On the data gathering capacity and latency in wireless sensor networks

Abstract

Abstract-In this paper, we investigate the fundamental properties of data gathering in wireless sensor networks, in terms of both capacity and latency. We consider a scenario in which s(n) out of n total network nodes have to deliver data to a set of d(n) sink nodes at a constant rate λ(n, s(n), d(n)). The goal is to characterize the maximum achievable rate, and the latency in data delivery. We present a simple data gathering scheme that achieves asymptotically optimal data gathering capacity and latency with arbitrary network deployments when d(n) = 1, and for most scaling regimes of s(n) and d(n) when d(n) > 1 in case of square grid and random node deployments. Differently from most previous work, our results and the presented data gathering scheme do not sacrifice energy efficiency to the need of maximizing capacity and minimizing latency. Finally, we consider the effects of a simple form of data aggregation on data gathering performance, and show that capacity can be increased by a factor f (n) with respect to the case of no data aggregation, where f (n) is the node density. To the best of our knowledge, the ones presented in this paper are the first results showing that asymptotically optimal data gathering capacity and latency can be achieved in arbitrary networks in an energy efficient way.

Fast Approximation Algorithm for Maximum Lifetime Aggregation Trees in Wireless Sensor Networks

“…In-network aggregation is an important paradigm to maximize lifetime and minimize energy consumption for a sensor network (Fasolo et al 2007), and it can also increase data gathering capacity in various scenarios (Santi 2010). We review two aggregation schemes that differ on how many messages can be aggregated into a single message.…”

Capacity of Data Collection in Wireless Sensor Networks Based on Mutual Information and MMSE Estimation

“…Capacity of data collection reflects how fast FC can collect sensing data from all sensors [2]. Understanding the capacity of the network is important for network designers in a feasibility of a large scale network deployment [3], particularly, to improve the performance of WSNs [1]. Furthermore, such understanding is essential in the development of efficient protocols [4].…”

“…Capacity limits of data collection in wireless sensor networks have been studied in the literature [1][2][3][4][5][6][7][8][9][10]. In [4,5], they introduced the transport capacity of many-to-one in dense sensor networks.…”

“…The model states that a successful transmission occurs when a sensor falls inside the transmission range of its intended transmitter and falls outside the interference ranges of other nonintended transmitters. However, the protocol model is relatively inaccurate, when simultaneous transmissions are allowed in the network [3,11].…”

“…In [6], they characterized the transport capacity of many-to-one dense wireless networks subject to a constraint on the total power. The energy efficiency and data latency are considered in [3] for designing data gathering capacity. However, they still do not provide how to allocate the power optimally.…”