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检索条件"主题词=Partitioning Algorithms"

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HP-ICM: Curiosity-Driven Offloading Based on Hypergraph partitioning

HP-ICM: Curiosity-Driven Offloading Based on Hypergraph Part...

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IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems (MASS)

作者： Chengwei Wang Kang Huang Chenxuan Hou Chao Qiu Xiaofei Wang College of Intelligence and Computing Tianjin University Tianjin China

ISBN: (数字)9798350363999

ISBN: (纸本)9798350364002

Computing power network (CPN) is a distributed network system designed to connect and integrate computing resources globally, enabling efficient sharing and utilization of computing power. In dependent task offloading, the dependency relationship between tasks is generally used to determine the ex-ecution order. However, the assignment phase often overlooks the relevance and sharing between tasks, leading to a waste of system resources in CPNs. In the learning process, agents frequently encounter the issue of sparse rewards, which results in slow learning and makes it challenging to develop effective strategies. To address the aforementioned issues, we design a dependent task offloading method based on hypergraph partitioning and an intrinsic curiosity module, i.e., HP-ICM, which offloads tasks with similar resource requirements or dependencies into the same partition and utilizes the ICM to enhance the speed and quality of learning. Simulation results show that HP-ICM can reduce latency by 22.8% and energy consumption by 25.7% compared to the PPO baseline during task offloading,

关键词： Training Energy consumption Simulation Smart systems Ad hoc networks partitioning algorithms Network systems

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Data partitioning and Storage Strategies for Artificial Intelligence and Machine Learning Applications: A Review of Techniques

Data Partitioning and Storage Strategies for Artificial Inte...

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International Conference on Computer and Applications (ICCA)

作者： Kingsley C. Nwosu Ibrahim Kamara Musbah Abdulgader Yen-Hung Hu Department of Computer Science Norfolk State University Norfolk VA USA

ISBN: (数字)9798350367560

ISBN: (纸本)9798350367577

This paper presents a review of data partitioning and storage strategies critical for optimizing the performance and scalability of Artificial Intelligence (AI) and Machine Learning (ML) applications. As the volume and complexity of data continue to grow, effective data management becomes increasingly essential for ensuring the efficiency and accuracy of AI/ML models. The review categorizes and evaluates various data partitioning techniques, including hash-based, range-based and graph-based algorithms, highlighting their strengths, weaknesses, and suitability for different types of datasets and applications. It also explores the data processing challenges with AI/ML applications, data access patterns for AI/ML algorithms; and implementation techniques and evaluation metrics. By identifying key factors that influence the choice of partitioning and storage strategies, this review provides valuable insights for researchers and practitioners seeking to enhance the performance of AI/ML systems. The review also serves as a foundation for future research and development, guiding the design of more efficient and scalable data management solutions in artificial intelligence.

关键词： Technological innovation Machine learning algorithms Reviews Scalability Distributed databases Machine learning Computer architecture Big Data Data processing partitioning algorithms

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A New Swap-Based Algorithm for Solving Multidimensional Multi-Way Number partitioning Problem

A New Swap-Based Algorithm for Solving Multidimensional Mult...

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International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Bozhan Zhang University of Electronic Science and Technology of China

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

The Multidimensional Multi-Way Number partitioning Problem (MDMWNPP) is a variant problem of the Number partitioning Problem (NPP). A special case of the Number partitioning Problem (NPP) known as the Two-Way Number partitioning Problem (TWNPP) is one of the original 21 problems that Richard Karp proved to be NP-complete. The existing algorithms usually solve the Mixed-Integer Linear Programming (MILP) model of the MDMWNPP by solver or consider the problem from the perspective of metaheuristics. This paper proposes a swap-based heuristic algorithm to solve the MDMWNPP from another point of view. At the same time, the paper provides theoretical supports for the swap process and applies the theory to the new algorithm. The new algorithm has achieved the best results on average when compared with the previous algorithms, and it can also provide solutions that previous algorithms were unable to obtain within a limited time. In terms of experimental performance, there is an improvement of approximately 30%-40% on the previous benchmark sets, while the time efficiency has been improved by one or two orders of magnitude.

