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distributed Consensus Problem in Federated Learning Paradigm 23

Distributed Consensus Problem in Federated Learning Paradigm

引用

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： Yan, Xin Qin, Yiming Hu, Xiaodong School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China The University of Hong Kong The Faculty of Education Hong Kong Hong Kong

ISBN: (纸本)9781665494571

Federated learning (FL) framework facilitates more and more applications of deep learning algorithms on the existing network architectures, where the model parameters are aggregated in a centralized manner. However, some of FL participants are often inaccessible, such as in a power shortage or device dormant state. That will force us to explore the probability that the parameter aggregation is operated in an ad hoc manner, which is based on consensus computing. In this paper, we first propose a novel FL paradigm, which supports an ad hoc operation mode for FL participants. Second, a discrete-time dynamic equation and its control law are formulated to satisfy the demands from FL framework, with a quantized caching scheme designed to mask the uncertainties from asynchronous updates and measurement noises. Then, the consensus conditions and the convergence of the consensus protocol are deduced analytically, and a strategy of quantized caching to optimize the convergence speed is provided. Last, the theoretical results are validated by numerical simulations. © 2021 IEEE.

关键词： Uncertainty Smart cities Delay effects Packet loss Collaborative work Particle measurements Numerical simulation

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Efficiently Managing Large-Scale Keys in HDFS 23

Efficiently Managing Large-Scale Keys in HDFS

引用

作者： Jin, Wei Geng, Kui Yu, Mingjie Guo, Yunchuan Li, Fenghua Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China School of Cyber Security University of Chinese Academy of Sciences Beijing100049 China School of Cyber Security University of Science and Technology of China Hefei230027 China

ISBN: (纸本)9781665494571

To transparently encrypt/decrypt data stored in Hadoop distributed File System (HDFS), the Key Management Server (KMS) has been designed to automatically assign encryption zone keys (EZK) to encryption zones. However, the current key-management scheme suffers from performance bottleneck. In this paper, dividing key files for storing key data into metadata file and material file, we propose a memory-disk coordinated key management architecture for Hadoop EZK to manage massive keys, where a tree structure is designed to index key metadata stored in memory, and the inverted index structure is used to record materials stored on hard disk. Further balance-tree-based management algorithms without Java serialization is designed to efficiently query keys (including metadata and materials). A series of theoretical analysis are conducted to show the upper and lower boundary of metadata query. Finally, we implement the above scheme in the Hadoop KMS without modifying the original key-management interfaces. A series of experiments are carried out on the simulated data. Experimental results show that, our scheme can efficiently manage ten billion keys and perform much better than the existing KMS in Hadoop. © 2021 IEEE.

关键词： Java Smart cities File systems Memory management distributed databases Metadata Hard disks

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distributed data-driven engine framework facing CPS brain-inspired intelligent transportation 23

Distributed data-driven engine framework facing CPS brain-in...

引用

作者： Yang, Zhengzhuang Xu, Mingyue Zhao, Kaidi Yang, Chao Zhi, Huiyu Zhang, Xihou Chen, Zhuoran Qiu, Song Han, Dingding School of Information Science and Technology Fudan University Shanghai China School of Communication and Electronic Engineering East China Normal University Shanghai China

ISBN: (纸本)9781665494571

Single data source, isolated data islands and low information utilization in intelligent transportation lead to the poor inversion of the cyber space to the physical space including Incomplete data integration, high interdependency of systems and poor anti-control ability. In this paper the data-driven method is adopted to optimize the W parameter in Webster method to reduce the waiting time of vehicles to realize the traffic congestion. In particular, a multi-source heterogeneous data processing method and a unified modeling of the multi-dimensional and multi-layer networks have been introduced. By data-driven engine, we have implemented both massive storage and fast processing system. We have also build a service system which can rapidly realize data integration and services delivery as well as be directly called by researchers from the database through network requests to reduce the data reprocessing. This paper also produces the data interaction process of the data engine framework in traffic management and control, and proposes a solution for the use of massive city data. © 2021 IEEE.

