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检索条件"任意字段=23rd International Conference on Distributed Computing and Networking, ICDCN 2022"

共 140 条记录，以下是51-60 订阅

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Message from the conference Chair

Message from the Conference Chair

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Summer Virtual conference on Software Engineering, Artificial Intelligence, networking and Parallel/distributed computing (SNPD-Summer), ACIS international

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Many-Constraint and Many-Objective Optimization with Bias Index for Intercloud Multi-Workflow Resource Provisioning 12

Many-Constraint and Many-Objective Optimization with Bias In...

引用

Joint 12th international conference on Soft computing and Intelligent Systems / 23rd international Symposium on Advanced Intelligent Systems (SCIS and ISIS)

作者： Powell, Courtney Miura, Katsunori Munetomo, Masaharu Hokkaido Univ Informat Initiat Ctr Sapporo Hokkaido Japan Otaru Univ Dept Informat & Management Sci Otaru Hokkaido Japan

ISBN: (纸本)9781665499248

Optimal deployment of multi-component big data applications is difficult in geo-distributed intercloud environments. This is because of the numerous infrastructure components and options available and the variety of constraints that must be satisfied, such as application, cloud infrastructure, data processing, and privacy-related constraints. The task becomes even more complicated when multiple scientific workflows must be executed with a severely limited resource-acquisition budget. This paper proposes a many-objective constrained optimization framework that addresses these issues. The proposed framework first conducts constraint satisfaction via equivalent transformation, then many-objective optimization using nondominated sorting, reference points, and elitism. In the case of multiple workflows, both optimization for each workflow and optimization for the ensemble of workflows are considered. Furthermore, a proposed bias index is presented that indicates on an objective-by-objective basis the effect of the configuration generated for each ensemble of workflows on the optimal configuration of each constituent workflow. It also provides a means of ascertaining on a granular level the relative fairness of each objective in each composite resource configuration, and can be used as a tool for prioritizing certain aspects of a workflow when deciding on the optimal configuration to utilize. We demonstrate the efficacy of the proposed framework through two genome analysis workflows, for which site availability and resource reliability need to be maximized, deployment cost and makespan need to be minimized, and several constraints must be satisfied.

关键词： bias index big data applications deployment constraint satisfaction equivalent transformation geo-distributed cloud multi-objective optimization multi-workflow optimization NSGA predicate logic specification

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The Rational for Developing Larger-scale 1000+Machine Emulation-based Research Test Beds

The Rational for Developing Larger-scale 1000+Machine Emulat...

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23rd international conference on Advanced Information networking and Applications Workshops

作者： Neville, Stephen W. Li, Kin Fun Univ Victoria Dept Elect & Comp Engn Victoria BC Canada

ISBN: (纸本)9781424439997

This position paper outlines the need and rational for developing large-scale emulation facilities structured to allow the scientific method tenets to be met on a per experiment basis. The work specifically focuses on the need to develop emulation-based test beds on the 1000+ machine scale, as expressed within the US. Defense Advanced Research Program Agency's (DARPA) BAA-08-43 Broad Agency Announcement of May 2008 for a National Cyber Range, the University of Victoria's Fall 2008 application to the Canadian Foundation for Innovation for a Canadian at-scale Emulation Laboratory (CASElab), and the recent HP-Intel-Yahoo global cloud computing test bed initiative. The work places these proposed large-scale facilities both within the general context of the standard research tools (i.e., analytical analysis, simulation studies, ad hoc testing, and smaller-scale emulation), as their placement against other available test beds, most notably Emulab, DETERlab, and PlanetLab.

