The document analyzes the probability of k-connectivity in wireless ad hoc networks under different mobility models. It compares the Random Waypoint, City Section, and Manhattan mobility models. Simulations show that the Random Waypoint model yields the highest probability of k-connectivity for most node densities and velocities. The probability of k-connectivity decreases as k increases and increases as node density increases, for all three models.
Mobility models for delay tolerant network a surveyijwmn
Delay Tolerant Network (DTN) is an emerging networking technology that is widely used in the
environment where end-to-end paths do not exist. DTN follows store-carry-forward mechanism to route
data. This mechanism exploits the mobility of nodes and hence the performances of DTN routing and
application protocols are highly dependent on the underlying mobility of nodes and its characteristics.
Therefore, suitable mobility models are required to be incorporated in the simulation tools to evaluate DTN
protocols across many scenarios. In DTN mobility modelling literature, a number of mobility models have
been developed based on synthetic theory and real world mobility traces. Furthermore, many researchers
have developed specific application oriented mobility models. All these models do not provide accurate
evaluation in the all scenarios. Therefore, model selection is an important issue in DTN protocol
simulation. In this study, we have summarized various widely used mobility models and made a comparison
of their performances. Finally, we have concluded with future research directions in mobility modelling for
DTN simulation.
A new clustering technique based on replication for MANET routing protocolsTELKOMNIKA JOURNAL
The cluster head nodes in most mobile ad hoc networks (MANET) clustering protocols take on an extraordinary role in managing routing information. The reliability, efficiency and scalability of the clustering in MANET will ultimately be dramatically impacted. In this work we establish a new approach to form the clusters in MANET called the square cluster-based routing protocol (SCBRP). That protocol is based on the theory of replication. The goal of the protocol is to achieve reliability, availability and scalability with in the MANET. The proposed protocol is evaluated by caring the performance analysis using the NS-3 simulator. The performance shows 50% improvementin data delivering ratio in large network size, also shows an improvement in network stability and availability which is reflected in energy consumption measurements and increase in the system lifetime to 20%.
PERFORMANCE STUDY AND SIMULATION OF AN ANYCAST PROTOCOL FOR WIRELESS MOBILE A...ijwmn
This paper conducts a detailed simulation study of stateless anycast routing in a mobile wireless ad hoc
network. The model covers all the fundamental aspects of such networks with a routing mechanism using
a scheme of orientation-dependent inter-node communication links. The simulation system Winsim is used
which explicitly represents parallelism of events and processes in the network. The purpose of these
simulations is to investigate the effect of node’s maximum speed, and different TTL over the network
performance under two different scenarios. Simulation study investigates five practically important
performance metrics of a wireless mobile ad hoc network and shows the dependence of this metrics on
the transmission radius, link availability, and maximal possible node speed
Route Stability in Mobile Ad-Hoc Networksarpublication
A Mobile Ad Hoc Network (MANET) is a wireless network consisting of mobile nodes, which can communicate with each other without any infrastructure support. In these networks, nodes typically cooperate with each other, by forwarding packets for nodes which are not in the communication range of the source node. A fundamental issue arising in mobile ad-hoc networks (MANETs) is the selection of the optimal path between any two nodes. A method that has been advocated to improve routing efficiency is to select the most stable path so as to reduce the latency and the overhead due to route reconstruction. In this work we study the stability of a routing path, which is subject to link failures caused by node mobility, and we consider as metrics of interest the duration and the availability of a path. Moreover, using the results on path duration and availability, we show how to determine the optimal path in terms of route stability, under the Random Direction mobility models.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
In ad hoc networks, routing plays a pertinent role. Deploying the appropriate routing protocol is very important in order to achieve best routing performance and reliability. Equally important is the mobility model that is used in the routing protocol. Various mobility models are available and each can have different impact on the performance of the routing protocol. In this paper, we focus on this issue by examining how the routing protocol, Optimized Link State Routing protocol, behaves as the mobility model is varied. For this, three random mobility models, viz., random waypoint, random walk and random direction are considered. The performance metrics used for assessment of Optimized Link State Routing protocol are Optimized Link State Routing protocol, end-to-end delay and packet delivery ratio.
A Proposal Analytical Model and Simulation of the Attacks in Routing Protocol...graphhoc
In this work we have devoted to some proposed analytical methods to simulate these attacks, and node mobility in MANET. The model used to simulate the malicious nodes mobility attacks is based on graphical theory, which is a tool for analyzing the behavior of nodes. The model used to simulate the Blackhole cooperative, Blackmail, Bandwidth Saturation and Overflow attacks is based on malicious nodes and the number of hops. We conducted a simulation of the attacks with a C implementation of the proposed mathematical models.
Dynamic K-Means Algorithm for Optimized Routing in Mobile Ad Hoc Networks IJCSES Journal
In this paper, a dynamic K-means algorithm to improve the routing process in Mobile Ad-Hoc networks
(MANETs) is presented. Mobile ad-hoc networks are a collocation of mobile wireless nodes that can
operate without using focal access points, pre-existing infrastructures, or a centralized management point.
In MANETs, the quick motion of nodes modifies the topology of network. This feature of MANETS is lead
to various problems in the routing process such as increase of the overhead massages and inefficient
routing between nodes of network. A large variety of clustering methods have been developed for
establishing an efficient routing process in MANETs. Routing is one of the crucial topics which are having
significant impact on MANETs performance. The K-means algorithm is one of the effective clustering
methods aimed to reduce routing difficulties related to bandwidth, throughput and power consumption.
This paper proposed a new K-means clustering algorithm to find out optimal path from source node to
destinations node in MANETs. The main goal of proposed approach which is called the dynamic K-means
clustering methods is to solve the limitation of basic K-means method like permanent cluster head and fixed
cluster members. The experimental results demonstrate that using dynamic K-means scheme enhance the
performance of routing process in Mobile ad-hoc networks.
Mobility models for delay tolerant network a surveyijwmn
Delay Tolerant Network (DTN) is an emerging networking technology that is widely used in the
environment where end-to-end paths do not exist. DTN follows store-carry-forward mechanism to route
data. This mechanism exploits the mobility of nodes and hence the performances of DTN routing and
application protocols are highly dependent on the underlying mobility of nodes and its characteristics.
Therefore, suitable mobility models are required to be incorporated in the simulation tools to evaluate DTN
protocols across many scenarios. In DTN mobility modelling literature, a number of mobility models have
been developed based on synthetic theory and real world mobility traces. Furthermore, many researchers
have developed specific application oriented mobility models. All these models do not provide accurate
evaluation in the all scenarios. Therefore, model selection is an important issue in DTN protocol
simulation. In this study, we have summarized various widely used mobility models and made a comparison
of their performances. Finally, we have concluded with future research directions in mobility modelling for
DTN simulation.
A new clustering technique based on replication for MANET routing protocolsTELKOMNIKA JOURNAL
The cluster head nodes in most mobile ad hoc networks (MANET) clustering protocols take on an extraordinary role in managing routing information. The reliability, efficiency and scalability of the clustering in MANET will ultimately be dramatically impacted. In this work we establish a new approach to form the clusters in MANET called the square cluster-based routing protocol (SCBRP). That protocol is based on the theory of replication. The goal of the protocol is to achieve reliability, availability and scalability with in the MANET. The proposed protocol is evaluated by caring the performance analysis using the NS-3 simulator. The performance shows 50% improvementin data delivering ratio in large network size, also shows an improvement in network stability and availability which is reflected in energy consumption measurements and increase in the system lifetime to 20%.
PERFORMANCE STUDY AND SIMULATION OF AN ANYCAST PROTOCOL FOR WIRELESS MOBILE A...ijwmn
This paper conducts a detailed simulation study of stateless anycast routing in a mobile wireless ad hoc
network. The model covers all the fundamental aspects of such networks with a routing mechanism using
a scheme of orientation-dependent inter-node communication links. The simulation system Winsim is used
which explicitly represents parallelism of events and processes in the network. The purpose of these
simulations is to investigate the effect of node’s maximum speed, and different TTL over the network
performance under two different scenarios. Simulation study investigates five practically important
performance metrics of a wireless mobile ad hoc network and shows the dependence of this metrics on
the transmission radius, link availability, and maximal possible node speed
Route Stability in Mobile Ad-Hoc Networksarpublication
A Mobile Ad Hoc Network (MANET) is a wireless network consisting of mobile nodes, which can communicate with each other without any infrastructure support. In these networks, nodes typically cooperate with each other, by forwarding packets for nodes which are not in the communication range of the source node. A fundamental issue arising in mobile ad-hoc networks (MANETs) is the selection of the optimal path between any two nodes. A method that has been advocated to improve routing efficiency is to select the most stable path so as to reduce the latency and the overhead due to route reconstruction. In this work we study the stability of a routing path, which is subject to link failures caused by node mobility, and we consider as metrics of interest the duration and the availability of a path. Moreover, using the results on path duration and availability, we show how to determine the optimal path in terms of route stability, under the Random Direction mobility models.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
In ad hoc networks, routing plays a pertinent role. Deploying the appropriate routing protocol is very important in order to achieve best routing performance and reliability. Equally important is the mobility model that is used in the routing protocol. Various mobility models are available and each can have different impact on the performance of the routing protocol. In this paper, we focus on this issue by examining how the routing protocol, Optimized Link State Routing protocol, behaves as the mobility model is varied. For this, three random mobility models, viz., random waypoint, random walk and random direction are considered. The performance metrics used for assessment of Optimized Link State Routing protocol are Optimized Link State Routing protocol, end-to-end delay and packet delivery ratio.
