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SBGC
             Final Year Projects
           SOFTWAREPROJECTS
        JAVA | DOTNET | NS-2 |
       Matlab | Power Electronics
 www.ieee2011projects.sbgc.in
    www.ieeeproject.in
             contact@sbgc.in, sathish@sbgc.in


SBGC                                     4th FLOOR SURYA
24/83, O Block, MMDA                             COMPLEX,
COLONY                                 SINGARATHOPE BUS
ARUMBAKKAM                                          STOP,
CHENNAI-106                           OLD MADURAI ROAD,
09944361169                                TRICHY- 620002
                                             0431-4012303
                                              09003012150
SBGC Provides IEEE 2011 Projects For all Final Year Students. We do assist the students with Technical

Guidance for both the categories.

Category 1 : Students with new project ideas.

Category 2 : Students selecting from our list.

When you register for a project we ensure that the project is implemented to your

fullest satisfaction

and you have a thorough understanding of every aspect of the project.


SBGC PROVIDES YOU THE LATEST IEEE 2011 PROJECTS/ IEEE 2012 PROJECTS FOR FOLLOWING
DEPARTMENT STUDENTS


B.E, B.TECH, M.TECH, M.E, DIPLOMA, MS, BSC, MSC, BCA, MCA, MBA, BBA, PHD,

NS-2, GLOMOSIM, MATLAB, JAVA, .NET,

B.E (ECE, EEE, E&I, ICE, MECH, PROD, CSE, IT, THERMAL, AUTOMOBILE,

MECATRONICS, ROBOTICS)

B.TECH(ECE, MECATRONICS, E&I, EEE, MECH , CSE, IT, ROBOTICS)

M.TECH(EMBEDDED SYSTEMS, COMMUNICATION SYSTEMS, POWER ELECTRONICS,

COMPUTER SCIENCE,

SOFTWARE ENGINEERING, APPLIED ELECTRONICS, VLSI Design)

M.E(EMBEDDED SYSTEMS, COMMUNICATION SYSTEMS, POWER ELECTRONICS,

COMPUTER SCIENCE, SOFTWARE

ENGINEERING, APPLIED ELECTRONICS, VLSI Design)

MBA(HR, FINANCE, MANAGEMENT, HOTEL MANAGEMENT, SYSTEM
MANAGEMENT, PROJECT MANAGEMENT,

HOSPITAL MANAGEMENT, SCHOOL MANAGEMENT, MARKETING MANAGEMENT,

SAFETY MANAGEMENT)

DIPLOMA (CE, EEE, E&I, ICE, MECH,PROD, CSE, IT)


We also have training and project, R & D division to serve the students and make them job oriented
professionals


IEEE 2011 NS-2 PROJECTS


Loss Performance Modeling for Hierarchical Heterogeneous Wireless Networks With Speed-Sensitive
Call Admission Control


A hierarchical overlay structure is an alternative solution that integrates existing and future
heterogeneous wireless networks to provide subscribers with better mobile broadband services. Traffic
loss performance in such integrated heterogeneous networks is necessary for an operator's network
dimensioning and planning. This paper investigates the computationally efficient loss performance
modeling for multiservice in hierarchical heterogeneous wireless networks. A speed-sensitive call
admission control (CAC) scheme is considered in our model to assign overflowed calls to appropriate
tiers. This approach avoids unnecessary and frequent handoff between cells and reduces signaling
overheads. An approximation model with guaranteed accuracy and low computational complexity is
presented for the loss performance of multiservice traffic. The accuracy of numerical results is validated
by comparing the results from the approximation with simulations


