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Multi-objective distributed Clustering Algorithm in Wireless Sensor Networks Using the Analytic Hierarchy Process

Multi-objective Distributed Clustering Algorithm in Wireless...

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

作者： Jingxia Zhang Ruqiang Yan The School of Instrument Science and Engineering Southeast University Nanjing China

In wireless sensor networks, unbalanced energy consumption may shorten network lifespan. In this paper, a multi-objective distributed clustering algorithm using the analytic hierarchy process is developed to ensure that the energy expenditure of the cluster head nodes is balanced and the network lifespan is enhanced. By adopting the analytic hierarchy process model, our proposed algorithm aggregates multiple factors such as the node energy, the node centrality, and the node degree to search for an optimal clustering structure. Furthermore, a super cluster head is selected among the cluster head nodes based on the distance from the cluster head to the base station, which further minimizes the energy dissipation. Simulation results indicate that the proposed algorithm outperforms the other existing ones in terms of clustering structure and network lifespan.

关键词： Clustering algorithms Wireless sensor networks Analytic hierarchy process Computational modeling Energy dissipation Fuzzy logic Measurement

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Time-sensitive-aware scheduling traffic (TSA-ST) algorithm in software-defined networking 12th

Time-sensitive-aware scheduling traffic (TSA-ST) algorithm i...

引用

12th international conference on Internet and distributed computing Systems, IDCS 2019

作者： Haur, Ng Kean Chin, Tan Saw Multimedia University CyberjayaSelangor63310 Malaysia

ISBN: (纸本)9783030349134

Time-sensitive-aware scheduling traffic system is capable to eliminate the queuing delay in the network that resulting hard real-time guarantees. Hence, this article aims to develop a time-sensitive-aware scheduling traffic system which is able to avoid multiple time-sensitive flows from conducting in the same path simultaneously so that the queueing delay can be eliminated. Under this prologue, an algorithm Time-Sensitive-Aware Scheduling Traffic (TSA-ST) is proposed to reduce the time complexity in the transmission schedule while maintaining the quality of the scheduling system. In the end, the transmission schedule will be computed in different network topologies to evaluate the performance and accuracy. © Springer Nature Switzerland AG 2019.

关键词： Cyber Physical System

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The Public Sentiment analysis within Big data distributed system for Stock market prediction– A case study on Colombo Stock Exchange

The Public Sentiment analysis within Big data Distributed sy...

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international conference on Information Technology Research (ICITR)

作者： M.V.D.H.P Malawana R. M. K. T Rathnayaka Sabaragamuwa university of Sri Lanka Belihuloya Sri Lanka

ISBN: (数字)9781665414753

ISBN: (纸本)9781665414760

Stock price prediction plays an important role on the journey of investors on the stock market. The prices of the company stocks on the market are performed by different deliverables. Social media data sets, news sites, feedback and reviews are some kind of online tools that can affect the stock market. It is often worth using this context to predict the performance of market shares. We take the advantage of Sentiment analysis on Market related announcement and respective public opinions for stock market trend predictions for more accurate recommendations. Sentiment Analysis is a machine learning program for extracting opinions from a text section that is designed to support any product, company, individual or other entity (positive, negatively, neutral). In this research calculations and data processing were performed within machine learning approach with use of Spark model on Google cloud platform. Among most of the stock prediction researches, only few researchers have done their researches on sentiment analysis within big data distributed environment. Logistic Regression and Naïve Bayes perform well in sentiment classification. Main finding of this research is that public opinion significantly influences the fluctuations of market forces and economic factors such as monetarism, government reforms, unforeseen pandemics, interest rates, public trust, and faith in bond market trust. The detection of the feelings pattern will enhance the market prediction as it ensures the consistency of decision.

关键词： Social networking (online) Stock markets Cloud computing Blogs Internet Sparks Companies

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Development and Reconstitution of Software Quality Measurement and Evaluation Standards 19

Development and Reconstitution of Software Quality Measureme...

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19th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, networking and Parallel/distributed computing (SNPD)

作者： Zhang, Yangyang Liu, Xiaojian Liu, Zengzhi Li, WenPeng China Elect Standardizat Inst Software Engn & Appraisal Ctr Beijing Peoples R China

ISBN: (纸本)9781538658895

How to measure and evaluate software quality is one important research subject in the computer software field. For helping people understand, measure and evaluate software quality, international Organization for Standardization(ISO), has been carrying out years of researches on software quality standardization. The thoughts and methods shown in standardization will help people further understand and predict software quality easier. This paper introduces the development process of the international quality standards and gives more focus on the software quality development trends.

