使用服務導向架構整合語意網技術於Hadoop與HBase

近年來網際網路的主流趨勢是社群網站，在人們普遍使用之下，資料成長是相當可觀的，社群網站的資料勢必構成巨量資料(Big Data)，這將導致系統在搜尋、儲存與運算效能上的嚴重負荷。本研究提出一個具語意服務導向的雲端運算架構(Semantic Service-Oriented Cloud Computing Framework，SSOCCF)，整合服務導向架構(Service-Oriented Architecture，SOA)與語意網(Semantic Web)技術於Hadoop雲端運算的環境，透過Hadoop雲端運算來改善社群網站中巨量資料的運算效能，採用語意網技術來改善巨量資料的搜尋效能，並使用HBase分散式資料庫來解決巨量資料的存取效能，HBase能有效分散式儲存和管理，並且支援Hadoop的MapReduce分散式運算，強化系統運算能力。本研究發展以餐飲為例的社群平台命名為"餐飲社群平台(Diet Social Platform，DSP)"，來驗證本研究所提出SSOCCF的可行性，在DSP中，針於餐飲資訊的分享以行動設備掃描QR Code作為識別依據，透過SOA啟動遠端的雲端運算，這也可提供其它平台來呼叫使用，提高重複使用與可擴充性。此外，DSP搜尋是基於語意網技術，由知識本體(Ontology)分類相關資訊，並制定Rule關係判斷，透過推論引擎區分資訊相關性，藉此尋找到符合使用者的資訊。經實際DSP的巨量資料測試，本研究所提出的SSOCCF能改善前述社群網站中巨量資料所衍生的問題。

關鍵字

語意網； Hadoop ； HBase ；服務導向架構；行動設備

並列摘要

Internet has become the main trend in social web. The main trend driven by the social web hasn’t underestimated yet. With widespread application, data growth is considerable. Social web data bound constitutes big data, which will lead to severe loading on system search, storage and computing performance. The current study proposes a Semantic Service-Oriented Cloud Computing Framework (SSOCCF), integration Service-Oriented Architecture (SOA) and semantic web technology in Hadoop cloud computing environment through Hadoop cloud computing to improve the social web in big data in computing performance. The use of semantic web technology to improve search performance of big data, and the use of HBase to distribute database to solve big data access performance. HBase could distribute storage and management effectively, provide support for Hadoop's MapReduce, distribute computing, and enhance system computing capabilities. The research and development of food would be exhibited as an example of the social platform named "Diet Social Platform (DSP)", to verify the feasibility of SSOCCF proposed in the current study. DSP in needle sharing information in using the QR Code identification serves as a basis for starting remote through SOA 's cloud computing in Mobile Device, which can provide other platforms to call use to improve reuse and scalability. In addition, DSP search is based on semantic web technology, the ontology classification of information, and the development of the relationship Rule judged by inference engine, which distinguishes the information relevance. By actual testing, DSP 's big data of user information may be acquired. SSOCCF proposed in this study to improve the aforementioned social web in big data problems arising.

並列關鍵字

Semantic Web ； Hadoop ； HBase ； Service-Oriented Architecture (SOA) ； Mobile Device

參考文獻

[1] Allen, J. P., March 2010, “Knowledge-Sharing Successes in Web 2.0 Communities”, Technology and Society Magazine, IEEE, pp. 58-64.

[2] I-Ching Hsu, May 2013, “Multilayer Context Cloud Framework for Mobile Web 2.0: A Proposed Infrastructure”, International Journal of Communication Systems, pp. 610-625.

[7] Niroshinie Fernando, Seng W. Loke and Wenny Rahayu, January 2013, “Mobile cloud computing: A survey”, Future Generation Computer Systems, pp. 84-106.

[8] Hadoop-Apache. Available: http://hadoop.apache.org/

[11] Joseph, R. C. and Johnson, N. A., Nov-Dec 2013, “Big Data and Transformational Government”, IT Professional, pp. 43-48.

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使用服務導向架構整合語意網技術於Hadoop與HBase

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