regression based wind generation and demand forecasts 11th

Deep quantile regression based wind generation and demand fo...

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11th international conference on Soft computing and Pattern Recognition, SoCPaR 2019, and 11th World Congress on Nature and Biologically Inspired computing, NaBIC 2019

作者： Kirthika, N. Ramachandran, K.I. Kottayil, Sasi K. Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India Center for Computational Engineering and Networking Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9783030493448

The widespread attention in the growth of clean energy for electricity production necessitates an accurate and reliable generation and demand forecasts. However, the decision-making process in electric power industry involves more uncertainty due to the transition towards distributed energy systems, which are not addressed in the conventional point forecasts. This paper proposes a probabilistic method termed as Deep Quantile Regression (DQR) for the construction of prediction intervals (PIs) that can potentially quantify uncertainty in the point forecasts of wind power generation and demand. The effectiveness of DQR is examined using the low and high seasonal wind and demand datasets. PIs with various confidence levels of 99%, 95% and 90% are estimated by constructing the appropriate quantiles using the proposed DQR method. The quantitative comparison of the quality in all the estimated PIs using the proposed method proves to outperform the other state-of-the-art methods. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Uncertainty analysis

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Convex Hull Formation for Programmable Matter 20

Convex Hull Formation for Programmable Matter

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21st international conference on distributed computing and networking (ICDCN)

作者： Daymude, Joshua J. Gmyr, Robert Hinnenthal, Kristian Kostitsyna, Irina Scheideler, Christian Richa, Andrea W. Arizona State Univ Comp Sci CIDSE Tempe AZ 85281 USA Univ Houston Dept Comp Sci Houston TX 77204 USA Paderborn Univ Dept Comp Sci Paderborn Germany TU Eindhoven Dept Math & Comp Sci Eindhoven Netherlands

ISBN: (纸本)9781450377515

We envision programmable matter as a system of nano-scale agents (called particles) with very limited computational capabilities that move and compute collectively to achieve a desired goal. Motivated by the problem of sealing an object using minimal resources, we show how a particle system can self-organize to form an object's convex hull. We give a distributed, local algorithm for convex hull formation and prove that it runs in O(B) asynchronous rounds, where B is the length of the object's boundary. Within the same asymptotic runtime, this algorithm can be extended to also form the object's (weak) O-hull, which uses the same number of particles but minimizes the area enclosed by the hull. Our algorithms are the first to compute convex hulls with distributed entities that have strictly local sensing, constant-size memory, and no shared sense of orientation or coordinates. Ours is also the first distributed approach to computing restricted-orientation convex hulls. This approach involves coordinating particles as distributed memory;thus, as a supporting but independent result, we present and analyze an algorithm for organizing particles with constant-size memory as distributed binary counters that efficiently support increments, decrements, and zero-tests - even as the particles move.

关键词： programmable matter self-organization distributed algorithms computational geometry convex hull restricted-orientation geometry

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IoT-Edge-Cloud computing Framework for QoS-Aware Computation Offloading in Autonomous Mobile Agents: Modeling and Simulation 1

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6th international conference on Mobile, Secure and Programmable networking, MSPN 2020

作者： Ismail, Leila Materwala, Huned Distributed Computing and Systems Research Laboratory Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University Al Ain Abu Dhabi15551 United Arab Emirates National Water and Energy Center United Arab Emirates University Al Ain Abu Dhabi15551 United Arab Emirates

ISBN: (数字)9783030675509

ISBN: (纸本)9783030675493

Edge-cloud computing is an emerging computational model that allows offloading of service requests by the autonomous mobile agents from the edge-server to the cloud-server. This is to reduce the network latency prevalent in the cloud-IoT model. However, Quality-of-Service (QoS)-Aware computation offloading in a heterogeneous and dynamic edge-cloud environment remains an open problem. In this paper, we propose a queuing theory-based edge-cloud computing framework for QoS-aware offloading in mobile autonomous agents. This framework model decides whether to execute an incoming request to the edge-server on the edge itself or to offload to one of the heterogeneous cloud servers such that the request’s execution time is the minimum. To model a request’s execution time, we consider the processing capabilities and the queues overheads of the edge and cloud servers, and the edge-cloud communications’ time. The details of the evaluation results, using dataset generated from real-life scenarios, are presented in the paper. © 2021, Springer Nature Switzerland AG.

关键词： Quality of service

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Message from conference Chairs

Proceedings - 22nd IEEE/ACIS International Conference on Sof...

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Proceedings - 22nd IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, networking and Parallel/distributed computing, SNPD 2021-Fall 2021年 VIII页

作者： Stenzel, Roland Yau, Her-Terng University of Applied Sciences Dresden Germany National Chin-Yi University of Technology Taiwan

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distributed Color-Based Particle Filter for Target Tracking in Camera Network 16th

Distributed Color-Based Particle Filter for Target Tracking ...

