1) The document proposes a new network construction method called k-SBCCS Protocol for strong k-barrier coverage using wireless sensor nodes for border security systems.
2) It aims to prolong network lifetime by establishing a balanced energy usage across nodes. The k-SBCCS Protocol uses a divide-and-conquer approach to construct local barriers in segmented regions and coordinate barrier coverage across segments.
3) Simulation results show that the k-SBCCS Protocol can reduce communication overhead and computation costs compared to centralized algorithms, and strengthens local barrier coverage through coordinated barriers across segments.
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,
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.
AN ENERGY EFFICIENT DISTRIBUTED PROTOCOL FOR ENSURING COVERAGE AND CONNECTIVI...ijasuc
As wireless sensor networks (WSNs) continue to attract more and more researchers attention, new ideas for
applications are continually being developed, many of which involve consistent coverage with good
network connectivity of a given area of interest. For the successful operation of the wireless Sensor
Network, the active sensor nodes must maintain both coverage and also connectivity. These are two closely
related essential prerequisites and they are also very important measurements of quality of service (QoS)
for wireless sensor networks. This paper presents the design and analysis of novel protocols that can
dynamically configure a sensor network to result in guaranteed degrees of coverage and connectivity. This
protocol is simulated using NS2 simulated and compared against a distributed probabilistic coveragepreserving configuration protocol (DPCCP) with SPAN [1] protocol in the literature and show that it
activates lesser number of sensor nodes, consumes much lesser energy and maximises the network lifetime
significantly.
Delaunay based two-phase algorithm for connected cover in WSNsMaynooth University
Monitoring applications are one of the main usages of wireless sensor networks, where the sensor nodes are responsible to report any event of interest in the monitoring area. Due to their limited energy storage, the nodes are prone to fail, which may lead to network partitioning problem. To cope with this problem, the number of deployed sensor nodes in an area is more than the required quantity. The challenge is to turn on a minimal number of nodes to preserve network connectivity and area coverage. In this paper, we apply computational geometry techniques to introduce a new 2-phase algorithm, called Delaunay Based Connected Cover (DBCC), to find a connected cover in an omnidirectional wireless sensor network. In the first phase, the Delaunay triangulation of all sensors is computed and a minimal number of sensors is selected to ensure the coverage of the region. In the second phase, connectivity of the nodes is ensured. The devised method is simulated by NS2 and is compared with two well-known algorithms, CCP and OGDC. For the case, where the communication and the coverage radii are equal, our method requires 23% and 45% fewer nodes compared to the aforementioned methods, respectively. In the second simulation case, the communication radius is set to 1.5 times of the coverage radius. The results demonstrate that DBCC chooses 14% and 34% fewer nodes, respectively.
Routing in Wireless Sensor Networks: Improved Energy Efficiency and Coverage ...CSCJournals
This paper proposes a new method for collecting distributed data in Wireless Sensor Networks (WSNs) that can improve the energy efficiency and network coverage; especially in remote areas. In multi-hop communication, sink nodes are responsible for collecting and forwarding data to base stations. The nodes that are located near a sink node usually deplete their battery faster than other nodes because they are responsible for aggregating the data from other sensor nodes. Several studies have proved the advantages of using mobile sink nodes to reduce energy consumption. Nonetheless, the need for compatible and efficient routing algorithms cannot be understated. Accordingly, a hybrid routing algorithm based on the Dijkstra�s and Rendezvous algorithms is proposed. To improve the energy efficiency and coverage, Energy Efficient Hybrid Unmanned Vehicle Based Routing Algorithm (E2HUV) is proposed to create a routing path for Unmanned Aerial Vehicles (UAVs) that can be used as mobile sinks in WSNs. Performance results show that the E2HUV algorithm offers better efficiency as compared to currently existing algorithms.
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,
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.
AN ENERGY EFFICIENT DISTRIBUTED PROTOCOL FOR ENSURING COVERAGE AND CONNECTIVI...ijasuc
As wireless sensor networks (WSNs) continue to attract more and more researchers attention, new ideas for
applications are continually being developed, many of which involve consistent coverage with good
network connectivity of a given area of interest. For the successful operation of the wireless Sensor
Network, the active sensor nodes must maintain both coverage and also connectivity. These are two closely
related essential prerequisites and they are also very important measurements of quality of service (QoS)
for wireless sensor networks. This paper presents the design and analysis of novel protocols that can
dynamically configure a sensor network to result in guaranteed degrees of coverage and connectivity. This
protocol is simulated using NS2 simulated and compared against a distributed probabilistic coveragepreserving configuration protocol (DPCCP) with SPAN [1] protocol in the literature and show that it
activates lesser number of sensor nodes, consumes much lesser energy and maximises the network lifetime
significantly.
Delaunay based two-phase algorithm for connected cover in WSNsMaynooth University
Monitoring applications are one of the main usages of wireless sensor networks, where the sensor nodes are responsible to report any event of interest in the monitoring area. Due to their limited energy storage, the nodes are prone to fail, which may lead to network partitioning problem. To cope with this problem, the number of deployed sensor nodes in an area is more than the required quantity. The challenge is to turn on a minimal number of nodes to preserve network connectivity and area coverage. In this paper, we apply computational geometry techniques to introduce a new 2-phase algorithm, called Delaunay Based Connected Cover (DBCC), to find a connected cover in an omnidirectional wireless sensor network. In the first phase, the Delaunay triangulation of all sensors is computed and a minimal number of sensors is selected to ensure the coverage of the region. In the second phase, connectivity of the nodes is ensured. The devised method is simulated by NS2 and is compared with two well-known algorithms, CCP and OGDC. For the case, where the communication and the coverage radii are equal, our method requires 23% and 45% fewer nodes compared to the aforementioned methods, respectively. In the second simulation case, the communication radius is set to 1.5 times of the coverage radius. The results demonstrate that DBCC chooses 14% and 34% fewer nodes, respectively.
