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

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parallel ATTRIBUTE COMPUTATION FOR distributed COMPONENT FORESTS 29

PARALLEL ATTRIBUTE COMPUTATION FOR DISTRIBUTED COMPONENT FOR...

引用

IEEE international conference on Image Processing (ICIP)

作者： Gazagnes, Simon Wilkinson, Michael H. F. Univ Texas Austin Dept Astron Austin TX 78712 USA Univ Groningen Bernouilli Inst Math & Artificial Intelligence Groningen Netherlands

ISBN: (数字)9781665496209

ISBN: (纸本)9781665496209

Component trees are powerful image processing tools to analyze the connected components of an image. One attractive strategy consists in building the nested relations at first and then deriving the components' attributes afterward, such that the user can switch between different attribute functions without having to re-compute the entire tree. Only sequential algorithms allow such an approach, while no parallel algorithm is available. In this paper, we extend a recent method using distributed memory techniques to enable posterior attribute computation in a parallel or distributed manner. This novel approach significantly reduces the computational time needed for combining several attribute functions interactively in Giga and Tera-Scale data sets.

关键词： Mathematical morphology Connected filters Component trees Image representation parallel computing

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SafetyNet: A Decentralized Police Complaint Management System for Bangladesh Using Blockchain Technology

SafetyNet: A Decentralized Police Complaint Management Syste...

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2024 international conference on advances in computing, Communication, Electrical, and Smart Systems, iCACCESS 2024

作者： Tanjim, Shah M.D. Chowdhury, Rahat Ahmed Amin, Ruhul Ahmed, Tanjil Chowdhury, Shovon Das Lysuzzaman, Md Sylhet Engineering College Computer Science & Engineering Sylhet Bangladesh

ISBN: (纸本)9798350350289

Efficient crime reporting and management is imperative for law enforcement agencies, yet conventional systems pose challenges with data integrity and accessibility. Traditional reporting processes further contribute to delays, errors, and inefficiencies in the overall crime reporting workflow. As a result of these complexities, numerous victims and witnesses are reluctant to seek assistance from legal mechanisms. This study addresses these issues by introducing SafetyNet, a decentralized application (DApp) built on Hyperledger Fabric technology. The prevailing risks of data tampering and unauthorized access are mitigated through Hyperledger Fabric's Private Data Collection, ensuring secure and restricted information storage. SafetyNet is a multifaceted solution comprising user reporting, police, and judge components. Users can seamlessly report crimes, while police and judges access and manage complaints securely within the system. This decentralized approach revolutionizes traditional complaint management, fostering transparency and accountability in law enforcement processes. Hyperledger Fabric emerges as the optimal choice for SafetyNet due to its scalability, permission-based access controls, and confidential transaction processing. This study aims to assess SafetyNet's impact on public trust, compare its effectiveness with traditional systems, and provide valuable insights into blockchain-based complaint management best practices. © 2024 IEEE.

关键词： distributed ledger

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MISA: UNVEILING THE VULNERABILITIES IN SPLIT FEDERATED LEARNING 49

MISA: UNVEILING THE VULNERABILITIES IN SPLIT FEDERATED LEARN...

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49th IEEE international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Wan, Wei Ning, Yuxuan Hu, Shengshan Xue, Lulu Li, Minghui Zhang, Leo Yu Jin, Hai Huazhong Univ Sci & Technol Sch Cyber Sci & Engn Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Software Engn Wuhan Peoples R China Griffith Univ Sch Informat & Commun Technol Nathan Australia Natl Engn Res Ctr Big Data Technol & Syst Beijing Peoples R China Serv Comp Technol & Syst Lab Wuhan Peoples R China Hubei Key Lab Distributed Syst Secur Wuhan Peoples R China Hubei Engn Res Ctr Big Data Secur Wuhan Peoples R China Cluster & Grid Comp Lab Wuhan Peoples R China