A Proposal Analytical Model and Simulation of the Attacks in Routing Protocol...graphhoc
In this work we have devoted to some proposed analytical methods to simulate these attacks, and node mobility in MANET. The model used to simulate the malicious nodes mobility attacks is based on graphical theory, which is a tool for analyzing the behavior of nodes. The model used to simulate the Blackhole cooperative, Blackmail, Bandwidth Saturation and Overflow attacks is based on malicious nodes and the number of hops. We conducted a simulation of the attacks with a C implementation of the proposed mathematical models.
Dynamic K-Means Algorithm for Optimized Routing in Mobile Ad Hoc Networks IJCSES Journal
In this paper, a dynamic K-means algorithm to improve the routing process in Mobile Ad-Hoc networks
(MANETs) is presented. Mobile ad-hoc networks are a collocation of mobile wireless nodes that can
operate without using focal access points, pre-existing infrastructures, or a centralized management point.
In MANETs, the quick motion of nodes modifies the topology of network. This feature of MANETS is lead
to various problems in the routing process such as increase of the overhead massages and inefficient
routing between nodes of network. A large variety of clustering methods have been developed for
establishing an efficient routing process in MANETs. Routing is one of the crucial topics which are having
significant impact on MANETs performance. The K-means algorithm is one of the effective clustering
methods aimed to reduce routing difficulties related to bandwidth, throughput and power consumption.
This paper proposed a new K-means clustering algorithm to find out optimal path from source node to
destinations node in MANETs. The main goal of proposed approach which is called the dynamic K-means
clustering methods is to solve the limitation of basic K-means method like permanent cluster head and fixed
cluster members. The experimental results demonstrate that using dynamic K-means scheme enhance the
performance of routing process in Mobile ad-hoc networks.
Data collection scheme for wireless sensor network with mobile collectorijwmn
In this paper, we investigate the problem of designing the minimum number of required mobile elements
tours such that each sensor node is either on the tour or one hop away from the tour, and the length of the
tour to be bounded by pre-determined value L. To address this problem, we propose heuristic-based
solution. This solution works by directing the mobile element tour towards the highly dense area in the
network. The experiment results show that our scheme outperform the benchmark scheme by 10% in most
scenarios.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Effect of mobility models on the performance of multipath routing protocol in...csandit
In this paper, we have analyzed the performance of multipath routing protocol with various mobility
models for Mobile Ad Hoc Networks. The basic purpose of any multipath routing protocol
is to overcome various problems occurs while data delivery through a single path routing protocol.
For high acceptability of routing protocol, analysis of routing protocol in ad hoc network
only with random way point mobility model is not sufficient. Here, we have considered Random
waypoint, Random Direction and Probabilistic Random Walk mobility Model for proper analysis
of AOMDV routing protocol. Results obtained show that with increasing node density, packet
delivery ratio increases but with increasing node mobility Packet delivery ratio decreases.
Routing in Wireless Mesh Networks: Two Soft Computing Based Approachesijmnct
Due to dynamic network conditions, routing is the most critical part in WMNs and needs to be optimised.
The routing strategies developed for WMNs must be efficient to make it an operationally self configurable
network. Thus we need to resort to near shortest path evaluation. This lays down the requirement of some
soft computing approaches such that a near shortest path is available in an affordable computing time. This
paper proposes a Fuzzy Logic based integrated cost measure in terms of delay, throughput and jitter.
Based upon this distance (cost) between two adjacent nodes we evaluate minimal shortest path that updates
routing tables. We apply two recent soft computing approaches namely Big Bang Big Crunch (BB-BC) and
Biogeography Based Optimization (BBO) approaches to enumerate shortest or near short paths. BB-BC
theory is related with the evolution of the universe whereas BBO is inspired by dynamical equilibrium in
the number of species on an island. Both the algorithms have low computational time and high convergence
speed. Simulation results show that the proposed routing algorithms find the optimal shortest path taking
into account three most important parameters of network dynamics. It has been further observed that for
the shortest path problem BB-BC outperforms BBO in terms of speed and percent error between the
evaluated minimal path and the actual shortest path.
A Transmission Range Based Clustering Algorithm for Topology Control Manetgraphhoc
This paper presents a novel algorithm for clustering of nodes by transmission range based clustering (TRBC).This algorithm does topology management by the usage of coverage area of each node and power management based on mean transmission power within the context of wireless ad-hoc networks. By reducing the transmission range of the nodes, energy consumed by each node is decreased and topology is formed. A new algorithm is formulated that helps in reducing the system power consumption and prolonging the battery life of mobile nodes. Formation of cluster and selection of optimal cluster head and thus forming the optimal cluster taking weighted metrics like battery life, distance, position and mobility is done based on the factors such as node density, coverage area, contention index, required and current node degree of the nodes in the clusters
Effect of node mobility onaomdv protocol in manetijwmn
In this paper, we have analyzed the effect of node mobility on theperformance of AOMDV multipath routing
protocol. This routing protocol in ad hoc network has been analyzed with random way point mobility model
only. This is not sufficient to evaluate the behavior of a routing protocol. Therefore, in this paper, we
have considered Random waypoint, Random Direction and Probabilistic Random Walk mobility Model for
performance analysis of AOMDV protocol. The result reveals that packet delivery ratio decreases with the
increasing node mobility forall mobility models. Also, average end-to-end delay is also vary with varying
node speed, initially upto 20 nodes in all mobility models delay is minimum.
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.
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...IEEEGLOBALSOFTTECHNOLOGIES
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Path constrained data gathering scheme for wireless sensor networks with mobi...ijwmn
Wireless Sensor Networks (WSNs) have emerged as a promising solution for variety of applications.
Recently, in order to increase the lifetime of the network, many proposals have introduced the use of
Mobile Elements (MEs) as a mechanical carrier to collect data. In this paper, we investigate the problem of
designing the mobile element tour to visit subset of the nodes, termed as caching points, where the length of
the mobile element tour is bounded by pre-determined length. Caching can be implemented at various
points on the network such that any node in the network is at most k-hops away from one of these caching
points. To address this problem, we present heuristic-based solution. Our solution works by partitioning
the network such that the depth of each partition is bounded by k. Then, in each partition, the minimum
number of required caching points is identified. We compare the resulting performance of our algorithm
with the best known comparable schemes in the literature.
Performance Comparison and Analysis of Mobile Ad Hoc Routing ProtocolsCSEIJJournal
A mobile ad hoc network (MANET) is a wireless network that uses multi-hop peer-to-peer routing instead
of static network infrastructure to provide network connectivity. MANETs have applications in rapidly
deployed and dynamic military and civilian systems. The network topology in a MANET usually changes
with time. Therefore, there are new challenges for routing protocols in MANETs since traditional routing
protocols may not be suitable for MANETs. Researchers are designing new MANET routing protocols
and comparing and improving existing MANET routing protocols before any routing protocols are
standardized using simulations. However, the simulation results from different research groups are not
consistent with each other. This is because of a lack of consistency in MANET routing protocol models
and application environments, including networking and user traffic profiles. Therefore, the simulation
scenarios are not equitable for all protocols and conclusions cannot be generalized. Furthermore, it is
difficult for one to choose a proper routing protocol for a given MANET application. According to the
aforementioned issues, this paper focuses on MANET routing protocols. Specifically, my contribution
includes the characterization of different routing protocols and compare and analyze the performance of
different routing protocols.
SHADOWING EFFECTS ON ROUTING PROTOCOL OF MULTIHOP AD HOC NETWORKSijasuc
Two-ray ground reflection model has been widely used as the propagation model to investigate the
performance of an ad hoc network. But two-ray model is too simple to represent a real world network. A
more realistic model namely shadowing propagation model has been used in this investigation. Under
shadowing propagation model, a mobile node may receive a packet at a signal level that is below a
required threshold level. This low signal level affects the routing protocol as well as the medium access
control protocol of a network. An analytical model has been presented in this paper to investigate the
shadowing effects on the network performance. The analytical model has been verified via simulation
results. Simulation results show that the performance of a network becomes very poor if shadowing
propagation model is used in compare to the simple two-ray model. Two solutions have also been proposed
in this paper to overcome the effects of shadowing. One solution is a physical layer solution and the other
one is a Medium Access Control (MAC) layer solution. Simulation results show that these two solutions
reduce the shadowing effect and improve network performance.
SHADOWING EFFECTS ON ROUTING PROTOCOL OF MULTIHOP AD HOC NETWORKSijasuc
Two-ray ground reflection model has been widely used as the propagation model to investigate the
performance of an ad hoc network. But two-ray model is too simple to represent a real world network. A
more realistic model namely shadowing propagation model has been used in this investigation. Under
shadowing propagation model, a mobile node may receive a packet at a signal level that is below a
required threshold level. This low signal level affects the routing protocol as well as the medium access
control protocol of a network. An analytical model has been presented in this paper to investigate the
shadowing effects on the network performance. The analytical model has been verified via simulation
results. Simulation results show that the performance of a network becomes very poor if shadowing
propagation model is used in compare to the simple two-ray model. Two solutions have also been proposed
in this paper to overcome the effects of shadowing. One solution is a physical layer solution and the other
one is a Medium Access Control (MAC) layer solution. Simulation results show that these two solutions
reduce the shadowing effect and improve network performance.
SHADOWING EFFECTS ON ROUTING PROTOCOL OF MULTIHOP AD HOC NETWORKSijasuc
Two-ray ground reflection model has been widely used as the propagation model to investigate the
performance of an ad hoc network. But two-ray model is too simple to represent a real world network. A
more realistic model namely shadowing propagation model has been used in this investigation. Under
shadowing propagation model, a mobile node may receive a packet at a signal level that is below a
required threshold level. This low signal level affects the routing protocol as well as the medium access
control protocol of a network. An analytical model has been presented in this paper to investigate the
shadowing effects on the network performance. The analytical model has been verified via simulation
results. Simulation results show that the performance of a network becomes very poor if shadowing
propagation model is used in compare to the simple two-ray model. Two solutions have also been proposed
in this paper to overcome the effects of shadowing. One solution is a physical layer solution and the other
one is a Medium Access Control (MAC) layer solution. Simulation results show that these two solutions
reduce the shadowing effect and improve network performance.