Routing in Wireless Sensor Networks: Improved Energy Efficiency and Coverage ...CSCJournals
This paper proposes a new method for collecting distributed data in Wireless Sensor Networks (WSNs) that can improve the energy efficiency and network coverage; especially in remote areas. In multi-hop communication, sink nodes are responsible for collecting and forwarding data to base stations. The nodes that are located near a sink node usually deplete their battery faster than other nodes because they are responsible for aggregating the data from other sensor nodes. Several studies have proved the advantages of using mobile sink nodes to reduce energy consumption. Nonetheless, the need for compatible and efficient routing algorithms cannot be understated. Accordingly, a hybrid routing algorithm based on the Dijkstra�s and Rendezvous algorithms is proposed. To improve the energy efficiency and coverage, Energy Efficient Hybrid Unmanned Vehicle Based Routing Algorithm (E2HUV) is proposed to create a routing path for Unmanned Aerial Vehicles (UAVs) that can be used as mobile sinks in WSNs. Performance results show that the E2HUV algorithm offers better efficiency as compared to currently existing algorithms.
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.
ENHANCED PARTICLE SWARM OPTIMIZATION FOR EFFECTIVE RELAY NODES DEPLOYMENT IN ...IJCNCJournal
One of the critical design problems in Wireless Sensor Networks (WSNs) is the Relay Node Placement
(RNP) problem. Inefficient deployment of RNs would have adverse effects on the overall performance and
energy efficiency of WSNs. The RNP problem is a typical example of an NP-hard optimization problem
which can be addressed using metaheuristics with multi-objective formulation. In this paper, we aimed to
provide an efficient optimization approach considering the unconstrained deployment of energy-harvesting
RNs into a pre-established stationary WSN. The optimization was carried out for three different objectives:
energy consumption, network coverage, and deployment cost. This was approached using a novel
optimization approach based on the integration of the Particle Swarm Optimization (PSO) algorithm and a
greedy technique. In the optimization process, the greedy algorithm is an essential component to provide
effective guidance during PSO convergence. It supports the PSO algorithm with the required information
to efficiently alleviate the complexity of the PSO search space and locate RNs in the spots of critical
significance. The evaluation of the proposed greedy-based PSO algorithm was carried out with different
WSN scenarios of varying complexity levels. A comparison was established with two PSO variants: the
classical PSO and a PSO hybridized with the pattern search optimizer. The experimental results
demonstrated the significance of the greedy algorithm in enhancing the optimization process for all the
considered PSO variants. The results also showed how the solution quality and time efficiency were
considerably improved by the proposed optimization approach. Such improvements were achieved using a
simple integration technique without adding to the complexity of the system and introducing additional
optimization stages. This was more evident in the RNP scenarios of considerably large search spaces, even
with highly complex and challenging setups.
Greedy – based Heuristic for OSC problems in Wireless Sensor NetworksIJMER
This paper contains optimize set coverage problem in wireless sensor networks with adaptable sensing range. Communication and sensing consume energy, so efficient power management can extended the network lifetime. In this paper we consider a enormous number of sensors with adaptable sensing range that are randomly positioned to monitor a number of targets. Every single target may be redundantly covered by various sensors. For preserving energy resources we organize sensors in sets stimulated successively. In this paper we introduce the Optimize Set Coverage (OSC) problem that has in unbiased finding with an extreme number of set covers in which every sensor node to be activated is connected to the base station. A sensor can be participated in various sensor sets, but the overall energy consumed in all groups is forced by the primary energy reserves. We show that the OSC problem is NP-complete and we propose the solutions: an integer programming for OSC problem, a linear programming for OSC problem with greedy approach, and a distributed and localized heuristic. Simulation results are presented and validated to our approaches.
Energy Conservation in Wireless Sensor Networks Using Cluster-Based ApproachIJRES Journal
In a wireless networking environment, the network is comprised of sensor nodes and backbones are subsets of sensors or actuators that suffice for performing basic data communication operations. They are applied for energy efficient broadcasting. In a broadcasting (also known as data dissemination) task, a message is to be sent from one node, which could be a sink or an actuator, to all the sensors or all the actuators in the network. The goal is to minimize the number of rebroadcasts while attempting to deliver messages to all sensors or actuators. Neighbor detection and route discovery algorithms that consider a realistic physical layer are described. An adaptive broadcasting protocol without parameters suitable for delay tolerant networks is further discussed. In existing solutions for minimal energy broadcasting problem, nodes can adjust their transmission powers. Wireless Sensor Networks (WSNs) are sets of many sensors that gather data and collaborate together. So, the procedures of broadcast or multicast are more important than traditional point-to-point communication in computer network. This paper focuses on broadcasting in structured WSNs. In such a kind, the procedure of network communications is easier than in unstructured WSNs. Thus, it will make an overview of Multi Point Relay (MPR) to show its weakness. Then define a cluster-based architecture for WSNs which is constructed using MPR. Next, provide a new broadcast algorithm based on the previous cluster architecture called 3B (Backbone Based Broadcasting). By the end, an illustration of 3B shows that it minimizes the energy consumption for accomplishing broadcast compared to MPR.
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.
