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

Software defined networking based resource management and quality of service support in wireless sensor network applications

To achieve greater performance in computing networks, a setup of critical computing aspects that ensures efficient network operation, needs to be implemented. One of these computing aspects is, Quality of Service (QoS). Its main functionality is to manage traffic queues by means of prioritizing sensitive network traffic. QoS capable networking allows efficient control of traffic especially for network critical data. However, to achieve this in Wireless Sensor Networks (WSN) is a serious challenge, since these technologies have a lot of computing limitations. It is even difficult to manage networking resources with ease in these types of technologies, due to their communication, processing and memory limitations. Even though this is the case with WSNs, they have been largely used in monitoring/detection systems, and by this proving their application importance. Realizing efficient network control requires intelligent methods of network management, especially for sensitive network data. Different network types implement diverse methods to control and administer network traffic as well as effectively manage network resources. As with WSNs, communication traffic and network resource control are mostly performed depending on independently employed mechanisms to deal with networking events occurring on different levels. It is therefore challenging to realize efficient network performance with guaranteed QoS in WSNs, given their computing limitations. Software defined networking (SDN) is advocated as a potential paradigm to improve and evolve WSNs in terms of capacity and application. A means to apply SDN strategies to these compute-limited WSNs, formulates software defined wireless sensor networks (SDWSN). In this work, a resource-aware OpenFlow-based Active Network Management (OF-ANM) QoS scheme that uses SDN strategies is proposed and implemented to apply QoS requirements for managing traffic congestion in WSNs. This scheme uses SDN programmability strategies to apply network QoS requirements and perform traffic load balancing to ensure congestion control in SDWSN. Our experimental results show that the developed scheme is able to provide congestion avoidance within the network. It also allows opportunities to implement flexible QoS requirements based on the system’s traffic state. Moreover, a QoS Path Selection and Resource-associating (Q-PSR) scheme for adaptive load balancing and intelligent resource control for optimal network performance is proposed and implemented. Our experimental results indicate better performance in terms of computation with load balancing and efficient resource alignment for different networking tasks when compared with other competing schemes.Thesis (PhD)--University of Pretoria, 2018.National Research FoundationUniversity of PretoriaElectrical, Electronic and Computer EngineeringPhDUnrestricte

Relevance- and Aggregation-based Scheduling for Data Transmission in IEEE 802.15.4e IoT Networks

Master's thesis Information- and communication technology IKT590 - University of Agder 2017Internet of thing (IoT) is regarded as a new communicating paradigm with Internet connectivity enabling embedded devices to interact with each other on a global scale. IoT has the potential to become the largest producer of information because of a massive number of connected devices with diverse applications ranging from environmental monitoring, home, and building automation. This ubiquitous connectivity requires reliability, efficiency, and sustainability of access to information. As an enabling technology, wireless sensor networks (WSNs) have opened new opportunity with recent technological developments in making miniaturized smart connected devices. With an increase in the activity of these smart devices, there are challenges in maintaining their limited energy, lifetime, and reliability required for IoT applications. The reason is that these devices are mostly battery powered. In this respect, an insight into the activities of sensing devices produced by different vendors with interoperability based on industrial standards is needed. As an enhancement of IEEE 802.15.4 MAC sublayer, the ratification of IEEE 802.15.4e standard makes a step towards IoT medium access control (MAC) for industrial applications. One of the significant enhancements in IEEE 802.15.4e is different MAC modes. However, IEEE 802.15.4e does not specify standardized scheduling policy for network building and data transmission maintenance. It is basically application specific. In general, activities performed at the MAC sublayer contribute to sensor energy consumption. Therefore, an efficient MAC scheme is needed to utilize network resources more efficiently, minimize energy consumption level and at the same time improve data transmission of the network. In this thesis work, we focus on proposing transmission schemes for improving energy consumption for data transmission in IoT networks and as well as increasing average packet delivery ratio (PDR). Our target is to improve time slotted channel hopping (TSCH) mode that enables deterministic access and robust network. The focus is on dedicated and shared slots in TSCH. More specifically, we propose two MAC schemes; relevance- and aggregation-based scheduling for data transmission in IEEE 802.15.4e IoT networks. With relevance-based scheduling, the coordinator node builds and maintains communication in the network based on a historical data value of member nodes. On the other hand, aggregation-based scheduling iii enables the coordinator node to build and maintain communication by integrating multiple data inside a single frame payload at the source node before transmission. Further, the proposed schemes are implemented using network simulator version 3 (ns-3). We use Ubuntu 16.04.2 as the operating system for our implementation and performance evaluation. Numerical results for a few performance metrics including PDR, collision probability, delay, and energy consumption are obtained through extensive simulations. The superiority of the proposed schemes is demonstrated by comparing the simulation results with that of IEEE 802.15.4e TSCH standard under varies network scenario

