Tai-Myoung Chung

CHEF: Cluster Head Election mechanism using Fuzzy logic in Wireless Sensor Networks

In designing the wireless sensor networks, the energy is the most important consideration because the lifetime of the sensor node is limited by the battery of it. To overcome this demerit many research have been done. The clustering is the one of the representative approaches. In the clustering, the cluster heads gather data from nodes, aggregate it and send the information to the base station. In this way, the sensor nodes can reduce communication overheads that may be generated if each sensor node reports sensed data to the base station independently. LEACH is one of the most famous clustering mechanisms. It elects a cluster head based on probability model. This approach may reduce the network lifetime because LEACH does not consider the distribution of sensor nodes and the energy remains of each node. However, using the location and the energy information in the clustering can generate big overheads. In this paper we introduce CHEF - cluster head election mechanism using fuzzy logic. By using fuzzy logic, collecting and calculating overheads can be reduced and finally the lifetime of the sensor networks can be prolonged. To prove efficiency of CHEF, we simulated CHEF compared with LEACH using the matlab. Our simulation results show that CHEF is about 22.7% more efficient than LEACH.

The Concentric Clustering Scheme for Efficient Energy Consumption in the PEGASIS

The wireless sensor network is a type of the wireless ad-hoc networks. It is composed of a collection of sensor nodes. Sensor nodes collect and deliver necessary data in response to users specific requests. It is expected to apply the wireless sensor network technology to various application areas such as the health, military and home. However, because of several limitations of sensor nodes, the routing protocols used in the wireless ad-hoc network are not suitable for the wireless sensor networks. For this reasons, many novel routing protocols for the wireless sensor networks are proposed recently. One of these protocols, the PEGASIS (power-efficient gathering in sensor information systems) protocol is a chain-based protocol. In general, the PEGASIS protocol presents twice or more performance in comparison with the LEACH (low energy adaptive clustering hierarchy) protocol. However, the PEGASIS protocol causes the redundant data transmission since one of nodes on the chain is selected as the head node regardless of the base stations location. In this paper, we propose the enhanced PEGASIS protocol based on the concentric clustering scheme to solve this problem. The main idea of the concentric clustering scheme is to consider the location of the base station to enhance its performance and to prolong the lifetime of the wireless sensor networks. As simulation results, the enhanced PEGASIS protocol using the concentric clustering scheme performs better than the current PEGASIS protocol by about 35%.

Cost analysis of IP mobility management protocols for consumer mobile devices

The rapid progress being made in mobile device technologies that enable consumers can enjoy Internet based multimedia/business services in travel will rely on IP mobility management protocols for enabling mobile services. The performance of mobility management protocols will largely effect on consumers¿ experiences. In this paper, an analytical cost model is developed for evaluating the performance of the existing IP mobility management protocols including the recently developed Proxy Mobile IPv6 (PMIPv6); they are analyzed and compared in terms of signaling cost, packet delivery cost, tunneling cost, and total cost. The conducted results identify each mobility management protocol¿s strengths and weaknesses that could be used to facilitate decision-making for consumer network design. In addition, suggestions for developing further PMIPv6 improvements are provided.

Comparative Handover Performance Analysis of IPv6 Mobility Management Protocols

IPv6 mobility management is one of the most challenging research topics for enabling mobility service in the forthcoming mobile wireless ecosystems. The Internet Engineering Task Force has been working for developing efficient IPv6 mobility management protocols. As a result, Mobile IPv6 and its extensions such as Fast Mobile IPv6 and Hierarchical Mobile IPv6 have been developed as host-based mobility management protocols. While the host-based mobility management protocols were being enhanced, the network-based mobility management protocols such as Proxy Mobile IPv6 (PMIPv6) and Fast Proxy Mobile IPv6 (FPMIPv6) have been standardized. In this paper, we analyze and compare existing IPv6 mobility management protocols including the recently standardized PMIPv6 and FPMIPv6. We identify each IPv6 mobility management protocols characteristics and performance indicators by examining handover operations. Then, we analyze the performance of the IPv6 mobility management protocols in terms of handover latency, handover blocking probability, and packet loss. Through the conducted numerical results, we summarize considerations for handover performance.

