Home Appliance Control and Monitoring System Model Based on Cloud Computing Technology

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1 Home Appliance Control and Monitoring System Model Based on Cloud Computing Technology Yun Cui 1, Myoungjin Kim 1, Seung-woo Kum 3, Jong-jin Jung 3, Tae-Beom Lim 3, Hanku Lee 2, *, and Okkyung Choi 2 1 Department of Internet & Multimedia Engineering, Konkuk University 2 Center for Social Media Cloud Computing, Konkuk University Neungdong-Ro 120, Gwangjin-Gu, Seoul, Republic of Korea 3 3 Digital Media Research Center, Korea Electronic Technology Institute, Electronics Center #1599, Sangam-dong, Seoul , Republic of Korea {ilycy, tough105, okchoi20, {swkum, mozzalt, * Author to whom correspondence should be addressed; Abstract. With the development of intelligent home appliance technology, realtime home appliance status information is now generated in large quantities. New technology is necessary in order to process the large amount of status information that is generated every day. An innovative technology that has recently been used to process large amounts of data is cloud computing. Therefore, in this paper, we propose a system model to control and monitor home appliances using home network and cloud computing technologies in a smart home environment. UPnP technology is used to extract status information from home appliances. Cloud computing technology analyzes and processes the information and also provides virtualization services to users. In the proposed method, the gateway collects and stores home appliance information using home network technologies and sends the information to the cloud server for storage and management. Keywords: cloud computing technology, UPnP, virtualization services, smart home 1 Introduction Users are constantly provided with more convenient services due to the development of a variety of computing techniques such as mobile communication technology and data processing techniques. As the development of home appliance control techniques, embedded techniques, and smart devices has progressed, innovative smart home technology has also developed in the last several years. However, it is difficult to store, process, and manage the large amounts of status information that is generated by the home appliances of a smart home on a single node (i.e., PC). A collection of regional smart homes generates a huge amount of data per day. Therefore, a 336

2 technology to store and process a large amount of data is urgently needed. The technology that can provide such a technique is cloud computing. Cloud computing is a very efficient technique to process and analyze large amounts of data. Consequently, in this paper, we propose a novel system to collect the data generated in smart homes and process it based on cloud computing technologies. The proposed system model is divided into three parts: the gateway, cloud server, and smart device. The gateway identifies home appliances that use UPnP services, extracts the status information of the home appliances, and transmits the extracted data to a cloud server [2], [3], [8]. The cloud server stores data classified by the user and provides home appliance monitoring services to users using the virtualized status information of the home appliances. It also offers a distributed computing function and data storage service to users via Hadoop-based technologies such as MapReduce, HDFS, and Hbase [1], [3], [10]. The smart device allows users to monitor and control home appliance functions. The smart device receives the virtualized data of the home appliances from the cloud server. All of the proposed components communicate with each other using HTTP and transmit data using XML [8]. The remainder of this paper is organized as follows: Section 2 discusses current research work related to smart home technologies. Section 3 describes the proposed system architecture and explains its main functions. Finally, we conclude the paper in Section 4. 2 Related Work Cloud computing technology provides functions to store, handle, and manage large amounts of data over the internet. It consists of three platforms, IaaS, PaaS, and SaaS to offer many kinds of services to users. IaaS (Infrastructure as a Service) is a platform as well as the base layer of the cloud computing environment offering computing resources for cloud computing. The core technology of the IaaS platform is virtualization, a technology that converts physical resources to virtual resources and increases resource utilization and flexibility. PaaS (Platform as a Service) is a platform that uses high-speed distributed computing technology to process the large numbers of media data requests from SaaS and manages the data storage in IaaS. SaaS (Software as a Service) is a service platform to provide data management APIs and web-based development tools in the cloud computing environment [3]. A smart home, in the conventional sense, supports automatic systems to control lighting and temperature and activate security apparatus. It is used to monitor many aspects of daily life [4]. Nowadays, smart homes incorporate many computing technologies to provide convenient personalized service to users within the home network [5]. Recently, much research on the smart home has focused on the home gateway. Using a home gateway, a smart home can form a peer-to-peer network to provide home network service anytime, anywhere [6]. The lack of a de facto communication standard for smart homes hinders the integration of different services. Therefore, Kim et al. proposed smart home software architecture based on OSGi (Open Services Gateway initiative) [7]. 337

