• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.1-7
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• 2019

In this paper, we implemented a Wi-Fi based cluster system using raspberry pi for multidisciplinary education. The cluster implementation on the desktop was more difficult to maintain the complexity, big size, high price, power consumption as the number of nodes increased. In this paper, we implemented a cluster using Raspberry Pi, which is developed for educational purposes, to reduce the cost of connecting nodes. In addition, the complexity of system construction is reduced by replacing the connection between each node with Wi-Fi. Also, the inconvenience of configuration due to node increase was reduced. It is expected that the implementation of the cluster will be a good alternative in the educational environment where distributed processing and parallel processing are performed in the embedded environment. Also, it is confirmed that it can be applied to the multidisciplinary education.

• Journal of Technology Innovation
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• v.13 no.2
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• pp.23-43
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• 2005

Industrial clusters are geographical concentrations of interconnected companies, specialised suppliers, service providers, firms in related industries, and associated institutions (for example, universities, standard agencies, and trade associations) that combine to create new products and/or services in specific lines of business. At present, the concept of industrial cluster becomes very popular worldwide, policy makers at national, regional and local levels and business people in both forerunner and latecomer countries are keen to implement the cluster concept as an economic development model. Though understanding of clusters and related promoting policies varies from one place to another, the underlying benefits of clusters from collective learning and knowledge spillovers between participating actors strongly attract the attention of these people. In Thailand, a latecomer country in terms of technological catching up, the cluster concept has been used as a means to rectify weakness and fragmentation of its innovation systems. The present Thai government aspires to apply the concept to promote both high-tech manufacturing clusters, services clusters and community-based clusters at the grass-root level. This paper analyses three very different clusters in terms of technological sophistication and business objectives, i.e., hard disk drive, software and chili paste. It portrays their significant actors, the extent of interaction among them and the evolution of the clusters. Though are very dissimilar, common characteristics attributed to qualified success are found. Main driving forces of the three clusters are cluster intermediaries. Forms of these organizations are different from a government research and technology organization (RTO), an industrial association, to a self-organised community-based organization. However, they perform similar functions of stimulating information and knowledge sharing, and building trust among participating firms/individuals in the clusters. Literature in the cluster studies argues that government policies need to be cluster specific. In this case, the best way to design and implement cluster-specific policies is through working closely with intermediaries and strengthening their institutional especially in linking member firms/individuals to other actors in clusters such as universities, government R&D institutes, and financial institutions.

• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.153-166
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• 2013

A hierarchical time division multiple access (HTDMA) medium access control (MAC) protocol is proposed for clustered mobile underwater acoustic networks. HTDMA consists of two TDMA scheduling protocols (i.e., TDMA1 and TDMA2) in order to accommodate mobile underwater nodes (UNs). TDMA1 is executed among surface stations (e.g., buoys) using terrestrial wireless communication in order to share mobility information obtained from UNs which move cluster to cluster. TDMA2 is executed among UNs, which send data to their surface station as a cluster head in one cluster. By sharing mobility information, a surface station can instantaneously determine the number of time slots in a TDMA2 frame up to as many as the number of UNs which is currently residing in its cluster. This can enhance delay and channel utilization performance by avoiding the occurrence of idle time slots. We analytically investigate the delay of HTDMA, and compare it with that of wellknown contention-free and contention-based MAC protocols, which are TDMA and Slotted-ALOHA, respectively. It is shown that HTDMA remarkably decreases delay, compared with TDMA and Slotted-ALOHA.

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.49-54
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• 2005

With the recent advances in Micro Electro Mechanical System (MEMS) technology, low cost and low power consumption wireless micro sensor nodes have become available. However, energy-efficient routing is one of the most important key technologies in wireless sensor networks as sensor nodes are highly energy-constrained. Therefore, many researchers have proposed routing protocols for sensor networks, especially cluster-based routing protocols, which have many advantages such as reduced control messages, bandwidth re-usability, and improved power control. Some protocols use information on the locations of sensor nodes to construct clusters efficiently. However, it is rare that all sensor nodes know their positions. In this article, we propose another cluster-based routing protocol for sensor networks. This protocol does not use information concerning the locations of sensor nodes, but uses the remaining energy of sensor networks and the desirable number of cluster heads according to the circumstances of the sensor networks. From performance simulation, we found that the proposed protocol shows better performance than the low-energy adaptive clustering hierarchy (LEACH).

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.359-373
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• 2019

For clustering large-scale data, which cannot be loaded into memory entirely, incremental clustering algorithms are very popular. Usually, these algorithms only concern the within-cluster compactness and ignore the between-cluster separation. In this paper, we propose two incremental fuzzy compactness and separation (FCS) clustering algorithms, Single-Pass FCS (SPFCS) and Online FCS (OFCS), based on a fuzzy scatter matrix. Firstly, we introduce two incremental clustering methods called single-pass and online fuzzy C-means algorithms. Then, we combine these two methods separately with the weighted fuzzy C-means algorithm, so that they can be applied to the FCS algorithm. Afterwards, we optimize the within-cluster matrix and betweencluster matrix simultaneously to obtain the minimum within-cluster distance and maximum between-cluster distance. Finally, large-scale datasets can be well clustered within limited memory. We implemented experiments on some artificial datasets and real datasets separately. And experimental results show that, compared with SPFCM and OFCM, our SPFCS and OFCS are more robust to the value of fuzzy index m and noise.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4228-4247
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• 2018