引用

16th EAI international conference on Collaborative computing: networking, Applications, and Worksharing, CollaborateCom 2020

作者： Jing, Yueqing Chen, Yanming Anhui University Hefei230000 China

ISBN: (纸本)9783030675394

Color-based particle filters have appeared in some literatures. However, there are still some important drawback in tracking targets, such as illumination changes, occlusion and low tracking accuracy. To solve these problems, in this paper, we propose a distributed color-based particle filter (DCPF) for target tracking, which can track targets accurately in a large-scale camera network with less data transmission and less computation. Compared with the previous algorithms, the algorithm proposed in this paper has two obvious advantages. First, the DCPF framework merges color features into the target’s state to obtain better robustness. Second, it considers the situation where the target is disappear in some cameras because of limited field of view (FoV). Convincing results are confirmed that the performance analysis of the proposed algorithm in this paper is very close to the centralized particle filter method. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Target tracking

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distributed Backup K-Placement and Applications to Virtual Memory in Wireless Networks 21

Distributed Backup K-Placement and Applications to Virtual M...

引用

22nd international conference on distributed computing and networking, ICDCN 2021

作者： Oren, Gal Barenboim, Leonid Beer Sheva Israel Open University of Israel Raanana Israel

ISBN: (纸本)9781450381840

The Backup Placement problem in networks in the distributed setting considers a network graph G = (V, E), in which the goal of each vertex v g V is selecting a neighbor, such that the maximum number of vertices in V that select the same vertex is minimized [9]. Previous backup placement algorithms suffer from obliviousness to main factors of heterogeneous wireless network. Specifically, there is no consideration of the nodes memory and storage capacities, and no reference to a case in which nodes have different energy capacity, and thus can leave (or join) the network at any time. These parameters are strongly correlated in wireless networks, as the load on different parts of the network can differ greatly, thus requiring more communication, energy, memory and storage. In order to fit the attributes of wireless networks, this work addresses a generalized version of the original problem, namely Backup K-Placement, in which each vertex selects K neighbors, for a positive parameter K. Our Backup K-Placement algorithm terminates within just one round. In addition we suggest two complementary algorithms which employ Backup K-Placement to obtain efficient virtual memory schemes for wireless networks. The first algorithm divides the memory of each node to many small parts. Each vertex is assigned the memories of a large subset of its neighbors. Thus more memory capacity for more vertices is gained, but with much fragmentation. The second algorithm requires greater round-complexity, but produces larger virtual memory for each vertex without any fragmentation. © 2021 ACM.

关键词： Wireless networks

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distributed Unsupervised Learning-Based Task Offloading for Mobile Edge computing Systems 15th

Distributed Unsupervised Learning-Based Task Offloading for ...

引用

15th EAI international conference on Communications and networking, ChinaCom 2020

作者： Wei, Jianming Liu, Qiuming Liu, Shumin Zeng, Yiping Xiong, Xin Department of Software Engineering Jiangxi University of Science and Technology Nanchang China

ISBN: (纸本)9783030677190

Mobile edge computing has emerged as a new paradigm to enhance computing capabilities by offloading complicated tasks to nearby cloud server. To conserve energy as well as maintain quality of service, algorithms with low time complexity for task offloading is required. In this paper, a multi-user with multiple tasks scenario is considered, taking full account of factors including data size, bandwidth, channel state information, we propose a distributed unsupervised learning-based offloading algorithm for task offloading, where distributed parallel networks are employed to guarantee the robustness of algorithm. Additionally, we exploit a memory pool to store input data and corresponding decisions as key-value pairs. Based on the experience mechanism, the proposed algorithm can omit the step of data calibration compared with supervised learning method. To further reduce the communication cost, we analyze four bandwidth allocation schemes. Results reveal that the channel state-based strategy cost 3% less than data size-based, mixed and user size-based. Besides, the proposed algorithm can save 14, 18% cost than local and edge schemes respectively. Numerous results show that the proposed algorithm can achieve near-optimal decisions timely as well as having high reliability. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Energy efficiency

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distributed MST: A Smoothed Analysis 20

Distributed MST: A Smoothed Analysis

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21st international conference on distributed computing and networking (ICDCN)

作者： Chatterjee, Soumyottam Pandurangan, Gopal Nguyen Dinh Pham Univ Houston Dept Comp Sci Houston TX 77204 USA

ISBN: (纸本)9781450377515

We study smoothed analysis of distributed graph algorithms, focusing on the fundamental minimum spanning tree (MST) problem. With the goal of studying the time complexity of distributed MST as a function of the "perturbation" of the input graph, we posit a smoothing model that is parameterized by a smoothing parameter 0 <= epsilon(n) <= 1 which controls the amount of random edges that can be added to an input graph G per round. Informally, epsilon(n) is the probability (typically a small function of n, e.g., n(-1/4)) that a random edge can be added to a node per round. The added random edges, once they are added, can be used (only) for communication. We show upper and lower bounds on the time complexity of distributed MST in the above smoothing model. We present a distributed algorithm that, with high probability,(1) computes an MST and runs in (O) over tilde (min{1/root epsilon(n)2(O(root log n)), D + root n}) rounds(2) where epsilon is the smoothing parameter, D is the network diameter and n is the network size. To complement our upper bound, we also show a lower bound of (Omega) over tilde (min{1/root epsilon(n), D + root n}). We note that the upper and lower bounds essentially match except for a multiplicative 2(O(root log n)) polylog(n) factor. Our work can be considered as a first step in understanding the smoothed complexity of distributed graph algorithms.

关键词： distributed algorithms smoothed analysis random model minimum spanning tree lower bound

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