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

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

D2D-Based Grouped Random Access to Mitigate Mobile Access Congestion in 5G Sensor Networks

The Fifth Generation (5G) wireless service of sensor networks involves significant challenges when dealing with the coordination of ever-increasing number of devices accessing shared resources. This has drawn major interest from the research community as many existing works focus on the radio access network congestion control to efficiently manage resources in the context of device-to-device (D2D) interaction in huge sensor networks. In this context, this paper pioneers a study on the impact of D2D link reliability in group-assisted random access protocols, by shedding the light on beneficial performance and potential limitations of approaches of this kind against tunable parameters such as group size, number of sensors and reliability of D2D links. Additionally, we leverage on the association with a Geolocation Database (GDB) capability to assist the grouping decisions by drawing parallels with recent regulatory-driven initiatives around GDBs and arguing benefits of the suggested proposal. Finally, the proposed method is approved to significantly reduce the delay over random access channels, by means of an exhaustive simulation campaign.Comment: First submission to IEEE Communications Magazine on Oct.28.2017. Accepted on Aug.18.2019. This is the camera-ready versio