ISBN: (纸本)9798350344868;9798350344851

Federated learning (FL) and split learning (SL) are prevailing distributed paradigms in recent years. They both enable shared global model training while keeping data localized on users' devices. The former excels in parallel execution capabilities, while the latter enjoys low dependence on edge computing resources and strong privacy protection. Split federated learning (SFL) combines the strengths of both FL and SL, making it one of the most popular distributed architectures. Furthermore, a recent study has claimed that SFL exhibits robustness against poisoning attacks, with a fivefold improvement compared to FL in terms of robustness. In this paper, we present a novel poisoning attack known as MISA. It poisons both the top and bottom models, causing a misalignment in the global model, ultimately leading to a drastic accuracy collapse. This attack unveils the vulnerabilities in SFL, challenging the conventional belief that SFL is robust against poisoning attacks. Extensive experiments demonstrate that our proposed MISA poses a significant threat to the availability of SFL, underscoring the imperative for academia and industry to accord this matter due attention.

关键词： Split Federated Learning Poisoning Attack Robustness

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New distributed Partitioning Approach for Large Spatial Networks 4

New Distributed Partitioning Approach for Large Spatial Netw...

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4th international conference on Digital Age and Technological advances for Sustainable Development, ICDATA 2023

作者： Aggour, Hafssa Mabrouk, Aziz Approximation Problem Modeling & Data Science Research Team Abdelmalek Essaadi University Tétouan Morocco

ISBN: (纸本)9798350311112

In urban areas, geographic spread of spatial networks continually produces massive data. In fact, the analysis of these spatial networks is squarely related to the partitioning of networks into sub-networks in a balanced manner using scalable analysis methods with the aim of minimizing processing time, namely, partitioning parallel and distributed with (Big Data, ML). Our objective, consist to partition in a distributed way a large spatial network into several Subnets. Therefore, we are conducting a comparative study of distributed partitioning algorithms such as Clustering and Hierarchical Clustering methods with the method that we have proposed in another paper [26] allowing to decompose the spatial network into sub-networks taking into account the Euclidean proximity between the nodes and the different Voronoï generators. the comparative study of the three partitioning methods that we have implemented, namely, Clustering, Hierarchical Clustering and our proposed method, have allowed us to deduce that our method is the most reliable and competitive compared to others, in terms of balance partitions as well as in terms of optimizing the partitioning time. © 2023 IEEE.

关键词： Cluster analysis

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A Fog-based Smart Agriculture System to Detect Animal Intrusion 29

A Fog-based Smart Agriculture System to Detect Animal Intrus...

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29th IEEE international conference on parallel and distributed Systems, ICPADS 2023

作者： Miao, Jinpeng Rajasekhar, Dasari Mishra, Shivakant Nayak, Sanjeet Kumar Yadav, Ramanarayan University of Colorado Boulder United States Iiitdm Kancheepuram India Iitram Ahmedabad India

ISBN: (纸本)9798350330717

Smart agriculture is one of the most promising areas where IoT-enabled technologies have the potential to substantially improve the quality and quantity of the crops and reduce the operational cost. However, building a smart agriculture system presents several challenges, including high latency and bandwidth consumption associated with cloud computing, Internet disconnections in rural areas, and the need to keep costs low for farmers. To address these issues, this paper proposes a fog-based smart agriculture infrastructure with edge computing and LoRa communication. We address the top concern of farmers - animals intruding - by proposing a solution that detects animal intrusion using low-cost PIR sensors, cameras, and computer vision and predicts animal locations using a novel algorithm. Our system can detect animals before the intrusion, identify them, predict their future locations, and alert farmers promptly. The paper proposes three sensor layouts, and experiments confirm the system's effectiveness and lower cost compared to state-of-the-art systems. © 2023 IEEE.

关键词： animal intrusion detection fog computing LoRa smart agriculture

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Descriptive Analysis of the Cloud computing Services and Deployment Models 2

Descriptive Analysis of the Cloud Computing Services and Dep...

