Abstract Unmanned Aerial Vehicles (UAVs) are an emerging technology with the potential to be used in various sectors for various applications and services. In wireless networking, UAVs can be used as a vital part of the supplementary infrastructure to improve coverage, principally during public safety emergencies. Because of their affordability and potential for widespread deployment, there has been a growing interest in exploring the ways in which UAVs can enhance the services offered to isolated ground devices. Large areas may lose cellular coverage following a public safety emergency that impacts critical communication infrastructure. This prompts the need for the employment of D2D communication frameworks as a complement. In such critical conditions, timely response and network connectivity are essential factors for reliable communication. This study focuses on the mathematical models of UAV-based wireless communication in the context of disaster recovery. Particularly, we aim to model a queuing framework comprising UAVs as mobile relay nodes between the stranded user devices and neighbouring operational base stations. We present an iterative solution with a novel method for generating initial conditions for the two-stage queuing model. The approximate approach presented is validated for its accuracy using discrete-event simulation. The effects of various factors on performance measures are also analysed in detail. The validation results show that the discrepancy between the analytical approach and the simulation is less than 5%, which is the confidence interval of the simulation.

Human Activity Recognition (HAR) has emerged as a crucial assistive technology in elderly healthcare, providing caregivers with the ability to monitor and assist in daily activities. HAR is typically conducted through the analysis of data obtained from various types of sensors, including body, object, and ambient sensors. This study focused specifically on utilizing data from internal sensors to recognize activities such as walking, ascending/descending stairs, sitting, standing, and falling. Data was gathered from smartphones, and all HAR models were tested using real-time data collected from Wireless Multimedia Sensor Networks (WMSNs). To perform activity recognition, neural network algorithms such as CNN and LSTM, along with traditional machine learning classification algorithms such as SVM, KNN, and Random Forest Classifier were employed. Additionally, dimension reduction techniques are utilized to decrease the number of features, thus reducing computational time and energy consumption. Furthermore, transfer learning was employed with different scenarios to improve accuracy. Finally, all functions were implemented and compared in two different WMSN architectures. The results enabled us to identify the most efficient and accurate methods for HAR utilizing data from internal sensors. This research has the potential to enhance the quality of life for the elderly and provide caregivers with the necessary tools to provide better care.

With improvements in the area of Internet of Things (IoT), surveillance systems have recently become more accessible. At the same time, optimizing the energy requirements of smart sensors, especially for data transmission, has always been very important and the energy efficiency of IoT systems has been the subject of numerous studies. For environmental monitoring scenarios, it is possible to extract more accurate information using smart multimedia sensors. However, multimedia data transmission is an expensive operation. In this study, a novel hierarchical approach is presented for the detection of forest fires. The proposed framework introduces a new approach in which multimedia and scalar sensors are used hierarchically to minimize the transmission of visual data. A lightweight deep learning model is also developed for devices at the edge of the network to improve detection accuracy and reduce the traffic between the edge devices and the sink. The framework is evaluated using a real testbed, network simulations, and 10-fold cross-validation in terms of energy efficiency and detection accuracy. Based on the results of our experiments, the validation accuracy of the proposed system is 98.28%, and the energy saving is 29.94%. The proposed deep learning model’s validation accuracy is very close to the accuracy of the best performing architectures when the existing studies and lightweight architectures are considered. In terms of suitability for edge computing, the proposed approach is superior to the existing ones with reduced computational requirements and model size.

Considering simultaneous wireless information and power transfer (SWIPT), we study a multiple-input- single-output (MISO) secrecy channel which consists of a multi-antenna trans- mitter and a cooperative jammer (CJ), multiple multi-antenna energy receivers (ERs), i.e., potential eavesdroppers, and multiple single-antenna co-located receivers (CRs). Both transmitter and CJ send the intend signal with artificial noise (AN) and jamming signal to interfere with the ERs. All receivers (CRs and ERs) adopt a power splitter to decode information and harvest power simultaneously. We exploit AN and CJ to facilitate efficient wireless energy transfer and secure transmission. Our aim is to maximize the minimum harvested energy among all ERs and CRs subject to the total power constraints at the transmitter and CJ while guaranteeing the minimum secrecy rate for each CR above its requirement. By incorporating norm-bounded channel uncertainty model, we propose a joint design of robust secure transmission. The original problem is solved by a two- step approach. In the first step, the proposed problem is reformulated as a sequence of semidefinite programs (SDPs). In the second step, the proposed problem can be handled by one-dimensional search to attain the optimal solution. Simulation results indicate that the performance of the proposed scheme outperforms that of separated AN-aided or CJ-aided scheme.