Communication Cost Minimization in Wireless Sensor and Actor Networks for Road Surveillance


wireless sensor and actor networks (WSANs) have been extensively deployed to monitor physical
environment and facilitate decision making based on data collected. Emerging applications such as road
surveillance highlight some interesting research issues in WSANs, including coordination problems in
sensor-actor or actor-actor communications. In this paper, the issue of choosing a set of working actors
for coordinating data transmission in a road sensor and actor network with minimum communication
cost is studied. A theoretical model is introduced to analyze the communication cost of data
transmission in WSANs, and the sensor-actor coordination problem is formulated as an optimization
problem. It is demonstrated that the problem can be divided into subproblems, and optimal solutions
can be obtained by using a dynamic programming algorithm. A novel graph-based algorithm is also
proposed with a communication-cost graph used to depict the cost of data transmission and a modified
Dijkstra’s algorithm to find optimal solutions in reduced time complexity. The efficiency of the proposed
algorithms is confirmed using extensive simulations.


Distributed Sensing in Multi-band Cognitive Networks


We consider a short range cognitive network searching for spectrum holes from very wide bandwidth. In
practice, one cognitive user can sense only a small portion of spectrum. Unfortunately, in fading
environment a reliable detection scheme requires measurements collected by multiple users. Because
of that, it is unreasonable to expect a small-sized network to sense the complete candidate bandwidth.
In this paper we propose an algorithm for optimal sensing of multiple spectrum bands by multiple
cognitive users. The user allocation is optimized so that the expected opportunistic throughput is
maximized and the total power spent for spectrum measurements is controlled. As a constraint we use
the detection performance requirements imposed by the primary systems. For a small number of
spectrum bands the optimal solution can be found by exhaustive search. For a large number of spectrum
bands we view the spectrum sensing as a multiple choice knapsack problem. By using algorithms for this
class of problems we propose two heuristics that are suitable for optimizing spectrum sensing in
multiband cognitive networks. These algorithms provide quick, near optimal solutions and are therefore
suitable for practical spectrum sensing systems.


Improving the Performance of Wireless Ad Hoc Networks Through MAC Layer Design


the performance of the ALOHA and CSMA MAC protocols are analyzed in spatially distributed wireless
networks. The main system objective is correct reception of packets, and thus the analysis is performed
in terms of outage probability. In our network model, packets belonging to specific transmitters arrive
randomly in space and time according to a 3-D Poisson point process, and are then transmitted to their
intended destinations using a fully-distributed MAC protocol. A packet transmission is considered
successful if the received SINR is above a predefined threshold for the duration of the packet. Accurate
bounds on the outage probabilities are derived as a function of the transmitter density, the number of
backoffs and retransmissions, and in the case of CSMA, also the sensing threshold. The analytical
expressions are validated with simulation results. For continuous-time transmissions, CSMA with
receiver sensing (which involves adding a feedback channel to the conventional CSMA protocol) is
shown to yield the best performance. Moreover, the sensing threshold of CSMA is optimized. It is shown
that introducing sensing for lower densities (i.e., in sparse networks) is not beneficial, while for higher
densities (i.e., in dense networks), using an optimized sensing threshold provides significant gain


Optimal Selective Forwarding for Energy Saving in Wireless Sensor Networks


Scenarios where nodes have limited energy and forward messages of different importances (priorities)
are frequent in the context of wireless sensor networks. Tailored to those scenarios, this paper relies on
stochastic tools to develop selective message forwarding schemes. The schemes will depend on
parameters such as the available battery at the node, the energy cost of retransmitting a message, or
the importance of messages. The forwarding schemes are designed for three different cases: 1) when
sensors maximize the importance of their own transmitted messages; 2) when sensors maximize the
importance of messages that have been successfully retransmitted by at least one of its neighbors; and
3) when sensors maximize the importance of messages that successfully arrive to the sink. More
sophisticated schemes will achieve better importance performance, but will also require information
from other sensors. The results contribute to identify the variables that, when made available to other
nodes, have a greater impact on the overall network performance. Suboptimal schemes that rely on
local estimation algorithms and entail reduced computational cost are also designed.


