Capacity of data collection in randomly-deployed wireless sensor networks

Data collection is one of the most important functions provided by wireless sensor networks. In this paper, we study theoretical limitations of data collection and data aggregation in terms of delay and capacity for a wireless sensor network where n sensors are randomly deployed. We consider different communication scenarios such as with single sink or multiple sinks, regularly-deployed or randomly-deployed sinks, with or without aggregation. For each scenario, we not only propose a data collection/aggregation method and analyze its performance in terms of delay and capacity, but also theoretically prove whether our method can achieve the optimal order (i.e., its performance is within a constant factor of the optimal). Particularly, with a single sink, the capacity of data collection is in order of \(\Uptheta(W)\) where W is the fixed data-rate on individual links. With k regularly deployed sinks, the capacity of data collection is increased to \(\Uptheta(kW)\) when \(k=O\left({\frac{n}{\log n}}\right)\) or \(\Uptheta\left({\frac{n}{\log n}}W\right)\) when \(k=\Upomega\left({\frac{n}{\log n}}\right)\). With k randomly deployed sinks, the capacity of data collection is between \(\Uptheta\left({\frac{k}{\log k}}W\right)\) and \(\Uptheta(kW)\) when \(k=O\left({\frac{n}{\log n}}\right)\) or \(\Uptheta\left({\frac{n}{\log n}}W\right)\) when \(k=\omega\left({\frac{n}{\log n}}\right)\). If each sensor can aggregate its receiving packets into a single packet to send, the capacity of data collection with a single sink is also increased to \(\Uptheta\left({\frac{n}{\log n}}W\right)\).