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Massively parallel Single-Source SimRanks in o(log n) Rounds 33

Massively Parallel Single-Source SimRanks in o(log n) Rounds

引用

33rd international Joint conference on Artificial Intelligence (IJCAI)

作者： Luo, Siqiang Zhui, Zulun Nanyang Technol Univ Singapore Singapore

ISBN: (纸本)9781956792041

SimRank is one of the most fundamental measures that evaluate the structural similarity between two nodes in a graph and has been applied in a plethora of data mining and machine learning tasks. These tasks often involve single-source SimRank computation that evaluates the SimRank values between a source node u and all other nodes. Due to its high computation complexity, single-source SimRank computation for large graphs is notoriously challenging, and hence recent studies resort to distributed processing. To our surprise, although SimRank has been widely adopted for two decades, theoretical aspects of distributed SimRanks with provable results have rarely been studied. In this paper, we conduct a theoretical study on single-source SimRank computation in the Massive parallel Computation (MPC) model, which is the standard theoretical framework modeling distributed systems. Existing distributed SimRank algorithms enforce either Omega(log n) communication round complexity or Omega(n) machine space for a graph of n nodes. We overcome this barrier. Particularly, given a graph of n nodes, for any query node v and constant error epsilon > 3/n, we show that using O(log(2) log n) rounds of communication among machines is enough to compute single-source SimRank values with at most epsilon absolute errors, while each machine only needs a space sub-linear to n. To the best of our knowledge, this is the first single-source SimRank algorithm in MPC that can overcome the Theta T(log n) round complexity barrier with provable result accuracy.

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distributed Localization of Wireless Sensor Networks in Indoor Environment 3

Distributed Localization of Wireless Sensor Networks in Indo...

引用

3rd international conference on Internet of Things and Smart City, IoTSC 2023

作者： Chen, Xinming Shi, Lei Shao, Jinliang School of Automation Engineering University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9781510666375

This paper studies the localization problem of wireless sensor network in indoor environment. In order to meet the mobile users' demand for location service in indoor environment, an indoor distributed localization method based on coordinate projection technology and barycentric coordinate representation is proposed, which can realize large-scale localization of wireless sensor networks in 3D indoor environment only through a few anchor nodes. Meanwhile, this method has no too many restrictions on the deployment of wireless sensor networks, and can flexibly adjust sensor nodes, and has strong scalability. Finally, the effectiveness of the proposed localization method is verified by numerical simulation. © 2023 SPIE.

关键词： Numerical methods

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Framework Design of Reconfigurable Convolution Neural Network Acceleration System for Edge Computing 3

Framework Design of Reconfigurable Convolution Neural Networ...

引用

3rd international conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2023

作者： Liao, Yibing Wang, Yu Zhao, Yuxuan Zhang, Chengyu Xiao, Bende Yang, Jiamei Wang, Hui Li, Jiaxuan School of Information Engineering Wuhan University of Technology China Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks Wuhan University of Technology China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

In this paper, we propose a reconfigurable framework optimized for resource-constrained platforms to accelerate CNNs using the high concurrency and data-proximate characteristics of edge computing devices. The framework is designed from three aspects: control flow, data flow, and storage flow. To address the impact of memory access cost on network computation efficiency, we introduce a parallel ping-pong data scheduling framework to compensate for it. Experimental results show that the system can support convolutional kernel operations of any size under structural constraints, and the computational efficiency is improved 2.28 times compared to CNN acceleration systems based on traditional data scheduling schemes. © 2023 SPIE.

关键词： Computational efficiency

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Performance optimization of Learning Trees modules in the ECL repository 3

Performance optimization of Learning Trees modules in the EC...

