This document summarizes a distributed localization algorithm for wireless sensor networks. It begins by introducing wireless sensor networks and noting that localization of sensor nodes is an important first task. It then discusses the benefits of distributed algorithms over centralized algorithms for localization, including scalability, reliability, and energy efficiency. The document goes on to describe a basic distributed localization algorithm that works in a discrete model where the operating region is divided into cells and nodes can communicate with others within a certain number of cells. The goals are to design a distributed algorithm, analyze its complexity and errors, and determine an optimal number of "known nodes" to minimize errors.
International Refereed Journal of Engineering and Science (IRJES)irjes
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications.
A Survey on Topology Control and Maintenance in Wireless Sensor Networksijeei-iaes
Wireless Sensor Networks (WSNs) consist of devices equipped with radio transceivers that cooperate to form and maintain a fully connected network of sensor nodes. WSNs do not have a fixed infrastructure and do not use centralized methods for organization. This flexibility enables them to be used whenever a fixed infrastructure is unfeasible or inconvenient, hence making them attractive for numerous applications ranging from military, civil, industrial or health. Because of their unique structure, and limited energy storage, computational and memory resources, many of the existing protocols and algorithms designed for wired or wireless ad hoc networks cannot be directly used in WSNs. Beside this, they offer a flexible low cost solution to the problem of event monitoring, especially in places with limited accessibility or that represent danger to humans. Applications of large scale WSNs are becoming a reality example are being a Smart Grid, Machine to Machine communication networks and smart environment. It is expected that a topology control techniques will play an important role in managing the complexity of such highly complicated and distributed systems through self-organization capabilities. WSNs are made of resource constrained wireless devices, which require energy efficient mechanisms, algorithm/protocol. Control on topology is very important for efficient utilization of networks and is composed of two mechanisms, Topology Construction (TC) and Topology Maintenance (TM). By using these mechanism various protocols/algorithm have came into existence, like: A3, A3-Coverage (A3-Cov), Simple Tree, Just Tree, etc. This paper provides a full view of the studies of above mentioned algorithms and also provides an analysis of their merits and demerits.
Redundant Actor Based Multi-Hole Healing System for Mobile Sensor NetworksEditor IJCATR
In recent years, the Mobile Wireless Sensor Network
is the emerging solution for monitoring of a specified region of
interest. Several anomalies can occur in WSNs that impair their
desired functionalities resulting in the formation of different
kinds of holes, namely: coverage holes, routing holes. Our
ultimate aim is to cover total area without coverage hole in
wireless sensor networks. We propose a comprehensive solution,
called holes detection and healing. We divided our proposed
work into two phases. The first phase consists of three sub- tasks;
Hole-identification, Hole-discovery and border detection. The
second phase treats the Hole-healing with novel concept, hole
healing area. It consists of two sub-tasks; Hole healing area
determination and node relocation.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Optimum Sensor Node Localization in Wireless Sensor Networkspaperpublications3
Abstract: Scientists, engineers, and researchers use wireless sensor networks (WSN) for a wide array of applications. Many of these applications rely on knowledge of the precise position of each node. An optimum localization algorithm can be used for determining the position of nodes in a wireless sensor network. This paper provides an overview of different approach of node localization discovery in wireless sensor networks. The overview of the schemes proposed by different scholars for the improvement of localization in wireless sensor networks is also presented. Experiments were performed in a testbed area containing anchor and blind nodes deployed in it to characterize the pathloss exponent and to determine the localization error of the algorithm. Details regarding the implementation of new algorithm are also discussed in this paper.
ER Publication,
IJETR, IJMCTR,
Journals,
International Journals,
High Impact Journals,
Monthly Journal,
Good quality Journals,
Research,
Research Papers,
Research Article,
Free Journals, Open access Journals,
erpublication.org,
Engineering Journal,
Science Journals,
International Refereed Journal of Engineering and Science (IRJES)irjes
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications.
A Survey on Topology Control and Maintenance in Wireless Sensor Networksijeei-iaes
Wireless Sensor Networks (WSNs) consist of devices equipped with radio transceivers that cooperate to form and maintain a fully connected network of sensor nodes. WSNs do not have a fixed infrastructure and do not use centralized methods for organization. This flexibility enables them to be used whenever a fixed infrastructure is unfeasible or inconvenient, hence making them attractive for numerous applications ranging from military, civil, industrial or health. Because of their unique structure, and limited energy storage, computational and memory resources, many of the existing protocols and algorithms designed for wired or wireless ad hoc networks cannot be directly used in WSNs. Beside this, they offer a flexible low cost solution to the problem of event monitoring, especially in places with limited accessibility or that represent danger to humans. Applications of large scale WSNs are becoming a reality example are being a Smart Grid, Machine to Machine communication networks and smart environment. It is expected that a topology control techniques will play an important role in managing the complexity of such highly complicated and distributed systems through self-organization capabilities. WSNs are made of resource constrained wireless devices, which require energy efficient mechanisms, algorithm/protocol. Control on topology is very important for efficient utilization of networks and is composed of two mechanisms, Topology Construction (TC) and Topology Maintenance (TM). By using these mechanism various protocols/algorithm have came into existence, like: A3, A3-Coverage (A3-Cov), Simple Tree, Just Tree, etc. This paper provides a full view of the studies of above mentioned algorithms and also provides an analysis of their merits and demerits.