关键词： Smart cities Soft sensors Transportation Data integration Process control distributed databases Data models

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Appraising SPARK on Large-Scale Social Media Analysis 1

引用

23rd international conference on Parallel and distributed computing (Euro-Par)

作者： Belcastro, Loris Marozzo, Fabrizio Talia, Domenico Trunfio, Paolo Univ Calabria DIMES Arcavacata Di Rende Italy

ISBN: (数字)9783319751788

ISBN: (纸本)9783319751788;9783319751771

Software systems for social media analysis provide algorithms and tools for extracting useful knowledge from user-generated social media data. ParSoDA (Parallel Social Data Analytics) is a Java library for developing parallel data analysis applications based on the extraction of useful knowledge from social media data. This library aims at reducing the programming skills necessary to implement scalable social data analysis applications. This work describes how the ParSoDA library has been extended to execute applications on Apache Spark. Using a cluster of 12 workers, the Spark version of the library reduces the execution time of two case study applications exploiting social media data up to 42%, compared to the Hadoop version of the library.

关键词： Social data analysis Scalability Spark Cloud computing Parallel library Big Data

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A look at the future of autonomous connected vehicle systems 23

A look at the future of autonomous connected vehicle systems

引用

23rd international conference on Software Engineering and Data Engineering, SEDE 2014

作者： Ingram, John E. McGregor, John D. School of Computing Clemson University United States

ISBN: (纸本)9781880843963

As vehicles become more autonomous they will form connections to intelligent infrastructure such as traffic signals, information sources, and other vehicles. The connections among vehicles and supporting infrastructure are extended by connections to yet more vehicles and infrastructure, which will form large-scale webs distributed over wide physical areas. Our current research is intended to understand how these systems, of a scale beyond anything previously subjected to engineering analysis, are different and how we can influence their creation and evolution. In this study we apply the characteristics of ultralarge scale (ULS) systems to evolving intelligent transportation systems in an effort to find explanations for past behavior and indications of future directions. Our results provide additional questions to be explored in future investigations. © ISCA, SEDE 2014.

关键词： Vehicles

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Bloomfish: A Highly Scalable distributed K-mer Counting Framework 23

Bloomfish: A Highly Scalable Distributed K-mer Counting Fram...

引用

23rd IEEE international conference on Parallel and distributed systems (ICPADS)

作者： Gao, Ta Guo, Yanfei Wei, Yanjie Wang, Bingqiang Lu, Yutong Cieotti, Pietro Balaji, Pavan Taufer, Michela Univ Delaware Newark DE 19716 USA Argonne Natl Lab Argonne IL 60439 USA San Diego Supercomp Ctr La Jolla CA USA Natl Univ Def Technol Changsha Hunan Peoples R China Natl Supercomp Ctr Guangzhou Guangzhou Guangdong Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China Sun Yat Sen Univ Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781538621295

K-mer counting is a fundamental operation in DNA research and genome analytics;its application includes estimating genome assembly, understanding similarities in genomic samples, and merging a newly processed genome with a reference genome. As the genome dataset becomes larger and larger, designing a highly optimized distributed-memory implementation becomes more and more important. Current distributed-memory solutions have two limitations: they have a high memory footprint, and they do not provide advanced optimizations for loading enormous genome datasets into memory. Based on these observations, we present Bloomfish, a distributed, memory-efficient, scalable solution to the limits of current work. To keep a low memory footprint, Bloomfish leverages the compact hash array design of the single-node Jellyfish system and the optimized workflow of the high-performance MapReduce framework Mimir. We have also codesigned Mimir's I/O to efficiently load enormous datasets. We ran Bloomfish on the Tianhe-2 supercomputer with large sequence datasets (up to 24 TB). Our results show that Bloomfish achieves unprecedented scalability in genome analytics.

关键词： K-mer counting Genome analysis MapReduce Memory efficiency I/O optimization Performance and scalability

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A QoS-aware MAC layer protocol for wireless LANs

A QoS-aware MAC layer protocol for wireless LANs

引用

23rd IEEE international Performance, computing, and Communications conference (IPCCC 2004)

作者： Choi, N Venkatesan, S Prakash, R Univ Texas Erik Jonsson Sch Engn & Comp Sci Richardson TX 75083 USA

ISBN: (纸本)0780383966

With advances in physical layer technologies, WLANs are now connected with wired networks and act as parts of the entire networks. Since demands for QoS sensitive applications are extremely high, WLANs, as parts of heterogeneous networks, are required to be QoS-aware. In this paper we present a new QoS-aware multi-access scheme, called ADCF, designed to assure weighted fair queuing in a purely distributed way and to achieve admission control per frame. The results of simulations show that ADCF yields stable weighted fair queuing with consistent performance under most conditions. In most cases, ADCF outperforms DCF of IEEE 802.11 and EDCF of IEEE 802.11e. Also, ADCF guarantees starvation free channel access for a low priority flow.

