Corrected strange bug.

2_texto_principal/3_related_work.tex

@@ -84,11 +84,11 @@
 Vários tipos de medições permitem inferir uma localização, nomeadamente:
 
 \begin{itemize}
-\item \acs{TOA} (\textit{Time of Arrival})
+\item \acs{TOA} (\textit{Time Of Arrival})
 \item \acs{TDOA} (\textit{Time Difference Of Arrival})
 \item \acs{RSS} (\textit{Received Signal Strength})
 \item \acs{POA} (\textit{Phase Of Arrival})
-\item \acs{AOA} (\textit{Angle of Arrival})
+\item \acs{AOA} (\textit{Angle Of Arrival})
 \end{itemize}
 
 Na medida do \textbf{\acs{TOA}} mede-se o tempo que um sinal demora a chegar ao nó de destino. A distância entre origem e destino é obtida multiplicando o atraso entre o momento da transmissão e o momento da recepção do sinal pela velocidade de propagação do sinal.O requisito mais importante é a sincronização entre nós que obriga à existência de hardware de maior complexidade e a troca de mensagens de sincronização. Ruído aditivo e efeitos multi-caminho são as maiores fontes de erro neste tipo de medição.

3_referencias-anexos/referencias.bib

@@ -29,7 +29,10 @@ @ARTICLE{19
   author = {Ian F. Akyildiz and Weilian Su and Yogesh Sankarasubramaniam and
 	Erdal Cayirci},
   title = {A survey on sensor networks},
+  journal = {Computer Networks},
   year = {2002},
+  volume = {38},
+  pages = {393-422},
   added-at = {2008-03-25T04:43:47.000+0100},
   biburl = {http://www.bibsonomy.org/bibtex/21dc15de32fdb023025f7c85af0c71d5a/yangzhen},
   interhash = {0db24af92855ac8fad443bb80d3cbd12},
@@ -49,24 +52,6 @@ @INCOLLECTION{27
   volume = {5801},
   series = {Lecture Notes in Computer Science},
   pages = {235-254},
-  note = {10.1007/978-3-642-04385-7_16},
-  abstract = {Over the past decade we have witnessed the evolution of wireless sensor
-	networks, with advancements in hardware design, communication protocols,
-	resource efficiency, and other aspects. Recently, there has been
-	much focus on mobile sensor networks, and we have even seen the development
-	of small-profile sensing devices that are able to control their own
-	movement. Although it has been shown that mobility alleviates several
-	issues relating to sensor network coverage and connectivity, many
-	challenges remain. Among these, the need for position estimation
-	is perhaps the most important. Not only is localization required
-	to understand sensor data in a spatial context, but also for navigation,
-	a key feature of mobile sensors. In this paper, we present a survey
-	on localization methods for mobile wireless sensor networks. We provide
-	taxonomies for mobile wireless sensors and localization, including
-	common architectures, measurement techniques, and localization algorithms.
-	We conclude with a description of real-world mobile sensor applications
-	that require position estimation.},
-  added-at = {2010-10-13T11:03:44.000+0200},
   affiliation = {Vanderbilt University Institute for Software Integrated Systems (ISIS)
 	Department of Electrical Engineering and Computer Science Nashville
 	TN 37235 USA},
@@ -229,6 +214,7 @@ @INPROCEEDINGS{14
 @INCOLLECTION{23,
   author = {Johnson, David B. and Maltz, David A. and Broch, Josh},
   title = {Ad hoc networking},
+  booktitle = {In Ad Hoc Networking, edited by Charles E. Perkins, Chapter 5},
   publisher = {Addison-Wesley Longman Publishing Co., Inc.},
   year = {2001},
   chapter = {DSR: the dynamic source routing protocol for multihop wireless ad
@@ -294,27 +280,6 @@ @PROCEEDINGS{25
   title = {{PEGASIS: Power-efficient gathering in sensor information systems}},
   year = {2002},
   volume = {3},
-  abstract = {{Sensor webs consisting of nodes with limited battery power and wireless
-	communications are deployed to collect useful information from the
-	field. Gathering sensed information in an energy efficient manner
-	is critical to operate the sensor network for a long period of time.
-	In W. Heinzelman et al. (Proc. Hawaii Conf. on System Sci., 2000),
-	a data collection problem is defined where, in a round of communication,
-	each sensor node has a packet to be sent to the distant base station.
-	If each node transmits its sensed data directly to the base station
-	then it will deplete its power quickly. The LEACH protocol presented
-	by W. Heinzelman et al. is an elegant solution where clusters are
-	formed to fuse data before transmitting to the base station. By randomizing
-	the cluster heads chosen to transmit to the base station, LEACH achieves
-	a factor of 8 improvement compared to direct transmissions, as measured
-	in terms of when nodes die. In this paper, we propose PEGASIS (power-efficient
-	gathering in sensor information systems), a near optimal chain-based
-	protocol that is an improvement over LEACH. In PEGASIS, each node
-	communicates only with a close neighbor and takes turns transmitting
-	to the base station, thus reducing the amount of energy spent per
-	round. Simulation results show that PEGASIS performs better than
-	LEACH by about 100 to 300\% when 1\%, 20\%, 50\%, and 100\% of nodes
-	die for different network sizes and topologies.}},
   author = {Lindsey, S. and Raghavendra, C. S.},
   booktitle = {Aerospace Conference Proceedings, 2002. IEEE},
   citeulike-article-id = {1598083},
@@ -373,6 +338,7 @@ @ARTICLE{15
   journal = {IEEE Distributed Systems Online},
   year = {2002},
   volume = {3},
+  pages = {10--13},
   number = {3},
   added-at = {2003-04-03T00:00:00.000+0200},
   biburl = {http://www.bibsonomy.org/bibtex/21771ad34e16292f862fc822d0e7ca478/dblp},

