• Journal of Communications and Networks
• /
• v.16 no.6
• /
• pp.613-619
• /
• 2014

Multicast routing algorithms designed for wireline networks are not suitable for wireless environments since they cannot efficiently exploit the inherent characteristics of wireless networks such as the broadcast advantage. There are many routing protocols trying to use these advantages to decrease the number of required transmissions or increase the reception probability of data (e.g., opportunistic routing).Reducing the number of transmissions in a multicast tree directly decreases the bandwidth consumption and interference and increases the overall throughput of the network. In this paper, we introduce a distributed multicast routing protocol for wireless mesh networks called NCast which take into account the data delivery delay and path length when constructing the tree. Furthermore, it effectively uses wireless broadcast advantage to decrease the number of forwarding nodes dynamically when a new receiver joins the tree.Our simulation results show that NCast improves network throughput, data delivery ratio and data delivery delay in comparison with on demand multicast routing protocol. It is also comparable with multichannel multicast even though it does not use channeling technique which eliminates the interference inherently.

• Journal of information and communication convergence engineering
• /
• v.10 no.3
• /
• pp.264-268
• /
• 2012

Tree-based structures offer assured optimal paths from the data source to the sink. Shortest routes are disregarded since these do not consider the remaining energy level of the nodes. This shortens the lifetime of the whole network. Most tree-based routing protocols, although aware of the nodes' energy, do not consider an energy aware sleep scheduling scheme. We propose an energy-aware sleep scheduling (EASS) scheme that will improve the sleep scheduling scheme of an existing tree-based routing protocol. An energy harvesting structure will be implemented on the wireless sensor network. The depth of sleep of every node will be based on the harvested energy.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.11
• /
• pp.1138-1143
• /
• 2006

Sensor deployment is an important issue in the mobile wireless sensor network. In this paper, we propose a deployment algorithm for mobile sensor network to spread out mobile sensor nodes widely as well as regularly. Since the proposed algorithm uses tree topology in deploying the sensor nodes, calculating power as well as spreading speed can be reduced compare to other deployment algorithms. The performance of the proposed algorithm is simulated using NS-2 simulator and demonstrated.

• ETRI Journal
• /
• v.27 no.4
• /
• pp.355-366
• /
• 2005

Automatic discovery of physical topology plays a crucial role in enhancing the manageability of modern metro Ethernet networks. Despite the importance of the problem, earlier research and commercial network management tools have typically concentrated on either discovering logical topology, or proprietary solutions targeting specific product families. Recent works have demonstrated that network topology can be determined using the standard simple network management protocol (SNMP) management information base (MIB), but these algorithms depend on address forwarding table (AFT) entries and can find only spanning tree paths in an Ethernet mesh network. A previous work by Breibart et al. requires that AFT entries be complete; however, that can be a risky assumption in a realistic Ethernet mesh network. In this paper, we have proposed a new physical topology discovery algorithm which works without complete knowledge of AFT entries. Our algorithm can discover a complete physical topology including inactive interfaces eliminated by the spanning tree protocol in metro Ethernet networks. The effectiveness of the algorithm is demonstrated by implementation.

• Proceedings of the IEEK Conference
• /
• 2001.06c
• /
• pp.63-66
• /
• 2001

In this paper, We propose the new interconnection network which is designed to edge numbering labeling using postorder traversal which can reduce diameter when it has same node number with Hypercube, which can reduce total node numbers considering node degree and diameter on Fibonacci trees and its jump sequence of circulant is Fibonacci numbers. It has a simple (shortest oath)routing algorithm, diameter, node degree. It has a spaning subtree which is Fibonacci tree and it is embedded to Fibonacci tree. It is compared with Hypercube. We improve diameter compared with Hypercube.