Redundant Actor Based Multi-Hole Healing System for Mobile Sensor NetworksEditor IJCATR
In recent years, the Mobile Wireless Sensor Network
is the emerging solution for monitoring of a specified region of
interest. Several anomalies can occur in WSNs that impair their
desired functionalities resulting in the formation of different
kinds of holes, namely: coverage holes, routing holes. Our
ultimate aim is to cover total area without coverage hole in
wireless sensor networks. We propose a comprehensive solution,
called holes detection and healing. We divided our proposed
work into two phases. The first phase consists of three sub- tasks;
Hole-identification, Hole-discovery and border detection. The
second phase treats the Hole-healing with novel concept, hole
healing area. It consists of two sub-tasks; Hole healing area
determination and node relocation.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Optimum Sensor Node Localization in Wireless Sensor Networkspaperpublications3
Abstract: Scientists, engineers, and researchers use wireless sensor networks (WSN) for a wide array of applications. Many of these applications rely on knowledge of the precise position of each node. An optimum localization algorithm can be used for determining the position of nodes in a wireless sensor network. This paper provides an overview of different approach of node localization discovery in wireless sensor networks. The overview of the schemes proposed by different scholars for the improvement of localization in wireless sensor networks is also presented. Experiments were performed in a testbed area containing anchor and blind nodes deployed in it to characterize the pathloss exponent and to determine the localization error of the algorithm. Details regarding the implementation of new algorithm are also discussed in this paper.
ER Publication,
IJETR, IJMCTR,
Journals,
International Journals,
High Impact Journals,
Monthly Journal,
Good quality Journals,
Research,
Research Papers,
Research Article,
Free Journals, Open access Journals,
erpublication.org,
Engineering Journal,
Science Journals,
DISTRIBUTED COVERAGE AND CONNECTIVITY PRESERVING ALGORITHM WITH SUPPORT OF DI...IJCSEIT Journal
Given a 3D space where should be supervised and a group of mobile sensor actor nodes with limited
sensing and communicating capabilities, this paper aims at proposing a distributed self-deployment
algorithm for agents to cover the space as much as possible by considering non-uniform sensing coverage
degree constraint of environment while preserving connectivity. The problem is formulated as coverage
maximization subject to connectivity and sensing coverage degree constraint. Considering a desired
distance between neighbouring nodes, an error function which depends on pairwise distance between
nodes is described. The maximization is encoded to an error minimization problem that is solved using
gradient descent algorithm and will yield in moving sensors into appropriate positions. Simulation results
are presented in two different conditions that importance of sensing coverage degree support of
environment is very high and is low.
Wireless Sensor Networks are highly distributed self-organized systems. WSN have been deployed in various fields. Now a day, Topology issues have received more and more attentions in Wireless Sensor Networks (WSN). While WSN applications are normally optimized by the given underlying network topology, another trend is to optimize WSN by means of topology control. In this area, a number of approaches have been invested, like network connectivity based topology control, cooperating schemes, topology directed routing, sensor coverage based topology control. Most of the schemes have proven to be able to provide a better network monitoring and communication performance with prolonged system lifetime. In this survey paper, I provide a full view of the studies in this area.
Energy efficient approach based on evolutionary algorithm for coverage contro...ijcseit
Coverage and connectivity are two important requirements in Wireless Sensor Networks (WSNs). In this
paper, we address the problem of network coverage and connectivity and propose an energy efficient
approach based on genetic evolutionary algorithm for maintaining coverage and connectivity where the
sensor nodes can have different sensing ranges and transmission ranges. The proposed algorithm is
simulated and it' efficiency is demonstrated via different experiments.
Spatial Correlation Based Medium Access Control Protocol Using DSR & AODV Rou...IOSR Journals
Abstract : In Wireless sensor network sensor nodes have a limited battery life and their efficient utilization is
a very much importent task. Their are many ways are proposed for efficient utilization of energy.For efficient
energy utilization many topologies,protocals are proposed by the help of which we can maximize the battery
life. In this paper we propesed a methode in which a correlation is made between all the sensor nodes including
ME(mobile element). A Vector Quantization methode are used for distance calculation between all the sensor
nodes and mobile element. After finding the corrélation we used the DSR & AODV routing Protocol. The
performance of the proposed protocol has been examined and evaluated with the NS-2 simulator in terms of
packet drop ratio and energy consumption. The simulation result shows that the proposed protocol with AODV
routing gives a batter result compared with same protocol with DSR routing.
Keywords: ME, DVT, DSR, AODV, Wireless Sensor Network, Efficient Energy Utilization
Computational Geometry based Remote Networkingidescitation
In recent years wireless sensor networks (WSNs) have become one of the most
active research areas due to the bright and interesting future promised to the world of
information technology. It is an emerging field which is accomplishing much importance
because of its vast contribution in varieties of applications. Coverage is one of the important
aspects of WSNs and many approaches are introduced to maximize it. It is the key research
issue in WSN as it can be considered as the measure of the Quality of Service (QoS) of
sensing function for a sensor network. The goal of coverage is to have each location in the
physical space of interest within the sensing range of at least one sensor. By combining
computational geometry and graph theoretic techniques, specifically the Voronoi Diagram
(VD), Delaunay Triangulation (DT) and Graph Search algorithms, can solve the problem.
This paper defines some recent research approaches on coverage of WSNs using VD and
DT. Also shows how they are being utilized in various research works.
Localization of nodes in an infrastructure less network serves many purposes. Several issues relating to
security, routing, etc it can be solved if only the actual location of nodes were known. Existing approaches
estimate the location of a node in a network by using received signal strength indicator (RSSI), Time of
Arrival, Time difference of Arrival and, if directional antennas are available, Direction of Arrival. In these
methods the localization accuracy is less (in the order of 20cm). The aim of this paper is to localize nodes
in adhoc networks with improved accuracy using ultra wide band.The proposed method uses a train of low
amplitude pulses of high bandwidth, which reduces the energy consumption, effects due to small scale
fading, and dispersion in time and frequency. The network was simulated in NS-2 with UWB extension and
the localization accuracy was found to be improved (upto 1cm).
