Continuous Data Collection Capacity of Wireless Sensor Networks under Physical Interference Model

• Authors: Shouling Ji;Raheem Beyah;Yingshu Li
• Venue: MASS '11 Proceedings of the 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems
• Year: 2011

Data collection is a common operation of Wireless Sensor Networks (WSNs). The performance of data collection can be measured by its achievable \emph{network capacity}. However, most existing works focus on the network capacity of \emph{unicast}, \emph{multicast} or/and \emph{broadcast}, which are different communication modes from data collection, especially continuous data collection. In this paper, we study the \emph{Snapshot/Continuous Data Collection} (SDC/CDC) problem under the Physical Interference Model (PhIM) for randomly deployed dense WSNs. For SDC, we propose a \emph{Cell-Based Path Scheduling} (CBPS) algorithm based on network partitioning. Theoretical analysis shows that its achievable network capacity is $\Omega(W)$ ($W$ is the data transmitting rate, \emph{i.e.} bandwidth, over a channel), which is order-optimal. For CDC, we propose a novel \emph{Segment-Based Pipeline Scheduling} (SBPS) algorithm that significantly speeds up the CDC process, and achieves a surprising network capacity, which is at least $\sqrt{\frac{n}{\log n}}$ or $\frac{n}{\log n}$ times better than the current best result.