Exchange of Data for Big Data in Hybrid Cloud Environment

Transcription

1 , pp Exchange of Data for Big Data in Hybrid Cloud Environment Chi-gon Hwang 1, Chang-Pyo Yoon 2 and Daesung Lee 3 1 Dept of Internet Information, Kyungmin College, Gyeonggi , Korea 2 Dept of Computer & Mobile Convergence, Gyeonggi Collage of Science and Technology, Gyeonggi , Korea 3 Dept of Computer Engineering, Catholic University of Pusan, Busan , Korea 1 duck1052@kw.ac.kr, 2 cpyoon@gtec.ac.kr, 3 dslee@cup.ac.kr Abstract The cloud environment is currently expanding rapidly, from its uses by individuals on standard computer devices to the mobile arena. Service providers for cloud computing are mutually exclusive, but their practices and protocols tend to influence each other, and this is referred to as a hybrid cloud environment. There are many of the types of services, software, and resources used and operated in the hybrid cloud environment, and the differences in defining and formatting data causes various problems in exchanging that data. We are proposing a specific document format for exchanging data as a means to solve the aforementioned issue. In short, we are suggesting the application of mapping techniques from data expression and new standards for document-oriented databases. Keywords: Hybrid Cloud Computing, Cloud computing, JSON (JavaScript object notation), Ontology, Data Exchange Method, Data Heterogeneity 1. Introduction Cloud computing is computing technology that provides IT resources to users directly from the Internet, as opposed to resources utilized from an individual s own computing device [1]. This service includes all types of IT resources utilizing hardware and/or software. This type of cloud computing emphasizes mobility in the eyes of the average user. There is a vast amount of data stored and trafficked through this environment [2]. The hybrid cloud is an environment that supports a combination of two or more independently operated, cloud-based environments [3]. But when independently operated cloud-based environments are utilized, there becomes an issue of data heterogeneity caused by different systems using different protocols. In order to solve this issue, JSON was created as a way of exchanging lightweight data [4]. However, the JSON data expression tends to be in a dual structure in the form of name/value. Here, it is feasible to solve an issue of heterogeneity of data by converting them to a triple format. This is performed by local and global mapping techniques. With the implementation of this type of JSON, it is also feasible to solve the issue of heterogeneity utilizing only one mapping. The global format used performs with existing data without the need for conversion and with only one mapping through XMDR [5, 6]. This study is intended to propose a hybrid format for document-oriented data for mutually operating the data in the hybrid cloud environment and evaluating the functionality of the application. In this paper, Chapter 2 describes related studies, Chapter 3 suggests a data format, Chapter 4 is an evaluation, and Chapter 5 concludes our findings. ISSN: IJSEIA Copyright c 2015 SERSC

2 2. Relative Works 2.1. Hybrid Cloud Environment The cloud is a technology that provides IT resources to users in the form of a service. The hybrid cloud is a permanent cloud connected by two or more cloud services, and there is a system for managing them [7]. It provides virtual IT solutions by combining public and private sector clouds. This provides more security for data and applications, and makes it feasible for many of the users to access information through Internet. In addition, it has an open structure, making it feasible to interface with other management systems. In summary, it is provided as an expansion of the cloud distribution model, networking, platform, storage, and software infrastructure or in on-demand services [3]. The hybrid cloud environment suggested in this document is an environment consisting of the existing hybrid system, which includes the mobile cloud arena as shown in the Figure 1. Collision Private Cloud (medical, enterprise, etc.) Public Cloud (google, facebook, etc.) Hybrid Cloud Collision Mobile Cloud Collision Figure 1. Hybrid Cloud Environment: It is a combination of Private Cloud, Public Cloud and Mobile Cloud 2.2. JSON (JavaScript Object Notation) JSON is designed for the exchange of lightweight data, is easily readable by people, and is also conveniently analyzed and processed by a computer. JSON has an analytical ability faster than XML on web browsers. However, JSON s weakness is a lack of name space support, input verification, and expansion in spite of the aforementioned outstanding functions. Hereupon, Crockford insisted, All the objects are name spaces. The set of keys is independent with all other objects. In addition, JSON is using context to avoid ambiguity like programming language. [4]. Individual domain application is responsible for input verification. Lack of expansion is solved by the flexibility of JSON s structure [8]. JSON s grammar is easily read by people. An object is an unordered set of name/value pairs. Following are the cases for encoding names and addresses and how to use them. { "Name": "Jason", "Address": "Seoul Korea" } Figure 2. A JSON of Simple Sample Construct Describing the Encoding of an Address 68 Copyright c 2015 SERSC

