Figure 7.10. TASC cluster s nodes distribution. in VS .NET

Create QR-Code in VS .NET Figure 7.10. TASC cluster s nodes distribution.
Figure 7.10. TASC cluster s nodes distribution.
Read QR Code 2d Barcode In .NET
Using Barcode Control SDK for .NET framework Control to generate, create, read, scan barcode image in VS .NET applications.
GRAPH-BASED APPROACHES FOR CLUSTERING IN WSN
Quick Response Code Generator In .NET Framework
Using Barcode creation for VS .NET Control to generate, create Denso QR Bar Code image in Visual Studio .NET applications.
2-hop environment. In a nonuniform deployment WSN, the node that tends to be the midmost related to all shortest communication paths (in terms of hops) gets the largest weight. Instead of incrementing the weight by one each time a node is used in a path, we increment the weight as a function of the distance a node contributes to the path.
Recognizing Quick Response Code In .NET
Using Barcode recognizer for VS .NET Control to read, scan read, scan image in .NET framework applications.
LISTING 2. Pseudocode for the TASC Algorithm
Barcode Printer In .NET
Using Barcode generator for VS .NET Control to generate, create barcode image in VS .NET applications.
public class TASC { int ID; double weight; TASC nominee, leader; int clusterSize; ArrayList clusterMembers; /* * 2HNeighborhood = Euclidean paths in the 2-hop neighborhood of the node * internode = Inter-node distance measurements * minClustSize = Minimum cluster size * Dr = Density reachability parameter */ public TASC(2HNeighborhood,internode,minClustSize,Dr){ //The node computes its own weight based on //2HNeighborhood weight = computeWeight(2HNeighborhood); broadcastToNeighborhood(weight); //all weights received If (receiveWeights()){ //finds the heaviest density reachable node nominee = findHDRNode(Dr); broadcastToNeighborhood(nominee); } //all nominations have been received If (receiveNominations()){ //Selects the closest nominee leader = findClosestNominee(); broadcastToNeighborhood(leader.ID, this.ID); } //this node is leader
Recognizing Barcode In VS .NET
Using Barcode scanner for VS .NET Control to read, scan read, scan image in Visual Studio .NET applications.
(Continued)
Making QR Code ISO/IEC18004 In Visual C#
Using Barcode creation for .NET Control to generate, create QR Code image in .NET framework applications.
CLUSTERING IN WIRELESS SENSOR NETWORKS: A GRAPH THEORY PERSPECTIVE
QR Code 2d Barcode Maker In .NET Framework
Using Barcode creator for ASP.NET Control to generate, create Denso QR Bar Code image in ASP.NET applications.
(LISTING 2. Continued)
QR Code JIS X 0510 Maker In Visual Basic .NET
Using Barcode encoder for VS .NET Control to generate, create QR Code ISO/IEC18004 image in .NET framework applications.
If (leader.ID == this.ID){ //Wait until election timeout while (!electionTimeOut); broadcastToNeighborhood(clusterMembers, clusterSize); } //cluster size is received If ((clusterSize = receiveClusterSize())!=0){ If (clusterSize < minClustSize){ //Selects the closest neighbor for which //clustersize >= minimum cluster size leader=selectClosestCluster (2HNeighborhood); //joins previous node s cluster; this.joinCluster(leader); } this.broadcastToNeighborhood(leader.ID, clustersize); } } }
Draw GTIN - 128 In VS .NET
Using Barcode generator for .NET framework Control to generate, create GTIN - 128 image in .NET applications.
The weight value calculated by the node is broadcasted to its 2-hop neighborhood. Since this is done by all nodes, each node also receives the weights of its 2-hop neighbors. By comparing the weights, each node nominates the node having biggest weight in the density-reachable subset of its 2-hop neighbors and broadcasts its nominee to its 2-hop neighborhood. After receiving all nominees in its 2-hop neighborhood, each node elects the closest nominee to its leader. Each node that ends up in a cluster where the total number of nodes is smaller than a prespeci ed minimum cluster size joins the closest cluster, where the number of nodes exceeds the required minimum cluster size. After creating the clusters, TASC uses an all-pairs-shortest path routing. Instead of trying to forward traf c to the neighboring node that is closest to the destination, TASC routing is based on distance measurements to extract information about the network topology. More speci cally, node weight is a measurement of two key quantities: (1) the frequency a node is found on the shortest path between pairs of nodes, and (2) the distance contribution of the edges of that node with respect to the total length of the path. As mentioned at the beginning of the section, creating balanced clusters is one of the main objectives for WSN. In reference 32, the authors propose an algorithm for clustering the sensor nodes such that each cluster (and its corresponding CH) is balanced and the total distance between sensor nodes and CH is minimized. Balancing the clusters is needed for evenly distributing the load on all master nodes. If there is
UPC-A Supplement 5 Generator In Visual Studio .NET
Using Barcode encoder for Visual Studio .NET Control to generate, create UPC Code image in VS .NET applications.