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

Enabling Cyber Physical Systems with Wireless Sensor Networking Technologies

[[abstract]]Over the last few years, we have witnessed a growing interest in Cyber Physical Systems (CPSs) that rely on a strong synergy between computational and physical components. CPSs are expected to have a tremendous impact on many critical sectors (such as energy, manufacturing, healthcare, transportation, aerospace, etc) of the economy. CPSs have the ability to transform the way human-to-human, human-toobject, and object-to-object interactions take place in the physical and virtual worlds. The increasing pervasiveness of Wireless Sensor Networking (WSN) technologies in many applications make them an important component of emerging CPS designs. We present some of the most important design requirements of CPS architectures. We discuss key sensor network characteristics that can be leveraged in CPS designs. In addition, we also review a few well-known CPS application domains that depend on WSNs in their design architectures and implementations. Finally, we present some of the challenges that still need to be addressed to enable seamless integration of WSN with CPS designs.[[incitationindex]]SCI[[booktype]]紙

Revolutionizing 5G Networks: A Synergy of Routing, Clustering, and Energy Optimization for Unprecedented Performance and Extended Lifespan

The concept of revolutionizing 5G (Fifth Generation) networks through a synergy of routing, clustering, and energy optimization is indeed a promising approach to enhancing the performance and lifespan of wireless networks. Exciting changes will occur in the physical, digital, and biological worlds over the next ten years. Although the needs for Beyond 5G (B5G) are not yet fully understood, an effort has been made to stratify 5G progression and B5G. This work highlights the focus on revolutionizing 5G networks through the integration of routing, clustering, and energy optimization techniques. By combining these methodologies, this research work aims to address the complex challenges in 5G networking, such as efficient data routing, resource allocation, and energy consumption. The objective is to achieve both exceptional performance and an extended lifespan for these networks. The proposed work holds promise for significantly enhancing the capabilities of 5G networks, resulting in improved user experiences, optimized resource utilization, and prolonged network lifespan. In order to completely meet the most stringent 5G standards, such as stratification, or deconstruction into existing technologies, will comprise technology scenarios of 5G evolutions. Wireless sensor networks (WSNs), which offer essential data collecting and monitoring capabilities, are made up entirely of 5G networks. These methods are designed specifically for use in 5G networks to increase the network’s lifespan and overall performance. For 5G networks, routing and clustering techniques from WSNs can be modified and optimized to increase energy efficiency and prolong the network lifetime in 5G networks

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over networks that support device-to-device (D2D) communication, e.g., D2D-enabled cellular networks and WiFi-Direct. In these ad-hoc types of IoT networks, efficient topology management is a crucial requirement, and in particular in massive scale deployments. Traditionally, clustering has been recognized as a common approach for topology management in ad-hoc networks, e.g., in Wireless Sensor Networks (WSNs). Topology management in WSNs and ad-hoc IoT networks has many design commonalities as both need to transfer data to the destination hop by hop. Thus, WSN clustering techniques can presumably be applied for topology management in ad-hoc IoT networks. This requires a comprehensive study on WSN clustering techniques and investigating their applicability to ad-hoc IoT networks. In this article, we conduct a survey of this field based on the objectives for clustering, such as reducing energy consumption and load balancing, as well as the network properties relevant for efficient clustering in IoT, such as network heterogeneity and mobility. Beyond that, we investigate the advantages and challenges of clustering when IoT is integrated with modern computing and communication technologies such as Blockchain, Fog/Edge computing, and 5G. This survey provides useful insights into research on IoT clustering, allows broader understanding of its design challenges for IoT networks, and sheds light on its future applications in modern technologies integrated with IoT.acceptedVersio