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3rd international conference on Communication, Control, and Intelligent systems, CCIS 2024

作者： Shashank, B. Sudershan, K.S. Shobha, G. Manonmani, S. Dev, Roger Rv College of Engineering Dept. of Computer Science Bangalore India LexisNexis Risk Solutions United States

ISBN: (纸本)9798331528201

Multi-Node computation, also known as distributed computing, is a paradigm that allows for the efficient utilization of multiple interconnected nodes or machines to perform complex computational tasks. By dividing the workload and distributing it across multiple nodes, multi-node computation enables parallel processing, scalability, and improved performance for a wide range of applications. HPCC systems® from LexisNexis Risk Solutions is a proven, open source solution for big data insights that can be implemented by businesses of all sizes. HPCC systems offers a consistent data-centric programming language, two processing platforms and a single, complete end-to-end architecture for efficient processing. ECL is the Enterprise Control Language designed specifically for huge data projects using the HPCC systems platform. It is extremely scalable and a powerful declarative data-processing language with native multi-processing capabilities and used for HPCC systems. Some core ECL functions, like the ones handling Learning Tree algorithms of Machine Learning Bundle are recursive in nature and hence high computational time is needed. This paper thus presents a solution to achieve optimized processing of ML learning tree algorithms in ECL through embedding python libraries. The proposed approach was tested on standard datasets and a significant decrease in computation time. For Real Estate Valuation Regression dataset the computation time was reduced from 11.371 seconds to 0.886 seconds using the proposed method showing 1324% improvement with no impact on the accuracy. Random Forests are also implemented using the proposed Decision Tree method allowing the users to specify the number of decision trees to be used in the forest. © 2024 IEEE.

关键词： parallel processing systems

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Spatial Data Analysis on On-Demand Cab Services using Spark 3

Spatial Data Analysis on On-Demand Cab Services using Spark

引用

3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Kokkiligadda, Manohar Raj Shaik, Fathimabi Likhitha, Poritigadda Velagapudi Ramakrishna Siddhartha Engineering College Department of Information Technology Vijayawada India Information Technology Velagapudi Ramakrishna Siddhartha Engineering College Vijayawada India

ISBN: (纸本)9798350343632

Spatial data analysis is a technique used to analyze large amounts of spatial data generated by on-demand cab services such as Uber, Lyft, and Grab. This type of data includes information on the pickup and drop-off locations of riders, the trajectories of drivers, and the time when demand for cabs is highest. By analyzing this data, the on-demand cab services can gain insights on the customer demand, optimize driver allocation, improve pricing strategies, and enhance overall system efficiency. Spark is an open-source framework used for processing large-scale spatial data. It provides a set of APIs for processing and analyzing spatial data in distributed computing environments by using Apache Spark as its computing engine. This research explores the utilization of Spark, an open-source framework tailored for large-scale spatial data processing. Spark offers a comprehensive set of APIs designed for distributed computing environments, leveraging the power of Apache Spark as its underlying computational engine. By using Spark, on on-demand cab services can efficiently analyze large amounts of spatial data generated by their systems, enabling them to make data-driven decisions and improve the efficiency of their services. There by, we did analyze and visualize, handle the spatial data through spark with the help of graphs. © 2023 IEEE.

关键词： Spark Spatial Data frame Spatial rdD

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A lightweight intrusion detection method for intelligent substations 3

A lightweight intrusion detection method for intelligent sub...

引用

3rd international conference on Electronic information Engineering and Data Processing, EIEDP 2024

作者： Zhang, Zidong Liu, Dongqi Liang, Haolan School of Electrical and Information Engineering Changsha University of Science and Technology Hunan410114 China National Engineering Research Center for Robot Visual Perception and Control Technology Hunan410012 China

ISBN: (纸本)9781510680531

Aiming at the current problem of lack of effective data and high service latency for intrusion detection in smart substations, this paper proposes a lightweight intrusion detection method for smart substations. Through the federated learning method and knowledge distillation method this paper trains a lightweight intrusion detection model based on LSTM. Experiments show that this paper's method has a large improvement in the accuracy and service delay on the NSL-KDD dataset. © 2024 SPIE.

关键词： Distillation

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A Hybrid Framework for Secure Group Communication Using Quantum-Classical Cryptography and Reinforcement Learning 3

A Hybrid Framework for Secure Group Communication Using Quan...

