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9th international conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023

9th International Conference of Pioneering Computer Scientis...

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9th international conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023

ISBN: (纸本)9789819959709

the proceedings contain 66 papers. the special focus in this conference is on international conference of Pioneering Computer Scientists, Engineers and Educators. the topics include: Prediction of Time Series Data with Low Latitude Features;lightweight and Efficient Attention-Based Superresolution Generative Adversarial Networks;the Multisource Time Series Data Granularity Conversion Method;outlier Detection Model Based on Autoencoder and Data Augmentation for High-Dimensional Sparse Data;dimension Reduction Based on Sampling;complex Time Series Analysis Based on Conditional Random Fields;Feature Extraction of Time Series Data Based on CNN-CBAM;optimization of a Network Topology Generation Algorithm Based on Spatial Information Network;MBTIviz: A Visualization System for Research on Psycho-Demographics and Personality;a Self-Attention-Based Stock Prediction Method Using Long Short-Term Memory Network Architecture;distributed Implementation of SM4 Block Cipher Algorithm Based on SPDZ Secure Multi-party Computation Protocol;DP-ASSGD: Differential Privacy Protection Based on Stochastic Gradient Descent Optimization;study on Tourism Workers’ Intercultural Communication Competence;a Novel Federated Learning with Bidirectional Adaptive Differential Privacy;Chaos-Based Construction of LWEs in Lattice-Based Cryptosystems;security Compressed Sensing Image Encryption Algorithm Based on Elliptic Curve;two-Dimensional Code Transmission System Based on Side Channel Feedback;an Updatable and Revocable Decentralized Identity Management Scheme Based on Blockchain;cloud-Edge Intelligent Collaborative computing Model Based on Transfer Learning in IoT;design and Validation of a Hardware-In-the-Loop Based Automated Driving Simulation Test Platform;CAD-Based Research on the Design of a Standard Unit Cabinet for Custom Furniture of the Cabinet Type;improving Transferability Reversible Adversarial Examples Based on Flipping Transformation;rolling Iterative Prediction for Correlated Multiv

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9th international conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023

9th International Conference of Pioneering Computer Scientis...

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9th international conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023

ISBN: (纸本)9789819959679

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Tailor : Datacenter Load Balancing for Accelerating distributed Deep Learning 9

Tailor : Datacenter Load Balancing for Accelerating Distribu...

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9th international conference on Advanced Cloud and Big Data, CBD 2021

作者： Xu, Zhengzhi Lu, Yifei Li, Jingqi Ma, Xu Qian, Lei Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210096 China State Key Lab of Mathematical Engineering and Advanced Computing Wuxi214215 China

ISBN: (纸本)9781665407458

Accelerating distributed Deep Learning draws increasing attention recently. Existing solutions like gradient compression, pipelining computation/communication, flow scheduling based on gradient disparities, neglect load balancing for distributed Deep Learning (DDL) flows in DataCenter Network. In this paper, we review the PS traffic pattern in usual DDL training and propose that minimizing tail Flow Completion Time (FCT) of DDL flows is objective for DDL traffic Load Balancing. Besides, traffics of DDL differ from traditional DataCenter in temporal and spatial distribution. Current DCN Load Balancing become unadaptable to optimization requirements of DDL traffic, so we propose Tailor, a brand new load balancing scheme for DDL traffics training in DCN. Tailor is a solution without complex switch modification that sufficiently leverages the known parameter amount of DDL flows to discover congestion and reroutes by ECMP-like hash function to compensate bandwidth for slower flows. With large-scale simulation, we validate the effectiveness of Tailor. Tailor behaves well in both symmetric and asymmetric topology. It reduces time cost of DDL training by decreasing about 20-30% tail FCT than other load balancing mechanisms. © 2022 IEEE.

关键词： Deep learning

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Research on Wide-Area-Cloud-Platform Operations Framework for Edge-Cloud System

Research on Wide-Area-Cloud-Platform Operations Framework fo...

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IEEE international conference on Cloud computing and Big Data Analysis (ICCCBDA)

作者： Yuqin Qin Jiali Liu State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350373554

ISBN: (纸本)9798350373561

With the rapid increase of data, the scale of cloud is gradually expanding, forming a wide-area cloud platform consisting of multiple data centers distributed across different locations. For industry professionals, maintaining the normal operation of such a large platform relies on reasonable system architecture and operational methods. this article provides an in-depth analysis of the operational requirements for wide-area cloud platforms, investigates relevant anomaly detection methods, and proposes suitable anomaly detection methods for high-frequency local operational status data in data center operations systems and global operational status data in central operations systems respectively. In addition, based on edge-cloud architecture, an operational framework tailored to wide-area cloud platforms is proposed to provide reference means for improving the efficiency of operations personnel. the feasibility of the framework has been verified through actual project testing.

