Platform-independent development of collaborative wireless body Sensor network applications

Authors:
G. Fortino;A. Guerrieri;F. Bellifemine;R. Giannantonio
Affiliations:
Dept. of Electronics, Informatics and Systems, University of Calabria, Rende, CS, Italy;Dept. of Electronics, Informatics and Systems, University of Calabria, Rende, CS, Italy;Telecom Italia Labs, Torino, Italy;Telecom Italia Labs, Torino, Italy
Venue:
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Year:
2009

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Abstract

Rapid development of Wireless Body Sensor Network (WBSN) applications can be enabled by suitable domain-specific frameworks which are usually organized in two parts: a base-station-side (or coordinator) and a sensor-node-side. While the former can be based on the Java language so being highly portable, the latter is usually highly dependent on the exploited sensor platform. Available state of the art frameworks follow such an organization and, in particular, the current version of SPINE is based on TinyOS and can be only used to effectively develop collaborative WBSN applications for TinyOS-based sensor platforms. To develop SPINE-based applications for new sensor platforms, the SPINE framework should be re-implemented for each new sensor platform to be exploited. This not only increases development efforts but also enforces SPINE-oriented developers to become skilled on the low-level programming abstractions provided by a new employed sensor platform. In this paper we discuss issues related to platform-independent development of collaborative WBSN applications and, specifically, describe the requirements, architecture and first implementation experiences of SPINE2 which aims at reaching a very high platform independency and raising the level of the used programming abstractions by providing a task-oriented programming model. The paper also discusses how such a task-oriented model enables dynamic task assignment and holistic collaborative task execution also for resource-constrained environments such as tiny sensor nodes.