A comparative performance analysis on Hierarchical Mobile IPv6 and Proxy Mobile IPv6

This paper presents comparative results on Hierarchical Mobile IPv6 and Proxy Mobile IPv6. The two mobility support protocols have similar hierarchical mobility management architectures but there are, however, clearly different perceptions: Hierarchical Mobile IPv6 has specific properties of a host-based mobility support protocol, whereas Proxy Mobile IPv6 is based on a network-based mobility support protocol. Thus, it is important to reveal their mobility characteristics and performance impact factors. In this paper, a cost based evaluation model is developed that evaluates the location update cost, the packet delivery cost, and the wireless power consumption cost based on the protocol operations used. Then, the numerical results are presented in where impacts of the various system parameters are evaluated. The results demonstrate that Proxy Mobile IPv6 always outperforms Hierarchical Mobile IPv6 due to its ability to avoid the mobility signaling sent by the mobile host, and its reduced tunneling overhead during communications with other nodes.

How much do we gain by introducing route optimization in Proxy Mobile IPv6 networks

Proxy Mobile IPv6 has been developed from the concept of network-based mobility support protocol in the Internet Engineering Task Force. The recently published specification of Proxy Mobile IPv6 only focuses on the mobility support without a mobile host’s participation in the mobility signaling. Then, route optimization issues are left in the basket for further works. In this paper, we explore the existing route optimization proposals that are analyzed and matched against a list of functional and operational angles. Then, the chosen two route optimization proposals are evaluated in terms of signaling cost, packet delivery cost, total cost, and service blocking probability. Through the provided analysis results, we demonstrate that route optimization solves the ineffective routing path problem when the mobile host communicates with its corresponding host and argue that the scalability of Proxy Mobile IPv6 architecture is also improved due to the distributed routing path. In addition, the cost model developed in this paper would be a reference model in order to facilitate decision making for further route optimization design.

Effective Value of Decision Tree with KDD 99 Intrusion Detection Datasets for Intrusion Detection System

A decision tree is a outstanding method for the data mining. In intrusion detection systems (IDSs), the data mining techniques are useful to detect the attack especially in anomaly detection. For the decision tree, we use the DARPA 98 Lincoln Laboratory Evaluation Data Set (DARPA Set) as the training data set and the testing data set. KDD 99 Intrusion Detection data set is also based on the DARPA Set. These three entities are widely used in IDSs. Hence, we describe the total process to generate the decision tree learned from the DARPA Sets. In this paper, we also evaluate the effective value of the decision tree as the data mining method for the IDSs, and the DARPA Set as the learning data set for the decision trees.

Context-Role based access control for context-aware application

The rapid growth of wireless network technology and the deployment of mobile computing devices have enabled the construction of pervasive computing environment. In pervasive computing environment, it is proliferated that many new applications that provide active and intelligent services by context information are collected by pervasive sensor devices. These new applications called context-aware applications must require new security mechanisms and policies different from typical ones. Specially, access control mechanism supports security policy that is based on context information, in order to provide automating context-aware services. So, this paper analyzes various access control mechanisms and proposes a context-role based access control mechanism for context-aware application.

A comparative signaling cost analysis of Hierarchical Mobile IPv6 and Proxy Mobile IPv6

In this paper, we present a comparative signaling cost analysis of hierarchical mobile IPv6 and proxy mobile IPv6. The two mobility support protocols have a similar hierarchical mobility management architecture. They, however, are clearly different: Hierarchical mobile IPv6 has a specific properties of host-based mobility support protocol and proxy mobile IPv6 is a kind of network-based mobility support protocols. Thus, it is important to reveal their mobility characters and performance impact factors. In this paper, we develop a cost model that evaluates the location update cost and the packet delivery cost based on protocol operations. Then, we present the numerical results in where the impacts of various system parameters are evaluated.

Attribute Relationship Evaluation Methodology for Big Data Security

There has been an increasing interest in big data and big data security with the development of network technology and cloud computing. However, big data is not an entirely new technology but an extension of data mining. In this paper, we describe the background of big data, data mining and big data features, and propose attribute selection methodology for protecting the value of big data. Extracting valuable information is the main goal of analyzing big data which need to be protected. Therefore, relevance between attributes of a dataset is a very important element for big data analysis. We focus on two things. Firstly, attribute relevance in big data is a key element for extracting information. In this perspective, we studied on how to secure a big data through protecting valuable information inside. Secondly, it is impossible to protect all big data and its attributes. We consider big data as a single object which has its own attributes. We assume that a attribute which have a higher relevance is more important than other attributes.