On optimal energy efficient convergecasting in unreliable sensor networks with applications to target tracking

Abstract

In this paper, we develop a mathematical framework for studying the problem of maximizing the "information" received at the sink in a data gathering wireless sensor network. We explicitly account for unreliable links, energy constraints, and in-network computation. The network model is that of a sensor network arranged in the form of a tree topology, where the root corresponds to the sink node, and the rest of the network detects an event and transmits data to the sink over one or more hops. This problem of sending data from multiple sources to a common sink is often referred to as the convergecasting problem. We develop an integer optimization based framework for this problem, which allows for tackling link unreliability using general error-recovery schemes. Even though this framework has a non-linear objective function, and cannot be relaxed to a convex programming problem, we develop a low complexity, distributed solution. The solution involves finding a Maximum Weight Increasing Independent Set (MWIIS) in rectangle graphs over each hop of the network, and can be obtained in polynomial time. Further, we apply these techniques to a target tracking problem where we optimally select sensors to track a given target such that the information obtained is maximized subject to constraints on the per-node sensing and communication energy. We validate our algorithms through numerical evaluations, and illustrate the advantages of explicitly considering link unreliability in the optimization framework.

Median Access Control Protocols for Sensor Data Collection: A Review

“…To achieve this, they made a vital assumption that for any internal node in the network, the transmission order of its child nodes is already known. In [56], the authors formulated an integer programming problem which explicitly accounted for unreliable links and per-node energy constraints. They developed a distributed solution with low time and message complexity, to wisely allocate the transmission and reception energies at every sensor node such that the QoA at the base station gets maximized.…”

“…Although neither the deadline nor the interference was considered in [56] and the authors did not build any transmission schedule, the algorithm developed in [56] served as a building block for their later work presented in [57], which considered a problem more general than problems considered in [55] and [56]. The work of [57] explicitly accounted for the per-node energy constraints, unreliable links, deadlines and interference.…”

“…Sensor data gathering is a major process involved in many wireless sensor network applications such as environmental monitoring and target tracking [53], [56]. In these applications, sensor nodes generate data every sampling interval and they coordinately transmit the data to a centralized controller (base station or sink node).…”

Efficient Solutions Framework for Optimal Multitask Resource Assignments for Data Fusion in Wireless Sensor Networks

“…Decentralized algorithms have been developed for relatively simpler reward functions. For instance, in Hariharan and Shroff [2011], the authors have developed a decentralized algorithm for a sensor network with a tree topology for the case where the overall reward obtained by fusing information from multiple sensors is a weighted sum of the rewards from individual sensors.…”

A Lifetime-Preserving and Delay-Constrained Data Gathering Tree for Unreliable Sensor Networks

“…Data gathering is a basic operation for many sensor network applications. In most cases, the sink only requires information aggregated by different nodes [1][2], e.g., average humidity, maximum pressure, top-k temperature, an indication whether a target is present, etc. In such cases, intermediate nodes perform respective functional computations on received data from multiple sources, which is known as a viable way to reduce redundant transmissions.…”