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检索条件"任意字段=International Conference on Parallel Distributed and Grid Computing"

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Intrusion detection and prevention system using cuckoo search algorithm with ANN in cloud computing 6

Intrusion detection and prevention system using cuckoo searc...

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6th international conference on parallel, distributed and grid computing, PDGC 2020

作者： Gupta, Anushikha Kalra, Mala NITTTR Dept. of Computer Science and Engineering Chandigarh India

ISBN: (纸本)9781728171326

The Security is a vital aspect of cloud service as it comprises of data that belong to multiple users. Cloud service providers are responsible for maintaining data integrity, confidentiality and availability. They must ensure that their infrastructure and data are protected from intruders. In this research work Intrusion Detection System is designed to detect malicious server by using Cuckoo Search (CS) along with Artificial Intelligence. CS is used for feature optimization with the help of fitness function, the server's nature is categorized into two types: normal and attackers. On the basis of extracted features, ANN classify the attackers which affect the networks in cloud environment. The main aim is to distinguish attacker servers that are affected by DoS/DDoS, Black and Gray hole attacks from the genuine servers. Thus, instead of passing data to attacker server, the server passes the data to the genuine servers and hence, the system is protected. To validate the performance of the system, QoS parameters such as PDR (Packet delivery rate), energy consumption rate and total delay before and after prevention algorithm are measured. When compared with existing work, the PDR and the delay have been enhanced by 3.0 %and 21.5 %. © 2020 IEEE.

关键词： Neural networks

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A Novel distributed Differential Privacy Preserving Based on Random Forest in Data Centers 9th

A Novel Distributed Differential Privacy Preserving Based on...

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9th international conference on Information Technology and Quantitative Management, ITQM 2022

作者： Wang, Xi Fan, Weibei He, Jing Chi, Chi-Hung Suzhou Institute of Industrial Technology Suzhou215006 China College of Computer Nanjing University of Posts and Telecommunications Nanjing210003 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130012 China Department of Neuroscience University of Oxford OxfordOX1 3QR United Kingdom School of Computer Nanyang Technological University Nanyang Avenue 639798 Singapore

Traditional privacy-preserving technologies have been unable to provide adequate protection and are vulnerable to background knowledge. MapReduce is parallel distributed computing model which has the advantages of good scalability and high fault tolerance. In this paper, we design a differential privacy protection based on MapReduce for the security problems faced in the distributed environment. Firstly, we propose a random forest algorithm DPMRRF that satisfies differential privacy under the MapReduce framework. Secondly, we use the MapReduce framework in the Hadoop platform to make the classification results satisfy differential privacy by adding random noise values to the leaf nodes. Finally, through the design of the feature selection scheme combined with the index mechanism, three different privacy budget allocation methods are adopted, namely, equal distribution, equal distribution and equal distribution. Experiments show that the algorithm has better classification accuracy while ensuring data availability. The proposed algorithm effectively improves the classification accuracy and operating efficiency, and greatly reduces the amount of computation. © 2022 The Authors. Published by Elsevier B.V.

关键词： MapReduce

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Dynamic Analysis of Solar Heat Stimulated Residential Absorption Cooling with Integrated Thermal Wall for Space Heating 7

Dynamic Analysis of Solar Heat Stimulated Residential Absorp...

引用

7th international conference on Smart and Sustainable Technologies, SpliTech 2022

作者： Kalair, Ali Raza Seyedmahmoudian, Mehdi Mekhilef, Saad Stojcevski, Alex School of Science Computing and Engineering Technologies Swinburne University of Technology VIC3122 Australia

