\citation{Nayak04}
\newlabel{sec:introduction}{{1}{1}}
\citation{li2013survey}
+\citation{Misra}
+\citation{yang2014novel}
+\citation{Kumar:2005}
+\citation{kim2013maximum}
+\citation{Deng2012}
+\citation{ling2009energy}
+\citation{jaggi2006}
+\citation{chin2007}
+\citation{pc10}
\citation{yangnovel,ChinhVu,qu2013distributed}
\citation{cardei2005improving,zorbas2010solving,pujari2011high}
+\citation{berman04,zorbas2010solving}
+\citation{cardei2005energy,5714480,pujari2011high,Yang2014}
\citation{castano2013column,rossi2012exact,deschinkel2012column}
-\citation{diongue2013alarm}
-\citation{shi2009}
-\citation{chenait2013distributed}
-\citation{cheng2014achieving}
-\citation{ling2009energy}
-\newlabel{sec:Literature Review}{{2}{2}}
-\citation{yang2014energy}
-\citation{qu2013distributed}
\citation{pedraza2006}
+\newlabel{sec:Literature Review}{{2}{2}}
\citation{Zhang05}
\citation{idrees2014coverage}
\newlabel{sec:The DiLCO Protocol Description}{{3}{3}}
\providecommand*\caption@xref[2]{\@setref\relax\@undefined{#1}}
\newlabel{fig2}{{1}{3}}
\citation{pedraza2006}
-\newlabel{cp}{{4}{4}}
\newlabel{alg:DiLCO}{{1}{4}}
+\newlabel{cp}{{4}{4}}
\newlabel{eq13}{{3}{4}}
+\newlabel{eq14}{{4}{4}}
+\newlabel{eq:ip2r}{{5}{4}}
\citation{varga}
\citation{ChinhVu}
\citation{raghunathan2002energy}
\citation{raghunathan2002energy}
\citation{raghunathan2002energy}
-\newlabel{eq14}{{4}{5}}
-\newlabel{eq:ip2r}{{5}{5}}
\newlabel{sec:Simulation Results and Analysis}{{5}{5}}
\newlabel{table3}{{1}{5}}
\newlabel{table4}{{2}{5}}
\citation{ChinhVu}
\citation{xu2001geography}
\newlabel{sub1}{{5.2}{6}}
-\newlabel{fig3}{{2}{7}}
+\newlabel{fig3}{{2}{6}}
\newlabel{fig95}{{3}{7}}
\newlabel{fig8}{{4}{7}}
+\newlabel{figLT95}{{5}{7}}
\bibstyle{apalike}
\bibdata{Example}
+\bibcite{berman04}{Berman and Calinescu, 2004}
\bibcite{cardei2005improving}{Cardei and Du, 2005}
+\bibcite{cardei2005energy}{Cardei et\nobreakspace {}al., 2005}
\bibcite{castano2013column}{Casta{\~n}o et\nobreakspace {}al., 2013}
-\bibcite{chenait2013distributed}{Chenait et\nobreakspace {}al., 2013}
-\bibcite{cheng2014achieving}{Cheng et\nobreakspace {}al., 2014}
\bibcite{conti2014mobile}{Conti and Giordano, 2014}
-\newlabel{figLT95}{{5}{8}}
-\newlabel{sec:Conclusion and Future Works}{{6}{8}}
+\bibcite{Deng2012}{Deng et\nobreakspace {}al., 2012}
\bibcite{deschinkel2012column}{Deschinkel, 2012}
-\bibcite{diongue2013alarm}{Diongue and Thiare, 2013}
\bibcite{idrees2014coverage}{Idrees et\nobreakspace {}al., 2014}
+\bibcite{jaggi2006}{Jaggi and Abouzeid, 2006}
+\bibcite{kim2013maximum}{Kim and Cobb, 2013}
+\bibcite{Kumar:2005}{Kumar et\nobreakspace {}al., 2005}
\bibcite{li2013survey}{Li and Vasilakos, 2013}
+\newlabel{sec:Conclusion and Future Works}{{6}{8}}
\bibcite{ling2009energy}{Ling and Znati, 2009}
+\bibcite{pujari2011high}{Manju and Pujari, 2011}
+\bibcite{Misra}{Misra et\nobreakspace {}al., 2011}
\bibcite{Nayak04}{Nayak and Stojmenovic, 2010}
+\bibcite{pc10}{Padmavathy and Chitra, 2010}
\bibcite{pedraza2006}{Pedraza et\nobreakspace {}al., 2006}
-\bibcite{pujari2011high}{Pujari, 2011}
\bibcite{qu2013distributed}{Qu and Georgakopoulos, 2013}
\bibcite{raghunathan2002energy}{Raghunathan et\nobreakspace {}al., 2002}
\bibcite{rossi2012exact}{Rossi et\nobreakspace {}al., 2012}
-\bibcite{shi2009}{Shi et\nobreakspace {}al., 2009}
\bibcite{varga}{Varga, 2003}
\bibcite{ChinhVu}{Vu et\nobreakspace {}al., 2006}
+\bibcite{chin2007}{Vu, 2009}
+\bibcite{5714480}{Xing et\nobreakspace {}al., 2010}
\bibcite{xu2001geography}{Xu et\nobreakspace {}al., 2001}
-\bibcite{yangnovel}{Yang and Chin, 2014}
-\bibcite{yang2014energy}{Yang et\nobreakspace {}al., 2014}
+\bibcite{yang2014novel}{Yang and Chin, 2014a}
+\bibcite{yangnovel}{Yang and Chin, 2014b}
+\bibcite{Yang2014}{Yang and Liu, 2014}
\bibcite{Zhang05}{Zhang and Hou, 2005}
\bibcite{zorbas2010solving}{Zorbas et\nobreakspace {}al., 2010}
@PhDThesis{chin2007,
author = {C. T. Vu},
-title = {DISTRIBUTED ENERGY-EFFICIENT SOLUTIONS FOR AREA COVERAGE PROBLEMS IN WIRELESS SENSOR NETWORKS},
