Heena Dhawan

Bio: Heena Dhawan is an academic researcher. The author has contributed to research in topics: Routing protocol & Wireless sensor network. The author has an hindex of 1, co-authored 1 publications receiving 46 citations.

A Comparative Study on LEACH Routing Protocol and Its Variants in Wireless Sensor Networks: A Survey

Abstract: Wireless sensor network consists of sensor nodes which are powered by battery; to communicate with each other for environment monitoring. Energy efficiency is the main issue in wireless sensor networks. Therefore, to maximize network lifetime and achieve maximum reliability and scalability, routing techniques have been developed. LEACH is the conventional hierarchical clustering protocol widely used in WSNs. This paper reviews the taxonomy of WSN routing protocols and also highlights issues in LEACH protocol along with disadvantages. The objective of this paper is to provide brief detail of some LEACH improved versions. Finally this paper compares some features of LEACH protocol variants. General Terms Comparison among various descendants of LEACH protocol

A Survey of Clustering Techniques in WSNs and Consideration of the Challenges of Applying Such to 5G IoT Scenarios

Abstract: Wireless sensor network (WSN) systems are typically composed of thousands of sensors that are powered by limited energy resources. To extend the networks longevity, clustering techniques have been introduced to enhance energy efficiency. This paper presents a survey on clustering over the last two decades. Existing protocols are analyzed from a quality of service (QoS) perspective including three common objectives, those of energy efficiency, reliable communication and latency awareness. This review reveals that QoS aware clustering demands more attention. Furthermore, there is a need to clarify how to improve quality of user experience (QoE) through clustering. Understanding the users’ requirements is critical in intelligent systems for the purpose of enabling the ability of supporting diverse scenarios. User awareness or user oriented design is one remaining challenging problem in clustering. In additional, this paper discusses the potential challenges of implementing clustering schemes to Internet of Things (IoT) systems in 5G networks. We indicate that clustering techniques enhanced with smart network selection solutions could highly benefit the QoS and QoE in IoT. As the current studies for WSNs are conducted either in homogeneous or low level heterogeneous networks, they are not ideal or even not able to function in highly dynamic IoT systems with a large range of user scenarios. Moreover, when 5G is finally realized, the problem will become more complex than that in traditional simplified WSNs. Several challenges related to applying clustering techniques to IoT in 5G environment are presented and discussed.

WSN-DS: A Dataset for Intrusion Detection Systems in Wireless Sensor Networks

Abstract: Wireless Sensor Networks (WSN) have become increasingly one of the hottest research areas in computer science due to their wide range of applications including critical military and civilian applications. Such applications have created various security threats, especially in unattended environments. To ensure the security and dependability of WSN services, an Intrusion Detection System (IDS) should be in place. This IDS has to be compatible with the characteristics of WSNs and capable of detecting the largest possible number of security threats. In this paper a specialized dataset for WSN is developed to help better detect and classify four types of Denial of Service (DoS) attacks: Blackhole, Grayhole, Flooding, and Scheduling attacks. This paper considers the use of LEACH protocol which is one of the most popular hierarchical routing protocols in WSNs. A scheme has been defined to collect data from Network Simulator 2 (NS-2) and then processed to produce 23 features. The collected dataset is called WSN-DS. Artificial Neural Network (ANN) has been trained on the dataset to detect and classify different DoS attacks. The results show that WSN-DS improved the ability of IDS to achieve higher classification accuracy rate. WEKA toolbox was used with holdout and 10-Fold Cross Validation methods. The best results were achieved with 10-Fold Cross Validation with one hidden layer. The classification accuracies of attacks were 92.8%, 99.4%, 92.2%, 75.6%, and 99.8% for Blackhole, Flooding, Scheduling, and Grayhole attacks, in addition to the normal case (without attacks), respectively.

Enhanced LEACH protocol for increasing a lifetime of WSNs

Abstract: WSNs that stand for wireless sensor networks and include many low-cost and low power-sensing tools, local processing, and the capacity of wireless communication face some problems in two aspects: the lifetime of the network and its energy. Therefore, the aim of this paper is to overcome these limitations through enhancing the LEACH (low energy adaptive clustering hierarchy) protocol, the protocol of cluster routing, in which, LEACH is extended by identifying a cluster head according to the lowest degree of distance from the base station in order to decrease power consumption in cluster head nodes and in the whole network. Hence, the results clarify the ability of LEACH in enhancing the network lifetime as well as in reducing and minimizing the consumption of power.

Intrusion Detection Algorithm for Mitigating Sinkhole Attack on LEACH Protocol in Wireless Sensor Networks

Abstract: In wireless sensor network (WSN), the sensors are deployed and placed uniformly to transmit the sensed data to a centralized station periodically. So, the major threat of the WSN network layer is sinkhole attack and it is still being a challenging issue on the sensor networks, where the malicious node attracts the packets from the other normal sensor nodes and drops the packets. Thus, this paper proposes an Intrusion Detection System (IDS) mechanism to detect the intruder in the network which uses Low Energy Adaptive Clustering Hierarchy (LEACH) protocol for its routing operation. In the proposed algorithm, the detection metrics, such as number of packets transmitted and received, are used to compute the intrusion ratio (IR) by the IDS agent. The computed numeric or nonnumeric value represents the normal or malicious activity. As and when the sinkhole attack is captured, the IDS agent alerts the network to stop the data transmission. Thus, it can be a resilient to the vulnerable attack of sinkhole. Above all, the simulation result is shown for the proposed algorithm which is proven to be efficient compared with the existing work, namely, MS-LEACH, in terms of minimum computational complexity and low energy consumption. Moreover, the algorithm was numerically analyzed using TETCOS NETSIM.

Efficient whale optimisation algorithm-based SDN clustering for IoT focused on node density

Abstract: The recent advent of Software Defined Networking (SDN) and intelligent networks have prompted the researcher to conduct further investigations into the high-density Wireless Sensor Network (WSN). WSNs have inherent issues that limit their performance, such as sensor resource restrictions that affect power supply, memory, processing units and communications capabilities. This paper proposes new clustering, using a Whale Optimisation Algorithm (WOA) based on the concept of SDN. The proposed protocol considers both sensor resource restrictions and the random diversification of node density in the geographical area. It begins by dividing the sensing area by the SDN controller into virtual zones (VZs) to balance the number of cluster heads (CHs) according to the node density in each VZ; it then uses the WOA, which considers residual energy, communication cost and node density, to define the optimal set of CHs. Simulation results show that the proposed protocol has improved network lifetime and resulted in efficient energy dissipation; furthermore, it has increased the number of packets sent to the sink by approximately 55% compared to traditional protocols, and by about 20% compared to an optimisation based routing protocol.