An Integrated Distributed Clustering Algorithm for Large Scale WSN...................................................1
S. R. Boselin Prabhu, S. Sophia, S. Arthi and K. Vetriselvi
An Efficient Connection between Statistical Software and Database Management System ................... 1
Sunghae Jun
Pragmatic Approach to Component Based Software Metrics Based on Static Methods ......................... 1
S. Sagayaraj and M. Poovizhi
SDI System with Scalable Filtering of XML Documents for Mobile Clients ............................................... 1
Yi Yi Myint and Hninn Aye Thant
An Easy yet Effective Method for Detecting Spatial Domain LSB Steganography .................................... 1
Minati Mishra and Flt. Lt. Dr. M. C. Adhikary
Minimizing the Time of Detection of Large (Probably) Prime Numbers ................................................... 1
Dragan Vidakovic, Dusko Parezanovic and Zoran Vucetic
Design of ATL Rules for TransformingUML 2 Sequence Diagrams into Petri Nets..................................... 1
Elkamel Merah, Nabil Messaoudi, Dalal Bardou and Allaoua Chaoui
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.
Security based Clock Synchronization technique in Wireless Sensor Network for...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Proactive Data Reporting of Wireless sensor Network using Wake Up Scheduling ...ijsrd.com
In Wireless Sensor Network (WSNs), gather the data by using mobile sinks has become popular. Reduce the number of messages which is used for sink location broadcasting, efficient energy data forwarding, become accustomed to unknown earthly changes are achieved by a protocol which is projected by a SinkTrail. The forecast of mobile sinks’ location are done by using logical coordinate system. When sensor nodes don’t have any data to send, at that time they switch to sleep mode to save the energy and to increase the network lifetime. And due to this reason there is a chance of the involvement of nodes that are in sleeping state between the path sources to the mobile sink which is selected by the SinkTrail protocol. Before become the fully functional and process the information, these sleeping nodes can drop the some information. Due to this reason, it is vital to wake-up the sleeping nodes on the path earlier than the sender can start transferring of sensed data. In this paper, on-demand wake-up scheduling algorithm is projected which is used to activates sleeping node on the path before data delivery. Here, in this work the multi-hop communication in WSN also considers. By incorporating wake-up scheduling algorithm to perk up the dependability and improve the performance of on-demand data forwarding extends the SinkTrail solution in our work. This projected algorithm improves the quality of service of the network by dishonesty of data or reducing the loss due to sleeping nodes. The efficiency and the effectiveness projected solution are proved by the evaluation results.
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.
AN IMPROVED DECENTRALIZED APPROACH FOR TRACKING MULTIPLE MOBILE TARGETS THROU...ijwmn
Target localization and tracking problems in WSNs have received considerable attention recently, driven
by the requirement to achieve high localization accuracy, with the minimum cost possible. In WSN based
tracking applications, it is critical to know the current location of any sensor node with the minimum
energy consumed. This paper focuses on the energy consumption issue in terms of communication
between nodes whenever the localization information is transmitted to a sink node. Tracking through
WSNs can be categorized into centralized and decentralized systems. Decentralized systems offer low
power consumption when deployed to track a small number of mobile targets compared to the centralized
tracking systems. However, in several applications, it is essential to position a large number of mobile
targets. In such applications, decentralized systems offer high power consumption, since the location of
each mobile target is required to be transmitted to a sink node, and this increases the power consumption
for the whole WSN. In this paper, we propose a power efficient decentralized approach for tracking a
large number of mobile targets while offering reasonable localization accuracy through ZigBee network
Unmanned aerial vehicles (UAVs) have become very popular recently for both civil uses and potential commercial uses, such as law enforcement, crop survey, grocery delivery, and photographing, although they were mainly used for military purposes before. Researchers need the help of simulations when they design and test new protocols for UAV networks because simulations can be done for a network of a size
that a test bed can hardly approach. In the simulation of an UAV network it is important to choose a radio propagation model for the links in the network. We study the shadowing radio propagation model in this paper and compare it with the free space model, both of which are available in the ns2 network simulation package. We also show how the choice of the parameters of the shadowing model would impact on the
network performance of a UAV network.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers reduces the energy consumption and increases the throughput of the wireless sensor networks.
Indeling
Begane grond:
Entree / hal, toilet, uitgebouwde woonkamer (41 m²), open keuken met inbouwapparatuur.
Eerste verdieping:
Overloop, 2 (voorheen 3) slaapkamers (resp. 19 m² en 12 m²), moderne badkamer met ligbad, 2e toilet en een vaste wastafel meubel.
Tweede verdieping:
Overloop, zolderkamer (8 m²) met dakraam en berging.
Kenmerken:
Type woning: Eengezinswoning
Bouwjaar: 1977
Woonoppervlakte: 108 m² NEN2580
Bruto vloeroppervlakte: ca. 120m²
Perceeloppervlakte: 199 m²
Aantal kamers: 4 (3 slaapkamers)
Bijzonderheden:
- Diepe tuin op het zuid westen
- Veel privacy
- Geen auto's voor de deur
- Uitgebouwde woonkamer
- Vaste trap naar de tweede verdieping
Binnen kijken?
Bel 030-6995616 voor een bezichtiging of bel René Hoksbergen voor meer informatie over deze woning op 06-50641697.
LET OP: Dit is een 3Droomhuis.
Door deze 3D foto's en video te bekijken krijg je een nóg realistischer beeld van dit huis.
Heb je (nog) geen 3D bril?
Vraag dan direct GRATIS jouw 3D bril aan op onze website. Wij sturen je z.s.m. een eigen exemplaar toe.
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.