Advancement in VANET Routing by Optimize the Centrality with ANT Colony Approachijceronline
In a wireless ad hoc network, an opportunistic routing strategy is a strategy where there is no predefined rule for choosing the next node to destination (as it is the case in conventional schemes such as OLSR, DSR or even Geo-Routing). A popular example of opportunistic routing is the “delay tolerant” forwarding to VANET network when a direct path to destination does not exist. Conventional routing in this case would just “drop” the packet. With opportunistic routing, a node acts upon the available information, In this thesis optimize the routing by centrality information then refine by ant colony metaheuristics. In this method validate our approach on different parameter like overhead, throughput.
Data collection scheme for wireless sensor network with mobile collectorijwmn
In this paper, we investigate the problem of designing the minimum number of required mobile elements
tours such that each sensor node is either on the tour or one hop away from the tour, and the length of the
tour to be bounded by pre-determined value L. To address this problem, we propose heuristic-based
solution. This solution works by directing the mobile element tour towards the highly dense area in the
network. The experiment results show that our scheme outperform the benchmark scheme by 10% in most
scenarios.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Effect of mobility models on the performance of multipath routing protocol in...csandit
In this paper, we have analyzed the performance of multipath routing protocol with various mobility
models for Mobile Ad Hoc Networks. The basic purpose of any multipath routing protocol
is to overcome various problems occurs while data delivery through a single path routing protocol.
For high acceptability of routing protocol, analysis of routing protocol in ad hoc network
only with random way point mobility model is not sufficient. Here, we have considered Random
waypoint, Random Direction and Probabilistic Random Walk mobility Model for proper analysis
of AOMDV routing protocol. Results obtained show that with increasing node density, packet
delivery ratio increases but with increasing node mobility Packet delivery ratio decreases.
Routing in Wireless Mesh Networks: Two Soft Computing Based Approachesijmnct
Due to dynamic network conditions, routing is the most critical part in WMNs and needs to be optimised.
The routing strategies developed for WMNs must be efficient to make it an operationally self configurable
network. Thus we need to resort to near shortest path evaluation. This lays down the requirement of some
soft computing approaches such that a near shortest path is available in an affordable computing time. This
paper proposes a Fuzzy Logic based integrated cost measure in terms of delay, throughput and jitter.
Based upon this distance (cost) between two adjacent nodes we evaluate minimal shortest path that updates
routing tables. We apply two recent soft computing approaches namely Big Bang Big Crunch (BB-BC) and
Biogeography Based Optimization (BBO) approaches to enumerate shortest or near short paths. BB-BC
theory is related with the evolution of the universe whereas BBO is inspired by dynamical equilibrium in
the number of species on an island. Both the algorithms have low computational time and high convergence
speed. Simulation results show that the proposed routing algorithms find the optimal shortest path taking
into account three most important parameters of network dynamics. It has been further observed that for
the shortest path problem BB-BC outperforms BBO in terms of speed and percent error between the
evaluated minimal path and the actual shortest path.
A Transmission Range Based Clustering Algorithm for Topology Control Manetgraphhoc
This paper presents a novel algorithm for clustering of nodes by transmission range based clustering (TRBC).This algorithm does topology management by the usage of coverage area of each node and power management based on mean transmission power within the context of wireless ad-hoc networks. By reducing the transmission range of the nodes, energy consumed by each node is decreased and topology is formed. A new algorithm is formulated that helps in reducing the system power consumption and prolonging the battery life of mobile nodes. Formation of cluster and selection of optimal cluster head and thus forming the optimal cluster taking weighted metrics like battery life, distance, position and mobility is done based on the factors such as node density, coverage area, contention index, required and current node degree of the nodes in the clusters
Effect of node mobility onaomdv protocol in manetijwmn
In this paper, we have analyzed the effect of node mobility on theperformance of AOMDV multipath routing
protocol. This routing protocol in ad hoc network has been analyzed with random way point mobility model
only. This is not sufficient to evaluate the behavior of a routing protocol. Therefore, in this paper, we
have considered Random waypoint, Random Direction and Probabilistic Random Walk mobility Model for
performance analysis of AOMDV protocol. The result reveals that packet delivery ratio decreases with the
increasing node mobility forall mobility models. Also, average end-to-end delay is also vary with varying
node speed, initially upto 20 nodes in all mobility models delay is minimum.
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.
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...IEEEGLOBALSOFTTECHNOLOGIES
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Path constrained data gathering scheme for wireless sensor networks with mobi...ijwmn
Wireless Sensor Networks (WSNs) have emerged as a promising solution for variety of applications.
Recently, in order to increase the lifetime of the network, many proposals have introduced the use of
Mobile Elements (MEs) as a mechanical carrier to collect data. In this paper, we investigate the problem of
designing the mobile element tour to visit subset of the nodes, termed as caching points, where the length of
the mobile element tour is bounded by pre-determined length. Caching can be implemented at various
points on the network such that any node in the network is at most k-hops away from one of these caching
points. To address this problem, we present heuristic-based solution. Our solution works by partitioning
the network such that the depth of each partition is bounded by k. Then, in each partition, the minimum
number of required caching points is identified. We compare the resulting performance of our algorithm
with the best known comparable schemes in the literature.
Performance Comparison and Analysis of Mobile Ad Hoc Routing ProtocolsCSEIJJournal
A mobile ad hoc network (MANET) is a wireless network that uses multi-hop peer-to-peer routing instead
of static network infrastructure to provide network connectivity. MANETs have applications in rapidly
deployed and dynamic military and civilian systems. The network topology in a MANET usually changes
with time. Therefore, there are new challenges for routing protocols in MANETs since traditional routing
protocols may not be suitable for MANETs. Researchers are designing new MANET routing protocols
and comparing and improving existing MANET routing protocols before any routing protocols are
standardized using simulations. However, the simulation results from different research groups are not
consistent with each other. This is because of a lack of consistency in MANET routing protocol models
and application environments, including networking and user traffic profiles. Therefore, the simulation
scenarios are not equitable for all protocols and conclusions cannot be generalized. Furthermore, it is
difficult for one to choose a proper routing protocol for a given MANET application. According to the
aforementioned issues, this paper focuses on MANET routing protocols. Specifically, my contribution
includes the characterization of different routing protocols and compare and analyze the performance of
different routing protocols.
SHADOWING EFFECTS ON ROUTING PROTOCOL OF MULTIHOP AD HOC NETWORKSijasuc
Two-ray ground reflection model has been widely used as the propagation model to investigate the
performance of an ad hoc network. But two-ray model is too simple to represent a real world network. A
more realistic model namely shadowing propagation model has been used in this investigation. Under
shadowing propagation model, a mobile node may receive a packet at a signal level that is below a
required threshold level. This low signal level affects the routing protocol as well as the medium access
control protocol of a network. An analytical model has been presented in this paper to investigate the
shadowing effects on the network performance. The analytical model has been verified via simulation
results. Simulation results show that the performance of a network becomes very poor if shadowing
propagation model is used in compare to the simple two-ray model. Two solutions have also been proposed
in this paper to overcome the effects of shadowing. One solution is a physical layer solution and the other
one is a Medium Access Control (MAC) layer solution. Simulation results show that these two solutions
reduce the shadowing effect and improve network performance.
SHADOWING EFFECTS ON ROUTING PROTOCOL OF MULTIHOP AD HOC NETWORKSijasuc
Two-ray ground reflection model has been widely used as the propagation model to investigate the
performance of an ad hoc network. But two-ray model is too simple to represent a real world network. A
more realistic model namely shadowing propagation model has been used in this investigation. Under
shadowing propagation model, a mobile node may receive a packet at a signal level that is below a
required threshold level. This low signal level affects the routing protocol as well as the medium access
control protocol of a network. An analytical model has been presented in this paper to investigate the
shadowing effects on the network performance. The analytical model has been verified via simulation
results. Simulation results show that the performance of a network becomes very poor if shadowing
propagation model is used in compare to the simple two-ray model. Two solutions have also been proposed
in this paper to overcome the effects of shadowing. One solution is a physical layer solution and the other
one is a Medium Access Control (MAC) layer solution. Simulation results show that these two solutions
reduce the shadowing effect and improve network performance.
SHADOWING EFFECTS ON ROUTING PROTOCOL OF MULTIHOP AD HOC NETWORKSijasuc
Two-ray ground reflection model has been widely used as the propagation model to investigate the
performance of an ad hoc network. But two-ray model is too simple to represent a real world network. A
more realistic model namely shadowing propagation model has been used in this investigation. Under
shadowing propagation model, a mobile node may receive a packet at a signal level that is below a
required threshold level. This low signal level affects the routing protocol as well as the medium access
control protocol of a network. An analytical model has been presented in this paper to investigate the
shadowing effects on the network performance. The analytical model has been verified via simulation
results. Simulation results show that the performance of a network becomes very poor if shadowing
propagation model is used in compare to the simple two-ray model. Two solutions have also been proposed
in this paper to overcome the effects of shadowing. One solution is a physical layer solution and the other
one is a Medium Access Control (MAC) layer solution. Simulation results show that these two solutions
reduce the shadowing effect and improve network performance.