3 We reference these concepts when designing a system model to provide a personalized smart home service using cloud computing technologies. 3 Proposed System Model The proposed system provides home appliance monitoring service to users via a home appliance virtualization function supported by a cloud server. The cloud server also stores the status information of the home appliances transmitted from the gateway of the smart home and uses cloud computing technology to process this information. The gateway consists of a PC and home network using UPnP to search and collect the metadata of the home appliances in a smart home. The collected metadata is transmitted to the cloud server by the gateway. Figure 1 shows the architecture of the proposed system model. Fig. 1. Proposed system model architecture diagram The gateway is an important component of the smart home because it acts as a network bridge between the cloud server and the smart home. The gateway also monitors the home appliance statuses, collecting home appliance status information every ten minutes. If a home appliance status changes, the gateway gets this 338

4 information and sends it to the cloud server. The gateway is composed of four modules to provide home appliance control functions as follows. The identification module authorizes separate users using OAuth [9] generated by the cloud server. The UPnP device control module provides device selection, registration, and status monitoring functions using SSDP and GENA. The device controlling module sends actions to control the home appliances. The device metadata extraction module extracts detailed metadata from the home appliances. The device log data transmission module sends the data to the cloud server. The cloud server manages data, but remains separate from a smart home. Thus, the cloud server stores and manages home appliances status in a smart home over the gateway. The cloud server distinguishes and stores each home appliance of every smart home by user ID. The user ID is managed by the cloud server using Hbase, generating an OAuth-based identification number for each user. The cloud server virtualizes the home appliance status data of each independent smart home to provide virtualization service to users by user ID. The cloud server sends the virtualized home appliance data to the user s smart devices to support home appliance virtualization services. The user s smart device communicates with the cloud server and receives the status information of the home appliances using a specific application. The smart device includes an XML data extraction module. This module is able to extract XML data transmitted from the cloud server. All of the components communicate with each other using XML data transmitted through HTTP. If users are at home with a smart device that communicates with the cloud server, the smart device is able to directly connect with the gateway over the home router, reducing unnecessary traffic among the gateway, cloud server, and smart devices. 4 Conclusion In this paper, we propose a cloud-based system model to provide real-time home appliance monitoring and control services. The cloud server stores and manages a large amount of the status data generated by home appliances in smart homes. For transmitting cloud server status data of home appliances, we designed a gateway to support data communication between the cloud server and smart homes. The status data of home appliances in the cloud server is transferred to a smart device. Users monitor and control home appliances through the smart devices using the virtualized status data from the cloud server. However, if many users connect to the cloud server at the same time, a high amount of network traffic will occur in the cloud server. Therefore, to support better load dispersion, we will research effective algorithms in our future work. Acknowledgments. This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the C-ITRC (Convergence Information Technology Research Center) support program (NIPA-2013-H ) supervised by the NIPA (National IT Industry Promotion Agency). 339

5 References 1. Dean, J., Ghemawat, S.: Mapreduce: Simplified Data Processing on Large Clusters. In: OSDI 04, 6 th Symposium on Operating Systems Design and Implementation, pp (2004) 2. Dugeon, O., Hahdi, M., Bars, R., Carbu, R.: Extended UPnP Multimedia Content Delivery with an HTTP Proxy. In: FMN 2010, LNCS 6157, pp (2010) 3. Cui, Y., Kim, M., Lee, H.: Social Media Sharing System: Supporting Personalized Social Media Service Using UPnP Technology in Cloud Computing Environment. Information 15, (2012) 4. Bregman, D.: Smart Home Intelligence The ehome that Learns. International Journal of Smart Home 4(4), (2010) 5. Lin, H.T.: The Development of Control and Energy Usage Information Modules for Smart Homes. In: ICCAIS 2012, pp (2012) 6. Wei, Z., Qin, S., Jia, D., Yang, Y.: Research and Design of Cloud Architecture for Smart Home. In: ICSESS 2010, pp (2010) 7. Kim, J.E., Boulos, G., Yackovich, J., Barth, T., Beckel, C., Mosse, D.: Seamless Integration of Heterogeneous Devices and Access Control in Smart Homes. In: th International Conference on Intelligent Environments, pp (2012) 8. Contributing members of UPnP Forum.: UPnP Device Architecture Version 1.1. In: UPnP Forum (2008) 9. Hammer-Lahav., E.: The OAuth 1.0 Protocol. In: Internet Engineering Task Force, RFC 5849 (2010) 10. Vora, M.N.: Hadoop-HBase for Large-Scale Data. In: 2011 International Conference on Computer Science and Network Technology, pp (2011) 340

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