Many methods have been developed for the vehicles to create clusters in vehicular ad hoc networks (VANETs). Usually, nodes are vehicles in the VANETs, and they are dynamic in nature. Clusters of vehicles are made for making the communication between the network nodes. Cluster Heads (CHs) are selected in each cluster for managing the whole cluster. This CH maintains the communication in the same cluster and with outside the other cluster. The lifetime of the cluster should be longer for increasing the performance of the network. Meanwhile, lesser the CH's in the network also lead to efficient communication in the VANETs. In this paper, a novel algorithm for clustering which is based on the social behavior of Gray Wolf Optimization (GWO) for VANET named as Intelligent Clustering using Gray Wolf Optimization (ICGWO) is proposed. This clustering based algorithm provides the optimized solution for smooth and robust communication in the VANETs. The key parameters of proposed algorithm are grid size, load balance factor (LBF), the speed of the nodes, directions and transmission range. The ICGWO is compared with the well-known meta-heuristics, Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO) for clustering in VANETs. Experiments are performed by varying the key parameters of the ICGWO, for measuring the effectiveness of the proposed algorithm. These parameters include grid sizes, transmission ranges, and a number of nodes. The effectiveness of the proposed algorithm is evaluated in terms of optimization of number of cluster with respect to transmission range, grid size and number of nodes. ICGWO selects the 10% of the nodes as CHs where as CLPSO and MOPSO selects the 13% and 14% respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.1001-1008
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• 2015

Mobile Ad hoc Network(MANET) consists of a node that has mobility. In MANET, the node has routing, the node builds a network of their own, no dependent infrastructure. Topology are exchanged due to node mobility in MANET. For reducing the change of topology, hierarchical network algorithm has been investigated. In hierarchical network, cluster member node communicates through cluster head node. When the load-balancing of cluster head node is exceed, assigned cluster member node can't communicate with base station. To solve this problem, we proposed Load Tolerance algorithm. The proposed algorithm, when cluster member node can't send a message by cluster head node that exceed load-balancing, then the cluster member node sends a message by selected load tolerance node. Through a simulation, the proposed algorithm improves packet delivery ratio in cluster routing.

• Journal of Computing Science and Engineering
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• v.10 no.1
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• pp.1-8
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• 2016

The fuzzy c-means (FCM) is a frequently utilized algorithm at present. Yet, the clustering quality and convergence rate of FCM are determined by the initial cluster centers, and so an improved FCM algorithm based on canopy cluster concept to quickly analyze the dataset has been proposed. Taking advantage of the canopy algorithm for its rapid acquisition of cluster centers, this algorithm regards the cluster results of canopy as the input. In this way, the convergence rate of the FCM algorithm is accelerated. Meanwhile, the MapReduce scheme of the proposed FCM algorithm is designed in a cloud environment. Experimental results demonstrate the hybrid canopy-FCM clustering algorithm processed by MapReduce be endowed with better clustering quality and higher operation speed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4644-4661
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• 2015

Wireless sensor networks are often organized in the form of clusters leading to the new framework of WSN called cluster or hierarchical WSN where each cluster head is responsible for its own cluster and its members. These hierarchical WSN are prone to various routing layer attacks such as Black hole, Gray hole, Sybil, Wormhole, Flooding etc. These routing layer attacks try to spoof, falsify or drop the packets during the packet routing process. They may even flood the network with unwanted data packets. If one cluster head is captured and made malicious, the entire cluster member nodes beneath the cluster get affected. On the other hand if the cluster member nodes are malicious, due to the broadcast wireless communication between all the source nodes it can disrupt the entire cluster functions. Thereby a scheme which can detect both the malicious cluster member and cluster head is the current need. Abnormal energy consumption of nodes is used to identify the malicious activity. To serve this purpose a learning based energy prediction algorithm is proposed. Thus a two level energy prediction based intrusion detection scheme to detect the malicious cluster head and cluster member is proposed and simulations were carried out using NS2-Mannasim framework. Simulation results achieved good detection ratio and less false positive.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.2042-2060
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• 2013

In wireless sensor networks (WSNs), energy efficiency is one of the most essential design considerations, since sensor nodes are resource constrained. Group communication can reduce WSNs communication overhead by sending a message to multiple nodes in one packet. In this paper, in order to simultaneously resolve the transmission security and scalability in WSNs group communications, we propose a hierarchical cluster-based secure and scalable group key management scheme, called HRKT, based on logic key tree and route key tree structure. The HRKT scheme divides the group key into cluster head key and cluster key. The cluster head generates a route key tree according to the route topology of the cluster. This hierarchical key structure facilitates local secure communications taking advantage of the fact that the nodes at a contiguous place usually communicate with each other more frequently. In HRKT scheme, the key updates are confined in a cluster, so the cost of the key updates is reduced efficiently, especially in the case of massive membership changes. The security analysis shows that the HRKT scheme meets the requirements of group communication. In addition, performance simulation results also demonstrate its efficiency in terms of low storage and flexibility when membership changes massively.