ENHANCED PARTICLE SWARM OPTIMIZATION FOR EFFECTIVE RELAY NODES DEPLOYMENT IN ...IJCNCJournal
One of the critical design problems in Wireless Sensor Networks (WSNs) is the Relay Node Placement
(RNP) problem. Inefficient deployment of RNs would have adverse effects on the overall performance and
energy efficiency of WSNs. The RNP problem is a typical example of an NP-hard optimization problem
which can be addressed using metaheuristics with multi-objective formulation. In this paper, we aimed to
provide an efficient optimization approach considering the unconstrained deployment of energy-harvesting
RNs into a pre-established stationary WSN. The optimization was carried out for three different objectives:
energy consumption, network coverage, and deployment cost. This was approached using a novel
optimization approach based on the integration of the Particle Swarm Optimization (PSO) algorithm and a
greedy technique. In the optimization process, the greedy algorithm is an essential component to provide
effective guidance during PSO convergence. It supports the PSO algorithm with the required information
to efficiently alleviate the complexity of the PSO search space and locate RNs in the spots of critical
significance. The evaluation of the proposed greedy-based PSO algorithm was carried out with different
WSN scenarios of varying complexity levels. A comparison was established with two PSO variants: the
classical PSO and a PSO hybridized with the pattern search optimizer. The experimental results
demonstrated the significance of the greedy algorithm in enhancing the optimization process for all the
considered PSO variants. The results also showed how the solution quality and time efficiency were
considerably improved by the proposed optimization approach. Such improvements were achieved using a
simple integration technique without adding to the complexity of the system and introducing additional
optimization stages. This was more evident in the RNP scenarios of considerably large search spaces, even
with highly complex and challenging setups.
Greedy – based Heuristic for OSC problems in Wireless Sensor NetworksIJMER
This paper contains optimize set coverage problem in wireless sensor networks with adaptable sensing range. Communication and sensing consume energy, so efficient power management can extended the network lifetime. In this paper we consider a enormous number of sensors with adaptable sensing range that are randomly positioned to monitor a number of targets. Every single target may be redundantly covered by various sensors. For preserving energy resources we organize sensors in sets stimulated successively. In this paper we introduce the Optimize Set Coverage (OSC) problem that has in unbiased finding with an extreme number of set covers in which every sensor node to be activated is connected to the base station. A sensor can be participated in various sensor sets, but the overall energy consumed in all groups is forced by the primary energy reserves. We show that the OSC problem is NP-complete and we propose the solutions: an integer programming for OSC problem, a linear programming for OSC problem with greedy approach, and a distributed and localized heuristic. Simulation results are presented and validated to our approaches.
Energy Conservation in Wireless Sensor Networks Using Cluster-Based ApproachIJRES Journal
In a wireless networking environment, the network is comprised of sensor nodes and backbones are subsets of sensors or actuators that suffice for performing basic data communication operations. They are applied for energy efficient broadcasting. In a broadcasting (also known as data dissemination) task, a message is to be sent from one node, which could be a sink or an actuator, to all the sensors or all the actuators in the network. The goal is to minimize the number of rebroadcasts while attempting to deliver messages to all sensors or actuators. Neighbor detection and route discovery algorithms that consider a realistic physical layer are described. An adaptive broadcasting protocol without parameters suitable for delay tolerant networks is further discussed. In existing solutions for minimal energy broadcasting problem, nodes can adjust their transmission powers. Wireless Sensor Networks (WSNs) are sets of many sensors that gather data and collaborate together. So, the procedures of broadcast or multicast are more important than traditional point-to-point communication in computer network. This paper focuses on broadcasting in structured WSNs. In such a kind, the procedure of network communications is easier than in unstructured WSNs. Thus, it will make an overview of Multi Point Relay (MPR) to show its weakness. Then define a cluster-based architecture for WSNs which is constructed using MPR. Next, provide a new broadcast algorithm based on the previous cluster architecture called 3B (Backbone Based Broadcasting). By the end, an illustration of 3B shows that it minimizes the energy consumption for accomplishing broadcast compared to MPR.
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.
An Integrated Distributed Clustering Algorithm for Large Scale WSN...................................................1
S. R. Boselin Prabhu, S. Sophia, S. Arthi and K. Vetriselvi
An Efficient Connection between Statistical Software and Database Management System ................... 1
Sunghae Jun
Pragmatic Approach to Component Based Software Metrics Based on Static Methods ......................... 1
S. Sagayaraj and M. Poovizhi
SDI System with Scalable Filtering of XML Documents for Mobile Clients ............................................... 1
Yi Yi Myint and Hninn Aye Thant
An Easy yet Effective Method for Detecting Spatial Domain LSB Steganography .................................... 1
Minati Mishra and Flt. Lt. Dr. M. C. Adhikary
Minimizing the Time of Detection of Large (Probably) Prime Numbers ................................................... 1
Dragan Vidakovic, Dusko Parezanovic and Zoran Vucetic
Design of ATL Rules for TransformingUML 2 Sequence Diagrams into Petri Nets..................................... 1
Elkamel Merah, Nabil Messaoudi, Dalal Bardou and Allaoua Chaoui
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.
Security based Clock Synchronization technique in Wireless Sensor Network for...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Proactive Data Reporting of Wireless sensor Network using Wake Up Scheduling ...ijsrd.com
In Wireless Sensor Network (WSNs), gather the data by using mobile sinks has become popular. Reduce the number of messages which is used for sink location broadcasting, efficient energy data forwarding, become accustomed to unknown earthly changes are achieved by a protocol which is projected by a SinkTrail. The forecast of mobile sinks’ location are done by using logical coordinate system. When sensor nodes don’t have any data to send, at that time they switch to sleep mode to save the energy and to increase the network lifetime. And due to this reason there is a chance of the involvement of nodes that are in sleeping state between the path sources to the mobile sink which is selected by the SinkTrail protocol. Before become the fully functional and process the information, these sleeping nodes can drop the some information. Due to this reason, it is vital to wake-up the sleeping nodes on the path earlier than the sender can start transferring of sensed data. In this paper, on-demand wake-up scheduling algorithm is projected which is used to activates sleeping node on the path before data delivery. Here, in this work the multi-hop communication in WSN also considers. By incorporating wake-up scheduling algorithm to perk up the dependability and improve the performance of on-demand data forwarding extends the SinkTrail solution in our work. This projected algorithm improves the quality of service of the network by dishonesty of data or reducing the loss due to sleeping nodes. The efficiency and the effectiveness projected solution are proved by the evaluation results.