Advancement in VANET Routing by Optimize the Centrality with ANT Colony Approachijceronline
In a wireless ad hoc network, an opportunistic routing strategy is a strategy where there is no predefined rule for choosing the next node to destination (as it is the case in conventional schemes such as OLSR, DSR or even Geo-Routing). A popular example of opportunistic routing is the “delay tolerant” forwarding to VANET network when a direct path to destination does not exist. Conventional routing in this case would just “drop” the packet. With opportunistic routing, a node acts upon the available information, In this thesis optimize the routing by centrality information then refine by ant colony metaheuristics. In this method validate our approach on different parameter like overhead, throughput.
QOS ROUTING AND PERFORMANCE EVALUATION FOR MOBILE AD HOC NETWORKS USING OLSR ...ijasuc
Mobile Ad-Hoc network is a collection of mobile nodes in communication without using infrastructure.
As the real-time applications used in today’s wireless network grow, we need some schemes to provide
more suitable service for them. We know that most of actual schemes do not perform well on traffic which
is not strictly CBR. Therefore, in this paper we have studied the impact, respectively, of mobility models
and the density of nodes on the performances (End-to-End Delay, Throughput and Packet Delivery ratio)
of routing protocol (Optimized Link State Routing) OLSR by using in the first a real-time VBR (MPEG-4)
and secondly the Constant Bit Rate (CBR) traffic. Finally we compare the performance on both cases.
Experimentally, we considered the three mobility models as follows Random Waypoint, Random
Direction and Mobgen Steady State. The experimental results illustrate that the behavior of OLSR change
according to the model and the used traffics.
In ad hoc networks, routing plays a pertinent role. Deploying the appropriate routing protocol is very important in order to achieve best routing performance and reliability. Equally important is the mobility model that is used in the routing protocol. Various mobility models are available and each can have different impact on the performance of the routing protocol. In this paper, we focus on this issue by examining how the routing protocol, Optimized Link State Routing protocol, behaves as the mobility model is varied. For this, three random mobility models, viz., random waypoint, random walk and random direction are considered. The performance metrics used for assessment of Optimized Link State Routing protocol are throughput, end-to-end delay and packet delivery ratio.
Ant Colony Optimization Based Energy Efficient on-Demand Multipath Routing Sc...ijsrd.com
Reliable transmission has become one of the major aspects of a wireless sensor network. The current paper provides an Ant Colony Optimization based method for providing multi path routes. These routes are provided on-demand, hence they can be used in any dynamic system. The advantage of this system is that it can provide near optimal results within the stipulated time.
AN EFFICIENT APPROACH FOR FOUR-LAYER CHANNEL ROUTING IN VLSI DESIGNVLSICS Design
Channel routing is a key problem in VLSI physical design. The main goal of the channel routing problem is to reduce the area of an IC chip. If we concentrate on reducing track number in channel routing problem then automatically the area of an IC chip will be reduced. Here, we propose a new algorithm to reduce the number of tracks using four layers (two horizontal layers and two vertical layers). To be more specific, through this algorithm we convert a two-layer channel routing problem into a four-layer channel routing problem using VCG of the channel. Next, we show the experimental results and graphical structure of that solution.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...IEEEGLOBALSOFTTECHNOLOGIES
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
JPD1428 Multicast Capacity in MANET with Infrastructure Supportchennaijp
We have best 2014 free dot not projects topics are available along with all document, you can easy to find out number of documents for various projects titles.
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/dot-net-projects/
Present new mechanisms for modelling multiple interfaces on a node, support for interference-limited links and a frame-work for modelling complex applications running on the nodes. Furthermore, provide an overview of concrete use cases where the simulator has been successfully exploited to study a variety of aspects related to opportunistic, message-based communications. Node movement is implemented by movement models. These are either synthetic models or existing movement traces. Connectivity between the nodes is based on their location, communication range and the bit-rate. The routing function is implemented by routing modules that decide which messages to forward over existing contacts. Finally, the messages themselves are generated either through event generators that generate random traffic between the nodes, or through applications that generate traffic based on application interactions. The main functions of the simulator are the modelling of node movement, inter-node contacts using various interfaces, routing, message handling and application interactions. Result collection and analysis are done through visualization, reports and post-processing tools.
JPN1404 Optimal Multicast Capacity and Delay Tradeoffs in MANETschennaijp
Get the latest IEEE ns2 projects in JP INFOTECH; we are having following category wise projects like Industrial Informatics, Vehicular Technology, Networking, WSN and Manet.
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/ns2-projects/
The Impact of Data Replication on Job Scheduling Performance in Hierarchical ...graphhoc
In data-intensive applications data transfer is a primary cause of job execution delay. Data access time depends on bandwidth. The major bottleneck to supporting fast data access in Grids is the high latencies of Wide Area Networks and Internet. Effective scheduling can reduce the amount of data transferred across the internet by dispatching a job to where the needed data are present. Another solution is to use a data replication mechanism. Objective of dynamic replica strategies is reducing file access time which leads to reducing job runtime. In this paper we develop a job scheduling policy and a dynamic data replication strategy, called HRS (Hierarchical Replication Strategy), to improve the data access efficiencies. We study our approach and evaluate it through simulation. The results show that our algorithm has improved 12% over the current strategies
DISTANCE TWO LABELING FOR MULTI-STOREY GRAPHSgraphhoc
An L (2, 1)-labeling of a graph G (also called distance two labeling) is a function f from the vertex set V (G) to the non negative integers {0,1,…, k }such that |f(x)-f(y)| ≥2 if d(x, y) =1 and | f(x)- f(y)| ≥1 if d(x, y) =2. The L (2, 1)-labeling number λ (G) or span of G is the smallest k such that there is a f with
max {f (v) : vє V(G)}= k. In this paper we introduce a new type of graph called multi-storey graph. The distance two labeling of multi-storey of path, cycle, Star graph, Grid, Planar graph with maximal edges and its span value is determined. Further maximum upper bound span value for Multi-storey of simple
graph are discussed.
Impact of Mobility for Qos Based Secure Manet graphhoc
Secure multicast communication in Mobile Adhoc Networks (MANETs) is challenging due to its inherent characteristics of infrastructure-less architecture with lack of central authority, limited resources such as bandwidth, energy and power. Several group oriented applications over MANETs create new challenges to routing protocols in terms of QOS requirements. In many multicast interactions, due to its frequent node mobility, new member can join and current members can leave at a time. It is necessary to choose a routing protocol which establishes true connectivity between the mobile nodes. The pattern of movement of members is classified into different mobility models and each one has its own distinct features. It is a crucial part in the performance of MANET. Hence key management is the fundamental challenge in achieving secure communication using multicast key distribution for mobile adhoc networks. This paper describes the impact of mobility models for the performance of a new cluster-based multicast tree algorithm with destination sequenced distance vector routing protocol in terms of QOS requirements such as end to end delay, energy consumption and key delivery ratio. For simulation purposes, three mobility models are considered. Simulation results illustrate the performance of routing protocol with different mobility models and different mobility speed under varying network conditions.
A Battery Power Scheduling Policy with Hardware Support In Mobile Devices graphhoc
A major issue in the ad hoc networks with energy constraints is to find ways that increase their lifetime. The use of multihop radio relaying requires a sufficient number of relaying nodes to maintainnetwork connectivity. Hence, battery power is a precious resource that must be used efficiently in order to avoid early termination of any node. In this paper, a new battery power scheduling policy based on dynamic programming is proposed for mobile devices.This policy makes use of the state information of each cell provided by the smart battery package and uses the strategy of dynamic programming to optimally satisfy a request for power. Using extensive simulation it is proved that dynamic programming based schedulingpolicyimproves the lifetime of the mobile nodes.Also a hardware support is proposed to succeeds in distinguishing between real-time and non-real-time traffic and provides the appropriate grade of service, to meet the time constraints associated with real time traffic.
A Review of the Energy Efficient and Secure Multicast Routing Protocols for ...graphhoc
This paper presents a thorough survey of recent work addressing energy efficient multicast routing protocols and secure multicast routing protocols in Mobile Ad hoc Networks (MANETs). There are so many issues and solutions which witness the need of energy management and security in ad hoc wireless networks. The objective of a multicast routing protocol for MANETs is to support the propagation of data from a sender to all the receivers of a multicast group while trying to use the available bandwidth efficiently in the presence of frequent topology changes. Multicasting can improve the efficiency of the wireless link when sending multiple copies of messages by exploiting the inherent broadcast property of wireless transmission. Secure multicast routing plays a significant role in MANETs. However, offering energy efficient and secure multicast routing is a difficult and challenging task. In recent years, various multicast routing protocols have been proposed for MANETs. These protocols have distinguishing features and use different mechanisms.
Case Study On Social Engineering Techniques for Persuasion Full Text graphhoc
There are plenty of security software in market; each claiming the best, still we daily face problem of viruses and other malicious activities. If we know the basic working principal of such malware then we can very easily prevent most of them even without security software. Hackers and crackers are experts in psychology to manipulate people into giving them access or the information necessary to get access. This paper discusses the inner working of such attacks. Case study of Spyware is provided. In this case study, we got 100% success using social engineering techniques for deception on Linux operating system, which is considered as the most secure operating system. Few basic principal of defend, for the individual as well as for the organization, are discussed here, which will prevent most of such attack if followed.
Breaking the Legend: Maxmin Fairness notion is no longer effective graphhoc
In this paper we analytically propose an alternative approach to achieve better fairness in scheduling mechanisms which could provide better quality of service particularly for real time application. Our proposal oppose the allocation of the bandwidth which adopted by all previous scheduling mechanism. It rather adopt the opposition approach be proposing the notion of Maxmin-charge which fairly distribute the congestion. Furthermore, analytical proposition of novel mechanism named as Just Queueing is been demonstrated
I-Min: An Intelligent Fermat Point Based Energy Efficient Geographic Packet F...graphhoc
Energy consumption and delay incurred in packet delivery are the two important metrics for measuring the performance of geographic routing protocols for Wireless Adhoc and Sensor Networks (WASN). A protocol capable of ensuring both lesser energy consumption and experiencing lesser delay in packet delivery is thus suitable for networks which are delay sensitive and energy hungry at the same time. Thus a smart packet forwarding technique addressing both the issues is thus the one looked for by any geographic routing protocol. In the present paper we have proposed a Fermat point based forwarding technique which reduces the delay experienced during packet delivery as well as the energy consumed for transmission and reception of data packets.
