Proposing a centralized algorithm to minimize message broadcasting energy in wireless sensor networks using directional antennas

In today’s healthcare environment, the Internet of Things technology provides suitability among physicians and patients, as it is valuable in numerous medicinal fields. Wireless body sensor network technologies are essential technologies in the growth of Internet of Things healthcare paradigm, where every patient is monitored utilising small-powered and lightweight sensor nodes. A dual-hop, inter–wireless body sensor network cooperation and an incremental inter–wireless body sensor network cooperation with energy harvesting in the Internet of Things health-based paradigm have been investigated and designed in this work. The three protocols have been named and abbreviated as follows: energy harvesting–based dual-hop cooperation, energy harvesting–based inter–wireless body sensor network cooperation and energy harvesting–based incremental inter–wireless body sensor network cooperation. Outage probabilities for the three designed protocols were investigated and inspected, and mathematical expressions of the outage probabilities were derived. The simulation and numerical results showed that the energy harvesting–based incremental inter–wireless body sensor network cooperation provided superior performance over the energy harvesting–based inter–wireless body sensor network cooperation and energy harvesting–based dual-hop cooperation by 1.38 times and 5.72 times, respectively; while energy harvesting–based inter–wireless body sensor network cooperation achieved better performance over energy harvesting–based dual-hop cooperation by 1.87 times.

Interference optimization for multicast and broadcast traffics in multi-radio multi-channel WMNs equipped with directional antennas

Recent advancement in technologies for wireless sensor networks has led to the emergence of wireless body sensor networks (WBSN). These networks are composed of various sensor nodes that are placed on the human body and have the ability to constantly detect, process and transmit any sensed vital signs of patients to physicians without confining the patients to their hospital beds or restraining their movement. In common with a good number of other sensor network applications, the sensors are constrained by not having sufficient energy for them to function, a situation which often leads to unexpected failures in the network. However, recent research has shown that the use of mobile nodes for data transfer can significantly reduce energy consumption of the network. Hence, in this paper, an energy efficient hybrid algorithm using particle swarm optimization (PSO) algorithm and teaching-learning-based optimization (TLBO) algorithm is presented. The proposed algorithm takes into consideration the residual energy and the distance of each node from the base station to select routes from the sensing nodes to the base station. The hybridization is performed by the incorporation of the teaching and learning factors of TLBO algorithm into the velocity equation of PSO algorithm in order to improve the convergence of the algorithm into global optimum. The performance of the new hybrid algorithm is compared to similar optimization algorithms. Extensive simulation results show the potential of the proposed algorithm to optimize the energy of wireless body sensor networks.

Directional antennas have numerous advantages over traditional omnidirectional antennas, which include more spatial reuse, extended range, less interference, and less energy consumption. Directional antennas introduce deafness and new hidden terminal problems. Deafness may cause more collisions, and hidden terminal problems may result in more retransmissions, poor quality of service, more energy consumption, and less packet delivery ratio. Hence, it is important to design of an effective medium access protocol specifically for directional antennas in order to reap the benefits of directional antennas while managing deafness and hidden terminal problems, otherwise the challenges can adversely affect system performance. In wireless sensor networks, the sensors are battery powered with limited supply of energy. Therefore, energy efficient protocols and solutions are immensely important with the desired goal of extending the network lifetime longer than what is possible through the omnidirectional antennas. In this thesis, I have proposed an energy efficient scheduled directional medium access control protocol (DTRAMA) which is specially designed for the wireless sensor nodes which use directional antennas in wireless sensor networks. It is a traffic adaptive scheduled medium access protocol in which nodes create their transmission and sleep schedules on the basis of their traffic. Scheduled medium access for packet transmission is used to address the deafness and hidden terminal problems caused by the use of directional communication in contention based MAC protocols. Use of directional antenna reduces interference which indirectly improves packet delivery ratio by improving the signal to noise ratio and by reducing the packet error rate. DTRAMA is energy efficient: firstly because the nodes use directional data communication which requires lower node transmit power than the omnidirectional data communication for the same transmission range; and secondly, because the nodes schedule their sleep period to reduce idle listening and overhearing which improves energy efficiency. In DTRAMA, sleep schedule of the node is traffic adaptive which is essential to maximize the sleep period. The node, by using spatial reuse checks, reuses the wireless medium to the maximum extent to reap the spatial reuse benefits of the directional antenna. The nodes reduce their packet latency through spatial reuse. Through simulation and by using different topologies, I have compared the performance of DTRAMA with those of omnidirectional schedule MAC protocol (TRAMA) and contention based directional MAC protocol (DMAC), which clearly shows that DTRAMA outperforms TRAMA and DMAC in packet delivery ratio and outperforms TRAMA in terms of packet latency.