3 Databases using the aforementioned data format are emerging. These databases are document-oriented databases such as mongodb or couchdb. The data formats of the databases saved on them are saved and operated in JSON [9]. 3. Data Exchanging Method for Hybrid Cloud Computing 3.1. Exchange Data Type As mobile computing and cloud computing are developed, a vast amount of data is created. Hereupon, bit data is being researched as a technique for processing that data. With big data, it is feasible to extract relevant data from a vast amount of data and analyze it. This becomes important information for making decisions. There is a type of JSON that can be used for processing big data. This JSON type has a name/value structure as expressed on the left in Figure 3. This might be efficient in one cloud with an equivalent schema structure. However, it is not efficient in the hybrid cloud. For this reason, this study is suggesting the method indicated on the right in Figure 3. JSON { } name" : "value", name : "value", Proposed type { } name" : "gname" : "value", name" : "gname" : "value", Figure 3. Proposed Type and JSON Type for Data Exchange The suggested method has a triple structure: name/gname/value. Name and value have an equivalent method used in the previous JSON type. Here, global name, which can be commonly applied to the hybrid cloud of gname, is added, mapping it by global name in the movement between clouds and converting it to each of the clouds in an appropriate format. Hereupon, global name utilizes ontology, identifying the semantic relationship used in the cloud and producing it. This operation is performed by the management system as shown in Figure 4. This system is used for mutual operation between clouds in the hybrid cloud. JSON type JSON type Cloud #1 G/L converter Proposed type G/L converter Cloud #2 control control monitoring Management System monitoring Figure 4. Data Exchange of Proposed Method. Within the Individual Cloud, Data is Moved by the Typical JSON Method. However, Data is Moved in between Clouds by the Above-Suggested JSON Type Method Copyright c 2015 SERSC 69

4 In this system, clouds belonging to the hybrid cloud are monitored, identifying the format and meaning, or the modified data and renewing the group global name. The renewed information produced then becomes information for converting the G/L converter. Then, the G/L converter is produced and transferred by the method suggested in Figure 3 when sending data to other clouds belonging to the hybrid cloud. The receiving cloud is able to solve the heterogeneity of the data by changing it to JSON. A B Figure 5. The Comparisons between JSON Type and Proposed Type. It is Time of Transmission Total Time and Average Time 3.2. Improvements of Multiple Alignments by Sequence Selections In the previous section, a data-transferring format was suggested. This section is intended to compare and analyze the transferring time when transferring with JSON, as well as the suggested method. Figure 5 is a result of comparing the transferring time of the JSON type method suggested. A is a comparison of the transferring time by increasing the number of objects from 1000 to 5000 for two methods. The two methods represent a similar distribution in an increasing trend. However, it is confirmed that the suggested method has a slower speed than the JSON type. This is time used for mapping and it represents a small difference. B is the average transferring time of the two methods. As a result, it was confirmed that the difference in time required for mapping was reduced as the amount of data increased. 4. Conclusion This study has suggested a data transferring method for improving the efficiency of data transfer between clouds in the hybrid cloud and a way to evaluate that efficiency. The researchers have applied mapping methods using the ontology suggested in XMDR to the previous data transferring method of JSON type and hence suggested an efficient method for data transfer. In addition, as a result of testing transfer speeds with the suggested method, the researchers have concluded their method to be efficient since the load from the data transfer is small. A follow-up study is recommended to deal with details concerning monitoring and converting the type. 70 Copyright c 2015 SERSC

5 References [1] H. T. Dinh, C. Lee, D. Niyato and P. Wang, A survey of mobile cloud computing: architecture, applications, and approaches, Wireless Communications and Mobile Computing, vol. 13, no. 18, (2013), pp [2] D. Agrawal, S. Das and A. El Abbadi, Big data and cloud computing: current state and future opportunities, Proceedings of the 14th International Conference on Extending Database Technology, ACM, (2011), pp [3] S. Ramgovind, M. M. Eloff and E. Smith, The management of security in cloud computing, Information Security for South Africa (ISSA), IEEE, (2010), pp [4] JSON, json.org. [5] Z. Jialei, C. G. Hwang, G. D. Jung and Y. K. Choi, A design of K-XMDR search system using topic maps, Journal of information and communication convergence engineering, vol. 9, no. 3, (2011), pp [6] C. P. Yoon, S. J. Moon and C. G. Hwang, MCSOSA: multimedia content share using ontology and secure access agent in mobile cloud, Multimedia Tools and Applications, (2013), pp [7] Global Netoptex Incorporated 2009, Demystifying the cloud. Important opportunities, crucial choices, viewed 13, (2009), pp [8] N. Nurseitov, M. Paulson, R. Reynolds and C. Izurieta, Comparison of JSON and XML Data Interchange Formats: A Case Study, Caine, (2009), pp [9] C. Strauch, U. L. S. Sites and W. Kriha, NoSQL databases, Lecture Notes, Stuttgart Media University, (2011). Authors Chi-Gon Hwang, he is a professor in the Department of Internet Information, Kyungmin College, Gyeonggi, Korea. He received the B.S. degree in Business Administration from Changwon National University, Korea, in The M.S. and Ph.D degree in computer software from Kwangwoon University, Seoul, Korea, in 2004 and His current research interests include distributed computing, cloud computing, interoperability, semantic social network, multimedia database, ontology. Chang-Pyo Yoon, he is a professor in the Department of Computer & Mobile Convergence, Gyeonggi Collage of Science and Technology, Gyeonggi, Korea. He received a B.S. and a M.S. degrees and a Ph.D. degree from the Department of Computer Science, Kwangwoon University, Seoul, Korea. His research interests IoT, mobile security, wireless network and network security. Daesung Lee, he is a professor in the Department of Computer Engineering, Catholic University of Pusan, Korea. He received the B.S., M.S. and Ph.D. degrees from the Inha University, Korea, in 1999, 2001 and 2008, respectively, all in Electrical Engineering Computer Science & Engineering from Inha University. His research interests include security in network, convergence and operating system. Copyright c 2015 SERSC 71

6 72 Copyright c 2015 SERSC