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.
AN IMPROVED DECENTRALIZED APPROACH FOR TRACKING MULTIPLE MOBILE TARGETS THROU...ijwmn
Target localization and tracking problems in WSNs have received considerable attention recently, driven
by the requirement to achieve high localization accuracy, with the minimum cost possible. In WSN based
tracking applications, it is critical to know the current location of any sensor node with the minimum
energy consumed. This paper focuses on the energy consumption issue in terms of communication
between nodes whenever the localization information is transmitted to a sink node. Tracking through
WSNs can be categorized into centralized and decentralized systems. Decentralized systems offer low
power consumption when deployed to track a small number of mobile targets compared to the centralized
tracking systems. However, in several applications, it is essential to position a large number of mobile
targets. In such applications, decentralized systems offer high power consumption, since the location of
each mobile target is required to be transmitted to a sink node, and this increases the power consumption
for the whole WSN. In this paper, we propose a power efficient decentralized approach for tracking a
large number of mobile targets while offering reasonable localization accuracy through ZigBee network
Unmanned aerial vehicles (UAVs) have become very popular recently for both civil uses and potential commercial uses, such as law enforcement, crop survey, grocery delivery, and photographing, although they were mainly used for military purposes before. Researchers need the help of simulations when they design and test new protocols for UAV networks because simulations can be done for a network of a size
that a test bed can hardly approach. In the simulation of an UAV network it is important to choose a radio propagation model for the links in the network. We study the shadowing radio propagation model in this paper and compare it with the free space model, both of which are available in the ns2 network simulation package. We also show how the choice of the parameters of the shadowing model would impact on the
network performance of a UAV network.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers reduces the energy consumption and increases the throughput of the wireless sensor networks.
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International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Extending network lifetime of wireless sensorIJCNCJournal
One critical issue in designing and managing a wireless sensor network is how to save the energy consumption
of the sensors in order to maximize network lifetime under the constraint of full coverage of the monitored
targets. In this paper, we adopt the common approach of creating disjoint sensor covers to prolong network
lifetime. The typical goal used in the literature is to maximize the number of covers without consideration of
the energy levels of the sensors. We argue that the network lifetime can be extended by maximizing the total
bottleneck energy of the created covers. We formally define the problem of maximizing the total bottleneck
energy of the covers, present for the first time an integer programming formulation of the problem, and develop
two algorithms to solve large problem instances. Extensive experimental tests show that the use of the goal of
maximizing the total bottleneck energy of the covers creates covers with substantially longer network lifetime
than the lifetime of the covers created with the goal of maximizing solely the number of covers.
AN EFFICIENT SLEEP SCHEDULING STRATEGY FOR WIRELESS SENSOR NETWORKijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
High-Energy-First (HEF) Heuristic for Energy-Efficient Target Coverage Problemijasuc
Target coverage problem in wireless sensor networks is concerned with maximizing the lifetime of the
network while continuously monitoring a set of targets. A sensor covers targets which are within the
sensing range. For a set of sensors and a set of targets, the sensor-target coverage relationship is
assumed to be known. A sensor cover is a set of sensors that covers all the targets. The target coverage
problem is to determine a set of sensor covers with maximum aggregated lifetime while constraining the
life of each sensor by its initial battery life. The problem is proved to be NP-complete and heuristic
algorithms to solve this problem are proposed. In the present study, we give a unified interpretation of
earlier algorithms and propose a new and efficient algorithm. We show that all known algorithms are
based on a common reasoning though they seem to be derived from different algorithmic paradigms. We
also show that though some algorithms guarantee bound on the quality of the solution, this bound is not
meaningful and not practical too. Our interpretation provides a better insight to the solution techniques.
We propose a new greedy heuristic which prioritizes sensors on residual battery life. We show
empirically that the proposed algorithm outperforms all other heuristics in terms of quality of solution.
Our experimental study over a large set of randomly generated problem instances also reveals that a very
naïve greedy approach yields solutions which is reasonably (appx. 10%) close to the actual optimal
solutions.
Scenarios of Lifetime Extension Algorithms for Wireless Ad Hoc NetworksIJCNCJournal
An Algorithm to extend sensor lifetime and energy is implemented for different scenarios of ad hoc and wireless sensor networks. The goal is to prolong the lifetimes of sensors, covering a number of targeted zones by creating subsets of sensors, in which each subset covers entirely the targeted zones. Probabilistic analysis is assumed in which each sensor covers one or more targets, according to their coverage failure probabilities. Case studies of different sensor subsets arrangements are considered such as load switching, variable target load demands as well as a perturbation in sensor planner locations.
Coverage and Connectivity Aware Neural Network Based Energy Efficient Routing...graphhoc
There are many challenges when designing and deploying wireless sensor networks (WSNs). One of the key challenges is how to make full use of the limited energy to prolong the lifetime of the network, because energy is a valuable resource in WSNs. The status of energy consumption should be continuously monitored after network deployment. In this paper, we propose coverage and connectivity aware neural network based energy efficient routing in WSN with the objective of maximizing the network lifetime. In the proposed scheme, the problem is formulated as linear programming (LP) with coverage and connectivity aware constraints. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage and connectivity aware routing with data transmission. The proposed scheme is compared with existing schemes with respect to the parameters such as number of alive nodes, packet delivery fraction, and node residual energy. The simulation results show that the proposed scheme can be used in wide area of applications in WSNs.
