Padmavati Khandnor

Intrusion detection system in wireless sensor networks: A comprehensive review

In todays era security is one of the main concern in every field also in wireless sensor networks. Resource limitation is main concern of sensor nodes in wireless sensor networks. There are many security threats which are affecting the, functionality, security and network life time of and wireless sensor networks. In this paper security threats, security goals, various attacks, classification of these attacks are presented along with the comparison of different intrusion detection systems in wireless sensor networks. Detailed information about intrusion detection systems is provided then, intrusion detection methodologies are compared based on different schemes. Intrusion detection schemes are categorized based on techniques used in the scheme: Specification based scheme, computational intelligence and data mining based scheme, game theory approach based intrusion detection scheme, probability distribution based detection scheme. At the end of paper advantages and disadvantages of each scheme is also presented.

Watermarking schemes for secure data aggregation in wireless sensor networks: A review paper

Wireless sensor networks consists of sensors nodes used for the communication purpose. Wireless sensor networks are self-organized and data-centric. In Wireless sensor networks, there are some issues like data redundancy, high energy conservation and injecting unnecessary data. Data aggregation method overcomes the data redundancy problem. In this paper, a data integrity protection strategy has been discussed based on watermarking technologies to protect the data integrity. At the end of the paper comparison of various schemes is also provided based on characteristics like the method adopted by each scheme and the position at which integrity is provided.

Energy Efficient Data Aggregation Using Multiple Mobile Agents in Wireless Sensor Network

Gathering data effectively has always been of primary importance in wireless sensor network. Mobile agent paradigm has made it possible to collect and aggregate data in a manner which is appropriate for real-time applications. In static wireless sensor network, the sensor nodes forward the data to the sink node through intermediate sensor nodes while mobile agents have an advantage as they reduce the passing of results between the intermediate nodes so consumption of network bandwidth also reduces. But mobile agent paradigm brings along its own challenges, and one of the major issues is to achieve energy efficiency. This paper proposes a data aggregation approach using multiple mobile agents which takes into account aggregation ratio, network lifespan, and energy efficiency. The network is divided into four quadrants, and a mobile agent is dispatched for each quadrant to collect data from the quadrant assigned to it. Simulation results show that the proposed approach consumes optimal amount of energy; hence, the network lifespan is elongated.

Classification of the Shoulder Movements for Intelligent Frozen Shoulder Rehabilitation

Frozen shoulder is a medical condition leading to stiffness in the shoulder joint and also restricting the range of motion of the shoulder joint. The paper compiles the details about the four basic movements of the shoulder joint, namely the flexion/extension, abduction/adduction, internal rotation and external rotation movements. Shoulder movements of 150 subjects were recorded, and the data was further analyzed and classified using the K-nearest neighbor algorithm, support vector machine, and also using logistic regression algorithm. The data is recorded using a module consisting of a triaxial accelerometer, a HC-05 Bluetooth module and triaxial gyroscope. SVM shows an accuracy of approximately 99.99% over the classification of the four shoulder movements and is proved to be better than other classifiers. Classification of the shoulder movements can be further used to classify an individual as either a patient suffering from frozen shoulder or a normal individual.

Human Fall Detection System over IMU Sensors Using Triaxial Accelerometer

A sudden increase in the number of deaths over the past few years by slipping and falling, especially in case of patients in hospitals and aged people at homes, is a serious concern and calls for the need of an autonomous system for detection of fall and alerting caretaker in case of emergency. We propose an algorithm which, first, derives features from an input stream of data sensed and uses it in learning of our system and further, provides it with the capability of classifying a sequence into either fall or activity of daily living sequence implemented using support vector machine. We propose a space and time efficient system, minimizing its cost by using only 3-axial accelerometer as sensor. Choice of type and number of features along with their operational complexity is a crucial factor for our system. Performance analysis is done by first training our system and then testing its accuracy in classifying test sequences using machine learning algorithm.

Clustering Based on Ant Colony Optimization and Relative Neighborhood (C-ACORN)

Wireless sensor network has emerged as a powerful technology and is growing day by day. Ease of availability and low maintenance of small, inexpensive, fault-tolerant, self-configured, self-reliant, easily deployable sensor nodes has made them useful in several critical areas like military, healthcare, industrial process control, security and surveillance, smart homes. But wireless sensor network face challenges of energy conservation, increasing the network lifetime. Clustering is the best-known solution to this problem. In this paper, ant colony optimization and relative neighborhood-based clustering algorithm have been proposed which uses graph-based techniques to form neighbors for the ants. The algorithm is evaluated for seven datasets using the cluster validity indices like Dunn’s index (DI), modified Dunn’s index (MDI), and Rand index (RI). The results are compared with the existing clustering techniques like density-based spatial clustering applications with noise (DBSCAN) and complete linkage clustering. The comparison is done on the parameters of the quality of solution. The proposed algorithm generates good clustering results and is able to detect all the target clusters efficiently.

Enhanced mobility based clustering protocol for wireless sensor networks

Thispaper introduces the enhanced mobility based clustering protocol forwireless sensor networks with mobile nodes which is further enhancement for mobility based clustering protocol. The proposed protocol is fault tolerant and reliable as sensor nodes send special packets to cluster head node when there is no data to send. Simulation results shows that the proposed protocol outperforms the mobility based clustering protocol and fault tolerant clustering protocol in terms of network lifetime and reliability.

Tree based heuristic algorithms for maximizing network lifetime: A review

Maximizing the network lifetime in wireless sensor networks using minimum spanning tree proves to be efficient in case of mobile sink. Sensor nodes route their data to root nodes through intermediate nodes. In Power Efficient Data Gathering and Aggregation lifetime is improved by taking minimum weight edge from root to leaf nodes while Energy conserving routing tree algorithm maximizes the life span of network. Local optimization algorithm enhances the lifetime of the network. Various balanced trees are used to diversify load of routing to nodes. Although balanced tree implementation is difficult but lifetime of network increases considerably. The various tree formation techniques are compared based on complexity of tree formation and underlying main ideas. All algorithms work on approximations as complete implementation is NP-complete.

Performance analysis of routing protocols in mobile wireless sensor network

Static wireless sensor network WSN routing protocols result in hot spot problem. In order to avoid hot-spot problem, routing protocols using mobile WSN can be used. In literature many routing protocols have been proposed based on mobile WSN. In this paper, initially mobile routing protocols are presented, later a comparative analysis is performed between mobility-based clustering MBC protocol and location aware fault tolerant clustering protocol LFCP for mobile WSN based on metrics such as stability period, network lifetime period and energy consumption. The simulation results show that LFCP-MWSN outperform MBC in terms of average stability period, average network lifetime, scalability and energy efficiency.

Validity of internal cluster indices

The evaluation of a clustering solution using cluster validity indices is necessary to identify the correct number of clusters, which is the fundamental consideration in clustering. Various techniques have been proposed in the literature to make advancements to the internal cluster validation. In this paper, various advancements in internal cluster validation like graph theory based indices, symmetry based indices, maximum intra-cluster distance based indices, separation and variance based indices, overlap and separation based indices, and density based indices have been reviewed. The impact of dimension, shape of cluster, size of cluster, density of cluster, noise, skewed distribution, overlap, and separation on the performance of the cluster validity indices have been analyzed to provide guidelines for selecting cluster validity indices for different clustering applications.