CP-NR Distributed Range Free Localization Algorithm in WSNIJAAS Team
Advancements in wireless communication technology have empowered the researchers to develop large scale wireless networks with huge number of sensor nodes. In these networks localization is very active field of research. Localization is a way to determine the physical position of sensor nodes which is useful in many aspects such as to find the origin of events, routing and network coverage. Locating nodes with GPS systems is expensive, power consuming and not applicable to indoor environments. Localization in three dimensional space and accuracy of the estimated location are two factors of major concern. In this paper, a new three dimensional Distributed range-free algorithm which is known as CP-NR is proposed. This algorithm has high localization accuracy and resolved the problem of existing NR algorithm. CP-NR (Coplanar and Projected Node Reproduction) algorithm makes use of co-planarity and projection of point on plane concepts to reduce the localization error. Results have shown that CP-NR algorithm is superior to NR algorithm and comparison is done for the localization accuracy with respect to variations in range, anchor density and node density.
Effective range free localization scheme for wireless sensor networkijmnct
Location aware sensors can be used in many areas such as military and civilian applications. Wireless
Sensor Networks help to identify the accurate location of the event. In this paper a cost effective schema for
localization has been proposed. It uses two beacon nodes to identify the location of unknown nodes. It
also uses flooding and estimating method to accurately identify the location of other nodes. Available area
is divided into zones and beacons are provided for each zone. Beacon nodes are placed in appropriate
locations normally two in a zone to provide location information. Using the two nodes location of unknown
nodes can be calculated accurately.
CODE AWARE DYNAMIC SOURCE ROUTING FOR DISTRIBUTED SENSOR NETWORKIJNSA Journal
Sensor network facilitates monitoring and controlling of physical environments. These wireless networks consist of dense collection of sensors capable of collection and dissemination of data. They have application in variety of fields such as military purposes, environment monitoring etc. Typical deployment of sensor network assumes central processing station or a gateway to which all other nodes route their data using dynamic source routing (DSR). This causes congestion at central station and thus reduces the efficiency of the network. In this work we will propose a better dynamic source routing technique using network coding to reduce total number of transmission in sensor networks resulting in better efficiency.
Scheduling different types of packets, such as
real-time and non-real-time data packets, at sensor nodes with
resource constraints in Wireless Sensor Networks (WSN) is of
vital importance to reduce sensors’ energy consumptions and endto-end
data transmission delays. Most of the existing packetscheduling
mechanisms of WSN use First Come First Served
(FCFS), non pre-emptive priority and pre-emptive priority
scheduling algorithms. These algorithms incur a high processing
overhead and long end-to-end data transmission delay due to the
FCFS concept, starvation of high priority real-time data packets
due to the transmission of a large data packet in non pre-emptive
priority scheduling, starvation of non-real-time data packets due
to the probable continuous arrival of real-time data in preemptive
priority scheduling, and improper allocation of data
packets to queues in multilevel queue scheduling algorithms.
Moreover, these algorithms are not dynamic to the changing
requirements of WSN applications since their scheduling policies
are predetermined.
In the Advanced Multilevel Priority packet scheduling
scheme, each node except those at the last level has three levels of
priority queues. According to the priority of the packet and
availability of the queue, node will schedule the packet for
transmission. Due to separated queue availability, packet
transmission delay is reduced. Due to reduction in packet
transmission delay, node can goes into sleep mode as soon as
possible. And Expired packets are deleted at the particular node
at itself before reaching the base station, so that processing
burden on the node is reduced. Thus, energy of the node is saved.
A NOVEL APPROACH FOR ENERGY EFFICIENT HIERARCHY BASED ROUTING IN SENSOR NETWO...cscpconf
Wireless sensor network (WSN) is the collection of many micro-sensor nodes, connecting each other by a
wireless medium. WSN exhibits different approaches to provide reliable sensing of the environment,
detecting and reporting events. In this paper, we have proposed an algorithm for hierarchy based protocols
of wireless sensor networks, which consist of two groups of sensor nodes in a single cluster node. Each
cluster consists of a three cluster head. The event driven data sensing mechanism is used in this paper and
this sensed data is transmitted to the master section head. Hence efficient way of data transmission is possible with larger group of nodes. In this approach, using hierarchy based protocols; the lifetime of the sensor network is increased.
Vertex covering has important applications for wireless sensor networks such as monitoring link failures,
facility location, clustering, and data aggregation. In this study, we designed three algorithms for
constructing vertex cover in wireless sensor networks. The first algorithm, which is an adaption of the
Parnas & Ron’s algorithm, is a greedy approach that finds a vertex cover by using the degrees of the
nodes. The second algorithm finds a vertex cover from graph matching where Hoepman’s weighted
matching algorithm is used. The third algorithm firstly forms a breadth-first search tree and then
constructs a vertex cover by selecting nodes with predefined levels from breadth-first tree. We show the
operation of the designed algorithms, analyze them, and provide the simulation results in the TOSSIM
environment. Finally we have implemented, compared and assessed all these approaches. The transmitted
message count of the first algorithm is smallest among other algorithms where the third algorithm has
turned out to be presenting the best results in vertex cover approximation ratio.
International Journal of Advanced Smart Sensor Network Systems (IJASSN)ijcseit
The placement of base stations in wireless sensor networks affect the energy consumption for
communication between sensor node and base station. In this paper we analyzed the performance of the
zone based clustering protocol [2] under varying position of base stations, different zone sizes and the
effect on network life time with multiple base stations. While evaluating the communication overhead of
various cluster sizes, we observed that the optimal cluster size for a given network is complex, depending
on a range of parameters. Simulation results show that communication overhead decreases as we increase
the number of zone in the network. We show that placing multiple base stations in place of single base
station in zone based routing protocol enhance the network life time.
Localization is one of the key technologies in wireless sensor networks (WSNs), since it provides
fundamental support for many location-aware protocols and applications. Constraints on cost and power
consumption make it infeasible to equip each sensor node in the network with a global position system
(GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use
anchor nodes, which are equipped with GPS units among unknown nodes and broadcast their current
locations to help nearby unknown nodes with localization. In this paper we can proposed a novel algorithm
of cuboid localization with the help of central point precision method. Simulation shows that the results are
far better then existing cuboid methods and gain accuracy of up to 83% with a localization error of 1.6m
and standard deviation of 2.7.