关键词： Cloud computing Data centers Root cause analysis Pain Image edge detection Systems architecture Personnel

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distributed Synchronous Particle Swarm Optimization for Edge computing 9

Distributed Synchronous Particle Swarm Optimization for Edge...

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9th international conference on Future Internet of things and Cloud, FiCloud 2022

作者： Busetti, Riccardo Ioini, Nabil El Barzegar, Hamid R. Pahl, Claus Free University of Bozen-Bolzano Bolzano Italy

ISBN: (数字)9781665493505

ISBN: (纸本)9781665493505

the wide adoption of edge computing has introduced several issues such as load balancing, resource provisioning, and workload placement as optimization problems. Particle swarm optimization (PSO) is a nature-inspired stochastic optimization algorithm, whose objective is to iteratively improve the solution of a problem over a given objective. the distribution of PSO to the edge would result in the transfer of resource-intensive computational tasks from the cloud to the edge, leading to more efficient use of existing resources. However, it introduces challenges related to performance and fault tolerance, due to the resource-constrained edge environment with a high probability of faults. We introduce multiple distributed synchronous variants of the PSO algorithm built on top of the Apache Spark distributed computing framework and Kubernetes container orchestration platform. these variants of the algorithm aim at addressing the performance and fault tolerance problems introduced by the execution in an edge network. A PSO algorithm that distributes the load across multiple executor nodes can effectively realize coarse-grained parallelism, thus can obtain a significant increase in performance, but also more fault tolerance and scalability. © 2022 IEEE.

关键词： Fault tolerance

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Asynchronous distributed Particle Swarm Optimization for Edge Cloud Architectures 9

Asynchronous Distributed Particle Swarm Optimization for Edg...

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9th international conference on Future Internet of things and Cloud, FiCloud 2022

作者： Busetti, Riccardo Barzegar, Hamid R. Ioini, Nabil El Pahl, Claus Free University of Bozen-Bolzano Bolzano Italy

ISBN: (数字)9781665493505

ISBN: (纸本)9781665493505

Edge computing poses a range of optimization problems such as load balancing, resource provisioning, and workload placement. Particle swarm optimization (PSO) is a bio-inspired stochastic optimization algorithm, with the objective to iteratively improve the solution of a problem for a given objective. the distribution of PSO workloads to the edge would transfer resource-intensive computational tasks from central large cloud data centers to the edge, resulting in more efficient use of existing resources there. However, this edge architecture introduces performance and fault tolerance challenges, due to the resource-constrained edge environment with a high probability of *** present here an asynchronous variant of an edge-distributed PSO algorithm built on top of the Apache Spark distributed computing framework [2]. this PSO variant aims at solving performance problems introduced by the execution in an edge setting. Our asynchronous PSO algorithm that distributes the load across multiple executor nodes can effectively realize both coarse-and fine-grained parallelism, allowing us to obtain a substantial performance increase. © 2022 IEEE.

关键词： Iterative methods

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Assessing the feasibility of Blockchain Technology in Automotive Industry 9

Assessing the feasibility of Blockchain Technology in Automo...

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9th IEEE Uttar Pradesh Section international conference on Electrical, Electronics and Computer Engineering, UPCON 2022

作者： Balachander, S. Murugan, A. Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Chengalpattu India

ISBN: (数字)9798350332506

ISBN: (纸本)9798350332506

Blockchain is a decentralised, distributed public ledger that has recently garnered enormous traction. the automotive industry, one of the most profitable markets worldwide, is undoubtedly responsible for the transformations in modern civilisation over the past century. this paper primarily focuses on the issue of the complexity of existing technologies in the field and the possibility of applying Blockchain technology as a replacement in the automotive sector. In addition, the researcher has considered compatible precedents for identifying lacunae in the existing technologies. As a result, the adoption of Blockchain technology provides access to a wide range of potential automotive applications that can develop modern business models moreover even transform the established automotive partaking economy. Further, after examining the advantages, limitations, opportunities, and risks, some suggestions are made to guide enterprises and researchers in future advancements in the cyber-resilient automotive sector. © 2022 IEEE.

关键词： Blockchain

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Towards Reliable CIDS: Hybrid Reputation and Challenge Strategies for Combating Internal Attacks

Towards Reliable CIDS: Hybrid Reputation and Challenge Strat...

