Throughput efficiency in body sensor networks: a clean-slate approach

Abstract

In this paper, a flexible role-based architecture for Body Sensor Networks (BSNs) is introduced. The proposed non-layered context-aware architecture is application-oriented and able to incorporate future applications. Particular applications have certain requirements. Functional units (roles) instead of protocol layers are designed to perform the required tasks for applications to work properly. The role data of an application is inserted in the role headers of the container and is available for other applications with the same basic, specific or particular roles. Furthermore, the performance of Automatic Repeat Request (ARQ), Forward Error Correction (FEC) block codes and FEC convolutional codes with respect to the throughput efficiency has also been analyzed for a BSN following the proposed role-based architecture. The numerical results show that the proposed role-based architecture outperforms the traditional layered architecture with respect to the throughput efficiency for all error control schemes. FEC block codes are able to maintain a high throughput efficiency over longer distances because the hop length extension technique is applied.