Frugal Sensor Assignment

Abstract

When a sensor network is deployed in the field it is typically required to support multiple simultaneous missions, which may start and finish at different times. Schemes that match sensor resources to mission demands thus become necessary. In this paper, we consider new sensor-assignment problems motivated by frugality, i.e., the conservation of resources, for both static and dynamic settings. In general, the problems we study are NP-hard even to approximate, and so we focus on heuristic algorithms that perform well in practice. In the static setting, we propose a greedy centralized solution and a more sophisticated solution that uses the Generalized Assignment Problem model and can be implemented in a distributed fashion. In the dynamic setting, we give heuristic algorithms in which available sensors propose to nearby missions as they arrive. We find that the overall performance can be significantly improved if available sensors sometimes refuse to offer utility to missions they could help based on the value of the mission, the sensor's remaining energy, and (if known) the remaining target lifetime of the network. Finally, we evaluate our solutions through simulations.

Assignment of Sensors for Multiple Tasks Using Path Information

“…We also defined a relaxed version of the problem and found the upper bound for it. The results indicated that the overall profit obtained with our method was 130% and 11% higher than those with the greedy method and the previous method [7] that did not use path information. Moreover, the percentage of live nodes was higher than that with the other approaches.…”

A flexible layered control policy for resource allocation in a sensor grid

“…Johnson et al [10] defined new sensor-assignment problems motivated by frugality and conservation of resources, in both static and dynamic settings. They proposed an efferent scheme for matching sense resources to missions, and evaluated the scheme through simulations.…”

Detection and Localization Sensor Assignment with Exact and Fuzzy Locations

“…In the past sensor-task assignment problems in wireless sensor networks have been studied mainly using simplified models in which utility from multiple sensors is assumed to combine additively [3,8,11]. [8] uses distributed approaches assign individual sensors to tasks, assuming additive utility and no competition for the same sensing resources between tasks.…”

“…[8] uses distributed approaches assign individual sensors to tasks, assuming additive utility and no competition for the same sensing resources between tasks. A problem variant motivated by frugality and conservation of resources is addressed in [11]. In this paper, we consider more complex models to evaluate the utility of a bundle of sensors, and show how such problems can be solved, even based on inexact sensor location information.…”