For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
Accurate and simple wireless localizations based on time product of arrival i...ieeeprojectsbangalore
This paper proposes a new wireless localization algorithm to improve accuracy for non-line-of-sight (NLOS) environments where there are no direct paths between the transmitter and receiver. The algorithm assumes NLOS errors follow a distance dependent model and uses a measurement called time product of arrival (TPOA) to construct a set of linear equations solved using least squares to estimate the location. Simulations show the new algorithm performs better than traditional methods in NLOS environments.
This document describes using materials informatics to predict materials properties like melting points more quickly than traditional experimentation or simulation. It proposes using descriptors of materials' structural properties in a linear regression model to predict properties. It applies this approach to predict melting points of over 400 materials based on descriptors like unit cell volume, atomic properties, and bond valence. The model achieves a correlation of 0.5349 between predicted and observed melting points, demonstrating the ability to predict properties without extensive testing.
OPTICS is an algorithm that identifies variable density clusters without specifying the distance parameter (eps) required by DBSCAN. It creates an ordering of database objects based on their core and reachability distances. This ordering represents the clustering structure and density connectivity of the data. OPTICS extends DBSCAN by processing multiple distance parameters simultaneously. It stores an object's core distance and reachability distance to assign cluster memberships based on density reachability.
This document discusses DBSCAN (Density-Based Spatial Clustering of Applications with Noise), a density-based clustering algorithm. DBSCAN groups together closely packed points considered core points, and separates clusters based on density rather than assigning points to predefined clusters. It requires two parameters, epsilon which defines a neighborhood distance, and MinPts specifying the minimum number of points required to form a dense region. Points are classified as core, border or noise based on their epsilon-neighborhood. DBSCAN forms clusters by linking core points that are density-reachable from each other, and identifies outliers as noise points not belonging to any cluster.
The document proposes algorithms for data collection in wireless sensor networks that support multiple applications. It introduces the interval data sharing problem, which aims to transmit minimal data while satisfying the sampling interval requirements of all applications. A 2-factor approximation algorithm is provided to solve this nonlinear nonconvex optimization problem with low complexity. Special cases can be solved optimally in polynomial time. Three online algorithms are also introduced to process continuous tasks. Both analysis and simulations show the effectiveness of the proposed algorithms in reducing communication costs for multi-application data collection in wireless sensor networks.
The document proposes algorithms for data collection in wireless sensor networks that support multiple applications. It introduces the interval data sharing problem, which aims to transmit minimal data while satisfying the sampling interval requirements of all applications. A 2-factor approximation algorithm is provided to solve this nonlinear nonconvex optimization problem with low complexity. Special cases can be solved optimally in polynomial time. Three online algorithms are also introduced to process tasks continuously as they arrive. Simulations demonstrate the effectiveness of the proposed algorithms in reducing communication costs for multi-application data collection in wireless sensor networks.
Multi objective game theoretic scheduling of bag-of-tasks workflows on hybri...Nexgen Technology
Ecruitment Solutions (ECS) is one of the leading Delhi based Software Development & HR Consulting Firm, which is assessed at the level of ISO 9001:2008 standard. ECS offers an awesome project and product based solutions to many customers around the globe.
In addition, ECS has also widened its wings by the way consummating academic projects especially for the final year professional degree students in India. ECS consist of a technical team that has solved many IEEE papers and delivered world-class solutions .
This document presents an improved multi-SOM clustering algorithm that uses the Davies-Bouldin index to determine the optimal number of clusters. The multi-SOM algorithm iteratively clusters an initial self-organizing map (SOM) grid using the DB index at each level until the index reaches its minimum value, indicating the best number of clusters. Experimental results on five datasets show the proposed algorithm performs as well as or better than k-means, BIRCH, and a previous multi-SOM algorithm in determining the correct number of clusters.
