A Design of Flexible Data Channels for Sensor-Cloud Integration

Abstract

The recent popularity of sensor networks and cloud computing has brought new opportunities of sensor-cloud integration that facilitates users to immediately forecast the future status of what they are observing. The main challenge is how to establish a series of elastic data channels from sensors to mobile users through data-analyzing jobs running in the cloud. The variation of network protocols, the dynamism of cloud-computing resources, and even user mobility result in the following three design problems. Data-analyzing programs must: (1) deal with the major sensor and cloud communication protocols, (2) include hard-coded sensor manipulation and data retrieval operations, and (3) handle job/user migration in dynamic cloud environments, which needs the recovery of broken data connections. To address these problems, we are developing the Connector software tool kit that provides cloud jobs with uniform data channels, allows them to exchange standard input/output as well as graphics with remote users, and re-establishes their data channels upon a job or user migration. This paper presents Connector's system overview, implementation, and performance consideration.