The Expansion of 3D wireless sensor network Bumps localizationIJERA Editor
Bump localization of wireless sensor network is a hot topic, but present algorithms of 3D wireless sensor node localization arenot accurate enough. In this paper, the DR-MDS algorithm is proposed, DR-MDS algorithm mainly calibrates the coordinatesof nodes and the ranging of nodes based on multidimensional scaling, it calculates the distance between any nodes exactlyaccording to the hexahedral measurement, introducing a modification factor to calibrate the measuring distance by ReceivedSignal Strength Indicator (RSSI). Results of simulation show that DR-MDS algorithm has significant improvement inlocalization accuracy compare with MDS-MAP algorithm.
Shortest path algorithm for data transmission in wireless ad hoc sensor networksijasuc
Wireless sensor networks determine probable in military, environments, health and commercial
applications. The process of transferring of information from a remote sensor node to other nodes in a
network holds importance for such applications. Various constraints such as limited computation, storage
and power makes the process of transferring of information routing interesting and has opened new arenas
for researchers. The fundamental problem in sensor networks states the significance and routing of
information through a real path as path length decides some basic performance parameters for sensor
networks. This paper strongly focuses on a shortest path algorithm for wireless adhoc networks. The
simulations are performed on NS2 and the results obtained discuss the role of transferring of information
through a shortest path.
DISTRIBUTED COVERAGE AND CONNECTIVITY PRESERVING ALGORITHM WITH SUPPORT OF DI...IJCSEIT Journal
Given a 3D space where should be supervised and a group of mobile sensor actor nodes with limited
sensing and communicating capabilities, this paper aims at proposing a distributed self-deployment
algorithm for agents to cover the space as much as possible by considering non-uniform sensing coverage
degree constraint of environment while preserving connectivity. The problem is formulated as coverage
maximization subject to connectivity and sensing coverage degree constraint. Considering a desired
distance between neighbouring nodes, an error function which depends on pairwise distance between
nodes is described. The maximization is encoded to an error minimization problem that is solved using
gradient descent algorithm and will yield in moving sensors into appropriate positions. Simulation results
are presented in two different conditions that importance of sensing coverage degree support of
environment is very high and is low.
Wireless Sensor Networks are highly distributed self-organized systems. WSN have been deployed in various fields. Now a day, Topology issues have received more and more attentions in Wireless Sensor Networks (WSN). While WSN applications are normally optimized by the given underlying network topology, another trend is to optimize WSN by means of topology control. In this area, a number of approaches have been invested, like network connectivity based topology control, cooperating schemes, topology directed routing, sensor coverage based topology control. Most of the schemes have proven to be able to provide a better network monitoring and communication performance with prolonged system lifetime. In this survey paper, I provide a full view of the studies in this area.
Energy efficient approach based on evolutionary algorithm for coverage contro...ijcseit
Coverage and connectivity are two important requirements in Wireless Sensor Networks (WSNs). In this
paper, we address the problem of network coverage and connectivity and propose an energy efficient
approach based on genetic evolutionary algorithm for maintaining coverage and connectivity where the
sensor nodes can have different sensing ranges and transmission ranges. The proposed algorithm is
simulated and it' efficiency is demonstrated via different experiments.
Spatial Correlation Based Medium Access Control Protocol Using DSR & AODV Rou...IOSR Journals
Abstract : In Wireless sensor network sensor nodes have a limited battery life and their efficient utilization is
a very much importent task. Their are many ways are proposed for efficient utilization of energy.For efficient
energy utilization many topologies,protocals are proposed by the help of which we can maximize the battery
life. In this paper we propesed a methode in which a correlation is made between all the sensor nodes including
ME(mobile element). A Vector Quantization methode are used for distance calculation between all the sensor
nodes and mobile element. After finding the corrélation we used the DSR & AODV routing Protocol. The
performance of the proposed protocol has been examined and evaluated with the NS-2 simulator in terms of
packet drop ratio and energy consumption. The simulation result shows that the proposed protocol with AODV
routing gives a batter result compared with same protocol with DSR routing.
Keywords: ME, DVT, DSR, AODV, Wireless Sensor Network, Efficient Energy Utilization
Computational Geometry based Remote Networkingidescitation
In recent years wireless sensor networks (WSNs) have become one of the most
active research areas due to the bright and interesting future promised to the world of
information technology. It is an emerging field which is accomplishing much importance
because of its vast contribution in varieties of applications. Coverage is one of the important
aspects of WSNs and many approaches are introduced to maximize it. It is the key research
issue in WSN as it can be considered as the measure of the Quality of Service (QoS) of
sensing function for a sensor network. The goal of coverage is to have each location in the
physical space of interest within the sensing range of at least one sensor. By combining
computational geometry and graph theoretic techniques, specifically the Voronoi Diagram
(VD), Delaunay Triangulation (DT) and Graph Search algorithms, can solve the problem.
This paper defines some recent research approaches on coverage of WSNs using VD and
DT. Also shows how they are being utilized in various research works.
Localization of nodes in an infrastructure less network serves many purposes. Several issues relating to
security, routing, etc it can be solved if only the actual location of nodes were known. Existing approaches
estimate the location of a node in a network by using received signal strength indicator (RSSI), Time of
Arrival, Time difference of Arrival and, if directional antennas are available, Direction of Arrival. In these
methods the localization accuracy is less (in the order of 20cm). The aim of this paper is to localize nodes
in adhoc networks with improved accuracy using ultra wide band.The proposed method uses a train of low
amplitude pulses of high bandwidth, which reduces the energy consumption, effects due to small scale
fading, and dispersion in time and frequency. The network was simulated in NS-2 with UWB extension and
the localization accuracy was found to be improved (upto 1cm).