Transient Analysis of IEEE 802.15.4 Sensor Networks


We study the delay performance of a sensor network, whose nodes access the medium by using the
unslotted MAC protocol specified by the IEEE 802.15.4 standard. Unlike previous works, which focus on
the average throughput and delay analysis, we develop a detailed model that allows us to obtain the
delivery delay distribution of messages sent by concurrently contending sensors toward a central
controller. We carry out a transient analysis that is of particular interest when sensor networks are
deployed to provide k-coverage for real-time applications, and we study both single- and multi-hop
network topologies. We validate our analytical results against simulation results obtained through ns2.


Fast Detection of Mobile Replica Node Attacks in Wireless Sensor Networks Using Sequential
Hypothesis Testing


Due to the unattended nature of wireless sensor networks, an adversary can capture and compromise
sensor nodes, generate their replicas, and thus mount a variety of attacks with these replicas. Such
attacks are dangerous because they allow the attacker to leverage the compromise of a few nodes to
exert control over much of the network. Several replica node detection schemes have been proposed in
the literature to defend against such attacks in static sensor networks. However, these schemes rely on
fixed sensor locations and hence do not work in mobile sensor networks, where sensors are expected to
move. In this work, we propose a fast and effective mobile replica node detection scheme using the
Sequential Probability Ratio Test. To the best of our knowledge, this is the first work to tackle the
problem of replica node attacks in mobile sensor networks. We show analytically and through
simulation experiments that our scheme provides effective and robust replica detection capability with
reasonable overheads.


Fault Localization Using Passive End-to-End Measurements and Sequential Testing for Wireless Sensor
Networks


Faulty components in a network need to be localized and repaired to sustain the health of the network.
In this paper, we propose a novel approach that carefully combines active and passive measurements to
localize faults in wireless sensor networks. More specifically, we formulate a problem of optimal
sequential testing guided by end-to-end data. This problem determines an optimal testing sequence of
network components based on end-to-end data in sensor networks to minimize testing cost. We prove
that this problem is NP-hard and propose a greedy algorithm to solve it. Extensive simulation shows that
in most settings our algorithm only requires testing a very small set of network components to localize
and repair all faults in the network. Our approach is superior to using active and passive measurements
in isolation. It also outperforms the state-of-theart approaches that localize and repair all faults in a
network.
Fast Data Collection in Tree-Based Wireless Sensor Networks


We investigate the following fundamental question - how fast can information be collected from a
wireless sensor network organized as tree? To address this, we explore and evaluate a number of
techniques using realistic simulation models under the many-to-one communication paradigm known as
convergecast. We first consider time scheduling on a single frequency channel with the aim of
minimizing the number of time slots required (schedule length) to complete a convergecast. Next, we
combine scheduling with transmission power control to mitigate the effects of interference, and show
that while power control helps in reducing the schedule length, scheduling transmissions using multiple
frequencies is more efficient. We give lower bounds on the schedule length when interference is
completely eliminated, and propose algorithms that achieve these bounds. We also evaluate the
performance of various channel assignment methods and find empirically that for moderate size
networks of about 100 nodes, multi-frequency scheduling can suffice to eliminate most of the
interference. Then, the data collection rate no longer remains limited by interference but by the
topology of the routing tree. To this end, we construct degree-constrained spanning trees and
capacitated minimal spanning trees, and show significant improvement in scheduling performance over
different deployment densities


On Reliable Broadcast in Low Duty-Cycle Wireless Sensor Networks


Broadcast is one of the most fundamental services in wireless sensor networks, where a distinct feature
is that sensor nodes may alternate between active and dormant states, so as to conserve energy and
extend the network lifetime. Unfortunately, the impact of such cycles has been largely ignored in
existing broadcast implementations that adopt the common assumption of all nodes being active all
over the time. In this paper, we revisit the broadcast problem with active/dormant cycles. We show
strong evidence that conventional broadcast approaches will suffer from severe performance
degradation, and, under low duty-cycles, they could easily fail to cover the whole network in an
acceptable timeframe. We remodel the broadcast problem in this new context, seeking a balance
between efficiency and latency with coverage guarantees. We demonstrate that this problem can be
translated into a graph equivalence, and develop a centralized optimal solution. We then extend it to an
efficient and scalable distributed implementation. The performance of our solution is evaluated under
diverse network configurations. The results suggest that our distributed solution is close to the lower
bounds of both time and forwarding costs, and it well resists to the wireless loss with good scalability on
the network size and density.