Accurate and simple wireless localizations based on time product of arrival i...ieeeprojectsbangalore
This paper proposes a new wireless localization algorithm to improve accuracy for non-line-of-sight (NLOS) environments where there are no direct paths between the transmitter and receiver. The algorithm assumes NLOS errors follow a distance dependent model and uses a measurement called time product of arrival (TPOA) to construct a set of linear equations solved using least squares to estimate the location. Simulations show the new algorithm performs better than traditional methods in NLOS environments.
This document describes using materials informatics to predict materials properties like melting points more quickly than traditional experimentation or simulation. It proposes using descriptors of materials' structural properties in a linear regression model to predict properties. It applies this approach to predict melting points of over 400 materials based on descriptors like unit cell volume, atomic properties, and bond valence. The model achieves a correlation of 0.5349 between predicted and observed melting points, demonstrating the ability to predict properties without extensive testing.
OPTICS is an algorithm that identifies variable density clusters without specifying the distance parameter (eps) required by DBSCAN. It creates an ordering of database objects based on their core and reachability distances. This ordering represents the clustering structure and density connectivity of the data. OPTICS extends DBSCAN by processing multiple distance parameters simultaneously. It stores an object's core distance and reachability distance to assign cluster memberships based on density reachability.
This document discusses DBSCAN (Density-Based Spatial Clustering of Applications with Noise), a density-based clustering algorithm. DBSCAN groups together closely packed points considered core points, and separates clusters based on density rather than assigning points to predefined clusters. It requires two parameters, epsilon which defines a neighborhood distance, and MinPts specifying the minimum number of points required to form a dense region. Points are classified as core, border or noise based on their epsilon-neighborhood. DBSCAN forms clusters by linking core points that are density-reachable from each other, and identifies outliers as noise points not belonging to any cluster.
The document proposes algorithms for data collection in wireless sensor networks that support multiple applications. It introduces the interval data sharing problem, which aims to transmit minimal data while satisfying the sampling interval requirements of all applications. A 2-factor approximation algorithm is provided to solve this nonlinear nonconvex optimization problem with low complexity. Special cases can be solved optimally in polynomial time. Three online algorithms are also introduced to process continuous tasks. Both analysis and simulations show the effectiveness of the proposed algorithms in reducing communication costs for multi-application data collection in wireless sensor networks.
The document proposes algorithms for data collection in wireless sensor networks that support multiple applications. It introduces the interval data sharing problem, which aims to transmit minimal data while satisfying the sampling interval requirements of all applications. A 2-factor approximation algorithm is provided to solve this nonlinear nonconvex optimization problem with low complexity. Special cases can be solved optimally in polynomial time. Three online algorithms are also introduced to process tasks continuously as they arrive. Simulations demonstrate the effectiveness of the proposed algorithms in reducing communication costs for multi-application data collection in wireless sensor networks.
Multi objective game theoretic scheduling of bag-of-tasks workflows on hybri...Nexgen Technology
Ecruitment Solutions (ECS) is one of the leading Delhi based Software Development & HR Consulting Firm, which is assessed at the level of ISO 9001:2008 standard. ECS offers an awesome project and product based solutions to many customers around the globe.
In addition, ECS has also widened its wings by the way consummating academic projects especially for the final year professional degree students in India. ECS consist of a technical team that has solved many IEEE papers and delivered world-class solutions .
This document presents an improved multi-SOM clustering algorithm that uses the Davies-Bouldin index to determine the optimal number of clusters. The multi-SOM algorithm iteratively clusters an initial self-organizing map (SOM) grid using the DB index at each level until the index reaches its minimum value, indicating the best number of clusters. Experimental results on five datasets show the proposed algorithm performs as well as or better than k-means, BIRCH, and a previous multi-SOM algorithm in determining the correct number of clusters.
This paper presents a new clustering algorithm called Robust Fuzzy n-Means (RFNM) that can determine the optimal number of clusters in a dataset and is robust to outliers. RFNM is a modification of existing Robust Fuzzy c-Means Clustering (RFCM) and Fuzzy c-Means Clustering (FCM) algorithms. RFCM improves on FCM by making it more resistant to outliers, but requires the user to specify the number of clusters. RFNM retains RFCM's robustness to outliers and does not require the user to specify the number of clusters in advance, allowing it to determine the optimal number of clusters automatically.