• Journal of Agricultural Extension & Community Development
• /
• v.16 no.4
• /
• pp.939-965
• /
• 2009

The Machine Learning has been identified as a promising approach to knowledge-based system development. This study aims to examine the ability of machine learning techniques for farmer's decision making and to develop the reference model for using pig farm data. We compared five machine learning techniques: logistic regression, decision tree, artificial neural network, k-nearest neighbor, and ensemble. All models are well performed to predict the sow's productivity in all parity, showing over 87.6% predictability. The model predictability of total litter size are highest at 91.3% in third parity and decreasing as parity increases. The ensemble is well performed to predict the sow's productivity. The neural network and logistic regression is excellent classifier for all parity. The decision tree and the k-nearest neighbor was not good classifier for all parity. Performance of models varies over models used, showing up to 104% difference in lift values. Artificial Neural network and ensemble models have resulted in highest lift values implying best performance among models.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.19 no.1
• /
• pp.109-118
• /
• 2023

Data-based analysis methods have become used more for estimating or predicting housing prices, and neural network models and decision trees in the field of big data are also widely used more and more. Neural network models are often evaluated to be superior to existing statistical models in terms of estimation or prediction accuracy. However, there is ambiguity in determining the input feature of the input layer of the neural network model, that is, the type and number of input features, and decision trees are sometimes used to overcome these disadvantages. In this paper, we evaluate the existing methods of using decision trees and propose the method of using decision trees to prioritize input feature selection in neural network models. This can be a complementary or combined analysis method of the neural network model and decision tree, and the validity was confirmed by applying the proposed method to house price estimation. Through several comparisons, it has been summarized that the selection of appropriate input characteristics according to priority can increase the estimation power of the model.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.3 no.6
• /
• pp.612-627
• /
• 2009

The high-level contribution of this paper is to illustrate the effectiveness of using graph theory tree traversal algorithms (pre-order, in-order and post-order traversals) to generate the chain of sensor nodes in the classical Power Efficient-Gathering in Sensor Information Systems (PEGASIS) data aggregation protocol for wireless sensor networks. We first construct an undirected minimum-weight spanning tree (ud-MST) on a complete sensor network graph, wherein the weight of each edge is the Euclidean distance between the constituent nodes of the edge. A Breadth-First-Search of the ud-MST, starting with the node located closest to the center of the network, is now conducted to iteratively construct a rooted directed minimum-weight spanning tree (rd-MST). The three tree traversal algorithms are then executed on the rd-MST and the node sequence resulting from each of the traversals is used as the chain of nodes for the PEGASIS protocol. Simulation studies on PEGASIS conducted for both TDMA and CDMA systems illustrate that using the chain of nodes generated from the tree traversal algorithms, the node lifetime can improve as large as by 19%-30% and at the same time, the energy loss per node can be 19%-35% lower than that obtained with the currently used distance-based greedy heuristic.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.8 no.5
• /
• pp.1089-1095
• /
• 2004

The genetic algorithms have been used to take a near optimal solution because The generation of the optimal Steiner tree from a given network is NP-hard problem,. The chromosomes in genetic algorithm are represented with the floating point representation instead of the existing binary string for solving this problem. A spanning tree was obtained from a given network using Prim's algorithm. Then, the new Steiner point was computed using genetic algorithm with the chromosomes in the floating point representation, and it was added to the tree for approaching the result. After repeating these evolving steps, the near optimal Steiner tree was obtained. Using this method, the tree is quickly and exactly approached to the near optimal Steiner tree compared with the existing genetic algorithms using binary string.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.1
• /
• pp.171-192
• /
• 2017

The change of any element in the network is possible to cause performance degradation of the multicast network. So it is necessary to optimize the topology path through the multicast update strategy, which directly affects the performance and user experience of the overlay multicast. In view of the above, a new multicast tree update strategy based on perturbation theory Musp (Multicast Update Strategy based on Perturbation theory) is proposed, which reduces the data transmission interruption caused by the multicast tree update and improves user experiences. According to the multicast tree's elements performance and the topology structure, the Musp strategy defines the multicast metric matrix and based on the matrix perturbation theory it also defines the multicast fluctuation factor. Besides it also demonstrates the calculability of the multicast fluctuation factor presents the steps of the Musp algorithm and calculates the complexity. The experimental results show that compared with other update strategies, as for the sensitivity of the multicast fluctuation factor's energized multicast tree to the network disturbance, the maximum delay of the Musp update strategy is minimal in the case of the local degradation of network performance.