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检索条件"任意字段=10th IFIP International Conference on Network and Parallel Computing, NPC 2013"

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parallel Computation of the Combination of Two Point Operations in Conic Curves Cryptosystem over GF(2n) Using Tile Self-assembly 20th

Parallel Computation of the Combination of Two Point Oper...

引用

20th ifip WG 10.3 international conference on network and parallel computing, npc 2024

作者： Li, Yongnan School of National Security People’s Public Security University of China Beijing100038 China

ISBN: (纸本)9789819628292

How to accomplish the basic operations in cryptosystem becomes a hot research direction in the field of DNA-based cryptography. this paper proposes a DNA computing model that could fulfill parallel computation of point-addition and point-doubling, two fundamental point operations in conic curves cryptosystem, using tile self-assembly. the combination of the two operations is a key step to compute point-multiplication, a point operation to generate intractability of conic curve discrete logarithm problem. Point-addition is deduced by division in one sub-model and another sub-model calculates point-doubling directly and generates the parameters for division. the assembly time complexity of this model is 2n2+3n-3, and the space complexity is n4+3n3-3n+1. © ifip international Federation for Information Processing 2025.

关键词： Cryptography

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CMS: A Computility Resource Status Management and Storage Framework 20th

CMS: A Computility Resource Status Management and Storage F...

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20th ifip WG 10.3 international conference on network and parallel computing, npc 2024

作者： Peng, Xiaohui Luo, Xudong Chang, Kuo Wang, Yifan Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Nanjing Institute of InforSuperBahn Nanjing China

ISBN: (纸本)9789819628292

With the increasing demand for computility, managing distributed computility resources is crucial for improving service quality and performance of the cross-region computility infrastructure. In order to ensure timely and accurate scheduling of computing tasks on such infrastructure, a distributed computility status storage and query system is needed to achieve millisecond-level performance in terms of multidimensional sort query and multidimensional range query for computility status. thus, we propose CMS, a computility resource status management and storage framework, which leverages specialized multidimensional indexes to support millisecond-level resource status reporting and querying, as well as sort and range queries. In addition, we developed BCQL and a set of querying algorithms to enhance throughput and reduce query latency. Experimental results show that the average query latency of the multidimensional sorting queries and range queries of the CMS system is 2.499 ms and 2.014 ms, respectively. While, the latency of those queries in Redis-based framework reach 25.66 ms and 25.13 ms, which are 10× higher than the CMS. © ifip international Federation for Information Processing 2025.

关键词： Structured Query Language

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LDChain: A Lightweight and Scalable Blockchain System for Dynamic IoT Scenarios 20th

LDChain: A Lightweight and Scalable Blockchain System for ...

引用

20th ifip WG 10.3 international conference on network and parallel computing, npc 2024

作者： Wang, Jianrong Cao, Yuxuan Hu, Dengcheng Li, Qi Li, Sen Li, Xuewei Liu, Xiulong College of Intelligence and Computing Tianjin University Tianjin China School of Electrical and Information Engineering Tianjin University Tianjin China School of Future Technology Tianjin University Tianjin China

ISBN: (纸本)9789819628292

As a distributed ledger, blockchain inherently guarantees data consistency. However, when applied to the Internet of things (IoT), existing solutions employing blockchain systems struggle to address the scalability demands posed by the dynamic mobility of heterogeneous devices. To this end, we propose Lightweight DAG Chain (LDChain), a lightweight and scalable blockchain system tailored for IoT scenarios. LDChain connects weak nodes and strong nodes through a hierarchical DAG consensus algorithm. For weak nodes, we introduce a transaction-based DAG consensus mechanism utilizing a snapshot synchronization strategy to cater to the dynamic nature of weak nodes and the scalability demands of the system. the integrated snapshot synchronization strategy, based on the second latest block transaction selection algorithm, reduces the storage and computational overhead for resource-restricted devices. For strong nodes, we devise a block-based DAG consensus mechanism and a repackaging strategy, which resolves transaction conflicts across regions by managing conflicting transactions through a priority queue. We implement a prototype of LDChain and conduct experiments in a network environment comprising 10 cloud servers, simulating several strong nodes and weak nodes. the experimental results show that our system achieves a throughput exceeding 7000 transactions per second (TPS) and a transaction confirmation latency of 1.3 s with 100 nodes. © ifip international Federation for Information Processing 2025.

关键词： Scalability

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Machine Learning-Based, networking and computing Infrastructure Resource Management 17th

Machine Learning-Based, Networking and Computing Infrastruct...

