Multichannel data collection for throughput maximization in wireless sensor networks

2012-10-09Recent studies have shown that wireless sensor networks are fundamentally throughput-limited because of their high densities, scale, and convergecast nature of data collection traffic. Thus, it is of interest to develop high-rate data collection techniques for sensor networks. In this thesis, we make four contributions to address this challenge. ❧ First, through systematic experiments with real WSN hardware (Tmote Sky), we identify the maximum possible throughput for many-to-one (convergecast) data collection in sensor networks as a function of key communication parameters such as packet size, use of acknowledgements, and network topology. ❧ Second, we demonstrate that the maximum achievable network throughput can in fact be attained in practice using a carefully designed mix of routing, frequency allocation and time scheduling. We implement this in the form of Multi-Channel Collection (MCC), the first near-optimal multi-channel time-scheduled protocol for fair, real-time data collection in Wireless Sensor Networks. Compared to state of the art single-channel random-access-based collection protocols for WSN, we show through testbed experiments that this approach offers 48-155% improvement in throughput. We also show how to exploit the time-scheduled nature of this approach for other benefits: dramatically reducing the number of required frequency channels as well as decreasing the energy utilization. ❧ Third, we measure and analyze the link qualities across all channels in an indoor testbed. We observe that, besides the time-varying and location-dependent features, links exhibit a large variety of qualities in different channels. And asymmetry is common (on average, about 30%) for links in all channels. Based on these observations, we argue that channel quality awareness is important for multichannel protocols. ❧ Finally, we design new routing and channel allocation approaches, CQAR (Channel-Quality-Aware Routing) and CQAA (Channel-Quality-Aware Allocation), which take the channel quality into consideration. Both CQAR and CQAA can be incorporated into the MCC framework. According to how MCC uses the channel quality information, we propose three different variants: ICRA (Ideal Channel-based Routing and Allocation), CQAA, CQARA. We evaluate these approaches by simulations based on real testbed measurement. The results show that CQAA and CQARA are able to achieve high overall delivery ratio and normalized throughput. Though ICRA has similar performance when network size is small, it does not scale very well as the other two. CQARA exhibits high efficiency of both channel utilization and energy consumption. This shows the benefits of considering channel quality in multichannel protocols