关键词： large-scale computing systems at-scale emulation distributed test bed real-world applications

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Research of Seismic Streaming Storage Based on Druid 23

Research of Seismic Streaming Storage Based on Druid

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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： Gao, Bing Chen, Jie Zou, Qijie Qin, Jing School of Information Engineering Dalian University Dalian Key Laboratory of Smart Medical and Health Dalian China School of Software Engineerin Dalian University Dalian Key Laboratory of Smart Medical and Health Dalian China

ISBN: (纸本)9781665494571

Along with the growth of seismic observation networks, the amount of seismic observation data is also increasing rapidly with the form of fast arrival stream, and it is an important and challenging task to store seismic data in time. However, two bottlenecks (slow read/write speed, poor user concurrency) still make the practical applications difficult. We proposes an Apache Druid-based storage solution for seismic observation data streams. The solution is more adaptable to the read/write requirement of large-scale seismic data streams. Specifically, we achieve real-time observation for two aspects: (I) using Kafka as a distributed message exchange system;and (II) implementing accesses and exchange with massive seismic stream data onto the Kafka indexing service provided by Druid. The experimental results show that the Druid-based temporal data storage solution has better stream input and real-time query performance compared with the existed Hbase storage method. © 2021 IEEE.

关键词： Concurrent computing Smart cities Time series analysis Memory distributed databases Real-time systems Task analysis

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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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Design and Implementation of a distributed Control Platform for a Smart Building Testbed 23

Design and Implementation of a Distributed Control Platform ...

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作者： Puryear, Nathan Zaman, Mostafa Eini, Roja Abdelwahed, Sherif Virginia Commonwealth University Department of Electrical and Computer Engineering RichmondVA United States

ISBN: (纸本)9781665494571

One of the leading frontiers of the Internet of Things (IoT) era, smart building systems have made modern homes more innovative, interconnected, and autonomous. The goal of a smart home system is to enhance users' comfort, safety, and efficiency. In this paper, a smart building testbed is designed and constructed as a cyber-physical system that allows testing and validating building control algorithms, communication networks, and user interfaces. The building control unit is responsible for optimizing the performance of testbed actuators (thermal, lighting, and access systems), whereby building parameters are aggregated via a set of distributed sensors and communicated to a management system. This data is observed and analyzed by the control system to produce optimal control commands. The building communication network is developed based on the Message Queuing Telemetry Transport (MQTT) protocol, in which subscribers receive the measurement data, format it, and send it to the user-interface unit. The user interface is implemented in a Node-RED platform, where the data is visualized in real-time, and users are capable of interacting with the automation system. Experimental results demonstrate the usefulness of such a prototype for smart building monitoring and control research. © 2021 IEEE.

关键词： Smart buildings Smart homes Thermal sensors Thermal management Sensor systems Safety Internet of Things

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computing Amplification Factors for Influence on Social Network based on Learning of Behaviors and Interacted Knowledge Graph 23

Computing Amplification Factors for Influence on Social Netw...

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作者： Nguyen, Hien D. Tran, Quan M. Pham, Vuong T. Huynh, Tai University of Information Technology Faculty of Computer Science Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam Kyanon Digital Ho Chi Minh City Viet Nam Sai Gon University Faculty of Information Technology Ho Chi Minh city Viet Nam Ostrava Czech Republic

ISBN: (纸本)9781665494571

This presentation proposes a metric to estimate the influence of users and communities on Social Media Networks through the combining of Knowledge Graph and Deep Learning approaches. An unsupervised deep learning model is constructed to learn and explore the behavior of users based on Variational Graph Autoencoder (VGAE). It enhances to automatically extract from the relationships among users. The model is robust to unseen data and takes no labeling effort. The experiments show significant performance and promising results which are competitive and outperforms some well-known Graph-convolutional-based. The proposed approach is applied to measure the influence of users on the practical social network. This sudy also presents an architecture of a system to mange campaigns of digital marketing on social network. © 2021 IEEE.

关键词： Knowledge engineering Deep learning Measurement Social networking (online) Smart cities Computer architecture Data models

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An Energy Dispatch Mechanism Based on Double Auction with Multiple Rounds for a Microgrid 23

An Energy Dispatch Mechanism Based on Double Auction with Mu...