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17th ifip WG 12.5 international conference on Artificial Intelligence Applications and Innovations (AIAI) / 6th 5G-PINE Workshop / AI-BIO Workshop / DAAI Workshop / DARE Workshop / EEAI Workshop / 10th MHDW Workshop

作者： Chochliouros, Ioannis P. Kostopoulos, Alexandros Payaro, Miquel Verikoukis, Christos di Vimercati, Sabrina De Capitani Vinogradov, Evgenii Ranjbar, Vida Vardakas, John Rahman, Md Arifur Soumplis, Polyzois Varvarigos, Emmanuel Hellen Telecommun Org OTE SA 99 Kifissias Ave Athens 15124 Greece Ctr Tecnol Telecomunicac Catalunya CTTC CERCA Barcelona Spain Univ Milan Milan Italy Katholieke Univ Leuven Leuven Belgium Iquadrat Informat SL Barcelona Spain IS Wireless Warsaw Poland Inst Commun & Comp Syst ICCS Athens Greece

ISBN: (纸本)9783030791599;9783030791575;9783030791568

5G mobile networks will be soon available to handle all types of applications and to provide service to massive numbers of users. In this complex and dynamic network ecosystem, end-to-end performance analysis and optimization will be key features in order to effectively manage the diverse requirements imposed by multiple vertical industries over the same shared infrastructure. To enable such a vision, the MARSAL project [ 1] targets the development and evaluation of a complete framework for the management and orchestration of network resources in 5G and beyond by utilizing a converged optical-wireless network infrastructure in the access and fronthaul/midhaul segments. At the network design domain, MARSAL targets the development of novel cell-free-based solutions. Namely, scalable and cost-efficient wireless access points deployment will be achieved by exploiting the distributed cell-free concept combined with wireless and wired serial fronthaul approaches. We will target the inclusion of these innovative functionalities in the O-RAN project. In parallel, in the fronthaul/midhaul segments MARSAL aims to radically increase the flexibility of optical access architectures for Beyond-5G cell site connectivity via different levels of fixed-mobile convergence. In the network and service management domain, the design philosophy of MARSAL is to provide a comprehensive framework for the management of the entire set of communication and computational network resources by exploiting novel ML-based algorithms of both edge and midhaul data centers, by incorporating the Virtual Elastic Data Centers/Infrastructures paradigm. Finally, at the network security domain, MARSAL aims to introduce mechanisms that provide privacy and security to application workload and data, targeting to allow applications and users to maintain control over their data when relying on the deployed shared infrastructures, while AI and Blockchain technologies will be developed in order to guarantee a secured

关键词： Cell-free Distributed cloud network automation Machine learning Secure multi-tenancy

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TPL: A Novel Analysis and Optimization Model for RDMA P2P Communication 17th

TPL: A Novel Analysis and Optimization Model for RDMA P2P Co...

引用

17th ifip WG 10.3 international conference on network and parallel computing, npc 2020

作者： Du, Zhen An, Zhongqi Xing, Jing University of Chinese Academy of Sciences Beijing China High Performance Computer Research Center Institute of Computing Technology CAS Beijing China

ISBN: (纸本)9783030794774

With increasing demand for networks with high throughput and low latency, RDMA is widely used because of its high performance. Because optimization for RDMA can fully exploit the performance potential of RDMA, methods for RDMA optimization is very important. Existing mainstream researches design optimization methods by constructing a more complete hardware view and exploring relation between software implementation and specific hardware behavior. However, the hardware architecture of NIC (like InfiniBand) is a "black box", which limits development of this type of optimization. So existing methods leave unsolvable problems. Besides, with development of RDMA technology, new features are proposed constantly. So, analysis and optimization methods of RDMA communication performance should be advancing with the times. the contributions of this paper are as follows: 1) We propose a new RDMA point-to-point communication performance analysis and optimization model: TPL. this model provides a more comprehensive perspective on RDMA optimization. 2) Guided by TPL, we design corresponding optimization algorithms for an existing problem, like WQE cache miss and a new scenario, like DCT. 3) We implement a new RDMA communication library, named ORCL, to put our optimizations together. ORCL eliminates WQE cache miss in real-time. And we simulate the workload of the in-memory KV system. Compared with existing RDMA communication implement, ORCL increases throughput by 95% and reduces latency by 10%. © 2021, ifip international Federation for Information Processing.

关键词： Optimization

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BGElasor: Elastic-Scaling Framework for Distributed Streaming Processing with Deep Neural network 16th

BGElasor: Elastic-Scaling Framework for Distributed Streamin...

