Server Selection, Configuration and Reconfiguration Technology for IaaS Cloud with Multiple Server Types

Yamato, Yoji

doi:10.1007/s10922-017-9418-z

Cited by 22 publications

(4 citation statements)

References 46 publications

(49 reference statements)

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“…To estimate the average and worst delays due to server placement position and number of servers, no placement rule that applies to every network appears when the controller performs distributed processing with multiple servers [17]. The work in [18] presented a server selection, configuration, reconfiguration and automatic performance verification technology to satisfy the user functional and performance requirements on several types of cloud compute servers.…”

Section: Related Workmentioning

confidence: 99%

Participating-Domain Segmentation Based Delay-Sensitive Distributed Server Selection Scheme

2019

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This paper proposes a participating-domain segmentation based server selection scheme in a delay-sensitive distributed communication approach to reducing the computational time for solving the server selection problem. The proposed scheme divides the users' participation domain into a number of regions. The delay between a region and a server is a function of locations of the region and the server. The length between the region and the server is considered based on conservative approximation. The location of the region is determined regardless of the number of users and their participation location. The proposed scheme includes two phases. The first phase uses the server finding process and determines the number of users that are accommodated from each region by each server, instead of actual server selection, to reduce the computational complexity. The second phase uses the delay improvement process and determines the overall delay and the selected server for each user. We formulate an integer linear programming problem for the server selection in the proposed scheme and evaluate the performance in terms of computation time and delay. The numerical results indicate that the computational time using the proposed scheme is smaller than that of the conventional scheme, and the effectiveness of the proposed scheme enhances as the number of users increases. INDEX TERMS Real-time application, distributed processing, edge computing, and dividing users' participation domain.

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Section: Related Workmentioning

confidence: 99%

Participating-Domain Segmentation Based Delay-Sensitive Distributed Server Selection Scheme

2019

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“…(iii) A data scientist may analyze raw data and update a model using Jubatus in a cloud to improve analysis accuracy. (iv) An updated model is distributed to edges by a cloud . These bidirectional updates improve the analysis accuracy both in edges and the cloud.…”

Section: Maintenance Platform Using Lambda Architecturementioning

confidence: 99%

Maintenance of business machines with edge and cloud collaboration

Yamato

Kumazaki

2018

IEEJ Transactions Elec Engng

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Recently, internet of things (IoT) technologies have progressed, but IoT maintenance applications are not widespread in Japan yet because of insufficient analyses of real-time situations and the high costs of configuring failure detection rules and collecting sensing data. In this paper, using lambda architecture concept, we propose a maintenance platform on which edge nodes analyze sensing data, detect anomalies and extract a new detection rule in real time, and a cloud orders maintenance automatically.

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“…However, with the increase in complexity level of the cloud infrastructure, such cloud computing environment consumes high energy [9]. Thus, the recent heterogeneous cloud architectures are employing FPGAs along with CPUs and GPUs to overcome the existing limitations [10]. Acceleration in execution of a service request on such heterogeneous architecture is a challenging issue in cloud.…”

Section: Introductionmentioning

confidence: 99%

Energy-Aware Real-Time Tasks Processing for FPGA-Based Heterogeneous Cloud

Majumder

Saha

Chakrabarti

et al. 2022

IEEE Trans. Sustain. Comput.

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Cloud computing is becoming a popular model of computing. Due to the increasing complexity of the cloud service request, it often exploits heterogeneous architecture. Moreover, some service requests (SRs)/tasks exhibit real-time features, which are required to be handled within a specified duration. Along with the stipulated temporal management, the strategy should also be energy efficient, as energy consumption in cloud computing is challenging. In this paper, we have proposed a strategy, called "Efficient Resource Allocation of Service Request" (ERASER) for energy efficient allocation and scheduling of periodic real-time SRs on cloud platform. The cloud platform is consists of Field Programmable Gate Arrays (FPGAs) as Processing Elements (PEs) along with the General Purpose Processors (GPP). We have further proposed, an SR migration technique to reduce the tasks rejection by serving maximum SRs. Simulation based experimental results demonstrate that the proposed methodology is capable to achieve upto 90% resource utilization with only 26% SR rejection rate over different experimental scenarios. Comparison results with other state-of-the-art techniques reveal that the proposed strategy outperforms the existing technique with 17% reduction in SR rejection rate and 21% reduction in energy consumption. Further, the simulation outcomes have been validated on real FPGA test-bed based on Xilinx Zynq SoC with standard benchmark tasks.

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Server Selection, Configuration and Reconfiguration Technology for IaaS Cloud with Multiple Server Types

Cited by 22 publications

References 46 publications

Participating-Domain Segmentation Based Delay-Sensitive Distributed Server Selection Scheme

Participating-Domain Segmentation Based Delay-Sensitive Distributed Server Selection Scheme

Maintenance of business machines with edge and cloud collaboration

Energy-Aware Real-Time Tasks Processing for FPGA-Based Heterogeneous Cloud

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