关键词： Heuristic algorithms Metaheuristics Information processing Media Benchmark testing Approximation algorithms Distance measurement partitioning algorithms Mixed integer linear programming

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A Dynamic Sharding Scheme For Blockchain Based On Graph partitioning

A Dynamic Sharding Scheme For Blockchain Based On Graph Part...

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IEEE International Conference on Blockchain (Blockchain)

作者： Huan Li Dongbin Wang Hui Zhi Yuchen Wang Tao Yang Jiang Song School of Cyberspace Engineering Beijing University of Post and Telecommunications Beijing China National Engineering Laboratory for Mobile Network Beijing China TravelSky Technology Limited Beijing China Cyberspace Security Research Center Peng Cheng Laboratory Shenzhen China

ISBN: (数字)9798350351590

ISBN: (纸本)9798350351606

Blockchain is a decentralized distributed ledger that is stored in a block chain, cannot be tampered with, is safe and trustworthy with the help of cryptography and consensus mechanism. However, the current performance and scalability of blockchain hinders its practical application in wider areas, so blockchain sharding technology was proposed. Sharding technology divides the blockchain into multiple shards. Each shard is responsible for processing a part of transactions and status. Multiple shards verify and process transactions in parallel, which improves the performance of the blockchain. Although sharding technology has potential in theory, in practical applications, it still faces a series of problems, such as shard load imbalance and a high proportion of cross-shard transactions. In order to solve the problems of unbalanced shard load and high proportion of cross-shard transactions in the blockchain sharding system, the DLDG (Dynamic Linear Deterministic Greedy) dynamic account division algorithm is proposed. DLDG constructs the shard load and cross-shard transaction ratio. The shard transaction rate balancing model periodically divides the account transaction network graph through historical transaction data, thereby achieving shard load balancing and reducing the cross-shard transaction rate. Experimental results show that this scheme alleviates performance problems caused by load imbalance and high cross-shard transaction rates.

关键词： Sharding Heuristic algorithms Scalability Smart contracts Load management Blockchains partitioning algorithms

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Time-Wheel based Multi-Series Sequence partitioning for Athlete Pain Detection Modeling

Time-Wheel based Multi-Series Sequence Partitioning for Athl...

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Information Technology and Contemporary Sports (TCS), International Conference on

作者： Jiadong Huang Tao Lin Biyuan Lin Dept. of Instrument research and development center Shenzhen YHLO Biotech Co. Ltd Shenzhen China School of Public Health Guangzhou Medical University Guangzhou China School of Biomedical Engineering Guangzhou Medical University Guangzhou China

ISBN: (数字)9798331529864

ISBN: (纸本)9798331529871

Athlete Pain detection is a crucial research area in sports science, with significant implications for improving performance, preventing injuries, and optimizing training plans. With the continuous development of Electronic Health Records (EHRs) technology, athlete health management and pain detection increasingly rely on multivariate time series data. In this paper, we propose a novel pain detection method for athletes, called Time-Wheel based Multi-Series Time-aware Toeplitz Inverse Covariance-based Clustering (TWM-TICC). The method models the athlete’s health status and pain progression by partitioning physiological data into subsequences and applying dynamic clustering to identify different stages of pain. TWM-TICC incorporates the multi-series nature and irregular time intervals of EHRs, allowing it to effectively capture pain patterns that may emerge during training. We first validate the method through experiments using real-world athlete physiological dataset from our university’s affiliated hospitals. The results show that TWM-TICC perform well in the accuracy and interpretability of pain detection.