CP-NR Distributed Range Free Localization Algorithm in WSNIJAAS Team
Advancements in wireless communication technology have empowered the researchers to develop large scale wireless networks with huge number of sensor nodes. In these networks localization is very active field of research. Localization is a way to determine the physical position of sensor nodes which is useful in many aspects such as to find the origin of events, routing and network coverage. Locating nodes with GPS systems is expensive, power consuming and not applicable to indoor environments. Localization in three dimensional space and accuracy of the estimated location are two factors of major concern. In this paper, a new three dimensional Distributed range-free algorithm which is known as CP-NR is proposed. This algorithm has high localization accuracy and resolved the problem of existing NR algorithm. CP-NR (Coplanar and Projected Node Reproduction) algorithm makes use of co-planarity and projection of point on plane concepts to reduce the localization error. Results have shown that CP-NR algorithm is superior to NR algorithm and comparison is done for the localization accuracy with respect to variations in range, anchor density and node density.
Effective range free localization scheme for wireless sensor networkijmnct
Location aware sensors can be used in many areas such as military and civilian applications. Wireless
Sensor Networks help to identify the accurate location of the event. In this paper a cost effective schema for
localization has been proposed. It uses two beacon nodes to identify the location of unknown nodes. It
also uses flooding and estimating method to accurately identify the location of other nodes. Available area
is divided into zones and beacons are provided for each zone. Beacon nodes are placed in appropriate
locations normally two in a zone to provide location information. Using the two nodes location of unknown
nodes can be calculated accurately.
CODE AWARE DYNAMIC SOURCE ROUTING FOR DISTRIBUTED SENSOR NETWORKIJNSA Journal
Sensor network facilitates monitoring and controlling of physical environments. These wireless networks consist of dense collection of sensors capable of collection and dissemination of data. They have application in variety of fields such as military purposes, environment monitoring etc. Typical deployment of sensor network assumes central processing station or a gateway to which all other nodes route their data using dynamic source routing (DSR). This causes congestion at central station and thus reduces the efficiency of the network. In this work we will propose a better dynamic source routing technique using network coding to reduce total number of transmission in sensor networks resulting in better efficiency.
Scheduling different types of packets, such as
real-time and non-real-time data packets, at sensor nodes with
resource constraints in Wireless Sensor Networks (WSN) is of
vital importance to reduce sensors’ energy consumptions and endto-end
data transmission delays. Most of the existing packetscheduling
mechanisms of WSN use First Come First Served
(FCFS), non pre-emptive priority and pre-emptive priority
scheduling algorithms. These algorithms incur a high processing
overhead and long end-to-end data transmission delay due to the
FCFS concept, starvation of high priority real-time data packets
due to the transmission of a large data packet in non pre-emptive
priority scheduling, starvation of non-real-time data packets due
to the probable continuous arrival of real-time data in preemptive
priority scheduling, and improper allocation of data
packets to queues in multilevel queue scheduling algorithms.
Moreover, these algorithms are not dynamic to the changing
requirements of WSN applications since their scheduling policies
are predetermined.
In the Advanced Multilevel Priority packet scheduling
scheme, each node except those at the last level has three levels of
priority queues. According to the priority of the packet and
availability of the queue, node will schedule the packet for
transmission. Due to separated queue availability, packet
transmission delay is reduced. Due to reduction in packet
transmission delay, node can goes into sleep mode as soon as
possible. And Expired packets are deleted at the particular node
at itself before reaching the base station, so that processing
burden on the node is reduced. Thus, energy of the node is saved.
A NOVEL APPROACH FOR ENERGY EFFICIENT HIERARCHY BASED ROUTING IN SENSOR NETWO...cscpconf
Wireless sensor network (WSN) is the collection of many micro-sensor nodes, connecting each other by a
wireless medium. WSN exhibits different approaches to provide reliable sensing of the environment,
detecting and reporting events. In this paper, we have proposed an algorithm for hierarchy based protocols
of wireless sensor networks, which consist of two groups of sensor nodes in a single cluster node. Each
cluster consists of a three cluster head. The event driven data sensing mechanism is used in this paper and
this sensed data is transmitted to the master section head. Hence efficient way of data transmission is possible with larger group of nodes. In this approach, using hierarchy based protocols; the lifetime of the sensor network is increased.
Vertex covering has important applications for wireless sensor networks such as monitoring link failures,
facility location, clustering, and data aggregation. In this study, we designed three algorithms for
constructing vertex cover in wireless sensor networks. The first algorithm, which is an adaption of the
Parnas & Ron’s algorithm, is a greedy approach that finds a vertex cover by using the degrees of the
nodes. The second algorithm finds a vertex cover from graph matching where Hoepman’s weighted
matching algorithm is used. The third algorithm firstly forms a breadth-first search tree and then
constructs a vertex cover by selecting nodes with predefined levels from breadth-first tree. We show the
operation of the designed algorithms, analyze them, and provide the simulation results in the TOSSIM
environment. Finally we have implemented, compared and assessed all these approaches. The transmitted
message count of the first algorithm is smallest among other algorithms where the third algorithm has
turned out to be presenting the best results in vertex cover approximation ratio.
International Journal of Advanced Smart Sensor Network Systems (IJASSN)ijcseit
The placement of base stations in wireless sensor networks affect the energy consumption for
communication between sensor node and base station. In this paper we analyzed the performance of the
zone based clustering protocol [2] under varying position of base stations, different zone sizes and the
effect on network life time with multiple base stations. While evaluating the communication overhead of
various cluster sizes, we observed that the optimal cluster size for a given network is complex, depending
on a range of parameters. Simulation results show that communication overhead decreases as we increase
the number of zone in the network. We show that placing multiple base stations in place of single base
station in zone based routing protocol enhance the network life time.
Localization is one of the key technologies in wireless sensor networks (WSNs), since it provides
fundamental support for many location-aware protocols and applications. Constraints on cost and power
consumption make it infeasible to equip each sensor node in the network with a global position system
(GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use
anchor nodes, which are equipped with GPS units among unknown nodes and broadcast their current
locations to help nearby unknown nodes with localization. In this paper we can proposed a novel algorithm
of cuboid localization with the help of central point precision method. Simulation shows that the results are
far better then existing cuboid methods and gain accuracy of up to 83% with a localization error of 1.6m
and standard deviation of 2.7.