+title = {Distributed Energy-Efficient solutions for area coverage problems in Wireless Sensor Networks},
school = {Georgia State University},
year = {2009},
}
@ARTICLE{pujari2011high,
title={High-Energy-First (HEF) Heuristic for Energy-Efficient Target Coverage Problem.},
- author={Pujari, Arun K},
+ author={Manju and Pujari, Arun K},
journal={International Journal of Ad Hoc, Sensor \& Ubiquitous Computing},
volume={2},
number={1},
organization={IEEE}
}
+@inproceedings{Kumar:2005,
+ author = {Kumar, Santosh and Lai, Ten H. and Arora, Anish},
+ title = {Barrier Coverage with Wireless Sensors},
+ booktitle = {Proceedings of the 11th Annual International Conference on Mobile Computing and Networking},
+ series = {MobiCom '05},
+ year = {2005},
+ isbn = {1-59593-020-5},
+ location = {Cologne, Germany},
+ pages = {284--298},
+ numpages = {15},
+ url = {http://doi.acm.org/10.1145/1080829.1080859},
+ doi = {10.1145/1080829.1080859},
+ acmid = {1080859},
+ publisher = {ACM},
+ address = {New York, NY, USA},
+ keywords = {barrier coverage, coverage, critical conditions, localized algorithms, network topology, random geometric graphs, wireless sensor networks},
+}
-
+@article{Deng2012,
+ title={Transforming Area Coverage to Target Coverage to Maintain Coverage and Connectivity for Wireless Sensor Networks},
+ author={Xiu Deng and Jiguo Yu, Dongxiao Yu and Congcong Chen},
+ journal={International Journal of Distributed Sensor Networks},
+ volume={2012},
+ year={2012},
+ ee = {http://dx.doi.org/10.1155/2012/254318}
+}
+
+ @inproceedings{jaggi2006,
+ title={Energy-efficient Connected Covereage in Wireless Sensor Networks},
+ author={N. Jaggi and A.A. Abouzeid},
+ booktitle={Proceeding of 4th Asian International Mobile Computing Conference AMOC2006},
+ year={2006}
+}
+
+@INPROCEEDINGS{5714480,
+author={Xiaofei Xing and Jie Li and Guojun Wang},
+booktitle={Mobile Ad-hoc and Sensor Networks (MSN), 2010 Sixth International Conference on},
+title={Integer Programming Scheme for Target Coverage in Heterogeneous Wireless Sensor Networks},
+year={2010},
+month={Dec},
+pages={79-84},
+keywords={energy conservation;integer programming;wireless sensor networks;ETCA;clustered configurations;clusterheads;energy first algorithm;energy-efficient target coverage algorithm;heterogeneous wireless sensor networks;integer programming;network lifetime;polytype target coverage;sensor node;Algorithm design and analysis;Clustering algorithms;Energy consumption;Logic gates;Sensors;Simulation;Wireless sensor networks;Heterogeneous wireless sensor networks;network lifetime;optimization;target coverage},
+doi={10.1109/MSN.2010.18},}
+
+@article{Yang2014,
+ title={A Maximum Lifetime Coverage Algorithm Based on Linear Programming},
+ author={Mengmeng Yang and Jie Liu},
+ journal={Journal of Information Hiding an dMultimedia Signal Processing, Ubiquitous International},
+ volume={5},
+ number={2},
+ pages={296-301},
+ year={2014}
+}
literature.
The most discussed coverage problems in literature
-can be classified into three types \cite{li2013survey}: area coverage (where
-every point inside an area is to be monitored), target coverage (where the main
-objective is to cover only a finite number of discrete points called targets),
-and barrier coverage (to prevent intruders from entering into the region of
-interest).
+can be classified into three types \cite{li2013survey}: area coverage \cite{Misra} where
+every point inside an area is to be monitored, target coverage \cite{yang2014novel} where the main
+objective is to cover only a finite number of discrete points called targets,
+and barrier coverage \cite{Kumar:2005}\cite{kim2013maximum} to prevent intruders from entering into the region of interest. In \cite{Deng2012} authors transform the area coverage problem to the target coverage problem taking into account the intersection points among disks of sensors nodes or between disk of sensor nodes and boundaries.