关键词： Training Accuracy Pain Hospitals Time series analysis Data models Physiology partitioning algorithms Information technology Sports

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Anchor-Oriented Localized Voronoi partitioning for GPS-denied Multi-Robot Coverage

Anchor-Oriented Localized Voronoi Partitioning for GPS-denie...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Aiman Munir Ehsan Latif Ramviyas Parasuraman School of Computing University of Georgia Athens GA USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Multi-robot coverage is crucial in numerous applications, including environmental monitoring, search and rescue operations, and precision agriculture. In modern applications, a multi-robot team must collaboratively explore unknown spatial fields in GPS-denied and extreme environments where global localization is unavailable. Coverage algorithms typically assume that the robot positions and the coverage environment are defined in a global reference frame. However, coordinating robot motion and ensuring coverage of the shared convex workspace without global localization is challenging. This paper proposes a novel anchor-oriented coverage (AOC) approach to generate dynamic localized Voronoi partitions based around a common anchor position. We further propose a consensus-based coordination algorithm that achieves agreement on the coverage workspace around the anchor in the robots’ relative frames of reference. Through extensive simulations and real-world experiments, we demonstrate that the proposed anchor-oriented approach using localized Voronoi partitioning performs as well as the state-of-the-art coverage controller using GPS.

关键词： Location awareness Robot motion Precision agriculture Target tracking Robot kinematics Heuristic algorithms partitioning algorithms Environmental monitoring Intelligent robots Global Positioning System

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DIAPASON: Differentiable Allocation, partitioning and Fusion of Neural Networks for Distributed Inference

DIAPASON: Differentiable Allocation, Partitioning and Fusion...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Federico Nicolás Peccia Alexander Viehl Oliver Bringmann FZI Research Center for Information Technology Germany University of Tübingen Germany

ISBN: (数字)9783981926385

ISBN: (纸本)9798350348606

Concerns in areas such as privacy, energy consumption, climate gas emissions, and costs, push the trend of migrating neural network inference from being executed on the cloud to embedded edge devices. We present our novel approach DIA-PASON to overcome restrictions brought on by the computing and application requirements that impede their execution on resource-constrained embedded devices. Our approach addresses these challenges by distributing the inference across multiple computing instances, which could be anything ranging from a multi-CPU configuration on the same SoC to geographically distributed devices. In contrast to recent efforts which tend to apply heuristics to reduce the search space of their problem definition to solve it in a timely fashion, our novel problem definition applies the concept of continuous relaxation to the categorical selection of partitioning, layer fusion, and allocation opportunities. This approach overcomes the problem of the poor exploration of the actual search space that arises when removing potential distribution opportunities during problem simplifications. We conduct numerical simulations and ablation experiments on each one of the configuration parameters of our algorithm by distributing several widely used neural networks. Finally, we compare DIAPASON against the commonly used MoDNN baseline and a state-of-the-art approach, CoopAI, achieving a 44 % and 12 % mean speed-up respectively.

关键词： Privacy Neural networks Search problems Prediction algorithms Numerical simulation partitioning algorithms Resource management

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MT-PART: Metamorphic-Testing-Based Adaptive Random Testing Through partitioning

MT-PART: Metamorphic-Testing-Based Adaptive Random Testing T...

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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Zhihao Ying Dave Towey Tsong Yueh Chen Zhi Quan Zhou School of Computer Science University of Nottingham Ningbo China Zhejiang People's Republic of China Department of Computer Science and Software Engineering Swinburne University of Technology Hawthorn VIC Australia School of Computing and Information Technology University of Wollongong Wollongong NSW Australia

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

Metamorphic Testing (MT) has been repeatedly proven effective in detecting software faults. MT detects faults by checking the Metamorphic Relations (MRs) among Source Test Cases (STCs) and Follow-up Test Cases (FTCs) and the corresponding outputs. Metamorphic Groups (MGs) denote the associated STCs and FTCs. The performance of MT relates strongly to the MRs and MGs. However, previous studies that on MG generation mainly focused on improving the effectiveness (i.e. fault-detection capability) of MT, but to some extent overlooked the efficiency. This paper proposes a new kind of MG generation algorithms called Metamorphic-Testing-based Adaptive Random Testing through partitioning (MT-PART). These algorithms at-tempt to improve both the effectiveness and the efficiency of MT by dynamically partitioning the input domain and generating new STCs and FTCs that are uniformly distributed over their corresponding input domains. Through empirical experiments, we found that our algorithms are able to significantly outper-form other existing MG generation algorithms in terms of test efficiency, while maintaining good test effectiveness.