The Expansion of 3D wireless sensor network Bumps localizationIJERA Editor
Bump localization of wireless sensor network is a hot topic, but present algorithms of 3D wireless sensor node localization arenot accurate enough. In this paper, the DR-MDS algorithm is proposed, DR-MDS algorithm mainly calibrates the coordinatesof nodes and the ranging of nodes based on multidimensional scaling, it calculates the distance between any nodes exactlyaccording to the hexahedral measurement, introducing a modification factor to calibrate the measuring distance by ReceivedSignal Strength Indicator (RSSI). Results of simulation show that DR-MDS algorithm has significant improvement inlocalization accuracy compare with MDS-MAP algorithm.
Shortest path algorithm for data transmission in wireless ad hoc sensor networksijasuc
Wireless sensor networks determine probable in military, environments, health and commercial
applications. The process of transferring of information from a remote sensor node to other nodes in a
network holds importance for such applications. Various constraints such as limited computation, storage
and power makes the process of transferring of information routing interesting and has opened new arenas
for researchers. The fundamental problem in sensor networks states the significance and routing of
information through a real path as path length decides some basic performance parameters for sensor
networks. This paper strongly focuses on a shortest path algorithm for wireless adhoc networks. The
simulations are performed on NS2 and the results obtained discuss the role of transferring of information
through a shortest path.
ENERGY EFFICIENT APPROACH BASED ON EVOLUTIONARY ALGORITHM FOR COVERAGE CONTRO...ijcseit
Coverage and connectivity are two important requirements in Wireless Sensor Networks (WSNs). In this
paper, we address the problem of network coverage and connectivity and propose an energy efficient
approach based on genetic evolutionary algorithm for maintaining coverage and connectivity where the
sensor nodes can have different sensing ranges and transmission ranges. The proposed algorithm is
simulated and it' efficiency is demonstrated via different experiments.
International Journal of Computer Science, Engineering and Information Techno...ijcseit
Coverage and connectivity are two important requirements in Wireless Sensor Networks (WSNs). In this paper, we address the problem of network coverage and connectivity and propose an energy efficient approach based on genetic evolutionary algorithm for maintaining coverage and connectivity where the sensor nodes can have different sensing ranges and transmission ranges .The proposed algorithm is simulated and it' efficiency
is demonstrated via different experiments.
A STRUCTURED DEEP NEURAL NETWORK FOR DATA-DRIVEN LOCALIZATION IN HIGH FREQUEN...IJCNCJournal
Next-generation wireless networks such as 5G and 802.11ad networks will use millimeter waves operating
at 28GHz, 38GHz, or higher frequencies to deliver unprecedentedly high data rates, e.g., 10 gigabits per
second. However, millimeter waves must be used directionally with narrow beams in order to overcome the
large attenuation due to their higher frequency. To achieve high data rates in a mobile setting,
communicating nodes need to align their beams dynamically, quickly, and in high resolution. We propose a
data-driven, deep neural network (DNN) approach to provide robust localization for beam alignment,
using a lower frequency spectrum (e.g., 2.4 GHz). The proposed DNN-based localization methods use the
angle of arrival derived from phase differences in the signal received at multiple antenna arrays to infer the
location of a mobile node. Our methods differ from others that use DNNs as a black box in that the
structure of our neural network model is tailored to address difficulties associated with the domain, such as
collinearity of the mobile node with antenna arrays, fading and multipath. We show that training our
models requires a small number of sample locations, such as 30 or fewer, making the proposed methods
practical. Our specific contributions are: (1) a structured DNN approach where the neural network
topology reflects the placement of antenna arrays, (2) a simulation platform for generating training and
evaluation data sets under multiple noise models, and (3) demonstration that our structured DNN approach
improves localization under noise by up to 25% over traditional off-the-shelf DNNs, and can achieve submeter
accuracy in a real-world experiment.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
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Energy Efficient Modeling of Wireless Sensor Networks using Random Graph Theoryidescitation
This paper deals with the discussion of an innovative and a design for the
efficient power management and power failure diagnosis in the area of wireless sensors
networks. A Wireless Network consists of a web of networks where hundreds of pairs are
connected to each other wirelessly. A critical issue in the wireless sensor networks in the
present scenario is the limited availability of energy within network nodes. Therefore,
making good use of energy is necessary in modeling a sensor network. In this paper we have
tried to propose a new model of wireless sensors networks on a three-dimensional plane
using the percolation model, a kind of random graph in which edges are formed between the
neighbouring nodes. An algorithm has been described in which the power failure diagnosis
is made and solved. The concepts of Electromagnetics, Wave Duality, Energy model of an
atom is linked with wireless networks. A model is prepared in which the positioning of
nodes of sensors are decided. Also the model is made more efficient regarding the energy
consumption, power delivery etc. using the concepts of graph theory concepts, probability
distribution.
Ca mwsn clustering algorithm for mobile wireless senor network [graphhoc
This paper proposes a centralized algorithm for cluster-head-selection in a mobile wireless sensor network.
Before execution of algorithm in each round, Base station runs centralized localization algorithm whereby
sensors update their locations to base station and accordingly Base station performs dynamic clustering.
Afterwards Base station runs CA-MWSN for cluster-head-selection. The proposed algorithm uses three
fuzzy inputs Residual energy, Expected Residual Energy and Mobility to find Chance of nodes to be elected
as Cluster-head. The node with highest Chance is declared as a Cluster-head for that particular cluster.
Dynamic clustering provides uniform and significant distribution of energy in a non-uniform distribution of
sensors. CA-MWSN guarantees completion of the round.
CA-MWSN: CLUSTERING ALGORITHM FOR MOBILE WIRELESS SENOR NETWORKFransiskeran
This paper proposes a centralized algorithm for cluster-head-selection in a mobile wireless sensor network.