COMPARATIVE PERFORMANCE ANALYSIS OF RNSC AND MCL ALGORITHMS ON POWER-LAW DIST...acijjournal
Cluster analysis of graph related problems is an important issue now-a-day. Different types of graph
clustering techniques are appeared in the field but most of them are vulnerable in terms of effectiveness
and fragmentation of output in case of real-world applications in diverse systems. In this paper, we will
provide a comparative behavioural analysis of RNSC (Restricted Neighbourhood Search Clustering) and
MCL (Markov Clustering) algorithms on Power-Law Distribution graphs. RNSC is a graph clustering
technique using stochastic local search. RNSC algorithm tries to achieve optimal cost clustering by
assigning some cost functions to the set of clusterings of a graph. This algorithm was implemented by A.
D. King only for undirected and unweighted random graphs. Another popular graph clustering
algorithm MCL is based on stochastic flow simulation model for weighted graphs. There are plentiful
applications of power-law or scale-free graphs in nature and society. Scale-free topology is stochastic i.e.
nodes are connected in a random manner. Complex network topologies like World Wide Web, the web of
human sexual contacts, or the chemical network of a cell etc., are basically following power-law
distribution to represent different real-life systems. This paper uses real large-scale power-law
distribution graphs to conduct the performance analysis of RNSC behaviour compared with Markov
clustering (MCL) algorithm. Extensive experimental results on several synthetic and real power-law
distribution datasets reveal the effectiveness of our approach to comparative performance measure of
these algorithms on the basis of cost of clustering, cluster size, modularity index of clustering results and
normalized mutual information (NMI).
This document summarizes an experiment on network designing and studying different topologies. The experiment involves using Packet Tracer to implement bus, ring, star, mesh, and hybrid network topologies. For the mesh topology implementation, 4 laptops and 4 switches are connected in a mesh configuration with each device having a unique IP address. Messages are sent between devices and the transmission is observed to verify proper mesh network implementation. Completing all procedures carefully results in successful message transmission between devices in the mesh network topology.
This document presents a method for downsampling point cloud data to enable real-time scan matching for autonomous vehicles. It introduces two new downsampling algorithms: Ring Random Filter and Distance Voxel Grid Filter. It evaluates the algorithms based on execution time of scan matching, downsampling time, and relative error compared to raw point cloud data from tests in suburban and city environments. The results show the downsampling enables real-time scan matching with relative errors generally less than 10 cm.
Clustering Using Shared Reference Points Algorithm Based On a Sound Data ModelWaqas Tariq
A novel clustering algorithm CSHARP is presented for the purpose of finding clusters of arbitrary shapes and arbitrary densities in high dimensional feature spaces. It can be considered as a variation of the Shared Nearest Neighbor algorithm (SNN), in which each sample data point votes for the points in its k-nearest neighborhood. Sets of points sharing a common mutual nearest neighbor are considered as dense regions/ blocks. These blocks are the seeds from which clusters may grow up. Therefore, CSHARP is not a point-to-point clustering algorithm. Rather, it is a block-to-block clustering technique. Much of its advantages come from these facts: Noise points and outliers correspond to blocks of small sizes, and homogeneous blocks highly overlap. This technique is not prone to merge clusters of different densities or different homogeneity. The algorithm has been applied to a variety of low and high dimensional data sets with superior results over existing techniques such as DBScan, K-means, Chameleon, Mitosis and Spectral Clustering. The quality of its results as well as its time complexity, rank it at the front of these techniques.
CLIQUE is an algorithm for subspace clustering of high-dimensional data. It works in two steps: (1) It partitions each dimension of the data space into intervals of equal length to form a grid, (2) It identifies dense units within this grid and finds clusters as maximal sets of connected dense units. CLIQUE efficiently discovers clusters by identifying dense units in subspaces and intersecting them to obtain candidate dense units in higher dimensions. It automatically determines relevant subspaces for clustering and scales well with large, high-dimensional datasets.
