Babacar DIop - Academia.edu (original) (raw)

Papers by Babacar DIop

Managing Target Coverage Lifetime in Wireless Sensor Networks with Greedy Set Cover

2014 6th International Conference on Multimedia, Computer Graphics and Broadcasting, 2014

The lifetime maximization problem in target coverage ap- plication can be addressed by the follow... more The lifetime maximization problem in target coverage ap-
plication can be addressed by the following question : how to partition sensors into an optimal number of sets and schedule their operating intervals so that the coverage requirement can be satis ed and the network
lifetime can be maximized? In this paper, we address this problem by using
cover set approach. A greedy algorithm that produces disjoints and non-
disjoints set covers is proposed, with veri ed approximation ratio. Simulation results show good performance over some other solutions found in the literature, that used the same paradigm.

As a powerful technique for solving combinatorial optimization problems, Genetic Algorithms (GA) ... more As a powerful technique for solving combinatorial
optimization problems, Genetic Algorithms (GA) inspired from
biological evolutionary process, present a variety of possibilities,
for approximating solution within a search space. In this optic,
GA stand as a suitable tool for coverage optimization in target
coverage (TC) application in wireless sensor networks (WSN),
due to their flexibility to model multiple objectives in the same
problem. In this paper, we review some genetic techniques applied
in GA, and discuss about their suitability in the context of target
coverage optimization. We also introduce some examples from
the literature that adopt these techniques, in order to provide
good features for GA modeling in TC application.

Recent improvements in affordable and efficient integrated electronic devices have enabled a wide... more Recent improvements in affordable and efficient
integrated electronic devices have enabled a wide range of applications
in the estate of wireless sensor networks. An important
issue addressed in wireless sensor networks is the coverage
problem. This latter is centered on a fundamental question:
how well do the sensors observe the physical space? A major
challenge in coverage problem is how to maximize the lifetime of
the network while ensuring coverage of a set of targets. To achieve
this, the usual process, consists on scheduling sensors activity,
which enables energy dissipation control. Scheduling process goes
by activating sensors by round such that in each round, only
one subset of sensors that satisfies the coverage requirement is
activated, while all other sensors are in a low energy mode and
will be activated later. In this paper, we propose a weight-based
greedy algorithm (WGA) which organizes sensors in multiple
subsets. Our objective is to partition an initial set of sensors
into a maximum possible number of sensors set covers (SSCs),
which can completely monitor targets in a region of interest.
Performance evaluation of WGA have proven its efficiency over
some well-known algorithms proposed in the literature, in term
of computed set covers.

When several low power sensors are randomly deployed in a field for monitoring targets located at... more When several low power sensors are randomly deployed in a field for monitoring targets located at fixed positions, managing the network lifetime is useful as long as replacing battery of dead sensors is not often feasible. The most commonly investigated mechanism for coverage preserving while maximizing the network lifetime is to design efficient sleep scheduling protocols, so that sensors can alternate their state between being active or not. Maximizing lifetime of a sensor network while satisfying a predefined coverage requirement is an optimization problem, which most of times cannot be optimally solved in polynomial time. In this paper, we address this problem by using set cover approach. We propose a greedy algorithm that distributes sensors among disjoints and non-disjoints set covers with the requirement that each set cover satisfies full targets coverage. The algorithm is an improvement of the classical greedy set cover algorithm, and its approximation ratio is verified to be not worse than log⁡(m). Simulation results show good performance over some other solutions found in the literature. We provide also a comparison of several greedy techniques found in the literature addressed in the context of different design choices linked to the target coverage problem.

As an important issue reflecting the QoS of the sensing task, coverage problem impacts widely on ... more As an important issue reflecting the QoS of the
sensing task, coverage problem impacts widely on the performance
of wireless sensor networks. The target coverage lifetime
maximization problem is yet a challenging problem, which tries
to settle a compromise between managing the coverage of a
set of targets and maximizing the lifetime of the network.
This problem becomes more accurate when targets detection is
distance dependent. In this paper, we address the target coverage
lifetime maximization problem by considering a probabilistic
coverage model, which takes into account the distance parameter.
We propose an algorithm based on a modified version of the
classical well-known weighed set cover which organizes sensors
in disjoint and non-disjoint set covers. Performance evaluation of our solution indicated good performance in managing coverage of targets while extending the network lifetime.