The popularity of Wireless Sensor Networks (WSN) have increased rapidly and tremendously due to the vast potential of the sensor networks to connect the physical world with the virtual world. Since sensor devices rely on battery power and node energy and may be placed in hostile environments, so replacing them becomes a difficult task. Thus, improving the energy of these networks i.e. network lifetime becomes important. The thesis provides methods for clustering and cluster head selection to WSN to improve energy efficiency using fuzzy logic controller. It presents a comparison between the different methods on the basis of the network lifetime. It compares existing ABC optimization method with BFO algorithm for different size of networks and different scenario. It provides cluster head selection method with good performance and reduced computational complexity. In addition it also proposes BFO as an algorithm for clustering of WSN which would result in improved performance with faster convergence.
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.
A NODE DEPLOYMENT MODEL WITH VARIABLE TRANSMISSION DISTANCE FOR WIRELESS SENS...ijwmn
The deployment of network nodes is essential to ensure the wireless sensor network's regular operation and affects the multiple network performance metrics, such as connectivity, coverage, lifetime, and cost. This paper focuses on the problem of minimizing network costs while meeting network requirements, and proposes a corona-based deployment method by using the variable transmission distance sensor. Based on the analysis of node energy consumption and network cost, an optimization model to minimize Cost Per Unit Area is given. The transmission distances and initial energy of the sensors are obtained by solving the model. The optimization model is improved to ensure the energy consumption balance of nodes in the same corona. Based on these parameters, the process of network node deployment is given. Deploying the
network through this method will greatly reduce network costs.
ADAPTIVE SENSOR SENSING RANGE TO MAXIMISE LIFETIME OF WIRELESS SENSOR NETWORK IJCNCJournal
Wireless Sensor Network (WSN) is commonly used to collect information from a remote area and one of the most important challenges associated with WSN is to monitor all targets in a given area while maximizing network lifetime. In wireless communication, energy consumption is proportional to the breadth of sensing range and path loss exponent. Hence, the energy consumption of communication can be minimized by varying the sensing range and decreasing the number of messages being sent. Sensing energy can be optimized by reducing the repeated coverage target. In this paper, an Adaptive Sensor Sensing Range (ASSR) technique is proposed to maximize the WSN Lifetime. This work considers a sensor network with an adaptive sensing range that are randomly deployed in the monitoring area. The sensor is adaptive in nature and can be modified in order to save power while achieving maximum time of monitoring to increase the lifetime of WSN network. The objective of ASSR is to find the best sensing range for each sensor to cover all targets in the network, which yields maximize the time of monitoring of all targets and eliminating double sensing for the same target. Experiments were conducted using an NS3 simulator to verify our proposed technique. Results show that ASSR is capable to improve the network lifetime by 20% as compared to other recent techniques in the case of a small network while achieving an 8% improvement for the case of a large networks.
Adaptive Sensor Sensing Range to Maximise Lifetime of Wireless Sensor NetworkIJCNCJournal
Wireless Sensor Network (WSN) is commonly used to collect information from a remote area and one of the most important challenges associated with WSN is to monitor all targets in a given area while maximizing network lifetime. In wireless communication, energy consumption is proportional to the breadth of sensing range and path loss exponent. Hence, the energy consumption of communication can be minimized by varying the sensing range and decreasing the number of messages being sent. Sensing energy can be optimized by reducing the repeated coverage target. In this paper, an Adaptive Sensor Sensing Range (ASSR) technique is proposed to maximize the WSN Lifetime. This work considers a sensor network with an adaptive sensing range that are randomly deployed in the monitoring area. The sensor is adaptive in nature and can be modified in order to save power while achieving maximum time of monitoring to increase the lifetime of WSN network. The objective of ASSR is to find the best sensing range for each sensor to cover all targets in the network, which yields maximize the time of monitoring of all targets and eliminating double sensing for the same target. Experiments were conducted using an NS3 simulator to verify our proposed technique. Results show that ASSR is capable to improve the network lifetime by 20% as compared to other recent techniques in the case of a small network while achieving an 8% improvement for the case of a large networks.
Node Deployment in Homogeneous and Heterogeneous Wireless Sensor NetworkIJMTST Journal
Optimal sensor deployment is necessary condition in homogeneous and heterogeneous wireless sensor
network. Effective deployment of sensor nodes is a major point of concern as performance and lifetime of any
WSN. Proposed sensor deployment in WSN explore every sensor node sends its data to the nearest sink node
of the WSN. In addition to that system proposes a hexagonal cell based sensor deployment which leads to
optimal sensor deployment for both homogeneous and heterogeneous sensor deployment. Wireless sensor
networks are receiving significant concentration due to their potential applications ranging from surveillance
to tracking domains. In limited communication range, a WSN is divided into several disconnected sub-graphs
under certain conditions. We deploy sensor nodes at random locations so that it improves performance of the
network.This paper aims to study, discuss and analyze various node deployment strategies and coverage
problems for Homogeneous and Heterogeneous WSN.