关键词： software quality international standards quality model quality characteristics measurement

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Time-aware reactive storage in wireless edge environments 19

Time-aware reactive storage in wireless edge environments

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Proceedings of the 16th EAI international conference on Mobile and Ubiquitous Systems: computing, networking and Services

作者： João A. Silva Hervé Paulino João M. Lourenço João Leitão Nuno Preguiça Universidade NOVA de Lisboa Caparica Portugal

ISBN: (纸本)9781450372831

Nowadays, smart mobile devices generate huge amounts of data in all sorts of gatherings. Much of that data has localized and ephemeral interest, but can be of great use if shared among co-located devices. However, these devices often experience poor connectivity, leading to availability issues if applications' storage and logic are fully delegated to a remote cloud infrastructure. In turn, the edge computing paradigm pushes computations and storage beyond the data center, closer to end-user devices where data is generated and consumed. Thus, enabling the execution of certain components of edge-enabled systems directly and cooperatively on edge devices. In this paper, we address the challenge of supporting reliable and efficient data storage and dissemination among co-located wireless mobile devices without resorting to centralized services or network infrastructures. We propose Thyme, a novel time-aware reactive data storage system for wireless edge networks, that exploits synergies between the storage substrate and the publish/subscribe paradigm. We present the design of Thyme and evaluate it through simulation, characterizing the scenarios best suited for its use. The evaluation shows that Thyme allows for reliable notification and retrieval of relevant data with low overhead and latency.

关键词： edge computing distributed storage mobile devices publish/subscribe wireless networks

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Hieff: Enabling Efficient VNF Clusters by Coordinating VNF Scaling and Flow Scheduling

Hieff: Enabling Efficient VNF Clusters by Coordinating VNF S...

引用

IEEE international conference on Performance, computing and Communications (IPCCC)

作者： Zenan Wang Jiao Zhang Haoran Wei Tao Huang State Key Laboratory of Networking and Switching Technology BUPT China Purple Mountain Laboratories Nanjing China

ISBN: (数字)9781728198293

ISBN: (纸本)9781728198309

A cluster of Virtual Network Functions (VNF) can serve massive fluctuating traffic by managing VNF instances and distributing flows. However, how to schedule the flows and manage VNF scaling efficiently in a VNF cluster is still an open question. Existing solutions such as hash based schemes encounter imbalance and passive flow remapping obstacles while flow table-based scheme suffers from high processing latency and flow entries overflow challenges. In this paper, we design and present Hieff, an efficient NFV system that coordinates VNF scaling and flow scheduling within a VNF cluster. The key idea of Hieff is to precisely manage the heavy flows with a flow table while simply allowing light flows be distributed by hash. Though this idea has been explored in previous work, we are the first to apply it with the VNF scaling process. We mathematically model the Hieff system and propose a heuristic algorithm to determine the optimized VNF scaling and flow scheduling strategies. We implement Hieff based on BESS and Click and use real-world tracing to evaluate the system. Results show that Hieff can handle co-existing massive flows efficiently with low latency while balancing the load of VNF instances at low cost.

关键词： Schedules Processor scheduling Heuristic algorithms conferences Scheduling Mathematical model Load modeling

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DAD-MCNN: DDoS Attack Detection via Multi-channel CNN 19

DAD-MCNN: DDoS Attack Detection via Multi-channel CNN

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11th international conference on Machine Learning and computing (ICMLC)

作者： Chen, Jinyin Yang, Yi-tao Hu, Ke-ke Zheng, Hai-bin Wang, Zhen Zhejiang Univ Technol Coll Informat Engn Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781450366007

With the continuous development of web services, the web security becomes more and more important. distributed Denial of Service (DDoS) attack as one of the most common form of attacks, has produced serious economic damages. DDoS attack detection as one of main defense methods is suffered increasing attention by researchers. Most of them use machine learning methods to make good detection performance. However, there are still gaps between real detection rate and expected one, conventional machine learning methods are limited compared with deep learning. In this paper, we propose DAD-MCNN, a multi-channel CNN(MC-CNN) based DDoS attack detection framework, which can fully utilize information from a huge amount of network packages and set up an earlier warning system. Our contributions can be summarized as follows: (1) we propose a new preprocessing method for the network dataset (2) MC-CNN is applied to detect DDoS attack and the detection result is decided by data in respective channels. (3) We use incremental training method to optimize training procedures and time in MC-CNN. (4) The experiment result shows that MC-CNN has the highest accuracy compared with conventional machine learning methods. The result also proves that our approach has performed well not only in DDoS attack detection but also in other anomaly attack detection.