The document summarizes research on developing efficient convolutional neural network architectures called MobileNets that are well-suited for mobile and embedded vision applications. The key ideas are using depthwise separable convolutions to factorize standard convolutions and using a width multiplier and resolution multiplier to control model size. Experiments show MobileNets achieve higher accuracy and speed than prior mobile networks on image classification and object detection tasks while having a smaller memory footprint.
Path constrained data gathering scheme for wireless sensor networks with mobi...ijwmn
This document summarizes a research paper on using mobile elements to gather data in wireless sensor networks. The paper proposes a heuristic algorithm called Graph Partitioning (GP) to address the K-Hop tour planning (KH-tour) problem of designing the shortest possible tour for a mobile element to visit a subset of sensor nodes called caching points, such that any node is at most k hops from the tour.
The GP algorithm works by first partitioning the sensor network graph into partitions where the depth of each partition is bounded by k hops. It then identifies the minimum number of caching points needed in each partition. Finally, it constructs the mobile element's tour to visit all the identified caching points.
Lbdp localized boundary detection and parametrization for 3 d sensor networksNexgen Technology
Ecruitment Solutions (ECS) is one of the leading Delhi based Software Development & HR Consulting Firm, which is assessed at the level of ISO 9001:2008 standard. ECS offers an awesome project and product based solutions to many customers around the globe.
In addition, ECS has also widened its wings by the way consummating academic projects especially for the final year professional degree students in India. ECS consist of a technical team that has solved many IEEE papers and delivered world-class solutions .
M.Phil Computer Science Mobile Computing ProjectsVijay Karan
This document lists several M.Phil Computer Science Mobile Computing project titles and abstracts. It describes projects related to throughput and delay analysis using MIMO in wireless networks, minimum bandwidth reservations for periodic streams in wireless real-time systems, converge-cast capacity and delay tradeoffs, optimal location updates in mobile ad hoc networks, fast data collection in tree-based wireless sensor networks, and optimal scheduling for multi-radio multi-channel cognitive cellular networks. The projects involve using techniques like MIMO, bandwidth reservations, converge-cast analysis, location updates, data collection trees, and multi-radio scheduling to analyze performance metrics in wireless networks and mobile computing systems.
This document summarizes a research paper that analyzes optimal multicast capacity and delay tradeoffs in mobile ad hoc networks (MANETs) under different node mobility models. It studies four node mobility models (two with two-dimensional mobility and two with one-dimensional mobility) and two mobility timescales (fast and slow mobility relative to data transmission). The paper characterizes the optimal multicast capacity under each model given a delay constraint and develops a scheme to achieve throughput close to the upper bound. It also extends the analysis to heterogeneous networks with infrastructure support like base stations.
The document discusses node localizability in wireless ad hoc and sensor networks. It introduces the concept of node localizability, which allows analyzing how many nodes can be located in sparsely or moderately connected networks. The study derives necessary and sufficient conditions for node localizability to determine if a specific node can be located. Experimental results on a real-world system show that node localizability provides useful guidance for network deployment and location-based services.
List of Parallel and Distributed System IEEE 2014 Projects. It Contains the IEEE Projects in the Domain Parallel and Distributed System for the year 2014
Parallel and Distributed System IEEE 2014 ProjectsVijay Karan
List of Parallel and Distributed System IEEE 2014 Projects. It Contains the IEEE Projects in the Domain Parallel and Distributed System for the year 2014
This document proposes a hybrid optimization algorithm using ant colony optimization and particle swarm optimization to solve the multiobjective multicast routing problem in wireless sensor networks. The goal is to optimize two objectives simultaneously - end-to-end delay and total transmitted power. ACO and PSO are combined to find Pareto-optimal solutions efficiently. Simulation results show the algorithm can find near-optimal solutions for minimizing delay and power consumption when routing data from a source to multiple destinations in wireless sensor networks.