Managing Target Coverage Lifetime in Wireless Sensor Networks with Greedy Set Cover

2014 6th International Conference on Multimedia, Computer Graphics and Broadcasting, 2014

The lifetime maximization problem in target coverage ap- plication can be addressed by the follow... more The lifetime maximization problem in target coverage ap-
plication can be addressed by the following question : how to partition sensors into an optimal number of sets and schedule their operating intervals so that the coverage requirement can be satis ed and the network
lifetime can be maximized? In this paper, we address this problem by using
cover set approach. A greedy algorithm that produces disjoints and non-
disjoints set covers is proposed, with veri ed approximation ratio. Simulation results show good performance over some other solutions found in the literature, that used the same paradigm.

As a powerful technique for solving combinatorial optimization problems, Genetic Algorithms (GA) ... more As a powerful technique for solving combinatorial
optimization problems, Genetic Algorithms (GA) inspired from
biological evolutionary process, present a variety of possibilities,
for approximating solution within a search space. In this optic,
GA stand as a suitable tool for coverage optimization in target
coverage (TC) application in wireless sensor networks (WSN),
due to their flexibility to model multiple objectives in the same
problem. In this paper, we review some genetic techniques applied
in GA, and discuss about their suitability in the context of target
coverage optimization. We also introduce some examples from
the literature that adopt these techniques, in order to provide
good features for GA modeling in TC application.

Recent improvements in affordable and efficient integrated electronic devices have enabled a wide... more Recent improvements in affordable and efficient
integrated electronic devices have enabled a wide range of applications
in the estate of wireless sensor networks. An important
issue addressed in wireless sensor networks is the coverage
problem. This latter is centered on a fundamental question:
how well do the sensors observe the physical space? A major
challenge in coverage problem is how to maximize the lifetime of
the network while ensuring coverage of a set of targets. To achieve
this, the usual process, consists on scheduling sensors activity,
which enables energy dissipation control. Scheduling process goes
by activating sensors by round such that in each round, only
one subset of sensors that satisfies the coverage requirement is
activated, while all other sensors are in a low energy mode and
will be activated later. In this paper, we propose a weight-based
greedy algorithm (WGA) which organizes sensors in multiple
subsets. Our objective is to partition an initial set of sensors
into a maximum possible number of sensors set covers (SSCs),
which can completely monitor targets in a region of interest.
Performance evaluation of WGA have proven its efficiency over
some well-known algorithms proposed in the literature, in term
of computed set covers.

When several low power sensors are randomly deployed in a field for monitoring targets located at... more When several low power sensors are randomly deployed in a field for monitoring targets located at fixed positions, managing the network lifetime is useful as long as replacing battery of dead sensors is not often feasible. The most commonly investigated mechanism for coverage preserving while maximizing the network lifetime is to design efficient sleep scheduling protocols, so that sensors can alternate their state between being active or not. Maximizing lifetime of a sensor network while satisfying a predefined coverage requirement is an optimization problem, which most of times cannot be optimally solved in polynomial time. In this paper, we address this problem by using set cover approach. We propose a greedy algorithm that distributes sensors among disjoints and non-disjoints set covers with the requirement that each set cover satisfies full targets coverage. The algorithm is an improvement of the classical greedy set cover algorithm, and its approximation ratio is verified to be not worse than log⁡(m). Simulation results show good performance over some other solutions found in the literature. We provide also a comparison of several greedy techniques found in the literature addressed in the context of different design choices linked to the target coverage problem.

As an important issue reflecting the QoS of the sensing task, coverage problem impacts widely on ... more As an important issue reflecting the QoS of the
sensing task, coverage problem impacts widely on the performance
of wireless sensor networks. The target coverage lifetime
maximization problem is yet a challenging problem, which tries
to settle a compromise between managing the coverage of a
set of targets and maximizing the lifetime of the network.
This problem becomes more accurate when targets detection is
distance dependent. In this paper, we address the target coverage
lifetime maximization problem by considering a probabilistic
coverage model, which takes into account the distance parameter.
We propose an algorithm based on a modified version of the
classical well-known weighed set cover which organizes sensors
in disjoint and non-disjoint set covers. Performance evaluation of our solution indicated good performance in managing coverage of targets while extending the network lifetime.