Suman Bhowmik

A Novel Fuzzy Sensing Model for Sensor Nodes in Wireless Sensor Network

To design an efficient Wireless Sensor Network application one need to understand the behavior of the sensor nodes deployed. To understand the behavior of a systemwe need a very good model, that can represent the system in amore realistic manner. There is a vagueness that we can identify in defining the sensing coverage of any sensor node. The human like reasoning that best suits for this vagueness is the fuzzy reasoning. Here in this paper, we are proposing a fuzzy based model and inference system to best way represent the sensing behavior of sensor nodes. Also, we propose a measure that can be used to check or compare the WSN system performance.

Fuzzy Logic Based Implementation for Forest Fire Detection Using Wireless Sensor Network

The detection and prevention of forest fire is a major problem now a days. Timely detection allows the prevention units to reach the fire in its initial stage and thus reduce the risk of spreading and the harmful impact on human and animal life. Because of the inadequacy of conventional forest fire detection on real time and monitoring accuracy the Wireless Sensor Network (WSN) is introduced. This paper proposes a fuzzy logic based implementation to manage the uncertainty in forest fire detection problem. Sensor nodes are used for detecting probability of fire with variations during different time in a day. The Sensor nodes sense temperature, humidity, light intensity, CO 2 density and time and send the information to the base station. This proposed system improves the accuracy of the forest fire detection and also provides a real time based detection system as all the input variables are collected in real time basis.

k-Fault Tolerant Topology Control in Wireless Sensor Network

In recent years research in wireless sensor network has gained immense importance. Fault tolerance is an important issue to be addressed in WSN application. Fault tolerance can be achieved at various levels of applications in WSNs. Specifically the categories of applications are: node placement, topology control, target and event detection, data gathering and aggregation and sensor monitoring. This paper proposed a distributed algorithm to control the topology of network to make it fault tolerant.

Fuzzy communication model for sensors in Wireless Sensor Network

Communication coverage is one of the very important problem of any Wireless Sensor Network (WSN) application. To get very good design and better performances we need to use a very efficient model that can truly represent the behavior of sensor nodes in respect of data communication. Qualitatively we can argue that there is a fuzziness in the communication behavior of sensors. In this paper we are proposing a fuzzy based communication model, find the membership function and inference rules that may truly represent the behavior of sensor nodes.

Energy Efficient Fuzzy Clustering in Wireless Sensor Network

The nodes used in wireless sensor network (WSN) are mostly battery operated and so energy is the most precious resource in any WSN application. Therefore, we need to develop algorithms which are energy efficient. In most WSN applications node density is made very high. Energy can be conserved if it is possible to turn off a substantial number of redundant nodes. Using clustering technique it is possible to turn off those nodes. In this chapter, we propose a fuzzy based, energy efficient clustering algorithm. We also find the time and communication complexities of the algorithm.

Convoy Tree Based Fuzzy Target Tracking in Wireless Sensor Network

One important application area of wireless sensor network (WSN) is tracking mobile target. When a target enters in a monitoring region and moves around it, the deployed WSN is used to collect information about the target and send it to the nearby base station. In this paper, we propose a fuzzy based target tracking algorithm (CTFTT). The algorithm constructs a convoy tree around the target and dynamically moves the tree along with the target by adding new nodes into the tree and removing old nodes from the tree. The expansion, contraction and reconfiguration of the tree is done using a fuzzy based sensing model. Important advantages are (1) convoy tree provides 100% coverage, (2) fuzzy mechanism helps to localize the evevts such as tree expansion, contraction and reconfiguration. This in turn helps to reduce the energy consumption in the network. Localized events also reduce communication overhead. Thus CTFTT is able to support the tracking of even fast moving objects. Extensive simulation shows that our algorithm performs better than the existing tree based algorithms in terms of coverage and energy.

Tree based tracking target in wireless sensor network

A wireless sensor network (WSN) consists of spatially distributed sensors for monitoring the physical environment. Target tracking based applications are widely referred as the most interesting applications of WSNs. It has many real-life applications such as wildlife monitoring, security applications for buildings and international border monitoring. The issues which are to be resolved in the wireless sensor networks are high energy consumption and low packet delivery rate. This paper studies these issues by proposing techniques to detect and track a mobile target. We use dynamic convoy tree-based collaboration with 100% tree coverage and low energy consumption. We propose a scheme for tree expansion and pruning and tree reconfiguration using the fuzzy sensing model. Extensive simulations are conducted to compare our algorithm with existing ones. The results show that our algorithm performs better than the existing ones in terms of coverage and energy.

A fuzzy communication model of sensor nodes in wireless sensor network

In any wireless sensor network WSN application communication coverage determines how efficiently sensor nodes can send data gathered by every active sensors to the central sink node. Sensors send gathered data using hop-by-hop delivery scheme with proper routing strategy, as the nodes use short range communication due to the limited energy availability. To develop better communication coverage algorithms it is required to use a very efficient model that can efficiently represent the behaviour of a sensor node in inspite of presence of noise, obstacles, etc. Again very well defined metrics are needed to quantify the performance of the network. In this paper we are proposing a fuzzy based model based on signal quality that will represent the data communication behaviour in a more realistic manner. We also proposed some measure and system parameters which can be used to quantify the performance and fine tune the WSN system.