R sk nn- knn search on road networks by incorporating social influencefinalsemprojects
This document proposes a new problem called k-nearest neighbor (kNN) search on road networks by incorporating social influence (RSkNN). It aims to find the k nearest objects to a query user on a road network while considering the query user's social information and social influence. Three efficient index-based search algorithms are proposed: road network-based, social network-based, and a hybrid approach. The algorithms aim to speed up computation of social influence over large road and social networks. The paper evaluates the efficiency and effectiveness of the solutions using real road and social network data.
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/
Extend Your Journey: Considering Signal Strength and Fluctuation in Location-...Chih-Chuan Cheng
Reducing the communication energy is essential to facilitate the growth of emerging mobile applications. In this paper, we introduce signal strength into location-based applications to reduce the energy consumption of mobile devices for data reception. First, we model the problem of data fetch scheduling, with the objective of minimizing the energy required to fetch location-based information without impacting the application’s semantics adversely. To solve the fundamental problem, we propose a dynamic programming algorithm and prove its optimality in terms of energy savings. Then, we perform postoptimal analysis to explore the tolerance of the algorithm to signal strength fluctuations. Finally, based on the algorithm, we consider implementation issues.We have also developed a virtual tour system integrated with existing web applications to validate the practicability of the proposed concept. The results of experiments conducted based on real-world case studies are very encouraging and demonstrate the applicability of the proposed algorithm towards signal strength fluctuations.
Skyline Query Processing using Filtering in Distributed EnvironmentIJMER
This document summarizes a research paper about skyline query processing in distributed databases. Skyline queries return multidimensional data points that are not dominated by other points. In distributed databases, skyline queries must be processed across multiple data sites. The paper proposes using multiple filtering points selected from each local skyline result to reduce the number of false positive results and communication costs between sites. Two heuristics called MaxSum and MaxDist are described for selecting filtering points that maximize their combined dominating potential across sites to improve distributed skyline query processing performance.
IoT-Daten: Mehr und schneller ist nicht automatisch besser.
Über optimale Sampling-Strategien, wie man rechnen kann, ob IoT sich rechnet, und warum es nicht immer Deep Learning und Real-Time-Analytics sein muss. (Folien Deutsch/Englisch)
This paper presents a new clustering algorithm called Robust Fuzzy n-Means (RFNM) that can determine the optimal number of clusters in a dataset and is robust to outliers. RFNM is a modification of existing Robust Fuzzy c-Means Clustering (RFCM) and Fuzzy c-Means Clustering (FCM) algorithms. RFCM improves on FCM by making it more resistant to outliers, but requires the user to specify the number of clusters. RFNM retains RFCM's robustness to outliers and does not require the user to specify the number of clusters in advance, allowing it to determine the optimal number of clusters automatically.
COMPARATIVE PERFORMANCE ANALYSIS OF RNSC AND MCL ALGORITHMS ON POWER-LAW DIST...acijjournal
Cluster analysis of graph related problems is an important issue now-a-day. Different types of graph
clustering techniques are appeared in the field but most of them are vulnerable in terms of effectiveness
and fragmentation of output in case of real-world applications in diverse systems. In this paper, we will
provide a comparative behavioural analysis of RNSC (Restricted Neighbourhood Search Clustering) and
MCL (Markov Clustering) algorithms on Power-Law Distribution graphs. RNSC is a graph clustering
technique using stochastic local search. RNSC algorithm tries to achieve optimal cost clustering by
assigning some cost functions to the set of clusterings of a graph. This algorithm was implemented by A.
D. King only for undirected and unweighted random graphs. Another popular graph clustering
algorithm MCL is based on stochastic flow simulation model for weighted graphs. There are plentiful
applications of power-law or scale-free graphs in nature and society. Scale-free topology is stochastic i.e.
nodes are connected in a random manner. Complex network topologies like World Wide Web, the web of
human sexual contacts, or the chemical network of a cell etc., are basically following power-law
distribution to represent different real-life systems. This paper uses real large-scale power-law
distribution graphs to conduct the performance analysis of RNSC behaviour compared with Markov
clustering (MCL) algorithm. Extensive experimental results on several synthetic and real power-law
distribution datasets reveal the effectiveness of our approach to comparative performance measure of
these algorithms on the basis of cost of clustering, cluster size, modularity index of clustering results and
normalized mutual information (NMI).