ISBN: (纸本)9789532901160

Decentralized trigeneration (solar heating-cooling) for residential and commercial applications is being researched and adapted extensively. The transition from traditional uni-directional grids to bidirectional smart grids has motivated energy engineers to develop novel decentralized architectures that fully exploit distributed generation technologies. Solar heat and light stimulated trigeneration system is modeled, simulated, and analyzed over one year for subtropical climate conditions of Melbourne, Australia. The architecture replaces an electrical compressor of traditional chillers with solar heat stimulated absorption chiller. A residential building is scheduled as per standard living trends of a family of 5 individuals. The goal was to maintain livable thermal conditions (PID controlled: 26Â°C) and meet essential electronic needs at best. A detailed thermal and electrical performance analysis is documented using parameters such as solar fraction, collector thermal efficiency, fractional non-purchased energy, and others. The architecture was designed to meet all energy loads, thermal and electrical, with minimal auxiliary or grid energy expenditure. The analysis revealed that this unique combination of active and passive solar electro-thermal technologies has the potential to improve the overall performance and save considerable space for residential build environments. The solar photovoltaics produced power in the range 200 kW to 519 kW, active solar evacuated tube collectors produced hot water in the range 60-80Â°C, and passive solar thermal wall recorded storing heated air up to 70Â°C in summers and 40Â°C in winters. Heated water passed through solar heat stimulated absorption chillers to produce chilled air in range 17-19Â°C. An excess of 1500 watts on some summer days was recorded while no excess was available in peak winters. Solar fraction and fractional non-purchased energy showed slightly better performance than the same systems without a thermal wall

关键词： Passive solar

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Energy routing strategy of cold and heat networks in integrated energy stations 4

Energy routing strategy of cold and heat networks in integra...

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4th IEEE international conference on Renewable Energy and Power Engineering, REPE 2021

作者： Yu, Qingguang Li, Le Jiang, Zhicheng Li, Xiaoyu Chen, Zhuoxu Ren, Jiali Chen, Yixuan Wei, Che Tsinghua University Dept. of E. E. Beijing China CNOOC Research Institute Beijing China

ISBN: (纸本)9781665443715

With the access of large-scale renewable energy sources and distributed power sources, the importance of building an energy internet with internet technology as the core to optimally coordinate and control the distributed renewable energy infrastructure settings through an energy management system in order to optimally complement multiple energy sources, such as electricity, cooling, heat and water, continues to be highlighted. This paper proposes an energy routing strategy based on the interoperability of the cold and heat pipeline networks of distributed energy stations, firstly using a neural network method to make short-Term predictions of the cooling and heating loads, and carrying out optimal scheduling before the integrated energy station day according to the prediction results;then carrying out a heat and pressure balance analysis of the cooling and heating system, adding a pipeline network loss constraint on the basis of the scheduling model;finally using a message queue telemetry transmission communication Finally, a message queue telemetry communication protocol is used to achieve efficient information security transfer and ensure smooth internal calls and external access to the edge server. © 2021 IEEE.

关键词： Edge computing

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A distributed Density-grid Clustering Algorithm for Multi-Dimensional Data 10

A Distributed Density-Grid Clustering Algorithm for Multi-Di...

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10th Annual computing and Communication Workshop and conference (CCWC)

作者： Brown, Daniel Shi, Yong Kennesaw State Univ Coll Comp & Software Engn Marietta GA 30060 USA

ISBN: (纸本)9781728137834

In recent years there have been many massive leaps in technology that have also resulted in large advancements in how we collect and use data. These advancements have caused a rise in the prominence of the field of Big Data. Organizations and businesses rely heavily on data analysis in almost every field of work. This need for data analysis combined with larger and more complex datasets has caused many challenges for these groups as they seek to keep up. Clustering is a field of data analysis, specifically unsupervised machine learning, that is heavily used in many different industries. Traditional clustering algorithms typically suffer in performance and accuracy as datasets increase in size and dimensionality. We previously proposed a new clustering algorithm called the Fast Density-grid clustering algorithm that successfully alleviated some of the problems related to runtimes. In modern data analysis however, serial algorithms are still too slow to be of much use. The Fast Density-grid algorithm was originally designed with parallelization in mind, and this paper discusses the steps taken to implement this. Our experimental results show that, when the number of records in the dataset exceed a certain amount, the parallel form of the algorithm overtakes the traditional in performance. Studying this critical point allows us to determine whether or not the algorithm is suitable for real world use.

