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Performance Analysis of Adaptive Resource Allocation Scheme for OpenCL-based FPGA Virtualization System 10

Performance Analysis of Adaptive Resource Allocation Scheme ...

10th international conference on Information and Communication technology convergence (ICTC) - ICT convergence Leading the Autonomous Future

作者： Le, Duc-Canh Oh, Eun-Young Cho, Gyu-Sang Lee, Kyung-Chae Kim, Sung-Hyun Youn, Chan-Hyun Korea Adv Inst Sci & Technol Sch Elect Engn Daejeon South Korea Korea Telecom Cloud Platform Dept Seoul South Korea Korea Adv Inst Sci & Technol Daejeon South Korea

ISBN: (纸本)9781728108933

A recent advance in the performance of FPGA devices is creating an industry trend toward an energy efficient, high-performance computing paradigm. In response to this trend, major cloud providers have begun to offer FPGA-as-a-Service (FaaS). Unfortunately, most of the current FPGA services and researches are inefficient in resource utilization, that they assign an FPGA per process which cannot be shared among users. In this paper, we propose a partial reconfiguration (PR) based virtualized FPGA (vFPGA) system with OpenCL compatibility. Moreover, we propose a run-time management system and dynamic resource allocation scheme to efficiently allocate resources in the system. With our system, FPGA resources can be fully utilized and shared by multiple users. Experimental results show that our proposed vFPGA system can accomodate multiple users with high resource utilization and low service latency. We suggest that our system is suitable for the current trend of cloud computing towards the mobile edge computing (MEC) cloud.

关键词： FPGA virtualization FPGA sharing FPGA as a Service (FaaS) Reconfigurable computing

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Design and Evaluation of Container-based Networking for Low-latency Edge Services 12

Design and Evaluation of Container-based Networking for Low-...

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12th international conference on ICT convergence (ICTC) - Beyond the Pandemic Era with ICT convergence Innovation

作者： Cha, Jae-Geun Kim, Sun Wook ETRI Artificial Intelligence Res Lab Daejeon South Korea

ISBN: (纸本)9781665423830

Edge computing processes and stores data on user devices located at the edge of the Internet to support latency-sensitive services such as autonomous vehicles, drones, and so on. This adopts container technology to quickly initialize and deploy applications. Containers interact with each other through Plugins implemented based on Container Network Interface (CNI). In particular, the network latency is different depending on the plugin. In this paper, we study plugins to provide low-latency edge services and evaluate the effect on data processing performance when multiple plugins are used at the same time. The SR-IOV plugins showed twice throughput than the kernel-based virtual network interface. Also, it had more than 50% bandwidth regardless of the addition of other virtual network interfaces on a single connection.

关键词： Edge computing Container network interface Low-latency edge service Kubernetes CNI plugin

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An Improved Particle Swarm Optimizer with Attraction and Repulsion

An Improved Particle Swarm Optimizer with Attraction and Rep...

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7th international conference on computing and convergence technology (ICCCT)

作者： Lu, Shilei Yu, Shunzheng Sun Yat Sen Univ Dept EE Guangzhou 510275 Guangdong Peoples R China

ISBN: (纸本)9781467308946;9788994364261

The particle swarm optimization (PSO) is a population-based strategy for global optimization. A rapid decrease of diversity in the iterative procedure leads the PSO to suffer from premature convergence on multimodal problems. This paper presents a novel variant of the PSO (PSO-CAR). It uses an animal foraging strategy with attraction and repulsion. This strategy guarantees a high diversity of the swarm to protect the PSO from premature convergence. The basic PSO (bPSO), genetic algorithm (GA) and two other variants of the original PSO are employed here to evaluate the effectiveness of the PSO-CAR using 6 standard numerical functions. Simulation results reveal that the proposed PSO-CAR outperforms the other approaches in solving multimodal problems.