Efficient Data Collection in Wireless Sensor Networks with Path-Constrained Mobile Sinks


Recent work shows that sink mobility along a constrained path can improve the energy efficiency in
wireless sensor networks. However, due to the path constraint, a mobile sink with constant speed has
limited communication time to collect data from the sensor nodes deployed randomly. This poses
significant challenges in simultaneously improving the amount of data collected and reduction in energy
consumption. To address this issue, we propose a novel data collection scheme, called the maximum
amount shortest path (MASP), that increases network throughput as well as conserves energy to
optimize the assignment of sensor nodes. MASP is formulated as an integer linear programming
problem and then solved with the help of a genetic algorithm. A two-phase communication protocol is
designed to implement the MASP scheme. Simulations experiments using OMNET++ show that MASP
outperforms the shortest path tree (SPT) and static sink methods in terms of system throughput and
energy efficiency.


Computing Localized Power-Efficient Data Aggregation Trees for Sensor Networks


We propose localized, self organizing, robust, and energy-efficient data aggregation tree approaches for
sensor networks,which we call Localized Power-Efficient Data Aggregation Protocols (L-PEDAPs). They
are based on topologies, such as LMST and RNG,that can approximate minimum spanning tree and can
be efficiently computed using only position or distance information of one-hopneighbors. The actual
routing tree is constructed over these topologies. We also consider different parent selection strategies
whileconstructing a routing tree. We compare each topology and parent selection strategy and conclude
that the best among them is theshortest path strategy over LMSTstructure. Our solution also involves
route maintenance procedures that will be executed when a sensor node fails or a new node is added to
the network. The proposed solution is also adapted to consider the remaining power levels of nodes
inorder to increase the network lifetime. Our simulation results show that by using our power-aware
localized approach, we can almost have the same performance of a centralized solution in terms of
network lifetime, and close to 90 percent of an upper bound derived here.
A Privacy-Preserving Location Monitoring System for Wireless Sensor Networks


Monitoring personal locations with a potentially untrusted server poses privacy threats to the
monitored individuals. To this end, we propose a privacy-preserving location monitoring system for
wireless sensor networks. In our system, we design two in-network location anonymization algorithms,
namely, resource and quality-aware algorithms, that aim to enable the system to provide high-quality
location monitoring services for system users, while preserving personal location privacy. Both
algorithms rely on the well-established k-anonymity privacy concept, that is, a person is
indistinguishable among k persons, to enable trusted sensor nodes to provide the aggregate location
information of monitored persons for our system. Each aggregate location is in a form of a monitored
area A along with the number of monitored persons residing in A, where A contains at least k persons.
The resource-aware algorithm aims to minimize communication and computational cost, while the
quality-aware algorithm aims to maximize the accuracy of the aggregate locations by minimizing their
monitored areas. To utilize the aggregate location information to provide location monitoring services,
we use a spatial histogram approach that estimates the distribution of the monitored persons based on
the gathered aggregate location information. Then, the estimated distribution is used to provide
location monitoring services through answering range queries. We evaluate our system through
simulated experiments. The results show that our system provides high-quality location monitoring
services for system users and guarantees the location privacy of the monitored persons.
HEAD OFFICE
SBGC
4th FLOOR SURYA COMPLEX,
SINGARATHOPE BUS STOP,
OLD MADURAI ROAD,
TRICHY- 620002
Phone No: 0431-4012303
Mobile:+919003012150.

