Chunsheng Zhu, Victor C. M. Leung, Hai Wang, Wei Chen, Xiulong Liu
{"title":"Providing Desirable Data to Users When Integrating Wireless Sensor Networks with Mobile Cloud","authors":"Chunsheng Zhu, Victor C. M. Leung, Hai Wang, Wei Chen, Xiulong Liu","doi":"10.1109/CloudCom.2013.86","DOIUrl":null,"url":null,"abstract":"Wireless sensor networks (WSNs) receive a lot of attention because of their great potential in monitoring the physical or environmental conditions of military, industry, and civilian. Moreover, mobile cloud computing (MCC) is widely focused, as they can greatly alleviate the hardware limit of mobile devices as well as enable a lot of new mobile applications. All these make the integration of WSNs and MCC a very hot research topic. In this paper, we first observe a context non-awareness issue between mobile user and WSNs, which affects the mobile user obtaining the desirable data when integrating WSNs and MCC. Then focusing on solving the context non-awareness issue to provide desirable data to mobile users, we propose a novel framework for integrating WSNs and MCC. The proposed framework performs data recommendation, data prediction as well as data traffic monitoring in the cloud to obtain the data feature information required by the mobile users and potential status of WSNs. Then these user data feature information and potential WSNs status information are utilized to optimize the deployment of WSNs and check the status of WSNs. This could in turn offer the desirable data to the mobile users. Extensive evaluations also validate the effectiveness of the proposed framework.","PeriodicalId":198053,"journal":{"name":"2013 IEEE 5th International Conference on Cloud Computing Technology and Science","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 5th International Conference on Cloud Computing Technology and Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CloudCom.2013.86","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22
Abstract
Wireless sensor networks (WSNs) receive a lot of attention because of their great potential in monitoring the physical or environmental conditions of military, industry, and civilian. Moreover, mobile cloud computing (MCC) is widely focused, as they can greatly alleviate the hardware limit of mobile devices as well as enable a lot of new mobile applications. All these make the integration of WSNs and MCC a very hot research topic. In this paper, we first observe a context non-awareness issue between mobile user and WSNs, which affects the mobile user obtaining the desirable data when integrating WSNs and MCC. Then focusing on solving the context non-awareness issue to provide desirable data to mobile users, we propose a novel framework for integrating WSNs and MCC. The proposed framework performs data recommendation, data prediction as well as data traffic monitoring in the cloud to obtain the data feature information required by the mobile users and potential status of WSNs. Then these user data feature information and potential WSNs status information are utilized to optimize the deployment of WSNs and check the status of WSNs. This could in turn offer the desirable data to the mobile users. Extensive evaluations also validate the effectiveness of the proposed framework.