Before execution of algorithm in each round, Base station runs centralized localization algorithm whereby
sensors update their locations to base station and accordingly Base station performs dynamic clustering.
Afterwards Base station runs CA-MWSN for cluster-head-selection. The proposed algorithm uses three
fuzzy inputs Residual energy, Expected Residual Energy and Mobility to find Chance of nodes to be elected
as Cluster-head. The node with highest Chance is declared as a Cluster-head for that particular cluster.
Dynamic clustering provides uniform and significant distribution of energy in a non-uniform distribution of
sensors. CA-MWSN guarantees completion of the round.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
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1. International Journal of Engineering Science Invention
ISSN (Online): 2319 – 6734, ISSN (Print): 2319 – 6726
www.ijesi.org Volume 2 Issue 6 ǁ June. 2013 ǁ PP.103-106
www.ijesi.org 103 | Page
Distributed Localization in Wireless Sensor Networks
Mrs.P.D.Patil1
, Dr(Smt).R.S.Patil2
1
(Department of Electronics and Telecommunication, DYPatil college of Engg& Technology, India)
ABSTRACT : Due to the success of the emerging wireless sensor network (WSN) technology, localization has
newly received research interest. This interest is expected to grow further with the proliferation of wireless
sensor network applications such as medicine, military, transport. In this context routing, protocols and
technologies of communication on those wireless area are enormously applied to sensor networks in order to
improve the quality of service and communication. Related to this work, we present a distributed algorithm for
localization of nodes in a discrete model of a random ad hoc communication network.
KEYWORDS: Distributed Algorithm, Localization, WSN
I. INTRODUCTION
Recent advances in micro-electro-mechanical system(MEMS), computing, and communication
technology have fomented the emergence of massively distributed, wireless sensor networks consisting of
hundreds or thousands of nodes. Each node is able to sense the environment, perform simple computations, and
communicate with its peers or to an external observer. The challenges these networks present are far beyond the
reach of the current theory and algorithms[1]. One way of deploying a sensor network is to scatter the nodes
throughout some region of interest. This makes the network topology random. Since there is no a priori
communication protocol, the network is ad hoc. The first task that has to be solved is to localize the nodes i.e.,
to compute their positions in some fixed coordinate system. Since most applications (such as tracking an object
moving through the network, environmental monitoring, etc.) depend on a successful localization, it is of great
importance to design scalable localization algorithms and provide error estimates that will enable us to choose
optimal network parameters before deployment.
1.1. COMPARISON CENTRALIZED AND DISTRIBUTED ALGORITHMS
Centralized and distributed distance-based localization algorithms can be compared from perspectives of
location estimation accuracy, implementation and computation issues, and energy consumption. It is worth
noting that decentralized localization is strictly harder than centralized, i.e., any algorithm for decentralized
localization can always be applied to centralized problems, but not the reverse. From the perspective of location
estimation accuracy, centralized algorithms are likely to provide more accurate location estimates than
distributed algorithms. However centralized algorithms suffer from the scalability problem and generally are not
feasible to be implemented for large scale sensor networks. Other disadvantages of centralized algorithms, as
compared to distributed algorithms, are their requirement of higher computational complexity and lower
reliability due to accumulated information inaccuracies/losses caused by multi-hop transmission over a wireless
network[2].On the other hand, distributed algorithms are more difficult to design because of the potentially
complicated relationship between local behavior and global behavior, e.g., algorithms that are locally optimal
may not perform well in a global sense. Optimal distribution of the computation of a centralized algorithm in a
distributed implementation in general is an unsolved research problem. Error propagation is another potential
problem in distributed algorithms. Moreover, distributed algorithms generally require multiple iterations to
arrive a stable solution which may cause the localization process to take longer time than the acceptable in some
cases. To compare the centralized and distributed distance-based localization algorithms from the
communication energy consumption perspective, one needs to consider the individual amounts of energy
required for each type of operation in the localization algorithm in the specific hardware and the transmission
range setting. Depending on the setting, the energy required for transmitting a single bit could be used to
execute 1,000 to 2,000 instructions [3]. Centralized algorithms in large networks require each sensor’s
measurements to be sent over multiple hops to a central processor, while distributed algorithms require only
local information exchange between neighboring nodes but many such local exchanges may be required,
depending on the number of iterations needed to arrive at a stable solution.
2. Distributed Localization In Wireless Sensor Networks
www.ijesi.org 104 | Page
1.2. BENEFITS OF DISTRIBUTED ALGORITHMS
Due to high long range communication costs and low battery power, it is natural to seek decentralized,
distributed algorithms for sensor networks. This means that instead of relaying data to a central location which
does all the computing, the nodes process information in a collaborative, distributed way. For instance, they can
form computational clusters, based on their distance from each other. The outcome of these distributed, local
computations is stored in local memory and can then be, when necessary, relayed to a centralized computing
unit. Robustness to node failures is another reason to seek distributed rather than centralized algorithms. This
paper is organized as follows. In Section 2, we establish the setting and introduce the basic terminology and
notation. In Section 3, we discuss the basic localization algorithm which described in Section 4, and provide
error estimates and simulation results.
II. PRIMARY WORKS
In this section we introduce the basic framework, terminology, and notation.We assume that in a square
region Q = [0, s] × [0, s], called the region of operations, we randomly scatter N nodes, each of which
is equipped with an RF transceiver with communication range r > 0. In other words, a node Si can communicate
with every node which lies in its communication region, which is the disk with radius r centered at Si. Each
node has a unique ID which is a number between 1 and N. The nodes form an ad hoc network N in which there
is an edge between and ,when their distance is less than r. We will call this the continuous model. Even
though it is a rather simplified model of how the network is formed, we adopt it because it leads to an easier
analytical treatment. However, instead of a disk of radius r, the communication range of a node could instead be
an annulus (in case a node is able to decide when a nearby node is at a distance greater than some threshold,
based, e.g., on signal strength), an angular sector (if a node is equipped, say, with laser transmitters and
receivers that can scan through some angle) or an intersection of an annulus and an angular sector. More
information on these types of constraints is available in [4].We assume that a certain positive number K of nodes
know their location in Q, i.e., they are able to compute their position relative to some fixed coordinate system in
Q.In practice this can be achieved by equipping K motes with GPS or a priori (meaning before deploying the ad
hoc network) placing in Q .A certain number of beacons which can serve to compute the position of the nodes
which are within certain distance from them. We call nodes that know their position as known nodes or beacon
nodes and all other ones, unknown nodes. Furthermore, each node has communication as well as sensing
capabilities [5].