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2nd international conference for Advancement in Technology, ICONAT 2023

作者： Kaur, Tajinder Kamboj, Sushil Chandigarh University Computer Science Department Mohali India

ISBN: (纸本)9781665475174

Cloud have wide-ranging implications in several areas of computing, notably massive knowledge, cloud computing has simply up to the highest of any list of technology subjects. Furthermore, it is one of the most important chop-chop developing technologies due to the availability of a wide range of computer infrastructure and services. The expansion of cloud computing has included mainframe computing, cluster and grid computing, distributed and parallel computing technologies, and so on. Cloud computing has mostly supplanted grid, cluster, and mainframe computing. This refers to the delivery of numerous services over the web differently. Such as databases, infrastructure, run time platforms, knowledge storage, servers, networking, and code area unit samples of these resources. Price savings, bigger productivity, speed, efficiency, high performance, high computing power, and security are simply many of the explanations why consumers and businesses embrace the on demand computing. This article goes through the definition of cloud computing as well as its properties, various cloud services, deployment models, and security concerns. © 2023 IEEE.

关键词： Grid computing

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Fully Decentralized Data Distribution for Exascale-HPC: End of the Provider-Demander Matching Puzzle

Fully Decentralized Data Distribution for Exascale-HPC: End ...

引用

2024 IEEE international conference on Cluster computing, CLUSTER 2024

作者： Shao, Mingtian Zhang, Wenzhe Wang, Ruibo Wu, Huijun Dai, Yiqin Lu, Kai National University of Defense Technology China

ISBN: (纸本)9798350358711

For many years, in the HPC data distribution scenario, as the scale of the HPC system continues to increase, manufacturers have to increase the number of data providers to improve the IO parallelism to match the data demanders. In the era of Exascale computing, this mode of decoupling the demander and provider has limited scalability and huge costs. In our view, only a distribution model in which the demander also acts as the provider can fundamentally cope with changes in scale and have the best scalability, which is called all-to-all data distribution mode in this paper. We design and implement the BitTorrent protocol on computing networks in HPC systems and propose FD3, a fully decentralized data distribution method. We design the Requested-to-Validated Table (RVT) and the Nearest and Longest consecutive piece Segment First (NLSF) policy based on the features of the HPC networking environment to improve the performance of FD3. Experimental results show that FD3 can scale smoothly to 11k+ computing nodes, and its performance is much better than that of the parallel file system. Compared with the original BitTorrent, the performance is improved by 7-11 times. FD3 shows the great potential of the all-to-all model in HPC data distribution scenarios. At the same time, the work of this paper can further stimulate the exploration of future distributed parallel file systems and provide a foundation and inspiration for the design of data access patterns for Exscale HPC systems. © 2024 IEEE.

关键词： BitTorrent Data Distribution Exascale High-Performance computing (HPC)

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MPS: A Multiple Poisoned Samples Selection Strategy in Backdoor Attack 22

MPS: A Multiple Poisoned Samples Selection Strategy in Backd...

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IEEE 22nd international conference on Trust, Security and Privacy in computing and Communications (TrustCom) / BigDataSE conference / CSE conference / EUC conference / ISCI conference

作者： Zou, Weihong Zhang, Shigeng Wang, Weiping Zhang, Jian Liu, Xuan Cent South Univ Schoosl Comp Sci & Engn Changsha Peoples R China Hunan Univ Coll Comp Sci & Elect Engn Changsha Peoples R China Sci & Technol Parallel & Distributed Proc Lab PDL Changsha Peoples R China