A Fault tolerant system based on Genetic Algorithm for Target Tracking in Wir...Editor IJCATR
In this paper, we explored the possibility of using Genetic Algorithm (GA) being used in Wireless Sensor Networks in general with
specific emphasize on Fault tolerance. In Wireless sensor networks, usually sensor and sink nodes are separated by long communication
distance and hence to optimize the energy, we are using clustering approach. Here we are employing improved K-means clustering algorithm to
form the cluster and GA to find optimal use of sensor nodes and recover from fault as quickly as possible so that target detection won’t be
disrupted. This technique is simulated using Matlab software to check energy consumption and lifetime of the network. Based on the
simulation results, we concluded that this model shows significant improvement in energy consumption rate and network lifetime than other
method such as Traditional clustering or Simulated Annealing
Congestion is said to occur in the network when the resource demands exceed the capacity and packets are lost due to too much queuing in the network. During congestion, the network throughput may drop to zero and the path delay may become very high. A congestion control scheme helps the network to recover from the congestion state. In fact, security plays a vital role in Wireless Ad hoc network. This paper presents a systematic literature review to provide comprehensive and unbiased information about various current model Congestion Control conceptions, proposals, problems and solutions in Ad hoc for safety transportation. For this purpose, a total of 33 articles related to the security model in Congestion Control published between 2008 and 2013 were extracted from the most relevant scientific sources (IEEE Computer Society, ACM Digital Library, Springer Link and Science Direct). However, 18 articles were eventually analyzed due to several reasons such as relevancy and comprehensiveness of discussion presented in the articles. Using the systematic method of review, this paper succeeds to reveal the main security threats and Error control, challenges for security, security requirement in Congestion Control in Wireless Ad hoc network (CCWAN) and future research within this scope.
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Major cyber events in 2024
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State of ICS and IoT Cyber Threat Landscape Report 2024 preview
C0361011014
1. International Journal of Computational Engineering Research||Vol, 03||Issue, 6||
www.ijceronline.com ||June ||2013|| Page 11
Local Maximum Lifetime Algorithms For Strong K-Barrier
Darshan R V1
, Manjunath C R2
, Nagaraj G S3
,
1
M.Tech, School of Engineering and Technology, JAIN University
2
Asst Prof, School of Engineering and Technology, JAIN University
3
Assoc Prof, RVCE, VTU
I. INTRODUCTION:
The main applications of wireless sensors involves movement detection, such as when deploying
sensors along international borders to become aware of illegal intrusion, around a chemical factory to identify
the spread of lethal chemicals, on both sides of a gas pipeline to detect potential damages, etc. barrier coverage,
which guarantees that every movement crossing a barrier of sensors will be detected, which is known to be an
appropriate model of coverage for such applications [1]. Chen et al. [2] devised a centralized algorithm to find
out whether a region is k-barrier covered, and resulting the critical conditions for weak barrier coverage in a
randomly deployment sensor network. But the centralized algorithm could acquire high communication
overhead and computation cost on large sensor networks, and conditions for strong barrier coverage remain an
open problem. Liu et al[3]., first discussed the strong barrier coverage problem. They map the strong barrier
coverage as a discrete bond percolation model and derive the conditions of having multiple disjoint sensor
barriers.
Figure 1: Weak coverage and Strong coverage.
In Figure 1, it illustrates [3] the difference between strong barrier coverage and weak barrier coverage.
In the top figure, the network has weak barrier coverage for all orthogonal crossing paths (dashed paths).
However, there is an uncovered path (solid path) through the region. The bottom figure shows an example of
strong barrier coverage where no intruders can cross the region undetected, no matter how they choose their
crossing paths. The barrier is highlighted using shaded sensing areas.
ABSTRACT
Barrier coverage of wireless sensor networks are been studied intensively in recent years
under the assumption that sensors are deployed uniformly at random in a large area. In this paper a
new network construction method of sensor nodes for Border Security Systems is proposed. This
Barrier coverage are known to be a appropriate model of coverage for sensor barriers to detect
intruders moving along restricted crossing paths, which is achieved by barriers of sensors. A Border
Security System watches intruders by using sensor nodes with communication function. The detection
of some intruders and the use of a long-term operation system are required in this system. This paper
suggests a new Divide-and-Conquer scheme. Based on it, a new local maximal lifetime algorithm can
be designed and following protocol for strong k- barrier with coordinated sensors. By computer
simulation, we try to show that the proposed barrier coverage network construction methods are
suitable for Border Security Systems and reduce the power consumption of the whole network system
by effective control of sensor nodes.
KEYWORDS: barrier coverage, data fusion, local algorithm, security, wireless sensor network;
2. Local Maximum Lifetime Algorithms…
www.ijceronline.com ||June ||2013|| Page 12
In [3], they proposed a critical condition for weak barrier coverage. But conditions for strong barrier coverage
remain an open problem. In [5-8], detection coverage models have been suggested based on different event
scenarios and detection techniques. In [8], Yang and Qiao first induced the detection coverage model into
barrier coverage and theoretically analyzed the constraints between data fusion algorithm and coverage regions.
By considering the above reasons, this paper talks about the setbacks of constructing strong k- barrier based on
detection coverage model. We consider neighboring sensors can cooperate in surveillance by data fusion.
In particular, our contributions are as follows:
First work is the problem of constructing strong k- barrier based on detection coverage model and data fusion.
Second to formalize a coordinated detection coverage model, where the data fusion rule is described by a
general function f(x).
Third is to analyze the influencing factors of barrier coverage lifetime, and transfer it to a multi-objective
optimization problem.
And fourth to introduce a new Divide-and-Conquer scheme to design a new local maximal lifetime algorithm.
II. EARLIER METHODOLOGY:
The local barrier coverage algorithms that been introduced in [1, 2, 3, 4, 5, 6, 8] have introduced the
centralized algorithms. One of algorithms for local barrier coverage, called RIS (Random independent sleeping
algorithm). This algorithm is based on a power saving method, in which the sensor nodes are scheduled and
switch between two modes, Active and Sleep. RIS provides weak barrier coverage with the high probability of
intrusion detection, in such a way that each sensor, in certain periods, selects Active or Sleep mode, with a
predetermined probability rate, P. The presented method will be based on the power saving method, used by
RIS. However, the modes considered in sensor nodes have been changed to Active and Passive modes. It must
be noticed that RIS does not guarantee the barrier coverage, deterministically. Initially global active scheduling
algorithms are not achievable in a large scale sensor network. Second, [1] proved that one sensor cannot locally
determines whether the surveillance field is k-barrier covered or not.