3_referencias-anexos/referencias.bib.bak

@@ -29,7 +29,10 @@
   author = {Ian F. Akyildiz and Weilian Su and Yogesh Sankarasubramaniam and
 	Erdal Cayirci},
   title = {A survey on sensor networks},
+  journal = {Computer Networks},
   year = {2002},
+  volume = {38},
+  pages = {393-422},
   added-at = {2008-03-25T04:43:47.000+0100},
   biburl = {http://www.bibsonomy.org/bibtex/21dc15de32fdb023025f7c85af0c71d5a/yangzhen},
   interhash = {0db24af92855ac8fad443bb80d3cbd12},
@@ -49,24 +52,6 @@
   volume = {5801},
   series = {Lecture Notes in Computer Science},
   pages = {235-254},
-  note = {10.1007/978-3-642-04385-7_16},
-  abstract = {Over the past decade we have witnessed the evolution of wireless sensor
-	networks, with advancements in hardware design, communication protocols,
-	resource efficiency, and other aspects. Recently, there has been
-	much focus on mobile sensor networks, and we have even seen the development
-	of small-profile sensing devices that are able to control their own
-	movement. Although it has been shown that mobility alleviates several
-	issues relating to sensor network coverage and connectivity, many
-	challenges remain. Among these, the need for position estimation
-	is perhaps the most important. Not only is localization required
-	to understand sensor data in a spatial context, but also for navigation,
-	a key feature of mobile sensors. In this paper, we present a survey
-	on localization methods for mobile wireless sensor networks. We provide
-	taxonomies for mobile wireless sensors and localization, including
-	common architectures, measurement techniques, and localization algorithms.
-	We conclude with a description of real-world mobile sensor applications
-	that require position estimation.},
-  added-at = {2010-10-13T11:03:44.000+0200},
   affiliation = {Vanderbilt University Institute for Software Integrated Systems (ISIS)
 	Department of Electrical Engineering and Computer Science Nashville
 	TN 37235 USA},
@@ -295,27 +280,6 @@
   title = {{PEGASIS: Power-efficient gathering in sensor information systems}},
   year = {2002},
   volume = {3},
-  abstract = {{Sensor webs consisting of nodes with limited battery power and wireless
-	communications are deployed to collect useful information from the
-	field. Gathering sensed information in an energy efficient manner
-	is critical to operate the sensor network for a long period of time.
-	In W. Heinzelman et al. (Proc. Hawaii Conf. on System Sci., 2000),
-	a data collection problem is defined where, in a round of communication,
-	each sensor node has a packet to be sent to the distant base station.
-	If each node transmits its sensed data directly to the base station
-	then it will deplete its power quickly. The LEACH protocol presented
-	by W. Heinzelman et al. is an elegant solution where clusters are
-	formed to fuse data before transmitting to the base station. By randomizing
-	the cluster heads chosen to transmit to the base station, LEACH achieves
-	a factor of 8 improvement compared to direct transmissions, as measured
-	in terms of when nodes die. In this paper, we propose PEGASIS (power-efficient
-	gathering in sensor information systems), a near optimal chain-based
-	protocol that is an improvement over LEACH. In PEGASIS, each node
-	communicates only with a close neighbor and takes turns transmitting
-	to the base station, thus reducing the amount of energy spent per
-	round. Simulation results show that PEGASIS performs better than
-	LEACH by about 100 to 300\% when 1\%, 20\%, 50\%, and 100\% of nodes
-	die for different network sizes and topologies.}},
   author = {Lindsey, S. and Raghavendra, C. S.},
   booktitle = {Aerospace Conference Proceedings, 2002. IEEE},
   citeulike-article-id = {1598083},
@@ -374,6 +338,7 @@
   journal = {IEEE Distributed Systems Online},
   year = {2002},
   volume = {3},
+  pages = {10--13},
   number = {3},
   added-at = {2003-04-03T00:00:00.000+0200},
   biburl = {http://www.bibsonomy.org/bibtex/21771ad34e16292f862fc822d0e7ca478/dblp},
@@ -474,6 +439,7 @@
   author = {Yan Yu and Ramesh Govindan and Deborah Estrin},
   title = {Geographical and Energy Aware Routing: a recursive data dissemination
 	protocol for wireless sensor networks},
+  institution = {UCLA - University of California, Los Angeles},
   year = {2001}
 }