Efficient Control Message Dissemination in Dense Wireless Lighting Networks

Modern lighting systems using LED light sources lead to dense lighting installations. The control of such systems using wireless Machine-to-Machine (M2M) where standard LED light sources are replaced by wirelessly controllable LED light sources create new problems which are investigated in this thesis. Current approaches for control message transmission is such networks are based on broadcasting messages among luminaires. However, adequate communication performance - in particular, sufficiently low latency and synchronicity - is difficult to ensure in such networks, in particular, if the network is part of a wireless building management system and carries not only low-latency broadcast messages but also collects data from sensors. In this thesis, the problem of simultaneously controlling dense wireless lighting control networks with a higher number of luminaires is addressed. Extensive computer simulation shows that current state-of-the-art protocols are not suitable for lighting control applications, especially if complex applications are required such as dimming or colour tuning. The novel D³LC-Suite is proposed, which is specially designed for dense wireless lighting control networks. This suite includes three sub-protocols. First, a protocol to organize a network in form of a cluster tree named CIDER. To ensure that intra-cluster messages can be exchanged simultaneously, a weighted colouring algorithm is applied to reduce the inter cluster interference. To disseminate efficiently control messages a protocol is proposed named RLL. The D³LC-Suite is evaluated and validated using different methods. A convergence analysis show that CIDER is able to form a network in a matter of minutes. Simulation results of RLL indicate that this protocol is well suited for dense wireless applications. In extensive experiments, it is shown that the D³LC-Suite advances the current state-of-the-art in several aspects. The suite is able to deliver control messages across multiple hops meeting the requirements of lighting applications. Especially, it provides a deterministic latency, very promising packet loss ratios in low interference environments, and mechanisms for simultaneous message delivery which is important in terms of Quality of Experience (QoE

Smart handoff technique for internet of vehicles communication using dynamic edge-backup node

© 2020 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/electronics9030524A vehicular adhoc network (VANET) recently emerged in the the Internet of Vehicles (IoV); it involves the computational processing of moving vehicles. Nowadays, IoV has turned into an interesting field of research as vehicles can be equipped with processors, sensors, and communication devices. IoV gives rise to handoff, which involves changing the connection points during the online communication session. This presents a major challenge for which many standardized solutions are recommended. Although there are various proposed techniques and methods to support seamless handover procedure in IoV, there are still some open research issues, such as unavoidable packet loss rate and latency. On the other hand, the emerged concept of edge mobile computing has gained crucial attention by researchers that could help in reducing computational complexities and decreasing communication delay. Hence, this paper specifically studies the handoff challenges in cluster based handoff using new concept of dynamic edge-backup node. The outcomes are evaluated and contrasted with the network mobility method, our proposed technique, and other cluster-based technologies. The results show that coherence in communication during the handoff method can be upgraded, enhanced, and improved utilizing the proposed technique.Published onlin

Intelligent Energy Management with IoT Framework in Smart Cities Using Intelligent Analysis: An Application of Machine Learning Methods for Complex Networks and Systems

Smart buildings are increasingly using Internet of Things (IoT)-based wireless sensing systems to reduce their energy consumption and environmental impact. As a result of their compact size and ability to sense, measure, and compute all electrical properties, Internet of Things devices have become increasingly important in our society. A major contribution of this study is the development of a comprehensive IoT-based framework for smart city energy management, incorporating multiple components of IoT architecture and framework. An IoT framework for intelligent energy management applications that employ intelligent analysis is an essential system component that collects and stores information. Additionally, it serves as a platform for the development of applications by other companies. Furthermore, we have studied intelligent energy management solutions based on intelligent mechanisms. The depletion of energy resources and the increase in energy demand have led to an increase in energy consumption and building maintenance. The data collected is used to monitor, control, and enhance the efficiency of the system

EEHC: Event-driven Energy Optimization in Heterogeneous Clustered Wireless Sensor Networks

Wireless sensor networks are used in various applications worldwide. Large numbers small sized, inexpensive, low-powered sensor nodes are deployed in the target field to monitor or track particular objects. Sensor nodes have limited energy and computation capability. Energy optimization is an important task should be performed to improve the lifetime of the wireless sensor networks. Many researches focus only on continuous delivery model. This paper proposed energy efficient event-driven heterogeneous clustered wireless sensor network (EEHC) system. The results show that the proposed system reduced the energy consumption and longer lifetime than its comparatives

Energy Efficiency

This book is one of the most comprehensive and up-to-date books written on Energy Efficiency. The readers will learn about different technologies for energy efficiency policies and programs to reduce the amount of energy. The book provides some studies and specific sets of policies and programs that are implemented in order to maximize the potential for energy efficiency improvement. It contains unique insights from scientists with academic and industrial expertise in the field of energy efficiency collected in this multi-disciplinary forum

Zigbee Based Home Automation and Agricultural Monitoring System A mesh networking approach for autonomous and manual system control

Today’s generation of electronic devices are more enhanced and capable than the previous ones with exciting changes in technology has seen to control a variety of home devices with the help of a home automation system. These devices can include lights, fans, doors, surveillance systems and consumer electronics. However along with the smartness and intuitiveness we want a system which is economic as well as low power consuming. ZigBee technology collects and monitors different types of measurements that reflect energy consumption and environment parameters. This paper details the designing of a protocol to monitor various environmental conditions in a home. We are using advanced technology of Micaz motes (which have their own routing capabilities), NESC language programming and Moteworks (used as a data acquisition platform)

On-demand fuzzy clustering and ant-colony optimisation based mobile data collection in wireless sensor network

In a wireless sensor network (WSN), sensor nodes collect data from the environment and transfer this data to an end user through multi-hop communication. This results in high energy dissipation of the devices. Thus, balancing of energy consumption is a major concern in such kind of network. Appropriate cluster head (CH) selection may provide to be an efficient way to reduce the energy dissipation and prolonging the network lifetime in WSN. This paper has adopted the concept of fuzzy if-then rules to choose the cluster head based on certain fuzzy descriptors. To optimise the fuzzy membership functions, Particle Swarm Optimisation (PSO) has been used to improve their ranges. Moreover, recent study has confirmed that the introduction of a mobile collector in a network which collects data through short-range communications also aids in high energy conservation. In this work, the network is divided into clusters and a mobile collector starts from the static sink or base station and moves through each of these clusters and collect data from the chosen cluster heads in a single-hop fashion. Mobility based on Ant-Colony Optimisation (ACO) has already proven to be an efficient method which is utilised in this work. Additionally, instead of performing clustering in every round, CH is selected on demand. The performance of the proposed algorithm has been compared with some existing clustering algorithms. Simulation results show that the proposed protocol is more energy-efficient and provides better packet delivery ratio as compared to the existing protocols for data collection obtained through Matlab Simulations

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