关键词： DDoS attack detection networking and information security multi-channel deep learning

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An Efficient distributed Approach for Load Balancing in IoT Based on SDN Principles

An Efficient Distributed Approach for Load Balancing in IoT ...

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international conference on computing and networking Technology (ICCNT)

作者： Zahra Eghbali Mina Zolfy Lighvan Arezoo Beheshti Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran

Internet of things is a new technology which is heavily affecting different aspects of human life. The number of smart devices connecting to IoT and the amount of data gathered or produced by these devices are increasing. In order to organize, secure and analyse the IoT data, novel and creative ideas for IoT design and management are required. Software Defined networking is a new and promising paradigm. Its main idea is to decouple the control functions from physical devices and set them inside a logically centralized control layer. In this paper, a distributed approach is proposed for accelerating data management and balancing the load between IoT devices based on SDN principles. The proposed framework makes it possible to apply different management strategies in a distributed manner. Experimental results indicate that our scheme distributes tasks between devices equally and exhibits a reduction in the average turnaround time and the average waiting time and it will improve the processing performance.

关键词： Internet of Things Computer architecture Task analysis Load management Scalability Logic gates Acceleration

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Power Allocation in Multi-cell System Using distributed Deep Neural Network Algorithm

Power Allocation in Multi-cell System Using Distributed Deep...

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IEEE international conference on Wireless and Mobile computing, networking And Communications (WiMob)

作者： Minghui Zhang Ming Chen National Mobile Communications Research Laboratory Southeast University Nanjing China

ISBN: (纸本)9781728133171

This paper proposes a DNN-based distributed algorithm by deploying one DNN in each base station controller (BSC) to approximate the weighted minimum mean-square error (WMMSE) algorithm, which can allocate power in parallel. Maximizing the weighted sum-rate is a common problem setup for power allocation in a single-input single-output (SISO) interfering broadcast channel (IBC). The WMMSE algorithm is a suboptimal and classical solution but has high computational complexity. Recently, a DNN-based algorithm is proposed to speed up the power allocation by approximating the WMMSE algorithm. Motivated by these, a DNN-based distributed algorithm is proposed and the system with 7 cells and 56 users is setup. The experimental results show that centralized DNN with at least 7 layers can achieve the sum-rate performance of 95.02%, but distributed DNN with only 5 layers can achieve the sum-rate performance of 97.40%.

关键词： Approximation algorithms Training Resource management Neural networks Interference Complexity theory Wireless communication

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A Reverse Auction Incentive Mechanism Based on the Participant’s Behavior in Crowdsensing 2nd

A Reverse Auction Incentive Mechanism Based on the Participa...

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2nd EAI international conference on Security and Privacy in New computing Environments, SPNCE 2019

作者： Zhou, Tao Jia, Bing Li, Wuyungerile Inner Mongolia A.R. Key Laboratory of Wireless Networking and Mobile Computing Hohhot010021 China College of Computer Science Inner Mongolia University Hohhot010021 China

ISBN: (纸本)9783030213725

Crowdsensing has been integrated into many aspects of human life. Compared with the general mode of perception which need to arrange a large number of sensors in advance, crowdsensing uses the idea of crowdsourcing to distribute tasks to participants carrying mobile sensing devices with them, which can save the cost of deploying sensing nodes. Therefore, how to make people actively participate in perception has become a hot issue. The existing incentives mainly include bonus incentives, game entertainment incentives, and social relationship incentives. This paper proposes a reverse auction incentive mechanism based on the participant’s behavior. Specifically, we analyze the user’s behavior and build a model of participant competency assessment firstly;then, according to the above analysis, each user is scored and the reward is distributed using the improved reverse auction algorithm. The experimental results show the effect of the proposed method. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Electronic commerce

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