BRANCH OFFICE
SBGC
24/83 , "O" Block,
MMDA Colony, Arumbakkam,
Chennai - 600 106.
Land Mark : Near By MMDA Market
Mail Id: contact@sbgc.in
Mobile:+919944361169

BRANCH OFFICE
SBGC ( Near To Dindigul , Near To Madurai )

AVT COMPLEX NATHAM

09003012150

sathish@sbgc.in, contact@sbgc.in

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Ieee projects 2011 ns 2 SBGC ( Trichy, Madurai, Chennai, Dindigul, Natham, Pudukkottai )

  • 1. SBGC Final Year Projects SOFTWAREPROJECTS JAVA | DOTNET | NS-2 | Matlab | Power Electronics www.ieee2011projects.sbgc.in www.ieeeproject.in contact@sbgc.in, sathish@sbgc.in SBGC 4th FLOOR SURYA 24/83, O Block, MMDA COMPLEX, COLONY SINGARATHOPE BUS ARUMBAKKAM STOP, CHENNAI-106 OLD MADURAI ROAD, 09944361169 TRICHY- 620002 0431-4012303 09003012150
  • 2. SBGC Provides IEEE 2011 Projects For all Final Year Students. We do assist the students with Technical Guidance for both the categories. Category 1 : Students with new project ideas. Category 2 : Students selecting from our list. When you register for a project we ensure that the project is implemented to your fullest satisfaction and you have a thorough understanding of every aspect of the project. SBGC PROVIDES YOU THE LATEST IEEE 2011 PROJECTS/ IEEE 2012 PROJECTS FOR FOLLOWING DEPARTMENT STUDENTS B.E, B.TECH, M.TECH, M.E, DIPLOMA, MS, BSC, MSC, BCA, MCA, MBA, BBA, PHD, NS-2, GLOMOSIM, MATLAB, JAVA, .NET, B.E (ECE, EEE, E&I, ICE, MECH, PROD, CSE, IT, THERMAL, AUTOMOBILE, MECATRONICS, ROBOTICS) B.TECH(ECE, MECATRONICS, E&I, EEE, MECH , CSE, IT, ROBOTICS) M.TECH(EMBEDDED SYSTEMS, COMMUNICATION SYSTEMS, POWER ELECTRONICS, COMPUTER SCIENCE, SOFTWARE ENGINEERING, APPLIED ELECTRONICS, VLSI Design) M.E(EMBEDDED SYSTEMS, COMMUNICATION SYSTEMS, POWER ELECTRONICS, COMPUTER SCIENCE, SOFTWARE ENGINEERING, APPLIED ELECTRONICS, VLSI Design) MBA(HR, FINANCE, MANAGEMENT, HOTEL MANAGEMENT, SYSTEM
  • 3. MANAGEMENT, PROJECT MANAGEMENT, HOSPITAL MANAGEMENT, SCHOOL MANAGEMENT, MARKETING MANAGEMENT, SAFETY MANAGEMENT) DIPLOMA (CE, EEE, E&I, ICE, MECH,PROD, CSE, IT) We also have training and project, R & D division to serve the students and make them job oriented professionals IEEE 2011 NS-2 PROJECTS Loss Performance Modeling for Hierarchical Heterogeneous Wireless Networks With Speed-Sensitive Call Admission Control A hierarchical overlay structure is an alternative solution that integrates existing and future heterogeneous wireless networks to provide subscribers with better mobile broadband services. Traffic loss performance in such integrated heterogeneous networks is necessary for an operator's network dimensioning and planning. This paper investigates the computationally efficient loss performance modeling for multiservice in hierarchical heterogeneous wireless networks. A speed-sensitive call admission control (CAC) scheme is considered in our model to assign overflowed calls to appropriate tiers. This approach avoids unnecessary and frequent handoff between cells and reduces signaling overheads. An approximation model with guaranteed accuracy and low computational complexity is presented for the loss performance of multiservice traffic. The accuracy of numerical results is validated by comparing the results from the approximation with simulations Communication Cost Minimization in Wireless Sensor and Actor Networks for Road Surveillance wireless sensor and actor networks (WSANs) have been extensively deployed to monitor physical environment and facilitate decision making based on data collected. Emerging applications such as road surveillance highlight some interesting research issues in WSANs, including coordination problems in
  • 4. sensor-actor or actor-actor communications. In this paper, the issue of choosing a set of working actors for coordinating data transmission in a road sensor and actor network with minimum communication cost is studied. A theoretical model is introduced to analyze the communication cost of data transmission in WSANs, and the sensor-actor coordination problem is formulated as an optimization problem. It is demonstrated that the problem can be divided into subproblems, and optimal solutions can be obtained by using a dynamic programming algorithm. A novel graph-based algorithm is also proposed with a communication-cost graph used to depict the cost of data transmission and a modified Dijkstra’s algorithm to find optimal solutions in reduced time complexity. The efficiency of the proposed algorithms is confirmed using extensive simulations. Distributed Sensing in Multi-band Cognitive Networks We consider a short range cognitive network searching for spectrum holes from very wide bandwidth. In practice, one cognitive