关键词： Particle Swarm Optimization (PSO) Premature convergence PSO with Attraction and Repulsion

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Context-aware recommendation using pattern discovery in ubiquitous computing

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ON THE convergence OF BIO-INFORMATION-, ENVIRONMENTAL-, ENERGY-, SPACE- AND NANO-TECHNOLOGIES, PTS 1 AND 2 2005年第I期277-279卷 278-286页

作者： Kwon, J Kim, S Kyonggi Univ Dept Comp Sci Suwon South Korea Seoul Coll Dept Internet Informat Seoul South Korea

Ubiquitous computing requires an intelligent environment and context-aware recommendations. This paper describes context-aware recommendations using pattern discovery in ubiquitous computing. The proposed method recommends information that may be useful without requiring any action on the part of the user by changing the user's context. To recommend information, we discovered interesting patterns between past experiences and the current context. We explained the process, the algorithms and gave an example. Several experiments were performed and the results showed that our method has a good recommendation performance.

关键词： ubiquitous computing context-aware recommendation data mining

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Implementing Quantum-behaved Particle Swarm Optimization Algorithm in FPGA for Embedded Real-time Applications

Implementing Quantum-behaved Particle Swarm Optimization Alg...

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4th international conference on Computer Sciences and convergence Information technology

作者： Chai, Zhilei Sun, Jun Cai, Rui Xu, Wenbo Jiangnan Univ Sch Informat Technol Wuxi Peoples R China

ISBN: (纸本)9781424452446

Quantum-behaved Particle Swarm Optimization (QPSO) algorithm is the algorithm proposed by our group to improve traditional PSOs. Comparing with traditional PSOs, the QPSO has better global-convergence and fewer parameters. Both PSO and QPSO were generally considered to have high requirement for the computing platform;hence, it is thought impractical to employ them into resource-constrained embedded real-time systems. However, with the development of FPGA technology, recently many complex algorithms were implemented in FPGA to get high computing performance for the embedded real-time applications. In this paper, a micro-architecture specific for QPSO suited to be implemented in a low-end FPGA is proposed. Furthermore, this micro-architecture is designed with reconfigurability to meet different requirements on computing performance and resource consumption.

关键词： PSO(Particle Swarm Optimization) QPSO(Quantum-behaved Particle Swarm Optimization) FPGA(Field Programmable Gate Arrays) embedded real-time systems computing performance

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Usage Aware VNF Placement for Improved QoS in Edge computing 10

Usage Aware VNF Placement for Improved QoS in Edge Computing

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10th international conference on Information and Communication technology convergence (ICTC) - ICT convergence Leading the Autonomous Future

作者： Mutichiro, Briytone Yang, Hyunsik Kim, Younghan Soongsil Univ Sch Elect Engn Seoul South Korea

ISBN: (纸本)9781728108933

The advent of edge computing has given rise to new opportunities and challenges in the domain of cloud computing. While the key deliverable is to ensure reliable service provision to users, the characteristics of the edge cloud including high latency, unreliable bandwidth, real-time response, distance from the edge cloud among others, make it challenging to meet set targets. A major challenge operators face is the optimal placement of virtual network functions (VNFs). This problem has been widely researched in the literature of data centers from an operator's perspective little attention given to the user. We formulate the usage-aware placement problem for enhanced user quality of service (QoS) in edge environment. We aim to minimize the user response time through efficient placement and model the user requests in terms of user preference and service selection probability in influencing placement of VNFs in edge-cloud environments. Further we formulate a heuristic usage-aware placement algorithm solution for placement of these service requests. Our results show that our approach achieves considerable reduction in user time response and minimizes resource costs. It meets the QoS requirement for latency sensitive services.

关键词： Edge cloud VNF placement latency user preference user response time minimization resource cost minimization

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convergence of Knowledge in Project Management 8

Convergence of Knowledge in Project Management

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IEEE 8th international conference on Intelligent Data Acquisition and Advanced computing System-technology and Applications (IDAACS)

作者： Bushuyev, Sergey D. Bushuyev, Denis A. Rogozina, Victoria B. Mikhieieva, Olga V. Kyiv Natl Univ Construct & Architecture Project Management Dept 31 Povitroflotskiy Pr Kiev Ukraine

The article presents the development of project management based on knowledge convergence. The authors propose a model of genome of methodologies for management of project, programs and portfolios of organization proj... 详细信息

ISBN: (纸本)9781467383615

关键词： knowledge knowledge convergence genome of methodologies for project management

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Prioritized job scheduling algorithm using parallelization technique in cloud computing 2

Prioritized job scheduling algorithm using parallelization t...