This document summarizes an experiment on network designing and studying different topologies. The experiment involves using Packet Tracer to implement bus, ring, star, mesh, and hybrid network topologies. For the mesh topology implementation, 4 laptops and 4 switches are connected in a mesh configuration with each device having a unique IP address. Messages are sent between devices and the transmission is observed to verify proper mesh network implementation. Completing all procedures carefully results in successful message transmission between devices in the mesh network topology.
This document presents a method for downsampling point cloud data to enable real-time scan matching for autonomous vehicles. It introduces two new downsampling algorithms: Ring Random Filter and Distance Voxel Grid Filter. It evaluates the algorithms based on execution time of scan matching, downsampling time, and relative error compared to raw point cloud data from tests in suburban and city environments. The results show the downsampling enables real-time scan matching with relative errors generally less than 10 cm.
Clustering Using Shared Reference Points Algorithm Based On a Sound Data ModelWaqas Tariq
A novel clustering algorithm CSHARP is presented for the purpose of finding clusters of arbitrary shapes and arbitrary densities in high dimensional feature spaces. It can be considered as a variation of the Shared Nearest Neighbor algorithm (SNN), in which each sample data point votes for the points in its k-nearest neighborhood. Sets of points sharing a common mutual nearest neighbor are considered as dense regions/ blocks. These blocks are the seeds from which clusters may grow up. Therefore, CSHARP is not a point-to-point clustering algorithm. Rather, it is a block-to-block clustering technique. Much of its advantages come from these facts: Noise points and outliers correspond to blocks of small sizes, and homogeneous blocks highly overlap. This technique is not prone to merge clusters of different densities or different homogeneity. The algorithm has been applied to a variety of low and high dimensional data sets with superior results over existing techniques such as DBScan, K-means, Chameleon, Mitosis and Spectral Clustering. The quality of its results as well as its time complexity, rank it at the front of these techniques.
CLIQUE is an algorithm for subspace clustering of high-dimensional data. It works in two steps: (1) It partitions each dimension of the data space into intervals of equal length to form a grid, (2) It identifies dense units within this grid and finds clusters as maximal sets of connected dense units. CLIQUE efficiently discovers clusters by identifying dense units in subspaces and intersecting them to obtain candidate dense units in higher dimensions. It automatically determines relevant subspaces for clustering and scales well with large, high-dimensional datasets.
The document summarizes research on developing efficient convolutional neural network architectures called MobileNets that are well-suited for mobile and embedded vision applications. The key ideas are using depthwise separable convolutions to factorize standard convolutions and using a width multiplier and resolution multiplier to control model size. Experiments show MobileNets achieve higher accuracy and speed than prior mobile networks on image classification and object detection tasks while having a smaller memory footprint.
Path constrained data gathering scheme for wireless sensor networks with mobi...ijwmn
This document summarizes a research paper on using mobile elements to gather data in wireless sensor networks. The paper proposes a heuristic algorithm called Graph Partitioning (GP) to address the K-Hop tour planning (KH-tour) problem of designing the shortest possible tour for a mobile element to visit a subset of sensor nodes called caching points, such that any node is at most k hops from the tour.
The GP algorithm works by first partitioning the sensor network graph into partitions where the depth of each partition is bounded by k hops. It then identifies the minimum number of caching points needed in each partition. Finally, it constructs the mobile element's tour to visit all the identified caching points.
Lbdp localized boundary detection and parametrization for 3 d sensor networksNexgen Technology
Ecruitment Solutions (ECS) is one of the leading Delhi based Software Development & HR Consulting Firm, which is assessed at the level of ISO 9001:2008 standard. ECS offers an awesome project and product based solutions to many customers around the globe.