user can sense only a small portion of spectrum. Unfortunately, in fading environment a reliable detection scheme requires measurements collected by multiple users. Because of that, it is unreasonable to expect a small-sized network to sense the complete candidate bandwidth. In this paper we propose an algorithm for optimal sensing of multiple spectrum bands by multiple cognitive users. The user allocation is optimized so that the expected opportunistic throughput is maximized and the total power spent for spectrum measurements is controlled. As a constraint we use the detection performance requirements imposed by the primary systems. For a small number of spectrum bands the optimal solution can be found by exhaustive search. For a large number of spectrum bands we view the spectrum sensing as a multiple choice knapsack problem. By using algorithms for this class of problems we propose two heuristics that are suitable for optimizing spectrum sensing in multiband cognitive networks. These algorithms provide quick, near optimal solutions and are therefore suitable for practical spectrum sensing systems. Improving the Performance of Wireless Ad Hoc Networks Through MAC Layer Design the performance of the ALOHA and CSMA MAC protocols are analyzed in spatially distributed wireless networks. The main system objective is correct reception of packets, and thus the analysis is performed in terms of outage probability. In our network model, packets belonging to specific transmitters arrive randomly in space and time according to a 3-D Poisson point process, and are then transmitted to their
  • 5. intended destinations using a fully-distributed MAC protocol. A packet transmission is considered successful if the received SINR is above a predefined threshold for the duration of the packet. Accurate bounds on the outage probabilities are derived as a function of the transmitter density, the number of backoffs and retransmissions, and in the case of CSMA, also the sensing threshold. The analytical expressions are validated with simulation results. For continuous-time transmissions, CSMA with receiver sensing (which involves adding a feedback channel to the conventional CSMA protocol) is shown to yield the best performance. Moreover, the sensing threshold of CSMA is optimized. It is shown that introducing sensing for lower densities (i.e., in sparse networks) is not beneficial, while for higher densities (i.e., in dense networks), using an optimized sensing threshold provides significant gain Optimal Selective Forwarding for Energy Saving in Wireless Sensor Networks Scenarios where nodes have limited energy and forward messages of different importances (priorities) are frequent in the context of wireless sensor networks. Tailored to those scenarios, this paper relies on stochastic tools to develop selective message forwarding schemes. The schemes will depend on parameters such as the available battery at the node, the energy cost of retransmitting a message, or the importance of messages. The forwarding schemes are designed for three different cases: 1) when sensors maximize the importance of their own transmitted messages; 2) when sensors maximize the importance of messages that have been successfully retransmitted by at least one of its neighbors; and 3) when sensors maximize the importance of messages that successfully arrive to the sink. More sophisticated schemes will achieve better importance performance, but will also require information from other sensors. The results contribute to identify the variables that, when made available to other nodes, have a greater impact on the overall network performance. Suboptimal schemes that rely on local estimation algorithms and entail reduced computational cost are also designed. Transient Analysis of IEEE 802.15.4 Sensor Networks We study the delay performance of a sensor network, whose nodes access the medium by using the unslotted MAC protocol specified by the IEEE 802.15.4 standard. Unlike previous works, which focus on the average throughput and delay analysis, we develop a detailed model that allows us to obtain the delivery delay distribution of messages sent by concurrently contending sensors toward a central controller. We carry out a transient analysis that is of particular interest when sensor networks are
