Youngmi Kwon

Adaptive and Energy Efficient Clustering Algorithm for Event-Driven Application in Wireless Sensor Networks (AEEC)

Wireless sensor networks (WSNs) consist of a large number of small, low data rate and inexpensive nodes that communicate in order to sense or control a physical phenomenon. The major difference between the WSN and the traditional wireless network is that sensors are very sensitive to energy consumption. Moreover, the performance of the sensor network applications highly depends on the lifetime of the network and we expect the lifetime of several months to several years. Thus, energy saving is crucial in designing long-lived wireless sensor networks. Many researchers have focused on developing energy efficient cluster based protocols for WSNs, but there has not been much research on event driven WSNs and, their focus is on continuous driven networks. In this paper, we propose a modified algorithm of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol which is a well known energy efficient clustering algorithm for WSNs. Our modified protocol called “Adaptive and Energy Efficient Clustering Algorithm for Event-Driven Application in Wireless Sensor Networks (AEEC)” is aimed at prolonging the lifetime of a sensor network by balancing energy usage of the nodes. AEEC makes the nodes with more residual energy have more chances to be selected as cluster head. Also, we use elector nodes which take the responsibility of collecting energy information of the nearest sensor nodes and selecting the cluster head. We compared the performance of our AEEC algorithm with the LEACH protocol using simulations .

Efficient RBS in Sensor Networks

Sensor networks have emerged as an interesting and important research area in the last few years. In order to construct a wireless sensor network, synchronization of base stations is very important. As the synchronization mechanisms based on the purpose of the sensor network, the RBS (reference broadcast synchronization) and TDP (time-diffusion synchronization protocol) have been proposed. This paper compared and analyzed the performance of the RBS and TDP mechanisms according to the number of generated messages, the elapsed time for overall synchronization, the number of nodes to be synchronized from a reference node and the number of reference nodes in the wireless sensor network. In the simulation results based on the number of generated messages and the elapsed time in overall synchronization, TDP is far better than RBS. But, in the environments with small number of nodes, RBS is far more accurate than TDP. So, if it requires only few base nodes in the network and the more high synchronization accuracy is necessary, RBS mechanism is more preferable. However, the RBS has a disadvantage that does not consider energy requirement of sensor nodes and a new E-RBS (Efficient RBS) is proposed. E-RBS decreases the number of messages to be processed and saves the energy consumption, with a range of an acceptable accuracy. So, E-RBS can be used efficiently in such an environment as small home/office sensor networks with small base nodes

An Energy Efficient Clustering Algorithm for Event-Driven Wireless Sensor Networks (EECED)

Wireless sensor networks have found many applications in different areas, including environmental surveillance, intelligent building, health monitoring, intelligent transportations, etc. The sensor networks consist of numerous tiny autonomous wireless devices with limited energy and memory that monitor physical phenomena. Therefore, energy efficient algorithms and protocols have been one of the most challenging issues for WSNs. Many researchers have focused on developing energy efficient cluster based protocols for WSNs, but there has not been much research on event driven WSNs and, their focus is on continuous networks. In this paper, we propose a modified algorithm of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol which is a well known energy efficient clustering algorithm for WSNs. Our modified protocol called “Energy Efficient Clustering Algorithm for Event-Driven Wireless Sensor Networks (EECED)” is aimed at prolonging the lifetime of a sensor network by balancing energy usage of the nodes. EECED makes the nodes with more residual energy have more chances to be selected as cluster head. Also, we use elector nodes which take the responsibility of collecting energy information of the nearest sensor nodes and selecting the cluster head. We compared the performance of our EECED algorithm with the LEACH protocol using simulations.

Emergency Handling for MAC Protocol in Human Body Communication

The human body communication (HBC) is a technology that enables short range data communication using the human body as a medium, like an electrical wire. Thus it removes the need for a traditional antenna. HBC may be used as a type of data communication in body area network (BAN), while the devices are being in contact with body. One of important issues in BAN is an emergency alarm because it may be closely related to human life. For emergency data communication, the most critical factor is the time constraint. IEEE 802.15.6 specifies that the emergency alarm for the BAN must be notified in less than 1 sec and must provide prioritization mechanisms for emergency traffic and notification. As one type of BAN, the HBC must follow this recommendation, too. Existing emergency handling methods in BAN are based on the carrier sensing capability on radio frequencies to detect the status of channels. However, PHY protocol in HBC does not provide the carrier sensing. So the previous methods are not well suitable for HBC directly. Additionally, in the environment that the emergency rate is very low, the allocation of dedicated slot(s) for emergency in each superframe is very wasteful. In this work, we proposed specific emergency handling operation for human body communications medium access control (HBC-MAC) protocol to meet the emergency requirements for BAN. We also showed the optimal number of emergency slots for the various combinations of beacon intervals and emergency rates.