CLUSTER S CONSTRUCTION AND MAINTENANCE IN MOBILE ENVIRONMENTS
Painting Barcode In Visual Studio .NET
Using Barcode creator for .NET Control to generate, create bar code image in .NET applications.
no balance constraint, the authors propose the utilization of Voronoi Diagrams [7], by constructing it based on the number of CH deployed previously in the sensor eld. However, each CH can only manage a certain number of communication channels. In this case, trying to solve the k-clustering problem optimally helps to maintain the network s operation. This k-clustering problem attempts to group the sensor nodes such that each cluster is balanced and has exactly one CH. To solve the problem, the authors transform it into a min-cost ow instance by adding a source node s and a sink node t to G, both with in nite capacity. Each edge has a weight equal to the message transmission energy dissipation between the two end vertices. There are n directed edges from s to all vertices corresponding to sensors nodes. Similarly, there are k directed edges from vertices corresponding to CH to t. All edges incident to s or t have weight 0. Finally, nodes corresponding to sensors have capacity 1, while nodes corresponding to CH have capacity n . Each ow solution is corresponding to a k k-clustering solution. Constructing G and the corresponding k-clustering solution can be done in O(n.k) time. Hence, the k-clustering problem can be optimally solved in O((n + k)3 ) time. However, the major drawback of this proposal is that it assumes that the nodes are not randomly deployed in the sensor eld. This is not a valid assumption for the majority of WSN application.
Making Leitcode In Visual Studio .NET
Using Barcode maker for Visual Studio .NET Control to generate, create Leitcode image in .NET framework applications.
7.4 CLUSTER S CONSTRUCTION AND MAINTENANCE IN MOBILE ENVIRONMENTS Maintaining clusters as the topology changes is an issue that arises in mobile wireless sensor networks. A local change in the weight may result in a different vertex becoming a cluster head. As an example, if we are using IDSG , when two CH become adjacent, one of them has to abdicate. This and other event occurrences can generate a total reordering of the nodes in the WSN and create the necessity to have maintenance operations, which in turn may cause other changes to propagate to the network. Despite the evident impact of mobility issues in WSN, very few clustering proposals take it into account. Most proposals consider the nodes as stationary since designing mechanisms to solve the issue is a very challenging task. During the development of this survey, we only found three research papers involving mobility in the clustering techniques proposed for WSN using Graph Theory. References 33 35 are the subject of our next analysis in this section. The purpose is to analyze how those proposals approach the creation and maintenance of clusters in a mobile environment. 7.4.1 Zone-Based Clustering Chen and Liestman [33], present a modi cation to their Zonal weakly connected clustering algorithm, presented in reference 26, including cluster maintenance in the presence of network topology changes. In this new proposal, the cluster maintenance is divided into two layers: intrazonal (inside the zones) and interzonal (between zones, at the borders). One of the assumptions made to manage mobility is that all the changes occur sequentially and that the network can be restructured before the next
EAN / UCC - 13 Generation In C#.NET
Using Barcode generator for .NET framework Control to generate, create USS-128 image in VS .NET applications.
Bar Code Creator In Java
Using Barcode generation for Java Control to generate, create barcode image in Java applications.
Encode European Article Number 13 In .NET
Using Barcode creator for ASP.NET Control to generate, create EAN 13 image in ASP.NET applications.
Barcode Generator In Visual Studio .NET
Using Barcode maker for ASP.NET Control to generate, create bar code image in ASP.NET applications.
Barcode Generator In Visual Basic .NET
Using Barcode encoder for VS .NET Control to generate, create bar code image in .NET applications.