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16th ifip WG 10.3 international conference on network and parallel computing, npc 2019

作者： Mu, Weimin Jin, Zongze Wang, Junwei Zhu, Weilin Wang, Weiping Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783030307080

In face of constant fluctuations and sudden bursts of data stream, elasticity of distributed stream processing system has become increasingly important. the proactive policy offers a powerful means to realize the effective elastic scaling. the existing methods lack the latent features of data stream, it leads the poor prediction. Furthermore, the poor prediction results in the high cost of adaptation and the instability. To address these issues, we propose the framework named BGElasor, which is a proactive and low-cost elastic-scaling framework based on the accurate prediction using deep neural networks. It can capture the potentially-complicated pattern to enhance the accuracy of prediction, reduce the cost of adaptation and avoid adaptation bumps. the experimental results show that BGElasor not only improves the prediction accuracy with three kinds of typical loads, but also ensure the end-to-end latency on QoS with low cost. © 2019, ifip international Federation for Information Processing.

关键词： Deep neural networks

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I/O Optimizations Based on Workload Characteristics for parallel File Systems 16th

I/O Optimizations Based on Workload Characteristics for Para...

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16th ifip WG 10.3 international conference on network and parallel computing, npc 2019

作者： Wei, Bing Xiao, Limin Zhou, Bingyu Qin, Guangjun Yan, Baicheng Huo, Zhisheng State Key Laboratory of Software Development Environment Beihang University Beijing China School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9783030307080

parallel file systems usually provide a unified storage solution, which fails to meet specific application needs. In this paper, we propose an extended file handle scheme to address this problem. It allows the file systems to specify optimizations for individual file or directory based on workload characteristics. One case study shows that our proposed approach improves the aggregate throughput of large files and small files by up to 5% and 30%, respectively. To further improve the access performance of small files in parallel file systems, we also propose a new metadata-based small file optimization method. the experimental results show that the aggregate throughput of small files can be effectively improved through our method. © 2019, ifip international Federation for Information Processing.

关键词： File organization

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Data fine-pruning: A simple way to accelerate neural network training 1

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15th ifip international conference on network and parallel computing, npc 2018

作者： Li, Junyu He, Ligang Ren, Shenyuan Mao, Rui The University of Warwick Coventry United Kingdom Shenzhen University ShenzhenGuangdong China

ISBN: (数字)9783030056773

ISBN: (纸本)9783030056766

the training process of a neural network is the most time-consuming procedure before being deployed to applications. In this paper, we investigate the loss trend of the training data during the training process. We find that given a fixed set of hyper-parameters, pruning specific types of training data can reduce the time consumption of the training process while maintaining the accuracy of the neural network. We developed a data fine-pruning approach, which can monitor and analyse the loss trend of training instances at real-time, and based on the analysis results, temporarily pruned specific instances during the training process basing on the analysis. Furthermore, we formulate the time consumption reduced by applying our data fine-pruning approach. Extensive experiments with different neural networks are conducted to verify the effectiveness of our method. the experimental results show that applying the data fine-pruning approach can reduce the training time by around 14.29% while maintaining the accuracy of the neural network. © ifip international Federation for Information Processing 2018.

关键词： Deep neural networks

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network and parallel computing - 10th ifip international conference, npc 2013, Proceedings

Network and Parallel Computing - 10th IFIP International Con...

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10th ifip international conference on network and parallel computing, npc 2013

ISBN: (纸本)9783642408199

the proceedings contain 34 papers. the topics discussed include: a virtual network embedding algorithm based on graph theory;access annotation for safe program parallelization;extracting threaded traces in simulation environments;a network-aware virtual machine allocation in cloud datacenter;totoro: a scalable and fault-tolerant data center network by using backup port;a cloud resource allocation mechanism based on mean-variance optimization and double multi-attribution auction;a scheduling method for multiple virtual machines migration in cloud;speeding up Galois field arithmetic on Intel MIC architecture;software/hardware hybrid network-on-chip simulation on FPGA;total exchange routing on hierarchical dual-nets;efficiency of flexible rerouting scheme for maximizing logical arrays;conditional diagnosability of complete Josephus cubes;accelerating parallel frequent itemset mining on graphics processors with sorting;and asymmetry- aware scheduling in heterogeneous multi-core architectures.

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A Fast and Accurate Way for API network Construction Based on Semantic Similarity and Community Detection 1

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14th ifip WG 10.3 international conference on network and parallel computing (npc)

作者： Yang, Xi Cao, Jian Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai 200240 Peoples R China

ISBN: (数字)9783319682105

ISBN: (纸本)9783319682105;9783319682099

With the rapid growth of the number and diversity of web APIs on the Internet, it has become more and more difficult for developers to look for their desired APIs and build their own mashups. therefore, web service recommendation and automatic mashup construction becomes a demanding technique. Most of the researches focus on the service recommendation part but neglect the construction of the mushups. In this paper, we will propose a new technique to fast and accurately build a API network based on the API's input and output information. Once the API network is built, each pair of the connected APIs can be seen as generating a promising mushup. therefore, the developers are freed from the exhausting search phase. Experiments using over 500 real API information gathered from the Internet has shown that the proposed approach is effective and performs well.

关键词： Web API Mashup construction API network

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