关键词： Clustering Density-Based Clustering grid-Based Clustering parallel computing distributed computing Apache Spark

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Impact of distributed Generation on Distribution System Under Fault and Islanding Condition 2nd

Impact of Distributed Generation on Distribution System Unde...

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2nd international conference on Power Engineering, computing and Control, PECCON 2019

作者： Harish Kumar, Pujari Mageshvaran, R. Baleboina, Guru Mohan Vasavi, Koppola School of Electrical Engineering Vellore Institute of Technology VelloreTamil Nadu632014 India Department of Electrical and Electronics Engineering East Point College of Engineering Bangalore India

ISBN: (纸本)9789811572401

The energy drawn from the wind power plant and photovoltaics is considered to be essential sources in the recent distributed generation (DG) of electrical power. Since a day-to-day load demand for electricity is increasing rapidly and therefore the generation of power, needs to be improved for balancing the current demand. Because of this growing demand, non-renewable energy sources are on the brink of extinction. In order to solve this problem, the concept of integration of renewable energy sources has been introduced in the electrical distribution system and thereby improves the power quality and reliability to meet out the existing needs of the customers. Hence, the concept of installation of the DG has an impact on the operation and characteristics of the electrical distribution system. Installing the DG units near to the load centers may solve the basic problems such as power losses and voltage drops. The overall system is simulated in MATLAB environment in which, the three-phase grid-connected photovoltaic system is integrated with the parallel loads. The outputs are being measured in the form of the power, voltage and current at various points in the existing system and are analyzed in both the normal and faulty conditions. At Point of Common Coupling (PCC), variations in voltage and current under different types of fault conditions, intentional islanding and nuisance tripping of load cases are analyzed without protection device. © 2021, Springer Nature Singapore Pte Ltd.

关键词： distributed power generation

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Agriculture monitoring and prediction using Internet of Things (IoT) 6

Agriculture monitoring and prediction using Internet of Thin...

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6th international conference on parallel, distributed and grid computing, PDGC 2020

作者： Saini, Mohit Kumar Saini, Rakesh Kumar School of Computing DIT University Dehradun Uttarakhand India

ISBN: (纸本)9781728171326

Agriculture has become the most significant growing sector all over the world because of increasing the population. The main challenge in the agriculture industry is to improving farming efficiency and quality without constant physical monitoring to full fill the speedily increasing demand for the food. Apart from the mounting population, the climate circumstance is also a huge challenge in the agricultural industry. The aim of this research paper is to propose a smart farming model based on the Internet of Things using the clustering to deal with the adverse condition. in this model, we use the different types of the sensors like soil moisture, air pressure, rain detection and humidity sensors for a different purpose. The data will collect on the cloud and calculated automatically. The smart agriculture can be adopted from the crop control, collection of useful data, and analysis automatically. The purpose of this paper is how the implement the Internet of Things (IoT) in the monitoring of humidity, soil condition, temperature, and supply water to the field, level of water, climate condition. The IoT based Smart Farming System being planned via this report is integrated with different Sensors and a Wi-Fi module producing live data feed that can be obtained online. © 2020 IEEE.

关键词： Internet of things

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DAPES: Named Data for Off-the-grid File Sharing with Peer-to-Peer Interactions 40

DAPES: Named Data for Off-the-Grid File Sharing with Peer-to...

