14 research outputs found
Set It and Forget It: Approximating the Set Once Strip Cover Problem
We consider the Set Once Strip Cover problem, in which n wireless sensors are
deployed over a one-dimensional region. Each sensor has a fixed battery that
drains in inverse proportion to a radius that can be set just once, but
activated at any time. The problem is to find an assignment of radii and
activation times that maximizes the length of time during which the entire
region is covered. We show that this problem is NP-hard. Second, we show that
RoundRobin, the algorithm in which the sensors simply take turns covering the
entire region, has a tight approximation guarantee of 3/2 in both Set Once
Strip Cover and the more general Strip Cover problem, in which each radius may
be set finitely-many times. Moreover, we show that the more general class of
duty cycle algorithms, in which groups of sensors take turns covering the
entire region, can do no better. Finally, we give an optimal O(n^2 log n)-time
algorithm for the related Set Radius Strip Cover problem, in which all sensors
must be activated immediately.Comment: briefly announced at SPAA 201
Energy-efficient Area Coverage by Sensors with Adjustable Ranges
In wireless sensor networks, density control is an important technique for prolonging a network’s lifetime. To reduce the overall energy consumption, it is desirable to minimize the overlapping sensing area of the sensor nodes. In this paper, we study the problem of energy-efficient area coverage by the regular placement of sensors with adjustable sensing and communication ranges. We suggest a more accurate method to estimate efficiency than those currently used for coverage by sensors with adjustable ranges, and propose new density control models that considerably improve coverage using sensors with two sensing ranges. Calculations and extensive simulation show that the new models outperform existing ones in terms of various performance metrics
A Survey of Coverage Problems in Wireless Sensor Networks
Coverage problem is an important issue in wireless sensor networks, which has a great impact on the performance of wireless sensor networks. Given a sensor network, the coverage problem is to determine how well the sensing field is monitored or tracked by sensors. In this paper, we classify the coverage problem into three categories: area coverage, target coverage, and barrier coverage, give detailed description of different algorithms belong to these three categories. Moreover, we specify the advantages and disadvantages of the existing classic algorithms, which can give a useful direction in this area
Average Case Network Lifetime on an Interval with Adjustable Sensing Ranges
Given n sensors on an interval, each of which is equipped with an adjustable sensing radius and a unit battery charge that drains in inverse linear proportion to its radius, what schedule will maximize the lifetime of a network that covers the entire interval? Trivially, any reasonable algorithm is at least a 2-approximation for this Sensor Strip Cover problem, so we focus on developing an efficient algorithm that maximizes the expected network lifetime under a random uniform model of sensor distribution. We demonstrate one such algorithm that achieves an expected network lifetime within 12 % of the theoretical maximum. Most of the algorithms that we consider come from a particular family of RoundRobin coverage, in which sensors take turns covering predefined areas until their battery runs out
Minimum-energy broadcast in random-grid ad-hoc networks: approximation and distributed algorithms
The Min Energy broadcast problem consists in assigning transmission ranges to
the nodes of an ad-hoc network in order to guarantee a directed spanning tree
from a given source node and, at the same time, to minimize the energy
consumption (i.e. the energy cost) yielded by the range assignment. Min energy
broadcast is known to be NP-hard.
We consider random-grid networks where nodes are chosen independently at
random from the points of a square grid in the
plane. The probability of the existence of a node at a given point of the grid
does depend on that point, that is, the probability distribution can be
non-uniform.
By using information-theoretic arguments, we prove a lower bound
on the energy cost of any feasible solution for
this problem. Then, we provide an efficient solution of energy cost not larger
than .
Finally, we present a fully-distributed protocol that constructs a broadcast
range assignment of energy cost not larger than ,thus still yielding
constant approximation. The energy load is well balanced and, at the same time,
the work complexity (i.e. the energy due to all message transmissions of the
protocol) is asymptotically optimal. The completion time of the protocol is
only an factor slower than the optimum. The approximation quality
of our distributed solution is also experimentally evaluated.
All bounds hold with probability at least .Comment: 13 pages, 3 figures, 1 tabl
Optimal Location through Distributed Algorithm to Avoid Energy Hole in Mobile Sink WSNs
In multihop data collection sensor network, nodes near the sink need to relay on remote data and, thus, have much faster energy dissipation rate and suffer from premature death. This phenomenon causes energy hole near the sink, seriously damaging the network performance. In this paper, we first compute energy consumption of each node when sink is set at any point in the network through theoretical analysis; then we propose an online distributed algorithm, which can adjust sink position based on the actual energy consumption of each node adaptively to get the actual maximum lifetime. Theoretical analysis and experimental results show that the proposed algorithms significantly improve the lifetime of wireless sensor network. It lowers the network residual energy by more than 30% when it is dead. Moreover, the cost for moving the sink is relatively smaller