Software Maintenance Evaluation of Agile Software Development Method Based on OpenStack

Journal of Information Processing

Fukumoto

Kumazaki

2017

Self Cite

Abstract:Recently, progress has been made in IoT technologies and applications in the maintenance area are expected. However, IoT maintenance applications are not widespread in Japan yet because of the one-off solution of sensing and analyzing for each case, the high cost collecting sensing data and insufficient maintenance automation. This paper proposes a maintenance platform which analyzes sound data in edges, analyzes only anomaly data in cloud and orders maintenance automatically.

Section: Proposed Platform Architecturementioning

confidence: 99%

Predictive Maintenance Platform with Sound Stream Analysis in Edges

Journal of Information Processing

Fukumoto

Kumazaki

2017

Self Cite

“…When the server reconfiguration function collects data, network load can be balanced by time shift of collecting each server data. (e.g., collecting user A's servers in night and collecting user B's servers in midday) 6. The server reconfiguration function determines whether FPGA reconfiguration is needed by matching each computation frequency on the server and accelerated computation logic of the FPGA.…”

Section: Server Configuration and Reconfigurationmentioning

confidence: 99%

“…Infrastructure as a service (IaaS) cloud services have advanced recently [1][2][3][4][5][6][7][8][9]. Users can use virtual resources, such as virtual servers, virtual networks, virtual routers, on demand from IaaS service providers and can coordinate on-premise servers using service coordination technologies such as [10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

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

2017

J Netw Syst Manage

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We propose a server selection, configuration, reconfiguration and automatic performance verification technology to meet user functional and performance requirements on various types of cloud compute servers. Various servers mean there are not only virtual machines on normal CPU servers but also container or baremetal servers on strong graphic processing unit (GPU) servers or field programmable gate arrays (FPGAs) with a configuration that accelerates specified computation. Early cloud systems are composed of many PC-like servers, and virtual machines on these severs use distributed processing technology to achieve high computational performance. However, recent cloud systems change to make the best use of advances in hardware power. It is well known that baremetal and container performances are better than virtual machines performances. And dedicated processing servers, such as strong GPU servers for graphics processing, and FPGA servers for specified computation, have increased. Our objective for this study was to enable cloud providers to provision compute resources on appropriate hardware based on user requirements, so that users can benefit from high performance of their applications easily. Our proposed technology select appropriate servers for user compute resources from various types of hardware, such as GPUs and FPGAs, or set appropriate configurations or reconfigurations of FPGAs to use hardware power. Furthermore, our technology automatically verifies the performances of provisioned systems. We measured provisioning and automatic performance verification times to show the effectiveness of our technology.

“…Users can utilize these applications as a service stably by contracting cloud providers. (The work of Refs [1][2][3][4][5] are examples of production cloud service developments, and the work of Ref. [6] is an example of cloud high available technology.)…”

Section: Introductionmentioning

confidence: 99%

Proposal of shoplifting prevention service using image analysis and ERP check

IEEJ Transactions Elec Engng

Fukumoto

Kumazaki

2017

Self Cite

In this paper, we propose a software‐as‐a‐service application that prevents shoplifting using image analysis and enterprise resource planning (ERP). In Japan, the total damage due to shoplifting has reached ¥450 billion per year, and each year more than 1000 small book stores give up their business because of shoplifting damage. Based on the recent advancement in cloud technology and data analysis technology, we propose a shoplifting prevention service with the image analysis of security camera movie and ERP data check for small shops. We also confirm the precision ratio of security camera stream movie analysis using the online machine learning framework Jubatus. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.