Fault tolerant wireless sensor mac protocol for efficient collision avoidancegraphhoc
In sensor networks communication by broadcast methods involves many hazards, especially collision. Several MAC layer protocols have been proposed to resolve the problem of collision namely ARBP, where the best achieved success rate is 90%. We hereby propose a MAC protocol which achieves a greater success rate (Success rate is defined as the percentage of delivered packets at the source reaching the destination successfully) by reducing the number of collisions, but by trading off the average propagation delay of transmission. Our proposed protocols are also shown to be more energy efficient in terms of energy dissipation per message delivery, compared to the currently existing protocol.
Enhancing qo s and qoe in ims enabled next generation networksgraphhoc
Managing network complexity, accommodating greater numbers of subscribers, improving coverage to support data services (e.g. email, video, and music downloads), keeping up to speed with fast-changing technology, and driving maximum value from existing networks – all while reducing CapEX and OpEX and ensuring Quality of Service (QoS) for the network and Quality of Experience (QoE) for the user. These are just some of the pressing business issues faced by mobileservice providers, summarized by the demand to “achieve more, for less.” The ultimate goal of optimization techniques at the network and application layer is to ensure End-user perceived QoS. The next generation networks (NGN), a composite environment of proven telecommunications and Internet-oriented mechanisms have become generally recognized as the telecommunications environment of the future. However, the nature of the NGN environment presents several complex issues regarding quality assurance that have not existed in the legacy environments (e.g., multi-network, multi-vendor, and multi-operator IP-based telecommunications environment, distributed intelligence, third-party provisioning, fixed-wireless and mobile access, etc.). In this Research Paper, a service aware policy-based approach to NGN quality assurance is presented, taking into account both perceptual quality of experience and technologydependant quality of service issues. The respective procedures, entities, mechanisms, and profiles are discussed. The purpose of the presented approach is in research, development, and discussion of pursuing the end-to-end controllability of the quality of the multimedia NGN-based communications in an environment that is best effort in its nature and promotes end user’s access agnosticism, service agility, and global mobility
Simulated annealing for location area planning in cellular networksgraphhoc
LA planning in cellular network is useful for minimizing location management cost in GSM network. In fact, size of LA can be optimized to create a balance between the LA update rate and expected paging rate within LA. To get optimal result for LA planning in cellular network simulated annealing algorithm is used. Simulated annealing give optimal results in acceptable run-time
Secure key exchange and encryption mechanism for group communication in wirel...graphhoc
Secured communication in ad hoc wireless networks is primarily important, because the communication signals are openly available as they propagate through air and are more susceptible to attacks ranging from passive eavesdropping to active interfering. The lack of any central coordination and shared wireless medium makes them more vulnerable to attacks than wired networks. Nodes act both as hosts and routers and are interconnected by Multi- hop communication path for forwarding and receiving packets to/from other nodes. The objective of this paper is to propose a key exchange and encryption mechanism that aims to use the MAC address as an additional parameter as the message specific key[to encrypt]and forward data among the nodes. The nodes are organized in spanning tree fashion, as they avoid forming cycles and exchange of key occurs only with authenticated neighbors in ad hoc networks, where nodes join or leave the network dynamically.
Simulation to track 3 d location in gsm through ns2 and real lifegraphhoc
In recent times the cost of mobile communication has dropped significantly leading to a dramatic increase in mobile phone usage. The widespread usage has led mobiles to emerge as a strong alternative for other applications one of which is tracking. This has enabled law-enforcing agencies to detect overspeeding vehicles and organizations to keep track its employees. The 3 major ways of tracking being employed presently are (a) via GPS [1] (b) signal attenuation property of a packet [3] and (c) using GSM Network [2]. The initial cost of GPS is very high resulting in low usage whereas (b) needs a very high precision measuring device. The paper presents a GSM-based tracking technique which eliminates the above mentioned overheads, implements it in NS2 and shows the limitations of the real life simulation. An accuracy of 97% was achieved during NS2 simulation which is comparable to the above mentioned alternate methods of tracking.
Performance Analysis of Ultra Wideband Receivers for High Data Rate Wireless ...graphhoc
For high data rate ultra wideband communication system, performance comparison of Rake, MMSE and Rake-MMSE receivers is attempted in this paper. Further a detail study on Rake-MMSE time domain equalizers is carried out taking into account all the important parameters such as the effect of the number of Rake fingers and equalizer taps on the error rate performance. This receiver combats inter-symbol interference by taking advantages of both the Rake and equalizer structure. The bit error rate performances are investigated using MATLAB simulation on IEEE 802.15.3a defined UWB channel models. Simulation results show that the bit error rate probability of Rake-MMSE receiver is much better than Rake receiver and MMSE equalizer. Study on non-line of sight indoor channel models illustrates that bit error rate performance of Rake-MMSE (both LE and DFE) improves for CM3 model with smaller spread compared to CM4 channel model. It is indicated that for a MMSE equalizer operating at low to medium SNR values, the number of Rake fingers is the dominant factor to improve system performance, while at high SNR values the number of equalizer taps plays a more significant role in reducing the error rate.
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.
An Overview of Mobile Ad Hoc Networks for the Existing Protocols and Applicat...graphhoc
Mobile Ad Hoc Network (MANET) is a collection of two or more devices or nodes or terminals with
wireless communications and networking capability that communicate with each other without the aid of
any centralized administrator also the wireless nodes that can dynamically form a network to exchange
information without using any existing fixed network infrastructure. And it’s an autonomous system in
which mobile hosts connected by wireless links are free to be dynamically and some time act as routers at
the same time, and we discuss in this paper the distinct characteristics of traditional wired networks,
including network configuration may change at any time , there is no direction or limit the movement and
so on, and thus needed a new optional path Agreement (Routing Protocol) to identify nodes for these
actions communicate with each other path, An ideal choice way the agreement should not only be able to
find the right path, and the Ad Hoc Network must be able to adapt to changing network of this type at any
time. and we talk in details in this paper all the information of Mobile Ad Hoc Network which include the
History of ad hoc, wireless ad hoc, wireless mobile approaches and types of mobile ad Hoc networks, and
then we present more than 13 types of the routing Ad Hoc Networks protocols have been proposed. In this
paper, the more representative of routing protocols, analysis of individual characteristics and advantages
and disadvantages to collate and compare, and present the all applications or the Possible Service of Ad
Hoc Networks
An Algorithm for Odd Graceful Labeling of the Union of Paths and Cycles graphhoc
In 1991, Gnanajothi [4] proved that the path graph n
P with n vertex and n −1edge is odd graceful, and
the cycle graph Cm with m vertex and m edges is odd graceful if and only if m even, she proved the
cycle graph is not graceful if m odd. In this paper, firstly, we studied the graphCm∪Pn when m = 4, 6,8,10
and then we proved that the graphCm∪Pn
is odd graceful if m is even. Finally, we described an
algorithm to label the vertices and the edges of the vertex set ( ) m n
V C ∪P and the edge set ( ) m n
E C ∪P .
ACTOR GARBAGE COLLECTION IN DISTRIBUTED SYSTEMS USING GRAPH TRANSFORMATIONgraphhoc
A lot of research work has been done in the area of Garbage collection for both uniprocessor and
distributed systems. Actors are associated with activity (thread) and hence usual garbage collection
algorithms cannot be applied for them. Hence a separate algorithm should be used to collect them. If we
transform the active reference graph into a graph which captures all the features of actors and looks like
passive reference graph then any passive reference graph algorithm can be applied for it. But the cost of
transformation and optimization are the core issues. An attempt has been made to walk through these
issues.
The Neighborhood Broadcast Problem in Wireless Ad Hoc Sensor Networksgraphhoc
to all neighbors of a network node v under the assumption that v does not participate due to
being corrupted or damaged. We present practical network protocol that can be used completely
reactive. It is parameterized with a positive integer k ∈ N and it is proven to guarantee delivery for
k ≥ 2d−1, if node v is d-locally connected, which means that the set of nodes with distance between
1 and d to v induces a connected subgraph of the communication graph. It is also shown that the
number of participating nodes is optimal under the restriction to 1-hop neighborhood information.
The protocol is also analyzed in simulations that demonstrate very high success rates for very low
values of k.
KEYWORD
In [1] Abdel-Aal has introduced the notions of m-shadow graphs and n-splitting graphs, for all m, n ³ 1.