The problems we address in this paper are:
Design a distributed algorithm for localization of nodes in.N.
Estimate the complexity and error of the above algorithm.
Find an optimal number of known nodes depending on Q, N and r, which minimizes the error of the
algorithm.
Centralized algorithms for localization were studied in [1, 2]. The reason we are interested in a
distributed rather than a centralized solution is that we envision a massively distributed network in which
communication with a centralized computer is expensive both because the power supply of each node is very
limited and long-range multi-hop data transmission is costly and often inefficient. However, one quickly
discovers that obtaining analytical estimates even in this simple setting can be rather challenging. Furthermore,
in the design of a decentralized algorithm relying on node-based data processing, one must take into account
that nodes have very limited computational power. This motivates the following discrete approach to the above
problems. Let n > 0 be an integer. Partition Q into congruent squares called cells of area and suppose that
for every known node S, we are only interested in finding the cell which contains S. To make this problem
tractable, we make a simplifying assumption that the communication range is ρ cells in the max metric, distance
denoted by . It is defined by
((i, j), (i` , j` )) = max(|i–i` |, |j – j`|)
Where (i, j) is initial distance vector, (i`, j`) is final distance vector. It is possible for several nodes to lie
inthe same cell. We call this the discretemodel of the network. For example, we can take
Each node S can communicate with every node lying in the square centered at S and containing
cells. Since all our results are independent of the choice of ρ as a function of r and n, we can clearly
select a different value for it. The situation where r is fixed and s, n → ∞ corresponds to increasing the size of
3. Distributed Localization In Wireless Sensor Networks
www.ijesi.org 105 | Page
the region of operations, while the situation where r/n and s stay constant while n → ∞ corresponds to refining
the position estimate. We usually think of n as large and r as much smaller than n. In particular, 2ρ + 1 < n.
Figure 1: Discrete model. Filled circles denote unknown nodes. The dashed line bounds thecommunication
range of the node at its center, with ρ = 3.
III. DISTRIBUTED ALGORITHM FOR LOCALIZATION
In this section we present a simple distributed algorithm for localization, based on the ideas in the
previous section.Let S be an arbitrary unknown node in N. The localization algorithm LOCS at S then goes as
follows –
Step 1. INITIALIZE the estimate: .
Step 2.SEND “Hello, can you hear me?”
Each known neighbor sends back (1, a, b), where (a, b) is its grid position, while each unknown neighbor sends
(0, 0, 0).
Step 3.For each response (1, a, b), UPDATE the estimate by
Step 4.STOP when all responses have been received. The position estimate is
IV. SIMULATION RESULTS
To analyze performance of algorithm, we have taken three scenarios by varying number of nodes, n and
number of beacon nodes, K in the network, where –
n = Unknown nodes + K;
Scenario 1: Chose No. of beacon nodes, K= 5.
Case 1: Chose unknown nodes=45 and calculated their positions.
Case 2: Chose unknown nodes=95 and calculated their positions.
Case 3: Chose unknown nodes=145 and calculated their positions.
Then we have calculated the performance of algorithm as shown in Fig. 2.
Figure 2: Performance of Network for K=5 and n=50,100 and 150.
4. Distributed Localization In Wireless Sensor Networks
www.ijesi.org 106 | Page
Scenario 2: Chose No. of beacon nodes, K= 10.
Case 1: Chose unknown nodes=40 and calculated their positions.
Case 2: Chose unknown nodes=90 and calculated their positions.
Case 3: Chose unknown nodes=140 and calculated their positions.Then we have calculated the performance of
algorithm as shown in Fig. 3.
Figure 3: Performance of Network for K=10 and n=50,100 and 150.
Scenario 3: Chose No. of beacon nodes, K= 15.
Case 1: Chose unknown nodes=35 and calculated their positions.
Case 2: Chose unknown nodes=85 and calculated their positions.
Case 3: Chose unknown nodes=135 and calculated their positions.
Then we have calculated the performance of algorithm as shown in Fig. 4
Figure 4: Performance of Network for K=15 and n=50,100 and 150.
Observe that the error of the algorithm steadily increases as total no. of nodes (n) increases. However, the
error does not change considerably for K>=10.
V. CONCLUSION
The main contributions of this paper are a distributed algorithm for localization of nodes in a wireless ad
hoc communication network and estimates of its error. There are many possible improvements of the algorithm.
REFERENCES
[1] AmitangshuPal,“Localization Algorithms in Wireless Sensor. Networks: Current Approaches and Future Challenges”,
macrothink, 2010, Vol. 2, No. 1
[2] Zhetao Li, Renfa Li, Yehua Wei and Tingrui Pei, 2010.” Survey of Localization Techniques in Wireless Sensor Networks”.
Information Technology Journal, 9: 1754-1757.
[3] J. Chen, K. Yao, and R. Hudson, “Source localization and beamforming,” IEEE Signal Processing Magazine, vol. 19, no. 2, pp.
30–39, 2002.
[4] L. Doherty. Algorithms for position and data recovery in wireless sensor networks. Master’s thesis, UC Berkeley, 2000.
[5] J.M. Kahn, R.H. Katzand, and K.S.J. Pister. Mobile networking for Smart Dust. In ACM/IEEE Intl. Conf. on Mobile Computing
and Networking, Seattle, WA, August 1999
[6]