AEEC-Adaptive and Energy Efficient Clustering Algorithm for Content Based Wireless Sensor Networks

Wireless sensor network (WSN) has increasingly been used for many applications such as building distributed systems, military applications, remote environmental monitoring and target tracking among others. This has been enabled by the availability, particularly in recent years, of sensors that are smaller, cheaper and intelligent. However, sensor nodes operate on limited battery power, energy usage is a very important concern in a WSN. There has been significant research focus that revolves around harvesting and minimizing energy. In this paper, we propose a modified algorithm of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol for Content based WSNs. Our modified protocol called AEEC (Adaptive and Energy Efficient Clustering) algorithm is aimed at prolonging the lifetime of a sensor network by balancing energy usage of the nodes in content based WSNs. AEEC makes the nodes with more residual energy have more chances to be selected as cluster head. Hence, we avoided single node failure due to maximize connectivity of network. We compared the performance of our AEEC algorithm with the LEACH protocol using simulations.

Compensated Time Synchronization in WSN with Multiple Reference Nodes

Recent technological advances such as MEMS and pervasive deployment of low-power wireless sensor devices have led to large-scaled wireless sensor networks. Time synchronization is important in largely deployed sensor nodes for various purposes including sensor data fusion and energy-efficiency. The time_sync_error is occurred to many factors. The main factor is that accumulated time error as hop count increases in multi-hop wireless sensor network. In the environment of multiple reference nodes, the reference nodes should be synchronized exactly before starting the node synchronization in the network. This paper suggests improved accuracy of the TSync algorithm in the environment of multiple reference nodes, by setting Multi time reference node (MtrN) to compensate the time differences among multiple reference nodes themselves. The simulation shows that proposed protocol reduces the accumulated time_sync_error; so improves the overall accuracy in WSN.

A Vulnerability Assessment Tool Based on OVAL in Linux System

Open Vulnerability Assessment Language (OVAL) is a standard language which is used to detect the vulnerability of local system based on the system characteristics and configurations. It is suggested by MITRE. OVAL consists of XML schema and SQL query statements. XML schema defines the vulnarable points and SQL query detects the vulnerable and weak points. This pa-per designed and implemented the vulnerability assesment tool with OVAL to detect the weak points in Linux System. It has more readability, reliability, scalability and simplicity than traditional tools.

A development of intrusion detection and protection system using netfilter framework

Information can be leaked, changed, damaged and illegally used regardless of the intension of the information owner. Intrusion Detection Systems and Firewalls are used to protect the illegal accesses in the network. But these are the passive protection method, not the active protection method. They only react based on the predefined protection rules or only report to the administrator. In this paper, we develop the intrusion detection and protection system using Netfilter framework. The system makes the administrators management easy and simple. Furthermore, it offers active protection mechanism against the intrusions.

Impact of Base Station Location on Wireless Sensor Networks

Wireless sensor networks (WSNs) have attracted much attention in recent years due to their potential use in many applications such as surveillance, militant etc. Given the importance of such applications, maintaining a dependable operation of the network is a fundamental objective. In Wireless Sensor Networks, many algorithms have been devised to improve energy maintenance in a whole network. Most of them assume the location of the Base Station (BS) to be at the border of the network even though location of Base Station takes some role in overall performance of the network. So in this paper, we simulated WSN performance in energy consumption, throughput, packets delivery ratio and delay with different locations of BS. Simulation results showed the best performance when a Base Station is located in the center of the WSN field and the worst when a Base Station is in the corner of the WSN. Compared to the existing location assumption, with the best positioned BS, Cluster Heads consumed 69% and with the worst positioned BS, they consumed 127% in energy. When we build WSN, if we spend some higher cost for installing BS inside the network, its overall performance can be improved much.

EECED: An Energy Efficient Clustering Algorithm for Event-Driven Wireless Sensor Networks

In recent years, a new wave of networks labelled Wireless Sensor Networks (WSNs) has attracted a lot of attention from researchers in both academic and industrial communities. A WSN consists of a collection of sensor nodes and a base station connected through wireless channels, and can be used for many applications such as military application, building distributed systems, physical environment monitoring, and security surveillance among others. A big advantage of sensor networks is represented by ease of deployment, reducing installation cost, possibility to distribute the tiny sensors over a wide region, and larger fault tolerance (V. Loscri et al., 2005). However, despite the infinite scopes of wireless sensor networks applications, they are limited by the node battery lifetime. Such constraints combined with a typical deployment of large number of sensor nodes have posed many challenges to the design and management of sensor networks and necessitate energyawareness at all layers of the networking protocol stack (Q. Xue & A. Ganz, 2004). Therefore, energy efficient algorithms have been one of the most challenging issues for WSNs. Sensor nodes can be in one of four states, namely transmit, receive, idle and sleep. The largest part of a node’s energy is consumed while transmitting and receiving. Minimizing the number of communications by eliminating or aggregating redundant sensed data saves much amount of energy (L. B. Ruiz et al., 2003). Among these clustering sensor networks are a very attractive approach because clustering allows for scalability, data aggregation, and energy efficiency. In a clustering network, nodes are grouped into clusters and there are special nodes called cluster head. They are responsible for an efficient way to lower energy consumption within a cluster by performing data aggregation. In a heterogeneous sensor network, two or more different types of nodes with different battery energy and functionality are used. On the other hand, in homogeneous networks all the sensor nodes are identical in terms of battery energy and hardware complexity. As a result, network performance decreases since the cluster head nodes goes down before other nodes do. Thus dynamic, energy efficient and adaptive cluster head selection algorithm is very important. Sensor networks can be divided in two classes as event-driven and continuous dissemination networks according to the periodicity of communication (L. B. Ruiz et al., 9