In this paper, we prove that, the m-shadow graphs for paths and complete bipartite graphs are odd
harmonious graphs for allm³ 1. Also, we prove the n-splitting graphs for paths, stars and symmetric
product between paths and null graphs are odd harmonious graphs for all n³ 1. In addition, we present
some examples to illustrate the proposed theories. Moreover, we show that some families of graphs admit
odd harmonious libeling.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
ON THE PROBABILITY OF K-CONNECTIVITY IN WIRELESS AD HOC NETWORKS UNDER DIFFERENT MOBILITY MODELS
1. International journal on applications of graph theory in wireless ad hoc networks and sensor networks
(GRAPH-HOC) Vol.2, No.3, September 2010
DOI : 10.5121/jgraphoc.2010.2301 1
ON THE PROBABILITY OF K-CONNECTIVITY IN
WIRELESS AD HOC NETWORKS UNDER DIFFERENT
MOBILITY MODELS
Natarajan Meghanathan1
and Sireesha Gorla2
1,2
Jackson State University, 1400 Lynch St, Jackson, MS, USA
1
natarajan.meghanathan@jsums.edu, 2
sireesha.gorla@gmail.com
ABSTRACT
We compare the probability of k-Connectivity of an ad hoc network under Random Way Point (RWP),
City Section and Manhattan mobility models. A Network is said to be k-Connected if there exists at least k
edge disjoint paths between any pair of nodes in that network at any given time and velocity. Initially, for
each of the three mobility models, the movement of the each node in the ad hoc network at a given
velocity and time are captured and stored in the Node Movement Database (NMDB). Using the
movements in the NMDB, the location of the node at a given time is computed and stored in the Node
Location Database (NLDB). A weighted graph is created using the location of the nodes from NLDB,
which is converted into a residual graph. The k-Connectivity of this residual graph is obtained by running
Ford-Fulkerson’s algorithm on it. Ford Fulkerson’s algorithm computes the maximum flow of a network
by recording the flows assigned to different routes from each node to all the other nodes in the network.
When run for a particular source-destination pair (s, d) pair on a residual network graph with unit edge
weights as capacity, the maximum flow determined by Ford-Fulkerson’ algorithm is the number of edge
disjoint s-d paths on the network graph. Simulations show that the RWP model yields the highest
probability of k-Connectivity compared to City Section and Manhattan mobility models for a majority of
different node densities and velocities considered. Simulation results also show that, for all the three
mobility models, as the k value increases, the probability of k-Connectivity decreases for a given density
and velocity and as the density increases the probability of k-Connectivity increases.
KEYWORDS
Wireless Ad hoc Networks, k-Connectivity, Mobility Models, Probability, Ford-Fulkerson Algorithm,
Simulations
1. INTRODUCTION
A mobile ad hoc network (MANET) is a collection of mobile wireless hosts which
communicate directly with each other in the absence of a fixed infrastructure [1], with some
constraints on the bandwidth of the wireless links. Communication between any two hosts,
which are outside the transmission range of each other is performed through the intermediate
hosts. The network in a MANET is decentralized where each wireless host has the routing
functionality incorporated within it. Variable wireless link quality, propagation path loss,
fading, multi-user interference, limited battery power, and rapid and unpredictable topological
changes are some of the issues that need to be dealt in a MANET.
Vehicular Ad-hoc Networks (VANET) is an emerging, new type of MANET, where vehicles on
the road form a MANET using wireless technology. Limited bandwidth, multi-hop
communication and self-organization are some of the common characteristics that VANET
shares with MANET. The main issue in a VANET is that the nodes move in a high speed with
respect to each other and this in turn results in very frequent topology changes [2]. Battery
power is not an issue with VANETs.
2. International journal on applications of graph theory in wireless ad hoc networks and sensor networks
(GRAPH-HOC) Vol.2, No.3, September 2010
2
Evaluating the characteristics of ad hoc networking protocols is usually done through the use of
simulation. Mobility model is an important component of a network simulation and usually
plays an important role in understanding real world MANETs. A mobility model describes the
movement patterns of mobile nodes within a network and the change of location, velocity and
acceleration over time [3]. Initially the nodes are distributed randomly within a network and the
mobility model controls the node movement within the network [4].
A number of mobility models were introduced for ad hoc networks and they vary widely in the
movement characteristics of the nodes. The Random Waypoint mobility model, commonly used
in MANET simulation studies, assumes that nodes can move randomly anywhere within a
network region. On the other hand, the City Section and Manhattan mobility models commonly
used in VANET simulation studies assume the network is composed of horizontal and vertical
streets and a node is allowed to move only along these streets [3].
A Network is said to be k-connected if there exists at least k edge disjoint paths between any
pair of nodes in that network at any given time and velocity. Equivalently, it is connected even
if k nodes are removed. k-Connectivity of a network is different for different mobility model.
Connectivity is one of the most important properties of a MANET. k-Connectivity of a network
is a helpful tool to balance the load and energy level at the nodes and to enable secure reliable
communication. In a k-connected wireless ad hoc and sensor networks, fault tolerance and
robustness increase with increasing k value.
The rest of the paper is organized as follows: In Section 2, we briefly review the three mobility
models considered. Section 3 describes the algorithms proposed to extract, store and use the
node mobility profiles for each of the three mobility models. Section 4 briefly reviews the Ford-
Fulkerson algorithm [5] and its use to determine the k-connectivity of an ad hoc network.
Section 5 describes the simulation environment and presents the analysis of k-connectivity of an
ad hoc network at different instants of the simulation as well as under diverse conditions of
network density and mobility. Section 6 concludes the paper.
2. REVIEW OF THE MOBILITY MODELS
In this section, we provide a brief overview of the Random Waypoint mobility model
commonly used in MANET simulation studies and the widely used City Section and Manhattan
mobility models for VANET simulation studies. All the three mobility models [3] assume the
network is confined within fixed boundary conditions. The Random Waypoint mobility model
assumes that the nodes can move anywhere within a network region. The City Section and the
Manhattan mobility models assume the network to be divided into grids: square blocks of
identical block length. The network is thus basically composed of a number of horizontal and
vertical streets. Each street has two lanes, one for each direction (north and south direction for
vertical streets, east and west direction for horizontal streets). A node is allowed to move only
along the grids of horizontal and vertical streets.
2.1 Random Waypoint Mobility Model
Initially, the nodes are assumed to be placed at random locations in the network. The movement
of each node is independent of the other nodes in the network. The mobility of a particular node
is described as follows: The node chooses a random target location to move. The velocity with
which the node moves to this chosen location is uniformly randomly selected from the interval
[vmin,…,vmax]. The node moves in a straight line (in a particular direction) to the chosen location
with the chosen velocity. After reaching the target location, the node may stop there for a certain
time called the pause time. The node then continues to choose another target location and moves
to that location with a new velocity chosen again from the interval [vmin,…,vmax]. The selection
3. International journal on applications of graph theory in wireless ad hoc networks and sensor networks
(GRAPH-HOC) Vol.2, No.3, September 2010
3
of each target location and a velocity to move to that location is independent of the current node
location and the velocity with which the node reached that location. In Figure 1, we observe that
nodes A and B move independent of each other, in random directions with randomly chosen
velocities.
Figure 1: Movement under Figure 2: Movement under Figure 3: Movement under
Random Waypoint Model City Section Model Manhattan Model
2.2 City Section Mobility Model
Initially, the nodes are assumed to be randomly placed in the street intersections. Each street
(i.e., one side of a square block) is assumed to have a particular speed limit. Based on this speed
limit and the block length, one can determine the time it would take move in the street. Each
node placed at a particular street intersection chooses a random target street intersection to
move. The node then moves to the chosen street intersection on a path that will incur the least
amount of travel time. If two or more paths incur the least amount of travel time, the tie is
broken arbitrarily. After reaching the targeted street intersection, the node may stay there for a
pause time and then again choose a random target street intersection to move. The node then
moves towards the new chosen street intersection on the path that will incur the least amount of
travel time. This procedure is repeated independently by each node. In Figure 2, the movement
of two nodes A and B according to the City Section mobility model has been illustrated.
2.3 Manhattan Mobility Model
Initially, the nodes are assumed to be randomly placed in the street intersections. The movement
of a node is decided one street at a time. To start with, each node has equal chance (i.e.,
probability) of choosing any of the streets leading from its initial location. In Figure 3, to start
with, node A has 25% chance to move in each of the four possible directions (east, west, north
or south), where as node B can move only either to the west, east or south with a 1/3 chance for
each direction. After a node begins to move in the chosen direction and reaches the next street
intersection, the subsequent street in which the node will move is chosen probabilistically. If a
node can continue to move in the same direction or can also change directions, then the node
has 50% chance of continuing in the same direction, 25% chance of turning to the east/north and
25% chance of turning to the west/south, depending on the direction of the previous movement.
If a node has only two options, then the node has an equal (50%) chance of exploring either of
the two options. For example, in Figure 3, once node A reaches the rightmost boundary of the
network, the node can either move to the north or to the south, each with a probability of 0.5
and the node chooses the north direction. After moving to the street intersection in the north,
node A can either continue to move northwards or turn left and move eastwards, each with a
probability of 0.5. If a node has only one option to move (this occurs when the node reaches any
of the four corners of the network), then the node has no other choice except to explore that
4. International journal on applications of graph theory in wireless ad hoc networks and sensor networks
(GRAPH-HOC) Vol.2, No.3, September 2010
4
option. For example, in Figure 3, we observe node B that was traveling westward, reaches the
street intersection, which is the corner of the network. The only option for node B is then to turn
to the left and proceed southwards.
3. ALGORITHMS TO GENERATE NODE MOBILITY PROFILE AND
DETERMINE NODE LOCATIONS AT A PARTICULAR TIME INSTANT
This section outlines the algorithms to generate the mobility profile for each node in the
network and also outlines the algorithms to determine the location of a node at any time instant
based on the mobility profiles generated.
3.1 Random Waypoint Model Node Movement Generator
Input: Velocity v, Simulation Time st, Node ID i
Auxiliary Variables:
startTime; // the beginning time of a direction change (waypoint)
endTime; // the ending time of a waypoint
time t; // current time of node movement
velocity v; // velocity of the node
Initialization:
startTime 0
endTime 0
t 0
Output: NMDBi; // Node mobility database for node i
Begin RWP-Node-Movement-Generator
Step 1: Generate a random point (x1, y1) within a 1000*1000 Square Unit area.