Directional antennas have numerous advantages over traditional omnidirectional antennas, which include more spatial reuse, extended range, less interference, and less energy consumption. Directional antennas introduce deafness and new hidden terminal problems. Deafness may cause more collisions, and hidden terminal problems may result in more retransmissions, poor quality of service, more energy consumption, and less packet delivery ratio. Hence, it is important to design of an effective medium access protocol specifically for directional antennas in order to reap the benefits of directional antennas while managing deafness and hidden terminal problems, otherwise the challenges can adversely affect system performance. In wireless sensor networks, the sensors are battery powered with limited supply of energy. Therefore, energy efficient protocols and solutions are immensely important with the desired goal of extending the network lifetime longer than what is possible through the omnidirectional antennas. In this thesis, I have proposed an energy efficient scheduled directional medium access control protocol (DTRAMA) which is specially designed for the wireless sensor nodes which use directional antennas in wireless sensor networks. It is a traffic adaptive scheduled medium access protocol in which nodes create their transmission and sleep schedules on the basis of their traffic. Scheduled medium access for packet transmission is used to address the deafness and hidden terminal problems caused by the use of directional communication in contention based MAC protocols. Use of directional antenna reduces interference which indirectly improves packet delivery ratio by improving the signal to noise ratio and by reducing the packet error rate. DTRAMA is energy efficient: firstly because the nodes use directional data communication which requires lower node transmit power than the omnidirectional data communication for the same transmission range; and secondly, because the nodes schedule their sleep period to reduce idle listening and overhearing which improves energy efficiency. In DTRAMA, sleep schedule of the node is traffic adaptive which is essential to maximize the sleep period. The node, by using spatial reuse checks, reuses the wireless medium to the maximum extent to reap the spatial reuse benefits of the directional antenna. The nodes reduce their packet latency through spatial reuse. Through simulation and by using different topologies, I have compared the performance of DTRAMA with those of omnidirectional schedule MAC protocol (TRAMA) and contention based directional MAC protocol (DMAC), which clearly shows that DTRAMA outperforms TRAMA and DMAC in packet delivery ratio and outperforms TRAMA in terms of packet latency.

Wireless sensor networks (WSNs) are composed of sensor nodes, having limited energy resources and low processing capability. Accordingly, major challenges are involved in WSNs Routing. Thus, in many use cases, routing is considered as an NP-hard optimization problem. Many routing protocols are based on metaheuristics, such as Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). Despite the fact that metaheuristics have provided elegant solutions, they still suffer from complexity concerns and difficulty of parameter tuning. In this paper, we propose a new routing approach based on Teaching Learning Based Optimization (TLBO) which is a recent and robust method, consisting on two essential phases: Teacher and Learner. As TLBO was proposed for continuous optimization problems, this work presents the first use of TLBO for the discrete problem of WSN routing. The approach is well founded theoretically as well as detailed algorithmically. Experimental results show that our approach allows obtaining lower energy consumption which leads to a better WSN lifetime. Our method is also compared to some typical routing methods; PSO approach, advanced ACO approach, Improved Harmony based approach (IHSBEER) and Ad-hoc On-demand Distance Vector (AODV) routing protocol, to illustrate TLBO's routing efficiency.

Network Traffic is one of the major issues in wireless Sensor Networks (WSNs). WSN is a self-constructed and organization less wireless networks which is used to observe and check the physical or environmental conditions and to cooperatively pass their data through the network to a sink where the data can be appropriately observed and examined. Number of research works in wireless sensor networks (WSNs) is primarily focused on improving the network performance along with enhancing the quality of service parameters such as the data arrival rate, available bandwidth, congestion, transmission rate, queue length and energy. Various natural computational algorithms have been proposed for overcoming these issues. In this paper we have discussed about some of the bio-based algorithms such as Genetic Algorithms, Simulated Annealing, Ant Colony Optimization, Particle Swarm Optimization, Firefly Algorithm, etc. to control congestion in wireless sensor networks.

Directional antennas in wireless sensor networks (WSNs) have several advantages including the enhanced capacity of the network, longer range of transmission, better spatial reuse and lower interference. By enhancing the alleviating contention and the range of communication, the directional antennas improve the performance of WSNs. In common, various methods like localisation, power management, data aggregation and optimisation obtain these advantages in WSNs; however, the reliability requirements and the energy concerns make the antenna technology more advantageous. When compared with methods, in which the directional antennas provide advantages like the extended range of transmission, energy savings, better prevention of wormhole attack, long coverage and high interference tolerance. This review provides a detailed study of recent improvements and open research problems on directional antennas in WSN applications. First, the introduction and the background of directional antennas briefly based on their classification radiation patterns and advantages in directional communication in WSNs. During the past years, a number of directional antennas are designed for the applications of WSNs. In this study, recently developed directional antennas and their applications in WSNs are reviewed. The applications of directional antenna in WSNs are classified into security benefits, localisation, convergecast, contention reduction and energy efficiency.