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40th IEEE international conference on distributed computing Systems (ICDCS)

作者： Mastorakis, Spyridon Li, Tianxiang Zhang, Lixia Univ Nebraska Omaha NE 68182 USA Univ Calif Los Angeles Los Angeles CA 90024 USA

ISBN: (纸本)9781728170022

This paper introduces DAta-centric Peer-to-peer filE Sharing (DAPES), a data sharing protocol for scenarios with intermittent connectivity and user mobility. DAPES provides a set of semantically meaningful hierarchical naming abstractions that facilitate the exchange of file collections via local connectivity. This enables peers to "make the most" out of the limited connection time with other peers by maximizing the utility of individual transmissions to provide data missing by most connected peers. DAPES runs on top of Named-Data Networking (NDN) and extends NDN's data-centric network layer abstractions to achieve communication over multiple wireless hops through an adaptive hop-by-hop forwarding/suppression mechanism. We have evaluated DAPES through real-world experiments in an outdoor campus setting and extensive simulations. Our results demonstrate that DAPES achieves 50-71% lower overheads and 15-33% lower file sharing delays compared to file sharing solutions that rely on IP-based mobile ad-hoc routing.

关键词： Data distribution Off-the-grid file sharing Named Data Networking

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Control of Multiple PV Integrated parallel Inverters for Microgrid Applications 3

Control of Multiple PV Integrated Parallel Inverters for Mic...

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3rd IEEE international conference on Power, Instrumentation, Control and computing, PICC 2020

作者： Singh, Yashi Singh, Bhim Mishra, Sukumar Indian Institute of Technology Delhi Department of Electrical Eng. New Delhi110016 India

ISBN: (纸本)9781728175904

To enhance the accessibility and reliability for a distributed generation system (DGS), a grid-tied photovoltaic (PV) generation system based on multiple parallel connected PV-inverters is developed for microgrid application in this work. This microgrid is designed to operate in the grid tied mode (GTM) as well as a standalone mode (SAM) and vice-versa. Here, a grid-forming inverter (GFI) technology is utilized for system with high penetration of renewables. The single stage PV-battery interfaced GFI inverter in parallel with a PV array supported inverters is considered to operate in the GTM as well as in (SAM) of operation. In SAM, the grid forming inverter maintains constant voltage and frequency across the load The control strategies of each unit are independent and using multi-loop controllers with switching logic. In the GTM, each PV panel in DGS is interfaced with an inverter with independent maximum power point tracking (MPPT) to harvest maximum power. The battery supports the PV units during peak load periods and maintains the power balance in the microgrid. Controlled charging and discharging profile of the battery is achieved by a DC-DC bidirectional converter (DBC). The control strategy of microgrid is verified with simulated results in detail. © 2020 IEEE.

关键词： Solar panels

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Improved MapReduce Load Balancing through Distribution-Dependent Hash Function Optimization 26

Improved MapReduce Load Balancing through Distribution-Depen...

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26th IEEE international conference on parallel and distributed Systems (IEEE ICPADS)

作者： Ahmad, Zafar Duppala, Sharmila Chowdhury, Rezaul Skiena, Steven SUNY Stony Brook Dept Comp Sci Stony Brook NY 11794 USA Univ Maryland Dept Comp Sci College Pk MD 20742 USA

ISBN: (纸本)9781728190747

Load balancing of skewed data in MapReduce systems like Hadoop is a well-studied problem. Many heuristics already exist to improve the load balance of the reducers thereby reducing the overall execution time. In this paper, we propose a lightweight optimization approach for MapReduce systems to minimize the makespan for repetitive tasks involving a typical frequency distribution. Our idea is to analyze the observed frequency distribution for the given task so as to identify an optimal offset parameter c to add in the hash function to minimize makespan. For two different bucketing methods - modulo labeling and consecutive binning - we present efficient algorithms for finding the optimal value of c. Finally, we present simulation results for both bucketing methods. The results vary with the data distribution and the number of reducers, but generally reduce makespan by 20% on average for power-law distributions, Results are confirmed with experiments on well-known real-world data sets.

关键词： Load Balancing Hashing MapReduce Hadoop Cloud computing Apache Spark distributed-memory Cluster computing

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