Step 2: Generate a random point (x2, y2)
Step 3: Compute distance = 2
21
2
21 )()( yyxx −+−
Step 4: Compute Angle =
( )
( )21
21
yy
xx
−
−
Step 5: Compute transTime = distance / v
Step 6: endTime endTime + transTime
Step 7: Store [startTime, endTime; (x1, y1) (x2, y2), v] in a Node Mobility Database (NMDB)
Step 8:
x1 x2,
y1 y2,
startTime endTime,
t t + transTime
Step 9: if (t ≤ st)
go to Step2
else
return NMDBi
End RWP-Node-Movement-Generator
Figure 4: Algorithm to Generate Mobility Profile under the Random Waypoint Model
5. International journal on applications of graph theory in wireless ad hoc networks and sensor networks
(GRAPH-HOC) Vol.2, No.3, September 2010
5
3.2 City Section Node Movement Generator
City Section Mobility Model
Let there be a set of nodes ‘N’, where N = {N1, N2, N3……..Nn}, where n is the number of
nodes.
Input: Street Intersection Graph SIG (maxRows, maxCols, blockLength, ILDB)
maxRows – Number of horizontal roads in the graph
maxColumns – Number of vertical roads in the graph
blockLength – The length of a block of road in the graph
ILDB – Database storing the location of each intersection in the SIG,
Speed Limit (Velocity) v m/s, Simulation Time st
Auxiliary Variables:
startTime; // the beginning time of a direction change (waypoint)
endTime; // the ending time of a waypoint
time t; // current time of node movement
Initialization:
startTime 0
endTime 0
t 0
Output: NMDBi; // Node Mobility database for node i
Begin City Section-Node-Movement-Generator
Step1: Generate a Random Intersection Point (x1, y1) with in the given graph
Step2: Generate a Random Intersection Point (x2, y2)
Step3: Find the path P with the minimum number of street intersections between (x1, y1)
and (x2, y2) using the Dijkstra’s shortest path algorithm.
Step4: Compute distanceTraveled = (blockLength) * (Psize)
where Psize – the number of intermediate street intersections in P
Step5: Compute transTime =
v
aveleddistanceTr
Step6: endTime endTime + transTime
Step7: Store [endTime; (x1, y1) (x2, y2), v] in a Node Mobility Database (NMDB)
Step8:
x1 x2,
y1 y2,
startTime endTime,
t t + transTime
Step9: if (t ≤ st) go to Step2
else
return NMDBi
End City Section-Node-Movement-Generator
Figure 5: Algorithm to Generate Mobility Profile under the City Section Mobility Model
3.3 Manhattan Node Movement Generator
6. International journal on applications of graph theory in wireless ad hoc networks and sensor networks
(GRAPH-HOC) Vol.2, No.3, September 2010
6
Let there be a set of nodes ‘N’, where N = {N1, N2, N3……..Nn}, where n is the number of
nodes.
Input: Street Intersection Graph SIG (maxRows, maxCols, blockLength, ILDB)
maxRows – Number of horizontal roads in the graph
maxColumns – Number of Vertical roads in the graph
blockLength – The length of a block of road in the graph
ILDB – Database storing the location of each intersection in the SIG,
(xI, yI) -next intersection to which a node moves
Speed Limit (Velocity) v m/s, Simulation Time st
Auxiliary Variables:
startTime; // the beginning time of a direction change (waypoint)
endTime; // the ending time of a waypoint
time t; // current time of node movement
Initialization:
startTime 0; endTime 0; t 0
Output: NMDBi; // Node Mobility database for node i
Begin Manhattan-Node-Mobility-Generator
Step1: Generate a Random Intersection Point (x1, y1) within the given graph SIG
Step2: Let (xS, yS) (x1, y1)
Step3: Let SI be the set of all neighboring intersections of (xS, yS) and nI be number of
elements in SI..
Step4: if (|SI | = 1) // SI = [(xA, yA)]
(xI, yI) (xA, yA)
Step5: if (nI = 2) // SI = [(xA, yA), (xB, yB)]
Generate a random number rI from 0 to 1
if (rI < 0.5)
(xI, yI) (xA, yA)
else
nextI (xB, yB)
Step6: if (nI = 3) // SI = [(xA, yA), (xB, yB), (xC, yC)]
Choose the intersection (xA, yA) ∈ SI which is in the same axis as that of (xS, yS)
Let (xB, yB) and (xC, yC) be the two intersections in SI that are not in the same axis as that
of (xS, yS) generate a random number rn from 0 to 1
if (rn < 0.5)
nextI (xA, yA)
else
if (0.5<rn < 0.75)
nextI (xB, yB)
else nextI (xC, yC)
Step7: Compute distanceTraveled = blockLength
Step8: Compute transTime =
v
aveleddistanceTr
Step9: Assign endTime+ = transTime
Store [endTime; (xS, yS), (xI, yI), v] in Node Mobility Database (NMDB)
Step10: Assign xS xI, yS yI, startTime endTime, t+ transTime
Step11: If (t <= st) go to Step3 Otherwise go to Step1
End Manhattan-Node-Mobility-Generator
7. International journal on applications of graph theory in wireless ad hoc networks and sensor networks
(GRAPH-HOC) Vol.2, No.3, September 2010
7
Figure 6: Algorithm to Generate Mobility Profile under the Manhattan Model
The Node Movement Generator algorithm for each of the three mobility models outputs a Node
Mobility Database (NMDB) for each node in the network. The NMDB of a node has the
movement information of the node. The information includes the time at which the node started
moving, starting location, ending location and the velocity of the node. The node location
algorithm of a mobility model takes the corresponding NMDBs of all the nodes in the network
and generates a Node Location Database (NLDB) which gives the location of each node at a
given time.
3.4 RWP Node Location Generator
Let there be set of nodes ‘N’ where N = {N1, N2, N3……..Nn} and T = {t1, t2, t3, t4,……..tst} and
N, T∈NMDBi
Input: time t, Simulation Time st, NMDB of Ni;
Output: NLDBi; // Node location database for node i
Begin RWP-Node-Location-Generator
Step1: if (t ∈ T) go to Step5
else go to Step2
Step2: Iterate through NMDB of Ni and find a value of ‘tj’ and ‘tj+1’ such that
tj < t < tj+1
Step3: Compute fraction f =
jj
j
tt
tt
−
−
+1
Step4: Let (xt, yt) be the location at time t then
Compute xt = f * xj+1 + (1-fr) * xj
Compute yt = f * yj+1 + (1-fr) * yj
Step5: Store [ Ni; (xt, yt) ,t] in Node Position Database (NLDB)
End RWP-Node-Location-Generator
Figure 7: Algorithm to Generate Node Location under the Random Waypoint Model
3.5 City Section Node Location Generator
Let there be a set of nodes ‘N’ where N = {N1, N2, N3……..Nn} and T = {t1, t2, t3, t4,……..tst}
and N, T∈NMDBi
Input: time t, Simulation Time st, Node Mobility Database (NMDB) of Ni; Velocity v;
Auxiliary Variables:
blockLength b;//length of any street between two intersections
TimePerBlock TB; //time taken to travel a single bockLength of street
Initialization:
8. International journal on applications of graph theory in wireless ad hoc networks and sensor networks
(GRAPH-HOC) Vol.2, No.3, September 2010
8
TB =
v
b
Output: NLDBi; // Node location database for node i
Begin City-Section-Node-Location-Generator
Step1: if (t ∈ T)
go to Step7
else
go to Step2
Step2: Iterate through NMDB and find a value of ‘tj’ and ‘tj+1’ such that
tj < t < tj+1
Step3: Find the shortest path P on the street intersection graph.
Let P be represented as (xj, yj), (xk1, yk1), (xk2, yk2), ……….(xkh, ykh), (xj+1, yj+1),
where k1, k2, k3, …………kh are the street intersections forming the shortest path,
and tk1, tk2, tk3,………tkh the times respectively.
and h is the number for street intersections between (xj, yj) and (xj+1, yj+1)
Let the l be the count, and tl be the time and count
Initialize l = 1 and tl = tj.
Step4: Let Xstart = xkl, Ystart = ykl and Xend = xkl+1, Yend = ykl+1
Step5: if (tl ≥ t >= tl + TB)
l = l + 1
Repeat Step4
else
Compute fraction f =
tt
tt
kl
kl
−
−
+1
Step6: Let (xt, yt) be the location at time t then
Compute xt = f * xkl+1 + (1-f) * xkl
Compute yt = f * ykl+1 + (1-f) * ykl
Step7: Store [ Ni; (xt, yt), t ] in Node Position Database (NPDB)
End City-Section-Node-Location-Generator
Figure 8: Algorithm to Generate Node Location under the City Section Mobility Model
3.6 Manhattan Node Location Generator
Let there be a set of nodes ‘N’ where N = {N1, N2, N3……..Nn} and T = {t1, t2, t3, t4,……..tst}
and N, T∈NMDBi
Input: time t, Simulation Time st, NMDB of Ni;
Output: NLDBi; // Node location database for node i
Begin Manhattan-Node-Location-Generator
Step1: if (t ∈ T)
go to Step5
else
9. International journal on applications of graph theory in wireless ad hoc networks and sensor networks
(GRAPH-HOC) Vol.2, No.3, September 2010
9
go to Step2
Step2: Iterate through NMDB of Ni and find a value of ‘tj’ and ‘tj+1’ such that
tj < t < tj+1
Step3: Compute fraction f =
jj
j
tt
tt
−
−
+1
Step4: Let (xt, yt) be the location at time t then
Compute xt = f * xj+1 + (1-fr) * xj
Compute yt = f * yj+1 + (1-fr) * yj
Step5: Store [ Ni; (xt, yt) ,t] in Node Position Database (NLDB)
End Manhattan-Node-Location-Generator
Figure 9: Algorithm to Generate Node Location under the Manhattan Mobility Model
4. DETERMINING THE K-CONNECTIVITY OF A RESIDUAL GRAPH USING
FORD-FULKERSON ALGORITHM
From the NLDBs obtained using the Node Location Generators for a mobility model, a graph is
created depending on the distances between the nodes and the transmission range of each node.