In addition, ECS has also widened its wings by the way consummating academic projects especially for the final year professional degree students in India. ECS consist of a technical team that has solved many IEEE papers and delivered world-class solutions .
M.Phil Computer Science Mobile Computing ProjectsVijay Karan
This document lists several M.Phil Computer Science Mobile Computing project titles and abstracts. It describes projects related to throughput and delay analysis using MIMO in wireless networks, minimum bandwidth reservations for periodic streams in wireless real-time systems, converge-cast capacity and delay tradeoffs, optimal location updates in mobile ad hoc networks, fast data collection in tree-based wireless sensor networks, and optimal scheduling for multi-radio multi-channel cognitive cellular networks. The projects involve using techniques like MIMO, bandwidth reservations, converge-cast analysis, location updates, data collection trees, and multi-radio scheduling to analyze performance metrics in wireless networks and mobile computing systems.
This document summarizes a research paper that analyzes optimal multicast capacity and delay tradeoffs in mobile ad hoc networks (MANETs) under different node mobility models. It studies four node mobility models (two with two-dimensional mobility and two with one-dimensional mobility) and two mobility timescales (fast and slow mobility relative to data transmission). The paper characterizes the optimal multicast capacity under each model given a delay constraint and develops a scheme to achieve throughput close to the upper bound. It also extends the analysis to heterogeneous networks with infrastructure support like base stations.
The document discusses node localizability in wireless ad hoc and sensor networks. It introduces the concept of node localizability, which allows analyzing how many nodes can be located in sparsely or moderately connected networks. The study derives necessary and sufficient conditions for node localizability to determine if a specific node can be located. Experimental results on a real-world system show that node localizability provides useful guidance for network deployment and location-based services.
List of Parallel and Distributed System IEEE 2014 Projects. It Contains the IEEE Projects in the Domain Parallel and Distributed System for the year 2014
Parallel and Distributed System IEEE 2014 ProjectsVijay Karan
List of Parallel and Distributed System IEEE 2014 Projects. It Contains the IEEE Projects in the Domain Parallel and Distributed System for the year 2014
This document proposes a hybrid optimization algorithm using ant colony optimization and particle swarm optimization to solve the multiobjective multicast routing problem in wireless sensor networks. The goal is to optimize two objectives simultaneously - end-to-end delay and total transmitted power. ACO and PSO are combined to find Pareto-optimal solutions efficiently. Simulation results show the algorithm can find near-optimal solutions for minimizing delay and power consumption when routing data from a source to multiple destinations in wireless sensor networks.
R sk nn- knn search on road networks by incorporating social influencefinalsemprojects
This document proposes a new problem called k-nearest neighbor (kNN) search on road networks by incorporating social influence (RSkNN). It aims to find the k nearest objects to a query user on a road network while considering the query user's social information and social influence. Three efficient index-based search algorithms are proposed: road network-based, social network-based, and a hybrid approach. The algorithms aim to speed up computation of social influence over large road and social networks. The paper evaluates the efficiency and effectiveness of the solutions using real road and social network data.
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/
Extend Your Journey: Considering Signal Strength and Fluctuation in Location-...Chih-Chuan Cheng
Reducing the communication energy is essential to facilitate the growth of emerging mobile applications. In this paper, we introduce signal strength into location-based applications to reduce the energy consumption of mobile devices for data reception. First, we model the problem of data fetch scheduling, with the objective of minimizing the energy required to fetch location-based information without impacting the application’s semantics adversely. To solve the fundamental problem, we propose a dynamic programming algorithm and prove its optimality in terms of energy savings. Then, we perform postoptimal analysis to explore the tolerance of the algorithm to signal strength fluctuations. Finally, based on the algorithm, we consider implementation issues.We have also developed a virtual tour system integrated with existing web applications to validate the practicability of the proposed concept. The results of experiments conducted based on real-world case studies are very encouraging and demonstrate the applicability of the proposed algorithm towards signal strength fluctuations.