  • 6. deployed to provide k-coverage for real-time applications, and we study both single- and multi-hop network topologies. We validate our analytical results against simulation results obtained through ns2. Fast Detection of Mobile Replica Node Attacks in Wireless Sensor Networks Using Sequential Hypothesis Testing Due to the unattended nature of wireless sensor networks, an adversary can capture and compromise sensor nodes, generate their replicas, and thus mount a variety of attacks with these replicas. Such attacks are dangerous because they allow the attacker to leverage the compromise of a few nodes to exert control over much of the network. Several replica node detection schemes have been proposed in the literature to defend against such attacks in static sensor networks. However, these schemes rely on fixed sensor locations and hence do not work in mobile sensor networks, where sensors are expected to move. In this work, we propose a fast and effective mobile replica node detection scheme using the Sequential Probability Ratio Test. To the best of our knowledge, this is the first work to tackle the problem of replica node attacks in mobile sensor networks. We show analytically and through simulation experiments that our scheme provides effective and robust replica detection capability with reasonable overheads. Fault Localization Using Passive End-to-End Measurements and Sequential Testing for Wireless Sensor Networks Faulty components in a network need to be localized and repaired to sustain the health of the network. In this paper, we propose a novel approach that carefully combines active and passive measurements to localize faults in wireless sensor networks. More specifically, we formulate a problem of optimal sequential testing guided by end-to-end data. This problem determines an optimal testing sequence of network components based on end-to-end data in sensor networks to minimize testing cost. We prove that this problem is NP-hard and propose a greedy algorithm to solve it. Extensive simulation shows that in most settings our algorithm only requires testing a very small set of network components to localize and repair all faults in the network. Our approach is superior to using active and passive measurements in isolation. It also outperforms the state-of-theart approaches that localize and repair all faults in a network.
  • 7. Fast Data Collection in Tree-Based Wireless Sensor Networks We investigate the following fundamental question - how fast can information be collected from a wireless sensor network organized as tree? To address this, we explore and evaluate a number of techniques using realistic simulation models under the many-to-one communication paradigm known as convergecast. We first consider time scheduling on a single frequency channel with the aim of minimizing the number of time slots required (schedule length) to complete a convergecast. Next, we combine scheduling with transmission power control to mitigate the effects of interference, and show that while power control helps in reducing the schedule length, scheduling transmissions using multiple frequencies is more efficient. We give lower bounds on the schedule length when interference is completely eliminated, and propose algorithms that achieve these bounds. We also evaluate the performance of various channel assignment methods and find empirically that for moderate size networks of about 100 nodes, multi-frequency scheduling can suffice to eliminate most of the interference. Then, the data collection rate no longer remains limited by interference but by the topology of the routing tree. To this end, we construct degree-constrained spanning trees and capacitated minimal spanning trees, and show significant improvement in scheduling performance over different deployment densities On Reliable Broadcast in Low Duty-Cycle Wireless Sensor Networks Broadcast is one of the most fundamental services in wireless sensor networks, where a distinct feature is that sensor nodes may alternate between active and dormant states, so as to conserve energy and extend the network lifetime. Unfortunately, the impact of such cycles has been largely ignored in existing broadcast implementations that adopt the common assumption of all nodes being active all over the time. In this paper, we revisit the broadcast problem with active/dormant cycles. We show strong evidence that conventional broadcast approaches will suffer from severe performance degradation, and, under low duty-cycles, they could easily fail to cover the whole network in an acceptable timeframe. We remodel the broadcast problem in this new context, seeking a balance between efficiency and latency with coverage guarantees. We demonstrate that this problem can be translated into a graph equivalence, and develop a centralized optimal solution. We then extend it to an efficient and scalable distributed implementation. The performance of our solution is evaluated under diverse network configurations. The results suggest that our distributed solution is close to the lower
