Wireless Sensor Networks with Energy Efficient Organization

Abstract

A critical aspect of applications with wireless sensor networks is network lifetime. Battery-powered sensors are usable as long as they can communicate captured data to a processing node. Sensing and communications consume energy, therefore judicious power management and scheduling can effectively extend the operational time. One important class of wireless sensor applications of deployment of large number of sensors in an area for environmental monitoring. The data collected by the sensors is sent to a central node for processing. In this paper we propose an efficient method to achieve energy savings by organizing the sensor nodes into a maximum number of disjoint dominating sets (DDS) which are activated successively. Only the sensors from the active set are responsible for monitoring the target area and for disseminating the collected data. All other nodes are into a sleep mode, characterized by a low energy consumption. We define the maximum disjoint dominating sets problem and we design a heuristic that computes the sets. Theoretical analysis and performance evaluation results are presented to verify our approach.

Energy-efficient coverage problems in wireless ad-hoc sensor networks

“…Most constrained-minimally constraining heuristic [19] Area coverage (1) energy-efficiency and (2) maximize network lifetime by reducing the number of working nodes Disjoint dominating sets heuristic [1] Area coverage same objectives as above Node self-scheduling algorithm [20] Area coverage same objectives as above Probing-based density control algorithm [25] Area coverage (1) energy-efficiency and (2) maximize network lifetime by controlling working nodes density Optimal geographical density control (OGDC) algorithm [26] Area coverage (1) energy-efficiency, (2) connectivity, and (3) maximize network lifetime by reducing the number of working nodes Coverage con_guration protocol (CCP) [21] Area coverage same objectives as above Connected dominating set based coverage [22] Area coverage same objectives as above Connected area dominating sets [3] Area coverage same objectives as above Disjoint set cover heuristic [2] Point coverage (1) energy-efficiency and (2) maximize network lifetime by reducing the number of working nodes Table 2 Characteristics of approaches listed in Table 1 Coverage approach Sensing range R s , comm. range R c Algorithm characteristics…”

“…The works in [1] and [19] consider a large population of sensors, deployed randomly for area monitoring. The goal is to achieve an energy-efficient design that maintains area coverage.…”

“…Cardei et al [1] model the disjoint sets as disjoint dominating sets in an undirected graph, where sensors form the vertex set and an edge joins any two vertices that are within each other's sensing range. The maximum disjoint dominating sets computation is NP-complete, and any polynomial-time approximation algorithm has a lower bound of 1.5.…”

Improving Wireless Sensor Network Lifetime through Power Aware Organization

“…One method is based on scheduling sensor activity so that for each sensor the active state, in which it actually performs its monitoring task alternates with a low-energy idle (sleep) state. As pointed out in [3,11] the ratio of energy consumed between the active and the sleep state is considerable and may be as high as 100.…”

“…In Section 4, we compared the performance of this heuristic versus the performance of our heuristic. In [3], we proposed an efficient node organization scheme, by grouping the sensors in disjoint dominating sets, with every set successively responsible for area monitoring.…”