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Robotics, Control and Automation (ICRCA), international conference on

作者： Yuandong Min Jingjing Zhang Sicong Liu Jia Li Furong Yu Jianjun Chen Hao Zhang National Engineering Research Center for E-Learning Faculty of Artificial Intelligence in Education Central China Normal University Wuhan China Wuhan Maritime Communication Research Institute (WMCRI) Wuhan China

ISBN: (数字)9798331544577

ISBN: (纸本)9798331544584

Collaborative Intrusion Detection Systems (CIDS) serve as crucial firewalls, maintaining system security through necessary information exchange and integration among nodes in distributed systems. While CIDS excel at defending against external network attacks, internal threats remain a significant challenge. To identify malicious internal nodes, researchers typically adopt trust management mechanisms. However, current methods often fail to effectively take into account nodes' global reputation and historical behavior. Recognizing the similarities between distributed networks and social networks, we propose a hybrid trust computation mechanism based on social network reputation theory and develop a high-performance node clustering model. Simulated experiments conducted on a network with 50 nodes demonstrate that our method achieves higher accuracy and recall rates in identifying malicious nodes under adverse conditions compared to traditional methods, thereby enhancing the resilience of distributed networks against internal attacks.

关键词： Social networking (online) Firewalls (computing) Computational modeling Intrusion detection Reliability theory Network security Trust management Robots Information exchange Resilience

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A distributed Multi-group Mutual Exclusion Algorithm for Intersection Traffic Control 9

A Distributed Multi-group Mutual Exclusion Algorithm for Int...

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9th international Symposium on computing and networking Workshops, CANDARW 2021

作者： Kakugawa, Hirotsugu Kamei, Sayaka Ryukoku University Otsu Shiga Japan Hiroshima University Higashi Hiroshima Hiroshima Japan

ISBN: (纸本)9781665428354

Connected vehicle (CV) is one of hot topics in recent intelligent transport systems (ITSs). Because safety is the most important aspect of vehicles and approximately half of road traffic accidents occur at intersections, we aim at considering the problem of traffic control in intersections from the viewpoint of distributed algorithms in vehicle ad-hoc network (VANET). Specifically, infrastructure-free (i.e., without traffic signals) and fully distributed autonomous traffic control mechanism is *** this paper, we propose a distributed multi-group mutual exclusion algorithm for intersection traffic control in VANET. In our framework, a vehicle that is allowed by mutual exclusion algorithm may enter an intersection, and multiple vehicles in multiple traffic lanes may be allowed to enter an intersection at the same time as long as they do not collide. the proposed algorithm uses quorums for message efficiency, and its message complexity is O( { n } ), where n is the number of vehicles in VANET. © 2021 IEEE.

关键词： Vehicular ad hoc networks

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Blockchain-Based Supply Chain for a Sustainable Digital Society: Security Challenges and Proposed Approach 9th

Blockchain-Based Supply Chain for a Sustainable Digital Soci...

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9th international conference on computing and Informatics, ICOCI 2023

作者： Md Nasir, Norshakinah Mohd Zaini, Khuzairi Hassan, Suhaidi Nordin, Noradila Politeknik Sultan Abdul Halim Mua’dzam Shah Bandar Darulaman Kedah Jitra06000 Malaysia InterNetWorks Research Laboratory School of Computing Universiti Utara Malaysia Kedah Sintok06000 Malaysia School of Games and Creative Technology University for the Creative Arts FarnhamGU9 7DS United Kingdom

ISBN: (纸本)9789819995882

Blockchain technology is a distributed digital ledger in a decentralized network that offers immutability, security, and transparency in various applications among digital societies. the consensus mechanism is the defining technology behind the security and performance of the Blockchain system. Under the Industrial Revolution 4.0, blockchain has been considered for integration into supply chain business as an innovative solution to tackle the challenges of traceability, transparency, lack of trust, and data counterfeiting in digital supply chain management. A private permissioned Blockchain is the most suitable type of Blockchain for Supply Chain Management (SCM) as it promises better performance with high throughput and low latency. However, private Blockchains that use the Byzantine Fault Tolerance (BFT) consensus mechanism have low-security capabilities and are more vulnerable to cyber-attacks triggered by malicious nodes. In this paper, we outline the research challenges from the security aspect towards the integration of Blockchain with SCM. then we design an approach for a private Blockchain-based Supply Chain with security capabilities by proposing an enhancement consensus model to the BFT consensus mechanism for identifying and terminating malicious nodes in the consensus process. the performance of the proposed approach will be validated experimentally and compared against Practical Byzantine Fault Tolerance (PBFT). the proposed approach is expected to prevent security attacks on the consensus mechanism, thereby improving the security and performance of the Blockchain system. © 2024, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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