{\it In DiLCO protocol, the area coverage, i.e. the coverage of every point in
the sensing region, is transformed to the coverage of a fraction of points
called primary points. }
+
The major approach to extend network lifetime while preserving coverage is to
divide/organize the sensors into a suitable number of set covers (disjoint or
non-disjoint) where each set completely covers a region of interest and to
activate these set covers successively. The network activity can be planned in
advance and scheduled for the entire network lifetime or organized in periods,
-and the set of active sensor nodes is decided at the beginning of each period.
+and the set of active sensor nodes is decided at the beginning of each period \cite{ling2009energy}.
Active node selection is determined based on the problem requirements (e.g. area
-monitoring, connectivity, power efficiency). Different methods have been
-proposed in literature.
-{\it DiLCO protocol works in periods, where each period contains a preliminary
+monitoring, connectivity, power efficiency). For instance, Jaggi et al. \cite{jaggi2006}
+adress the problem of maximizing network lifetime by dividing sensors into the maximum number of disjoint subsets such that each subset can ensure both coverage and connectivity. A greedy algorithm is applied once to solve this problem and the computed sets are activated in succession to achieve the desired network lifetime.
+Vu \cite{chin2007}, Padmatvathy et al \cite{pc10}, propose algorithms working in a periodic fashion where a cover set is computed at the beginning of each period.
+{\it Motivated by these works, DiLCO protocol works in periods, where each period contains a preliminary
phase for information exchange and decisions, followed by a sensing phase
where one cover set is in charge of the sensing task.}
-Various approaches, including centralized, distributed, and localized
+Various approaches, including centralized, or distributed
algorithms, have been proposed to extend the network lifetime.
%For instance, in order to hide the occurrence of faults, or the sudden unavailability of
%sensor nodes, some distributed algorithms have been developed in~\cite{Gallais06,Tian02,Ye03,Zhang05,HeinzelmanCB02}.
provide nearly or close to optimal solution since the algorithm has global view
of the whole network, but such a method has the disadvantage of requiring high
communication costs, since the node (located at the base station) making the
-decision needs information from all the sensor nodes in the area.
+decision needs information from all the sensor nodes in the area and the amount of information can be huge.
+{\it In order to be suitable for large-scale network, in the DiLCO protocol, the area coverage is divided into several smaller
+ subregions, and in each of which, a node called the leader is on charge for
+ selecting the active sensors for the current period.}
-A large variety of coverage scheduling algorithms have been proposed. Many of
+A large variety of coverage scheduling algorithms have been developed. Many of
the existing algorithms, dealing with the maximization of the number of cover
sets, are heuristics. These heuristics involve the construction of a cover set
by including in priority the sensor nodes which cover critical targets, that is
-to say targets that are covered by the smallest number of sensors. Other
-approaches are based on mathematical programming formulations and dedicated
+to say targets that are covered by the smallest number of sensors \cite{berman04,zorbas2010solving}. Other
+approaches are based on mathematical programming formulations~\cite{cardei2005energy,5714480,pujari2011high,Yang2014} and dedicated
techniques (solving with a branch-and-bound algorithms available in optimization
solver). The problem is formulated as an optimization problem (maximization of
the lifetime or number of cover sets) under target coverage and energy
constraints. Column generation techniques, well-known and widely practiced
techniques for solving linear programs with too many variables, have been also
-used~\cite{castano2013column,rossi2012exact,deschinkel2012column}.
+used~\cite{castano2013column,rossi2012exact,deschinkel2012column}. {\it In DiLCO protocol, each leader, in each subregion, solves an integer
+ program with a double objective consisting in minimizing the overcoverage and
+ limiting the undercoverage. This program is inspired from the work of
+ \cite{pedraza2006} where the objective is to maximize the number of cover
+ sets.}
% ***** Part which must be rewritten - Start
% Start of Ali's papers catalog => there's no link between them or with our work
% (use of subregions; optimization based method; etc.)
-
+\iffalse
Diongue and Thiare~\cite{diongue2013alarm} proposed an energy aware sleep
scheduling algorithm for lifetime maximization in wireless sensor networks
(ALARM). The proposed approach permits to schedule redundant nodes according to
% What is the link between the previous work and this paragraph about DiLCO ?
-{\it In DiLCO protocol, the area coverage is divided into several smaller
- subregions, and in each of which, a node called the leader is on charge for
- selecting the active sensors for the current period.}
+
Yang et al.~\cite{yang2014energy} investigated full area coverage problem under
the probabilistic sensing model in the sensor networks. They have studied the
The work proposed by \cite{qu2013distributed} considers the coverage problem in
WSNs where each sensor has variable sensing radius. The final objective is to
maximize the network coverage lifetime in WSNs.
-
+\fi
% Same remark, no link with the two previous citations...
-{\it In DiLCO protocol, each leader, in each subregion, solves an integer
- program with a double objective consisting in minimizing the overcoverage and
- limiting the undercoverage. This program is inspired from the work of
- \cite{pedraza2006} where the objective is to maximize the number of cover
- sets.}
+
% ***** Part which must be rewritten - End