关键词： Heuristic algorithms Software algorithms Software partitioning algorithms Testing

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Research on the Generation Method of Power Grid partitioning Schemes Under the Background of High Proportion of New Energy Integration

Research on the Generation Method of Power Grid Partitioning...

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Energy Systems and Electrical Power (ICESEP), International Conference on

作者： Zijing LU Zishou Lil Jun Tang Hongkun Chen State Grid Hubei Electric Power Co. Ltd State Grid Corporation of China Wuhan Hubei China School of Electrical Engineering and Automation Wuhan University Wuhan Hubei China Hubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network Wuhan University Wuhan Hubei China

ISBN: (数字)9798350353563

ISBN: (纸本)9798350353570

Power grid partition is utilized widely for simplifying network structure, facilitating system monitoring and scheduling, and is an inevitable trend in development of large power grid. However, in the context of large-scale new energy integration, the uncertainty and volatility of its output have a significant impact on the operational characteristics of the power grid. Aiming at the shortcomings of traditional power grid partitioning methods that do not consider the impact of new energy integration, a generation method of power grid partitioning schemes considering the background of new energy integration is proposed. Firstly, a typical set of new energy output scenarios is obtained based on scenario generation and scenario reduction; Afterwards, the definition of electrical distance is given, the electrical distance matrix of the network is constructed, and a correction coefficient is defined based on the typical scenario set of new energy output to modify the electrical distance matrix. Then, the Dijkstra algorithm is used to expand it to the full dimensional electrical distance matrix; Finally, affinity propagation algorithm is used to complete the power grid partitioning, and a case study is conducted on an improved IEEE 39 node system to verify the effectiveness and rationality of the proposed method.

关键词： Renewable energy sources Uncertainty Affinity propagation Market research Power grids partitioning algorithms Scenario generation

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Leveraging the Cuboidal partitioning for Low Complexity CTU Structure Prediction in Versatile Video Coding

Leveraging the Cuboidal Partitioning for Low Complexity CTU ...

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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Md. Zahirul Islam Tanvir Ahmed Redoy Ashek Ahmmed Manoranjan Paul Manzur Murshed Department of CSE Rajshahi University of Engineering and Technology Bangladesh School of Computer Science University of Sydney Australia School of Computing and Mathematics Charles Sturt University Australia School of Info Technology Deakin University Australia

ISBN: (数字)9798350379037

ISBN: (纸本)9798350379044

As the capacity of communications systems is currently being outpaced by the increasing demand for access to audio-visual services, the versatile video coding (VVC) standard has emerged. It shows around 40% bit rate savings over the predecessor codec, the high efficiency video coding (HEVC) standard. However, this coding gain is obtained with a significant increase in the computational complexity associated with VVC. The cuboidal partitioning algorithm has shown capabilities in modeling both the global and local commonality of a video frame and discovers a set of non-overlapping rectangular regions, known as cuboids, over the current frame. Since cuboids are highly homogeneous and are computationally efficient, in this paper, it is proposed to employ their intrinsic homogeneity information in predicting the coding tree unit (CTU) structure of VVC. Experimental results show that up to 10.5% complexity reduction for intra coded 4K resolution video sequences, with an increase in bit rate by 1.4%.

关键词： Computational modeling Bit rate Video sequences Prediction algorithms Encoding partitioning algorithms Computational efficiency Standards High efficiency video coding Periodic structures

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