Skyline Query Processing using Filtering in Distributed EnvironmentIJMER
This document summarizes a research paper about skyline query processing in distributed databases. Skyline queries return multidimensional data points that are not dominated by other points. In distributed databases, skyline queries must be processed across multiple data sites. The paper proposes using multiple filtering points selected from each local skyline result to reduce the number of false positive results and communication costs between sites. Two heuristics called MaxSum and MaxDist are described for selecting filtering points that maximize their combined dominating potential across sites to improve distributed skyline query processing performance.
IoT-Daten: Mehr und schneller ist nicht automatisch besser.
Über optimale Sampling-Strategien, wie man rechnen kann, ob IoT sich rechnet, und warum es nicht immer Deep Learning und Real-Time-Analytics sein muss. (Folien Deutsch/Englisch)
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
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.
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This document discusses efficient rendezvous algorithms for wireless sensor networks with mobile base stations. It proposes an approach where select sensor nodes act as rendezvous points, buffering and aggregating data from other sensors. These rendezvous points then transfer the collected data to the base station when it arrives, combining the advantages of controlled mobility and in-network caching. Algorithms are presented for rendezvous design with mobile base stations having variable or fixed tracks. Both theoretical analysis and simulations validate that this approach can achieve a good balance between energy savings and reduced data collection latency in the network.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
This document discusses preventing private information inference attacks on social networks. It explores how released social networking data could be used to predict undisclosed private information about individuals, such as their political affiliation or sexual orientation. It then describes three sanitization techniques that could be used to decrease the effectiveness of such attacks. An experiment is conducted applying these techniques to a Facebook dataset to attempt to discover sensitive attributes through collective inference and show that the sanitization methods decrease the effectiveness of local and relational classification algorithms.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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Find out more about ISO training and certification services
Training: ISO/IEC 27001 Information Security Management System - EN | PECB
ISO/IEC 42001 Artificial Intelligence Management System - EN | PECB
General Data Protection Regulation (GDPR) - Training Courses - EN | PECB
Webinars: https://pecb.com/webinars
Article: https://pecb.com/article
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For more information about PECB:
Website: https://pecb.com/
LinkedIn: https://www.linkedin.com/company/pecb/
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Slideshare: http://www.slideshare.net/PECBCERTIFICATION
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
Gender and Mental Health - Counselling and Family Therapy Applications and In...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
Gender and Mental Health - Counselling and Family Therapy Applications and In...
4
1. Impulse Technologies
Beacons U to World of technology
044-42133143, 98401 03301,9841091117 ieeeprojects@yahoo.com www.impulse.net.in
Continuous Detour Queries in Spatial Networks (world in a nut
shell )
Abstract
We study the problem of finding the shortest route between two locations
that includes a stopover of a given type. An example scenario of this problem is
given as follows: “On the way to Bob's place, Alice searches for a nearby take-
away Italian restaurant to buy a pizza.” Assuming that Alice is interested in
minimizing the total trip distance, this scenario can be modeled as a query where
the current Alice's location (start) and Bob's place (destination) function as query
points. Based on these two query points, we find the minimum detour object
(MDO), i.e., a stopover that minimizes the sum of the distances: 1) from the start to
the stopover, and 2) from the stopover to the destination. In a realistic location-
based application environment, a user can be indecisive about committing to a
particular detour option. The user may wish to browse multiple (k) MDOs before
making a decision. Furthermore, when a user moves, the k{rm MDO} results at
one location may become obsolete. We propose a method for continuous detour
query (CDQ) processing based on incremental construction of a shortest path tree.
We conducted experimental studies to compare the performance of our proposed
method against two methods derived from existing k-nearest neighbor querying
techniques using real road-network data sets. Experimental results show that our
proposed method significantly outperforms the two competitive techniques.
Your Own Ideas or Any project from any company can be Implemented
at Better price (All Projects can be done in Java or DotNet whichever the student wants)
1