  • 8. bounds of both time and forwarding costs, and it well resists to the wireless loss with good scalability on the network size and density. Efficient Data Collection in Wireless Sensor Networks with Path-Constrained Mobile Sinks Recent work shows that sink mobility along a constrained path can improve the energy efficiency in wireless sensor networks. However, due to the path constraint, a mobile sink with constant speed has limited communication time to collect data from the sensor nodes deployed randomly. This poses significant challenges in simultaneously improving the amount of data collected and reduction in energy consumption. To address this issue, we propose a novel data collection scheme, called the maximum amount shortest path (MASP), that increases network throughput as well as conserves energy to optimize the assignment of sensor nodes. MASP is formulated as an integer linear programming problem and then solved with the help of a genetic algorithm. A two-phase communication protocol is designed to implement the MASP scheme. Simulations experiments using OMNET++ show that MASP outperforms the shortest path tree (SPT) and static sink methods in terms of system throughput and energy efficiency. Computing Localized Power-Efficient Data Aggregation Trees for Sensor Networks We propose localized, self organizing, robust, and energy-efficient data aggregation tree approaches for sensor networks,which we call Localized Power-Efficient Data Aggregation Protocols (L-PEDAPs). They are based on topologies, such as LMST and RNG,that can approximate minimum spanning tree and can be efficiently computed using only position or distance information of one-hopneighbors. The actual routing tree is constructed over these topologies. We also consider different parent selection strategies whileconstructing a routing tree. We compare each topology and parent selection strategy and conclude that the best among them is theshortest path strategy over LMSTstructure. Our solution also involves route maintenance procedures that will be executed when a sensor node fails or a new node is added to the network. The proposed solution is also adapted to consider the remaining power levels of nodes inorder to increase the network lifetime. Our simulation results show that by using our power-aware localized approach, we can almost have the same performance of a centralized solution in terms of network lifetime, and close to 90 percent of an upper bound derived here.
  • 9. A Privacy-Preserving Location Monitoring System for Wireless Sensor Networks Monitoring personal locations with a potentially untrusted server poses privacy threats to the monitored individuals. To this end, we propose a privacy-preserving location monitoring system for wireless sensor networks. In our system, we design two in-network location anonymization algorithms, namely, resource and quality-aware algorithms, that aim to enable the system to provide high-quality location monitoring services for system users, while preserving personal location privacy. Both algorithms rely on the well-established k-anonymity privacy concept, that is, a person is indistinguishable among k persons, to enable trusted sensor nodes to provide the aggregate location information of monitored persons for our system. Each aggregate location is in a form of a monitored area A along with the number of monitored persons residing in A, where A contains at least k persons. The resource-aware algorithm aims to minimize communication and computational cost, while the quality-aware algorithm aims to maximize the accuracy of the aggregate locations by minimizing their monitored areas. To utilize the aggregate location information to provide location monitoring services, we use a spatial histogram approach that estimates the distribution of the monitored persons based on the gathered aggregate location information. Then, the estimated distribution is used to provide location monitoring services through answering range queries. We evaluate our system through simulated experiments. The results show that our system provides high-quality location monitoring services for system users and guarantees the location privacy of the monitored persons.
  • 10. HEAD OFFICE SBGC 4th FLOOR SURYA COMPLEX, SINGARATHOPE BUS STOP, OLD MADURAI ROAD, TRICHY- 620002 Phone No: 0431-4012303 Mobile:+919003012150. BRANCH OFFICE SBGC 24/83 , "O" Block, MMDA Colony, Arumbakkam, Chennai - 600 106. Land Mark : Near By MMDA Market Mail Id: contact@sbgc.in Mobile:+919944361169 BRANCH OFFICE SBGC ( Near To Dindigul , Near To Madurai ) AVT COMPLEX NATHAM 09003012150 sathish@sbgc.in, contact@sbgc.in