Exploring the effects of directional antennas on the secure connectivity and hop count of secure multi-hop ad-hoc wireless networks

Although directional antennas have been used in mobile communications systems for quite a long time, realistic applications of directional or smart antennas in wireless ad hoc network have emerged just in recent years. Directional antennas provide numerous benefits, such as higher gains, increased transmission range and low interferences. Wireless medium access schemes play a crucial role in ensuring the efficient and fair sharing of wireless resources. Therefore there are many research work on mechanisms at the wireless medium access layer by using directional antennas. The new features of MAC with directional antennas can cause not only location dependent carrier sensing problems, which have appeared in omnidirectional wireless networks, but also novel issues related to directional antennas. In this paper, an introduction of directional antennas is given. We give a classification of the current wireless MAC protocols using directional antennas. We also present different MAC protocols and compare them. This survey discusses the challenges in the design of these MAC protocols.

Profiling environmental parameter using a large number of spatially distributed wireless sensor network (WSN) NODEs is an extensive illustration of advanced modern technologies, but high power requirement for WSN NODEs limits the widespread deployment of these technologies. Currently, WSN NODEs are extensively powered up using batteries, but the battery has limitation of lifetime, power density, and environmental concerns. To overcome this issue, energy harvester (EH) is developed and presented in this paper. Solar-based EH has been identified as the most viable source of energy to be harvested for autonomous WSN NODEs. Besides, a novel chemical-based EH is reported as the potential secondary source for harvesting energy because of its uninterrupted availability. By integrating both solar-based EH and chemical-based EH, a hybrid energy harvester (HEH) is developed to power up WSN NODEs. Experimental results from the real-time deployment shows that, besides supporting the daily operation of WSN NODE and Router, the developed HEH is capable of producing a surplus of 971 mA·hr equivalent energy to be stored inside the storage for NODE and 528.24 mA·hr equivalent energy for Router, which is significantly enough for perpetual operation of autonomous WSN NODEs used in environmental parameter profiling.

Herein, an Internet of Things (IoT) system with remote reconfigurable wireless sensor network (WSN) nodes is presented and its application to measure group work activity in a classroom is discussed. This IoT system consists of wiki pages, bots, (defined as remotely controlled devices), gateways, and remotely reconfigurable WSN Nodes. The bots/gateways and WSN nodes of the IoT system are controlled by scripts written on wiki pages that are read by the bot/gateways, which then forward the commands contained in the scripts to the WSN nodes. Each WSN node then executes the commands, obtains the resulting sensor values, and then returns those values to the bot/gateways. The bot/gateways relay the values and write them onto the wiki page. Each WSN node is flexible and reconfigurable because its behavior can be changed by the script commands written onto the wiki page. Using this IoT system, we created a measurement system to evaluate activity levels of group work in a classroom. After developing the measurement system, we found it was possible to adjust the sampling rate for obtaining sensor values simply by rewriting the script on the wiki page without directly manipulating the WSN.

A suburban ad-hoc network (SAHN) interconnects a cooperative group at broadband speed using wireless links. The nodes are stationary. A SAHN involves low installation and service costs for SAHN specific traffic. Some current routing solutions for mobile ad-hoc networks may be used in the SAHN after certain optimizations. Efficiency can be improved by using smart directional antennas. Neighboring nodes falling outside the transmission region of a directional antenna are less vulnerable to co-channel interference. Additionally, increased transmission range can be achieved by reducing noise, interference and multipath fading. We emphasize the interference reduction capability of directional antennas and investigate the routing performances using three antenna schemes; multiple fixed directional, multiple omnidirectional and single omnidirectional antennas. We present an estimate of the achievable performance in a SAHN through extensive simulations. We also discuss the impact of using omnidirectional antennas on routing performance where different networks, using overlapping frequency channels, exist within each other's transmission ranges.

The objective of this paper is to study the effect and suitability of directionality in near-field microwave head imaging system. To that end, the near-field performances of directional and omnidirectional antennas are compared. The imaging performance comparison is carried out through experimental validation of a realistic artificial head phantom with an emulated brain injury. The results conclude that the directional antenna yields more focused images with low artifacts than the omnidirectional antenna.

Neighbor discovery in wireless networks with sectored antennas