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2nd international conference for convergence in technology (I2CT)

作者： Mhatre, Mallika Shree, Pragya Sharma, Sanjay Kumar Banasthali Univ Dept Comp Sci Vanasthali Rajasthan India

ISBN: (纸本)9781509043071

Cloud computing is a distributed and parallel computing model in which cloud service providers guarantees to provide services to client by pay-per-use model. Now-a-days, it is possible to share pool of virtualized computer resources, computational equipments, servers and storages in cloud computing environment. Allocating resources to highly prioritized job within estimated time is one of the biggest issues in job scheduling Job should be scheduled properly in order to provide higher throughput of the system and to maintain Quality of Service & Economic Principles of Management policies. To solve such scheduling problem, we have proposed prioritized job scheduling algorithm with parallelization technique. This algorithm mainly focuses on equally prioritized job problem and uses master-slave concept for job scheduling. We had compared and analyzed our algorithm with other priority based algorithm. Results shows that proposed algorithm improves performance and resource utilization of cloud and it reduces execution time period by balancing load across cloud.

关键词： cloud computing job scheduling priority parallelization

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Endorsement Policy for Industrial Internet of Thing with Private Blockchain 12

Endorsement Policy for Industrial Internet of Thing with Pri...

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12th international conference on ICT convergence (ICTC) - Beyond the Pandemic Era with ICT convergence Innovation

作者： Lee, Yunseong Lee, Donghyun Oh, Junsuk Park, Laihyuk Na, Woongsoo Cho, Sungrae Chung Ang Univ Sch Comp Sci & Engn Seoul South Korea Seoul Natl Univ Sci & Technol Sch Comp Sci & Engn Seoul South Korea Kongju Natl Univ Dept Comp Sci & Engn Cheonan South Korea

ISBN: (纸本)9781665423830

In the industrial Internet of Things (IIoT) environment, managing a significant amount of real-time sensing data generated by IIoT devices is a primary concern. Edge computing technology can effectively resolve this problem for low latency data exchange. However, it faces security challenges and management overhead of large volume of real-time IIoT traffic. In this paper, we propose to integrate a private blockchain into edge computing server systems to tack the challenges. The proposed system overcomes security challenges by allowing IIoT edge devices to execute smart contracts and verify transactions in private blockchain. In order to alleviate management overhead, we simplify the existing transaction process by introducing a novel endorsement policy. Performance evaluation shows that the proposed system can satisfy the low latency requirement and reduce energy consumption of the IIoT devices.

关键词： IIoT blockchain edge computing

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Virtual technology on CPSE-Bio

Virtual Technology on CPSE-Bio

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7th international conference on computing and convergence technology (ICCCT)

作者： Xie, Jiang Xia, Shangyun Zhang, Wu Nie, Qing Shanghai Univ Sch Comp Engn & Sci Shanghai 200444 Peoples R China Shanghai Univ Inst Syst Biol Shanghai 200444 Peoples R China Univ Calif Irvine Dept Math Irvine CA 92697 USA

ISBN: (纸本)9781467308946;9788994364261

Explosive growth of biomedical data in various platforms presents a major challenge for bioinformatics research. To analyze the ever-increasing amount of data, it requires unprecedented storage resources and computing power. To maximize the limited resources for big data, we propose a model on Bioinformatics Problem Solving Environment based on Cloud computing (CPSE-Bio). The proposed technique combines the Hadoop with virtualization technology, allowing each core on multicore computers to be virtualized as a computing node in the Hadoop cluster to take advantage of a common feature of modern processor with multicores. Adding virtualization creates more effective computing nodes in the cluster than the one without, and analysis and experiments demonstrate that our model enhances the resource utilization and computing efficiency in CPSE-Bio.

关键词： Virtualization CPSE-Bio Bioinformatics Hadoop KVM

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