ISBN: (纸本)9798350381993;9798350382006

Recently there has been many studies on backdoor attacks, which involve injecting poisoned samples into the training set in order to embed backdoors into the model. Existing multiple-poisoned samples attacks usually randomly select a subset from clean samples to generate the poisoned samples. Filtering-and-Updating Strategy (FUS) has shown that the poisoning efficiency of each poisoned sample is inconsistent and random selection is not optimal. However, FUS does not fully considered the selection of multiple poisoned samples, there are still some issues with the selection of multiple poisoned samples. In this paper, we formulate the selection of multiple types of poisoned samples as a multi-objective optimization problem and proposed a Multiple Poisoned Samples Selection Strategy (MPS) to solve the issue. Unlike FUS, we consider the potential of clean samples that are not selected as to become efficient poisoned samples. Specifically, we use a weight-based contribution approach to calculate the contribution of each sample (clean sample and poisoned sample) during the training process from multiple dimensions. Finally, based on the greedy approach, we retain a subset of samples with the largest contribution in each dimension through iterations. We evaluate the effectiveness of MPS on various attack methods, including BadNet, Blended, ISSBA, and WaNet, as well as benchmark datasets. The experimental results on CIFAR-10 and GTSRB show that MPS can increase the attack strength by 1.45% to 18.34% compared to RSS and 0.43% to 10.84% compared to FUS in multiple-poisoned samples attacks, thereby enhancing the stealthiness of the attack. Meanwhile, MPS is suitable for black-box settings, meaning that poisoned samples selected in one setiing can be applied to other settings.

关键词： Backdoor attack Multiple poisoned samples Poisoning efficiency Optimization problem Stealthiness

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Topology Identification Technology for Low-voltage distributed Photovoltaic Distribution Network Lines 3

Topology Identification Technology for Low-voltage Distribut...

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3rd international conference on Energy and Electrical Power Systems (ICEEPS)

作者： Zheng, Guoquan Zhu, Enguo Zhang, Hailong Liu, Yan Wang, Junlong Liu, Zhe China Elect Power Res Inst Beijing Peoples R China State Grid Hebei Elect Power Beijing Peoples R China

ISBN: (纸本)9798350375145;9798350375138

The large-scale penetration of distributed photovoltaic (PV) power generation systems has brought new challenges to the topology identification and detection of traditional distribution networks. This article mainly studies the topology identification technology (TIT) of distributed PV low-voltage (LV) distribution network lines, aiming to design a topology identification method that can adapt to the dynamic changes of the power grid, have large-scale capacity, and improve system accuracy under the same conditions. At the same time, the data processing speed has been improved. This article first constructs a system model, including node model, edge model, and parameter model. It mathematically represents the topology structure of the power grid using graph theory and designs a topology recognition algorithm based on optimization techniques and state estimation. This algorithm is used to solve the distributed characteristics of power grid topology recognition, the difficulty of data collection, the dynamic diversity of power grid structure, the uncertainty of equipment parameters, the high computational complexity of data processing, and the communication constraints of power grid topology recognition. This algorithm adopts modern programming languages and parallel computing frameworks, making it easy to implement efficiently. The results on the simulation platform show that the highest recall rate for 22 test cases is 93.8%, and the response time for test cases is 425 ms to 980 ms, providing a fast response to the information space of the grid.

关键词： Low-voltage distributed Photovoltaic Distribution Network Topology Identification Technology Simulation Platform Recall Ratio

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Is Performance of Object Storage Predictable for Serverless I/O Workloads? A Comparative Study 31

Is Performance of Object Storage Predictable for Serverless ...

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31st IEEE international conference on Network Protocols (ICNP)

作者： Eizaguirre, German T. Sanchez-Artigas, Marc Univ Rovira & Virgili Comp Sci & Math Tarragona Spain

ISBN: (纸本)9798350303223

Serverless architectures abstract resource provisioning away from the user. However, this property may be at odds with performance. One example of this is Function as a Service (FaaS), where the lack of network addressability compels developers to resort to serverless storage services such as AWS S3 to share (intermediate) data between the functions. For IO-bound workflows, the literature has shown that the performance of parallel reads and writes highly depends on the level of parallelism. Simply put, both an excess or a deficiency in the number of functions may lead to longer IO times. The good news is that the provisioning of functions is fast. Consequently, it is feasible to auto-provision the serverless functions to the optimal number to minimize IO latency. For this, the performance of object storage must be predictable and consistent. We confirmed this in the past for IBM COS. And in this paper, we show that the same occurs to AWS S3. Concretely, we prove that the optimal level of parallelism for parallel reads and writes can be approximated analytically for AWS S3.

关键词： distributed algorithms serverless computing resource management

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