Enhancing lifetime and quality of data in cluster-based hierarchical routing protocol for wireless sensor network

Wireless Sensor Network (WSN) performs energy extensive tasks and it is essential to rotate sensor nodes frequently so that Cluster Head selections can be made efficiently. In this paper, we aim to improve the lifetime of sensor network by using LEACH based protocols and efficiently utilizing the limited energy available in these sensor nodes. In sensor network, the amount of data delivered at the base station is not important but it is the quality of the data which is of utmost importance. Our proposed approach significantly improves the life time and quality of data being delivered at the base station in sensor network. We evaluate our proposed approach using different sets of node energy levels and in each case our approach shows significant improvement over existing cluster-based hierarchical routing protocols. We evaluate our scheme in terms of energy consumption, life time and quality of data delivered at the base station. © 2013 IEEE

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

An Efficient Analysis on Performance Metrics for optimized Wireless Sensor Network

Wireless Sensor Networks have the revolutionary significance in many new monitoring applications and self-organized systems. Based on the nature of application WSN are needed to support various levels of Quality of Services. Quality of service parameters are most significant aspect in WSN during data transmission from sensor nodes to sink. This paper surveys the factor on reliability, predictability, sustainability, optimal clustering and scheduling by analyzing various models existing in WSN. A network that satisfies all these Qos parameters ensures outstanding throughput in performance. We concluded by exploring some of the dimensions for research interest and addressed open issues ahead to enhance the performance of WSNs

Enhancing network lifetime with an improved MOD- LEACH

Wireless sensor network will be the most dominating field in future era. There are certain issues which wireless sensor network suffers from. The main concern with wireless sensor network is limited energy which directly impact on network lifetime. In this paper we modify the cluster selection procedure of MODLEACH. MODLEACH protocol use threshold value for selecting cluster head. Once a cluster head is selected, it retains its position until it bypasses the threshold limit. In Basic LEACH, it does not use any threshold value but it randomly selects cluster head from the available nodes. We combine the probabilistic nature of LEACH to select the cluster head and threshold base selection of cluster head of MODLEACH. We also apply proposed modification in EAMMH protocol. Our main focus is on the enhancement of network lifetime, and we got significant improvement in network lifetime

A Review of Wireless Sensor Networks with Cognitive Radio Techniques and Applications

The advent of Wireless Sensor Networks (WSNs) has inspired various sciences and telecommunication with its applications, there is a growing demand for robust methodologies that can ensure extended lifetime. Sensor nodes are small equipment which may hold less electrical energy and preserve it until they reach the destination of the network. The main concern is supposed to carry out sensor routing process along with transferring information. Choosing the best route for transmission in a sensor node is necessary to reach the destination and conserve energy. Clustering in the network is considered to be an effective method for gathering of data and routing through the nodes in wireless sensor networks. The primary requirement is to extend network lifetime by minimizing the consumption of energy. Further integrating cognitive radio technique into sensor networks, that can make smart choices based on knowledge acquisition, reasoning, and information sharing may support the network's complete purposes amid the presence of several limitations and optimal targets. This examination focuses on routing and clustering using metaheuristic techniques and machine learning because these characteristics have a detrimental impact on cognitive radio wireless sensor node lifetime

Energy-efficient routing and secure communication in wireless sensor networks

University of Technology Sydney. Faculty of Engineering and Information Technology.Wireless Sensor Networks (WSNs) consist of miniature sensor nodes deployed to gather vital information about an area of interest. The ability of these networks to monitor remote and hostile locations has attracted a significant amount of research over the past decade. As a result of this research, WSNs have found their presence in a variety of applications such as industrial automation, habitat monitoring, healthcare, military surveillance and transportation. These networks have the ability to operate in human-inaccessible terrains and collect data on an unprecedented scale. However, they experience various technical challenges at the time of deployment as well as operation. Most of these challenges emerge from the resource limitations such as battery power, storage, computation, and transmission range, imposed on the sensor nodes. Energy conservation is one of the key issues requiring proper consideration. The need for energy-efficient routing protocols to prolong the lifetime of these networks is very much required. Moreover, the operation of sensor nodes in an intimidating environment and the presence of error-prone communication links expose these networks to various security breaches. As a result, any designed routing protocol need to be robust and secure against one or more malicious attacks. This thesis aims to provide an effective solution for minimizing the energy consumption of the nodes. The energy utilization is reduced by using efficient techniques for cluster head selection. To achieve this objective, two different cluster-based hierarchical routing protocols are proposed. The selection of an optimal percentage of cluster heads reduces the energy consumption, enhances the quality of delivered data and prolongs the lifetime of a network. Apart from an optimal cluster head selection, energy consumption can also be reduced using efficient congestion detection and mitigation schemes. We propose an application-specific priority-based congestion control protocol for this purpose. The proposed protocol integrates mobility and heterogeneity of the nodes to detect congestion. Our proposed protocol uses a novel queue scheduling mechanism to achieve coverage fidelity, which ensures that the extra resources consumed by distant nodes are utilized effectively. Apart from energy conservation issue, this thesis also aims to provide a robust solution for Sybil attack detection in WSN. In Sybil attack, one or more malicious nodes forge multiple identities at a given time to exhaust network resources. These nodes are detected prior to cluster formation to prevent their forged identities from participating in cluster head selection. Only legitimate nodes are elected as cluster heads to enhance utilization of the resources. The proposed scheme requires collaboration of any two high energy nodes to analyse received signal strengths of neighbouring nodes. Moreover, the proposed scheme is applied to a forest wildfire monitoring application. It is crucial to detect Sybil attack in a wildfire monitoring application because these forged identities have the ability to transmit high false-negative alerts to an end user. The objective of these alerts is to divert the attention of an end user from those geographical regions which are highly vulnerable to a wildfire. Finally, we provide a lightweight and robust mutual authentication scheme for the real-world objects of an Internet of Thing. The presence of miniature sensor nodes at the core of each object literally means that lightweight, energy-efficient and highly secured schemes need to be designed for such objects. It is a payload-based encryption approach which uses a simple four way handshaking to verify the identities of the participating objects. Our scheme is computationally efficient, incurs less connection overhead and safeguard against various types of replay attacks