引用

3rd international conference on Intelligent systems, Advanced Computing, and Communication, ISACC 2025

作者： Renisha, P.S. Rudra, Bhawana National Institute of Technology Department of Information Technology Karnataka Surathkal India

ISBN: (纸本)9798331523893

This research work describes a framework for secured and effective way of group interaction incorporating classical cryptography and quantum communication technique. This framework employs a classical cryptographic methods for group logistics like as transmitting of messages and membership management while employing quantum communication strategy for secure key distribution and related authentication. In order to increase the flexibility and data-security of the proposed system further, a supervisor learning based mechanism is incorporated into the framework where reinforcement learning will employed in controlling the interaction of the protocols and the decision-making processes in an active manner. This combination of classical, quantum and supervisor learning strategies gives a solution to the issues of scalability, efficiency, effective and timely actionable response to increasing cyber threats especially in the era of quantum computing. The framework is highly effective and secured for group interaction in distributed network infrastructures. It will be a leading the approach for advanced cryptographic mechanism in the future. © 2025 IEEE.

关键词： Qubits

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Research on tactical edge cloud service model for joint intelligence 3

Research on tactical edge cloud service model for joint inte...

引用

3rd international conference on Electronics, Electrical and information Engineering, ICEEIE 2023

作者： Du, Bo Yuan, Chen Yu, Zhaojun Engineering University of PAP Urumqi830049 China

ISBN: (纸本)9781510671423

To cope with the problems of insufficient level of intelligence in attempting combat missions under tactical edge conditions, high command, and control delay, and difficulty in sharing data across domains, the joint intelligent tacti-cal edge cloud service model is proposed, the definition and formal description of joint intelligence are given, and the synergistic mechanism of the joint intel-ligent cloud service model is analyzed, to provide theoretical references for distributed combat at the tactical edge under intelligent conditions. © 2023 SPIE.

关键词： distributed database systems

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Recursive Broadcasting Approach 33

Recursive Broadcasting Approach

引用

33rd Euromicro international conference on parallel, distributed, and Network-Based Processing, PDP 2025

作者： Harutyunyan, Hovhannes A. Hovhannisyan, Narek Concordia University Department of Computer Science and Software Engineering MontrealQCH3G 1M8 Canada Institute for Informatics and Automation Problems NAS RA Yerevan0014 Armenia

ISBN: (纸本)9798331524937

Broadcasting is one of the fundamental information dissemination primitives in interconnection networks, where a message is passed from one node (called originator) to all other nodes in the network. Following the increasing interest in interconnection networks, extensive research was dedicated to broadcasting. Two main research goals of this area are finding inexpensive network structures that maintain efficient broadcasting and finding the broadcast time for well-known and widely used network topologies. In the scope of this study, we will mainly focus on determining the broadcast time and nearoptimal broadcasting schemes in networks. Determination of the broadcast time of any node in an arbitrary network is known to be NP-hard. Polynomial time solutions are known only for a few network topologies. There also exist various heuristic and approximation algorithms for different network topologies. In this study, we consider the broadcast time problem on graphs that comprise some recursive structures. We initiate a novel direction to designing broadcasting algorithms on recursively defined graphs. We provide a theoretical foundation for future broadcasting studies, as well as discuss several practical applications of the approach we introduce. © 2025 IEEE.

关键词： Interconnection networks (circuit switching)

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Design of anti-counterfeiting system based on blockchain and NFC tag 3

Design of anti-counterfeiting system based on blockchain and...

引用

3rd international conference on information Science, parallel and distributed systems, ISPDS 2022

作者： He, Mai Yang, Shulin College of Information Engineering Beijing Institute of Graphic Communication Beijing China

ISBN: (数字)9781665487474

ISBN: (纸本)9781665487474

In order to solve the problems of centralized anti-counterfeiting system and illegal merchants copy authentic commodities at low cost and with low difficulty. This paper proposes an anti-counterfeiting system design based on the combination of blockchain and NFC tag. This system uses the Hyperledger Fabric blockchain development platform, Anti-counterfeiting certificates are used to prove that the commodities are genuine, encrypting the anti-counterfeiting certificate with ECC (Elliptic Curve Cryptography) public key forms ciphertext, then store the ciphertext in the blockchain ledger. Write the SHA256 value of the anti-counterfeiting certificate and the ECC private key, which can transform from ciphertext to anti-counterfeiting certificate, into the NFC tag. the query times can be recorded through MySQL database. It ensures the uniqueness and non replicability of the anti-counterfeiting certificate of the product, greatly improves the anti-counterfeiting performance and the difficulty of counterfeiting. © 2022 IEEE.

关键词： Blockchain

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