A residual graph [5] is a directed graph where each edge has a positive residual capacity and is
labeled by its residual capacity. For a given graph G = (V, E) with source s and destination t, let
f be the flow in G and u, v ∈ V be a pair of vertices then, the additional amount of net flow that
can be pushed from u to v before exceeding the capacity c(u, v) is the residual capacity of (u, v),
which is given by: cf (u, v) = c(u, v) – f(u ,v).
Input: Given a NLDB at a particular time t,
Transmission rage R
Output: G = (V, E)
V – the set of all vertices corresponding to the nodes N1, N2, …, Nn where n is
the number of nodes in the network
E – the set of all edges such that the distance between the two constituent nodes
of an edge is less than or equal to the transmission range R.
Begin Graph Generator
for ∀ i ∈V
for ∀ j ∈ V-{i}
Step 1: Compute the distance dij = 22
)()( yjyixjxi −+−
Step 2: if (dij <= R)
(i, j)∈E
weight (i, j) 1
end if
end for
end for
End Graph Generator
10. International journal on applications of graph theory in wireless ad hoc networks and sensor networks
(GRAPH-HOC) Vol.2, No.3, September 2010
10
Figure 10: Algorithm to Create a Weighted Graph for a Given NLDB
Input: Residual Graph GR, initially GR = G (V, E)
Auxiliary Variables:
flow f;
capacity c;
flow capacity cf;
count connectivity kC;//count which keeps track of the connectivity
Initialization: kC 0
Output: k-Connectivity Database (KCDB) that has the set of all source-destination (s-d) paths
that has k-edge disjoint paths; In this research, 0 ≤ k ≤ 40
Each entry in KCDB is a tuple [k, SDk] where k is the number of edge-disjoint paths and SDk is
the set of all s-d pairs that have k-edge disjoint paths
Begin Ford-Fulkerson-Algorithm for k-Connectivity
for∀ s-d pair where s ∈V and d ∈V
kC 0 // the number of edge-disjoint paths between s and d
Step1: for each edge (u, v) ∈E
do f [u, v] 0
f [v, u] 0
c[u, v] weight(u, v) 1
if (v, u) ∉E
c[v, u] 0
Step2: if there exits an s-d path P (i.e., a path from node s to node d) in GR
do cf (P) min{cf (u, v): (u, v) is in P}
for each edge (u, v) in P
do f[u, v] f[u, v] + cf (P)
f[v, u] – f[u, v]
c(u, v) = c (u, v) – f (u, v)
c(v, u) = c (v, u) – f (v, u)
kC kC+ 1
go to Step2
Step3: Add (s, d) to SDkC
end for
End Ford-Fulkerson-Algorithm for k-Connectivity
Figure 11: Finding the k-Connectivity of a Residual Graph using Ford-Fulkerson Algorithm
5. SIMULATIONS
Simulations have been conducted in a discrete-event simulator implemented by the authors in
Java. The network dimensions are 1000m x 1000m. The network density is varied with 25
nodes (low density), 50 nodes (medium density) and 75 nodes (high density). The simulation
time is 1000 seconds. The velocity is uniformly distributed in the range [0…. Vmax]. The Vmax
values used are 5m/s (representing low node mobility), 15m/s (representing medium node
mobility) and 30m/s (representing high node mobility). Pause time is 0 seconds. The
transmission range of each node is 250m. The mobility models used are Random Waypoint,
11. International journal on applications of graph theory in wireless ad hoc networks and sensor networks
(GRAPH-HOC) Vol.2, No.3, September 2010
11
City Section and Manhattan models. Using For-Fulkerson’s algorithm, the k-Connectivity of the
network is calculated at k = 1, 2, …, 10 and the time instants at which k-Connectivity is
captured are 100, 600 and 900th
seconds, as illustrated in Figures 12 through 20.
In low density networks, for all conditions node mobility (5m/s, refer Figure 12; 15m/s, refer
Figure 13; and 30m/s, refer Figure 14), the Random Waypoint mobility model has the highest
probability of k-Connectivity at lower values of k (k = 1, 2, 3) while Manhattan has the highest
probability of k-Connectivity at medium (k = 4, 5, 6, 7) and higher (k = 4, 5, 6, 7) values. For
medium density networks, for all conditions node mobility (5m/s, refer Figure 15; 15m/s, refer
Figure 16; and 30m/s, refer Figure 17), the Random Waypoint mobility model has the highest
probability of k-Connectivity at lower (k = 1, 2, 3), medium (k = 4, 5, 6, 7) and higher (k = 8, 9,
10) values of k. For high density networks, in conditions of low node mobility (5m/s, refer
Figure 18), Random Waypoint mobility model has the highest probability of k-Connectivity at
lower (k = 1, 2, 3), medium (k = 4, 5, 6, 7) and higher (k = 8, 9, 10) values of k at low velocity
and high density. In conditions of moderate node mobility (15m/s, refer Figure 19), the
Manhattan mobility model has the highest probability of k-Connectivity at lower values of k (k
= 1, 2, 3) while the Random Waypoint model has the highest probability of k-Connectivity at
medium (k = 4, 5, 6, 7) and higher (k = 8, 9, 10) values of k at medium mobility and high
density. In conditions of high node mobility (30m/s, refer Figure 20), the Manhattan mobility
model has the highest probability of k-Connectivity at lower values of k (k = 1, 2, 3) while the
Random Waypoint model has the highest probability of k-Connectivity at medium (k = 4, 5, 6,
7) and higher (k = 8, 9, 10) values of k at high mobility and high density.
Figure 12.1: @ 100th
second Figure 12.2: @ 600th
second Figure 12.3: @ 900th
second
Figure 12: Probability of k-Connectivity (Low Density, Low Mobility)
Figure 13.1: @ 100th
second Figure 13.2: @ 600th
second Figure 13.3: @ 900th
second
Figure 13: Probability of k-Connectivity (Low Density, Moderate Mobility)
Figure 14.1: @ 100th
second Figure 14.2: @ 600th
second Figure 14.3: @ 900th
second
Figure 14: Probability of k-Connectivity (Low Density, High Mobility)
12. International journal on applications of graph theory in wireless ad hoc networks and sensor networks
(GRAPH-HOC) Vol.2, No.3, September 2010
12
Figure 15.1: @ 100th
second Figure 15.2: @ 600th
second Figure 15.3: @ 900th
second
Figure 15: Probability of k-Connectivity (Moderate Density, Low Mobility)
Figure 16.1: @ 100th
second Figure 16.2: @ 600th
second Figure 16.3: @ 900th
second
Figure 16: Probability of k-Connectivity (Moderate Density, Moderate Mobility)
Figure 17.1: @ 100th
second Figure 17.2: @ 600th
second Figure 17.3: @ 900th
second
Figure 17: Probability of k-Connectivity (Moderate Density, High Mobility)
Figure 18.1: @ 100th
second Figure 18.2: @ 600th
second Figure 18.3: @ 900th
second
Figure 18: Probability of k-Connectivity (Moderate Density, Low Mobility)
Figure 19.1: @ 100th
second Figure 19.2: @ 600th
second Figure 19.3: @ 900th
second
Figure 19: Probability of k-Connectivity (Moderate Density, Moderate Mobility)
13. International journal on applications of graph theory in wireless ad hoc networks and sensor networks
(GRAPH-HOC) Vol.2, No.3, September 2010
13
Figure 20.1: @ 100th
second Figure 20.2: @ 600th
second Figure 20.3: @ 900th
second
Figure 20: Probability of k-Connectivity (Moderate Density, High Mobility)
6. CONCLUSIONS
The Random Waypoint mobility model has the highest probability of k-Connectivity when
compared to City Section and Manhattan models. At low values of k (k = 1, 2, and 3), City
Section model has better probability of k-Connectivity than the Manhattan model for almost
scenarios. At medium (k = 4, 5, 6, and 7) and high (k = 8, 9, and 10) values of k, the Manhattan
model has the highest probability of k-Connectivity at lower densities, while the City Section
model has the highest probability of k-Connectivity at moderate and higher densities. For each
mobility model, with increase in density, the variation in the probability of k-Connectivity
decreases and the absolute mean value of the k-Connectivity increases. For a given density,
velocity and k, the Random Waypoint mobility model has less variation in k-Connectivity
compared to the City Section and Manhattan mobility models.
REFERENCES
[1] N. Chatterjee, A. Potluri and A. Negi, “A Self-Organizing Approach to MANET Clustering,” Vol.
4882, Lecture Notes in Computer Science, pp. 73-78, November 2007.
[2] M. Rudack, M. Meincke, K. Jobmann and M. Lott, “On Traffic Dynamical Aspects Inter-vehicle
Communication (IVC),” Proceedings of the 57th
IEEE Semiannual Vehicular Technology Conference
(VTC03 Spring), April 2003.
[3] T. Camp, J. Boleng and V. Davies, “A Survey of Mobility Models for Ad Hoc Network Research,”
Wireless Communication and Mobile Computing, Vol. 2, No. 5, pp. 483-502, September 2002.
[4] A. Jardosh, E. M. Belding-Royer, K. C. Almeroth, S. Suri, “Towards Realistic Mobility Models For
Mobile Ad hoc Networks,” Proceedings of the 9th
Annual International Conference on Mobile
Computing and Networking, 2003, San Diego, CA, USA.
[5] T. H. Cormen, C. E. Leiserson, R. L. Rivest and C. Stein, “Single-Source Shortest Paths,”
Introduction to Algorithms, 2nd
Edition, MIT Press, 2001.