2.1.Traditional Activity of Scheduling Strategy
One traditional method is to start the nodes with highest left energy [1,2,3,4], which can avoid the
nodes with less left energy died too early and prolong the barrier coverage lifetime. Yet there usually exists the
situation that the horizontal projection of above-mentioned nodes is relative small, i.e. the count of active nodes
is not optimal. The other method is to activate the least nodes by greedy algorithms [8][9]. The nodes in suitable
location can been activated frequently and died untimely, which affect the sensor network connectivity, and
further shorten barrier coverage lifetime.
2.2. Proposed work:
The main problem to be solved includes providing a k-barrier graph which creates and describes k-
barrier coverage in a barrier area. As a result, all paths crossing through the barrier area are covered k-times, by
the network sensors. The proposed method consists:
2.3.Modeling Maximum Barrier Coverage Lifetime
An effective sensor activity scheduling should tradeoff the count of nodes in a cover set, their left
energy and consumed energy in one cycle. As a result, maximum of barrier coverage lifetime essentially is a
multi objective optimization problem. We can form the problem as three minimizing objectives and one
maximization objective, i.e. minimizing the count of active nodes ,minimizing the total energy used in one
cycle, minimizing the ratio of an active node’s consumed energy in one cycle and its left energy, the
maximizing minimum ratio of an active node’s left energy and its initialized energy. The n nodes only can
switch between active state and sleep state, and the active nodes whose count is less than n can make up not less
than k-disjoint barrier, n and k are constraints.
2.4.k-CLBCS Algorithm
In this paper, it suggests a global k-CLBCS algorithm for constructing Local k-Barrier with
Coordinated Sensors, the main idea of k-CLBCS algorithm is described as follows:
step1: Calculate every edge’s capacity, and construct the coverage graph G(N);
step2: Search k disjoint paths from s to t in the G(N);
step3: If the k disjoint paths are found, return the nodes ID that should be activated to form k-barrier, otherwise,
return constructing failure.
3. Local Maximum Lifetime Algorithms…
www.ijceronline.com ||June ||2013|| Page 13
2.5.k-SBCCS Protocol
Based on the overlapped divide-and-conquer scheme and k- CLBCS algorithm, we propose a practical
protocol. A sink and n sensors are assumed in the rectangle belt, at the beginning, all sensors are active. The
main idea of k-SBCCS Protocol (Protocol of Strong k-Barrier Coverage with Coordinated Sensors) is described
as follows:
step1: Sink divide the belt region into v equal-width sub-regions, and broadcast the value of (width of each sub
region),(width of overlapped strip)and v(equal width sub-regions).
step2: Every node calculates which sub-region it belongs to, judge if it is located in the overlapped strip, and
reports its information to the sensor which have highest energy.
step3:In each sub-region, the sensor who has the highest energy runs k- CLBCS algorithm .If k disjoint barriers
are found, it activates these sensors, otherwise, it reports the failure information to sink.
step4: The activated sensor who has the highest energy in every overlapped strip checks if the overlapped strip
is strong k-barrier covered or not. If it found the overlapped strip not strong k-barrier covered, some other nodes
will be activated to form strong k-barrier coverage in the overlapped strips. If all live sensors in the overlapped
strip can’t form strong k-barrier, the above sensor reports the failure information to sink.
step5: Repeat step3 and step4 until all sensors die.
III. RESULTS:
The advantage of this divide-and-conquer over centralized approach is:
Lower communication overhead and computation costs. By dividing the large network area into small
segments, the message delay, communication overhead, and computation cost can be significantly reduced.
The location and sensing area information of a sensor node only need to be broadcast within the strip
segment (or within the thin vertical strip) where the node is located, resulting in a smaller delay and
communication overhead compared to the whole network broadcasting.
Improved robustness of the barrier coverage. In a centralized approach which constructs global
horizontal barriers for the whole strip, a horizontal sensor barrier could be broken if some nodes on the
barrier fail, or become compromised or displaced by adversaries. In our divide-and-conquer approach, the
original strip is divided into segments by interleaving vertical barriers. In case of node failure, these vertical
barriers act as firewalls" that prevent intruders from moving from its current segment to adjacent segments.
This limits the barrier damages within the local segment and hence improving the robustness of the barrier
coverage .improving the robustness of the barrier coverage.
Strengthened local barrier coverage. By dividing the original strip into small segments and computing
barriers in each segment, a larger number of local horizontal barriers will be found in each segment than for
the whole strip. These local barriers are not necessarily part of the global barriers for the whole strip, whose
number remains unchanged. Since adjacent segments are blocked by interleaving vertical barriers, a larger
number of local barriers results in strengthened local barrier coverage for each segment.
IV. CONCLUSION
In this paper, we introduce a k-barrier coverage protocol, called k-SBCCS, for prolonging the network
lifetime. The proposed protocol tries to prolong the network lifetime by establishing a balance in using nodes
energies. The proposed protocol maximum lifetime scheduling for strong k- barrier coverage based on detection
coverage model, which is more appropriate for intrusion detection scenarios. we transfer maximal barrier
coverage lifetime to a multi objective optimization problem, and model the evaluation function as the capacity
of coverage graph.Moreover, based on the enhanced coverage graph, we propose k- CLBCS algorithm of
maximum network lifetime. Theoretical proof shows that the activated nodes by in every overlapped strip can
form k-barrier. At last, we design a new Divide-and-Conquer scheme and k- SBCCS protocol for strong k-
barrier with coordinated sensors.
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