关键词： Wireless telecommunication systems

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distributed Trust Evaluation Mechanism of LEO Satellites for 6G Network 23

Distributed Trust Evaluation Mechanism of LEO Satellites for...

引用

作者： Li, Hui Shi, DongCong Zhou, Ruijin Liao, Dan Zhang, Ming Zhou, Yuliang School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China Chengdu Research Institute University of Electronic Science and Technology of China Chengdu China School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781665494571

In 6G network, the LEO satellite communication is popular because of the lower development costs and lower transmission delay. However, due to the instability, openness and exposure of links between satellites, LEO satellite is vulnerable to internal attacks during data routing. Considering that trust management has a better performance in solving the internal attacks between satellite communications, this paper proposed a new distributed trust evaluation mechanism (DTEM) of LEO satellites based on D-S evidence theory. In the proposed trust evaluation mechanism, it evaluates the trust degree of satellite nodes by direct trust, indirect trust and aggregate trust. Then it detects the malicious satellite nodes for 6G networks and takes corresponding isolation measures. The simulations verifies that the proposed trust evaluation mechanism has superior performance in packet delivery rate and packet loss rate for data routing. © 2021 IEEE.

关键词： 6G mobile communication Satellites Smart cities Evidence theory Low earth orbit satellites Packet loss Routing

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SEKEN (Secure and Efficient Key Exchange for sensor Networks)

SEKEN (Secure and Efficient Key Exchange for sensor Networks...

引用

23rd IEEE international Performance, computing, and Communications conference (IPCCC 2004)

作者： Jamshaid, K Schwiebert, L Wayne State Univ Dept Comp Sci Detroit MI 48202 USA

ISBN: (纸本)0780383966

Wireless Sensor Networks are edging closer to widespread feasibility with recent research showing promising results in developing and adapting new mechanisms to suit their environment. Secure communication between these distributed wireless devices is a desired characteristic, especially in scenarios where these sensors will be used for military and other mission-critical operations. This paper highlights some of the research challenges for extending secure communications over these resource-limited devices and points out why current protocols do not scale well in this unique application realm. A new key setup protocol (SEKEN) is proposed that neatly fits into the requirements of these device types. The performance of SEKEN is then analyzed against some other possible key setup mechanisms. Our initial results confirm that it performs better under most of the conditions anticipaied for general wireless sensor networks.

关键词： Wireless telecommunication systems

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A Fast, General Storage Replication Protocol for Active-Active Virtual Machine Fault Tolerance 23

A Fast, General Storage Replication Protocol for Active-Acti...

引用

23rd IEEE international conference on Parallel and distributed systems (ICPADS)

作者： Wang, Cheng Chen, Xusheng Wang, Zixu Zhu, Youwei Cui, Heming Univ Hong Kong Dept Comp Sci Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781538621295

Cloud computing enables more and more online services deployed in virtual machines (VMs), making fast VM fault tolerance particularly crucial. Unfortunately, despite much effort, achieving fast VM fault tolerance remains an open problem. A traditional way to provide VM fault tolerance is the active-passive approach, which frequently transfers tremendous updated states, including memory and storage, of a primary VM to a suspended secondary VM. The other emerging approach, namely the active-active approach, runs the secondary VM concurrently with the primary. Compared to active-passive, active-active is faster because it only performs the transfer when the externally visible states (e.g., network outputs) of the primary and secondary diverge. However, active-active aggravates the performance issue on I/O intensive workloads. In existing active-active systems, storage replication protocols hold updated storage states from both the primary and secondary on the secondary, incurring excessive I/O contention. For instance, both our evaluation and prior study show that a well-engineered active-active system, COLO, degrades the throughput of I/O intensive services by up to 61.6%. To tackle this open problem, this paper presents GANNET, a fast and general storage replication protocol for active-active VM fault tolerance systems. It greatly alleviates the I/O contention on the secondary's storage by efficiently buffering the updated disk states from both the primary and secondary VM in memory. GANNET carries a lightweight storage checkpoint algorithm to avoid consuming too much memory. GANNET is proved to be as reliable as existing storage replication protocols. We integrated GANNET into two popular active active systems. Evaluation on six widely used services shows that GANNET incurred 15.9% overhead compared to the native executions and outperformed COLO's storage replication protocol by 1.2X similar to 2.6X. GANNET'S source code is available ***/hku-systems/gannet.

关键词： Cloud computing Fault Tolerance Virtual Machine Storage Replication

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