Experimental Performance Evaluation of POBICOS Middleware for Wireless Sensor Networks

The advances in the theory of wireless sensor networks have been remarkable during the past decades, but there is a lack of extensive experimental evaluations. In this paper we present performance-evaluation methods and results for POBICOS (platform for opportunistic behaviour in incompletely specified, heterogeneous object communities), which is an advanced middleware for wireless sensor networks (WSNs). The measurements concern energy consumption, duty cycle, and OS task profiling as well as communication characteristics such as round trip time (RTT) and throughput. In addition, a bandwidth analysis during a long-term experiment of fully functional POBICOS network and application is studied. Based on the evaluation results, power mode and data cache improvements are presented as well as CPU clock frequency optimizations. 1. Introduction The research done in the field of WSNs has advanced a lot in the past decades. The achieved performance of a WSN implementation is inevitably tied to the characteristics of the used platform, and therefore, the performance evaluation cannot rely solely on the theoretical background. Our study presents an experimental performance evaluation of POBICOS which is an advanced opportunistic WSN middleware implemented on TinyOS operating system and Imote2 hardware platform. The performance evaluation methods and results are related to energy consumption, duty cycle, and OS task profiling as well as communication characteristics such as round trip time and throughput. In addition, a bandwidth analysis during a long-term experiment of fully functional POBICOS network and application is included. Based on the evaluation results, power mode and data cache improvements are presented as well as CPU clock frequency optimizations. Energy consumption of battery-powered sensor motes is a very crucial implementation issue which affects the operational costs of the WSN. The energy consumption is mainly affected by the achieved duty cycle and power modes of the motes. The overall operational energy consumption of the motes may be obtained through online energy consumption monitoring or through a hybrid method, in which the results of offline energy consumption measurements and online duty cycle monitoring are combined. The duty cycle investigation is based on CPU usage monitoring which, in case of the Imote2 platform, can be implemented through performance monitoring unit (PMU) events. The duty cycle optimization can be achieved through monitoring the CPU usage of each running task with a task profiler. This usually requires modifications