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作者： Liu, Weirong Ma, Cheng Cheng, Yijun Jiang, Fu Rong, Jieqi Peng, Jun School of Computer Science and Engineering Central South University Changsha China School of Automation Central South University Changsha China

ISBN: (纸本)9781665494571

In a microgrid, distributed energy resources (DERs) can supply energy for consumers. How to schedule energy between DERs and consumers and reduce the dependence on the main power grid is of extreme importance for a microgrid. In this paper, a multi-round double auction mechanism is proposed to achieve coordinated and optimal energy dispatch, which allows multiple sellers to trade energy with multiple buyers through adjusting prices dynamically in each round until the buyers' bids are not less than the sellers' asks. Different from existing auctions, the excessive energy of one seller can be divided and traded to multiple buyers, and one buyer can purchase the energy from multiple sellers. The simulation results show that the proposed mechanism significantly reduces auction rounds and the dependence on the main power grid and improves auction utility when compared with the existing double auction. © 2021 IEEE.

关键词： Schedules Smart cities Energy resources Simulation Microgrids distributed power generation Resource management

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A Deep Learning Approach for Intrusion Detection 23

A Deep Learning Approach for Intrusion Detection

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作者： Dhahbi, Roua Jemili, Farah University of Sousse Hammam Sousse4011 Tunisia University of Sousse Mars Research Lab LR17ES05 Hammam Sousse4011 Tunisia

ISBN: (纸本)9781665494571

Intrusion detection has been widely studied in both industry and academia, but cybersecurity analysts always want more accuracy and global threat analysis to secure their systems in cyberspace. Big data represent the great challenge of intrusion detection systems, making it hard to monitor and analyze this large volume of data using traditional techniques. Recently, deep learning has been emerged as a new approach which enables the use of Big Data with a low training time and high accuracy rate. In this paper, we propose an approach of an IDS based on cloud computing and the integration of big data and deep learning techniques to detect different attacks as early as possible. To demonstrate the efficacy of this system, we implement the proposed system within Microsoft Azure Cloud, as it provides both processing power and storage capabilities, using a convolutional neural network (CNN-IDS) with the distributed computing environment Apache Spark, integrated with Keras Deep Learning Library. We study the performance of the model in two categories of classification (binary and multiclass) using CSE-CIC-IDS2018 dataset. Our system showed a great performance due to the integration of deep learning technique and Apache Spark engine. © 2021 IEEE.

关键词： Deep learning Training Industries Cloud computing Intrusion detection Cluster computing Big Data

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Rethinking Deep Packet Inspection Design and Deployment in the era of SDN and NFV 23

Rethinking Deep Packet Inspection Design and Deployment in t...

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作者： Mustapha, Hanan Djahel, Soufiene Perry, Philip Zhang, Zonghua Manchester Metropolitan University Glasgow United Kingdom Ulster University Glasgow United Kingdom Huawei France Research Center Paris France

ISBN: (纸本)9781665494571

With the advent of Software-Defined networking (SDN) and Network Functions Virtualization (NFV), the design and deployment of DPI (Deep Packet Inspection) must be reconsidered. The programmability, global visibility and centralized control of SDN, as well as the NFV enabled lightweight service creation and migration, have potential to empower the capability of DPI tools. On the other hand, dynamic environments make the deployment of DPI challenging. Although it has been validated that some security functions like firewall, and Intrusion Detection System (IDS) can be implemented in SDN controllers or NFV, it remains unclear whether or not DPI can be done in the similar way considering its sophisticated interactions with the network traffic packets, especially for the stateful protocols and encrypted traffic. In other words, the design and deployment of DPI in an SDN and NFV architecture would not be as straightforward. Therefore, this paper aims to shed the light on the challenges facing DPI design and deployment in the context of SDN and NFV and propose a solution to overcome them. © 2021 IEEE.

关键词： Protocols Firewalls (computing) Intrusion detection Telecommunication traffic Inspection Network function virtualization Cryptography

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