In Wireless Sensor Networks (WSNs), performance and availability are important in providing Quality of Service (QoS). WSNs are prone to failures that may result from software and hardware malfunctions, battery drain, tampering and link failures. In addition, sensors are resource constrained in terms of inadequate processing capacity, limited storage memory and restricted power supply. Alternating sensor operations between sleep and active modes whilst saving energy, has also introduced more challenges to the performance and dependability of WSN systems. This paper therefore seeks to investigate performance and availability concerns resulting from link and node failures in addition to the buffer restrictions and challenges caused by alternating sensor operations between active and sleep states. First, a finite queue capacity analytical model integrating performance and availability in the presence of node and channel failures and repairs is developed. Using the model, we analyse performance and availability of WSNs in terms of network throughput, delays and dependability. Finally, the model is used to evaluate tradeoffs between performance metrics. The analytical solutions using Spectral Expansion and Kolmogorov Forward equations as well as the simulation results are in good agreement.

This paper investigates relay selection for reliable data transmission in relay-assisted multisource multicast networks (RMMNs) where multiple source nodes distribute information to a set of destination nodes with the assistance of multiple relay nodes. Hybrid automatic repeat request with incremental redundancy (HARQ-IR) is used and supported by either a physical-layer network coding (PNC) or an analog network coding (ANC) technique employed at the relays. By deriving efficiency metrics of the HARQ-IR protocols, we propose relay selection schemes for RMMNs to minimize the transmission delay and energy consumption. Simulation results are provided to analyse each relay selection scheme.

Service and Buffer Management techniques can be used to ensure Quality of Service (QoS) for different traffic flows according to some specific policies. In this study, a single buffer queuing system is considered to model single and multi-channel, homogeneous wireless network systems such as wireless local area networks (WLANs) and cellular networks. These systems are now being used to carry both voice and data traffic and hence it is important to optimise these systems in an attempt to reduce the blocking, and minimize the latency to acceptable ranges. Since voice packets are delay sensitive, they have the priority to receive service. Also they require smaller buffering capacities, since the response time to voice requests should be below specific values. In addition, in order to reduce retransmission on reliable data connections, data packets are not usurped by incoming voice packets. In this paper, a mathematical analysis of this scenario is explored. The proposed mathematical model is represented by two dimensions, one for incoming voice packets and one for data packets. The models proposed show that it is possible to store incoming voice packets in the queue in case the channel or channels are busy. Both voice and data packets have finite buffering. Incoming voice packets are blocked when the voice buffer or the common queue is full. Therefore there is an added blocking probability of voice due to the presence of data packets in the system when the common queue is full. The analytical model is validated using simulation. The system proposed attempts to provide minimum delay for voice while reducing the disruption to reliable data connections. Numerical results show that, it is possible to attain these goals with reasonable buffer sizes. This study is useful for understanding the trade-offs and thresholds of single and multi-channel systems with voice and data traffic.

This paper presents a new analytical model to enhance the modelling of vertical handover for integrated cellular/WLAN systems. The WLAN system considered is within the coverage area of cellular network, hence users can have a downward vertical handover to the WLAN and/or an upward vertical handover to the cellular network. Recent work on the modelling of these systems using a two-stage model with feedback encountered some complications in terms of handling certain streams. The possibility of having continuous streams which keep on switching between WLAN and cellular systems, may reduce the practicality of the models. The new analytical model presented in this paper restricts certain flows to make sure that the handover calls from the WLAN to the cellular system are not allowed back to the WLAN. Previously proposed analytical models, which do not nullify these streams may not reflect real systems and the results obtained may not be practically applicable especially for such a configuration of cellular/WLAN interaction. A new model is presented with an extra random variable in order to ensure that Markovian property is not violated. Results are presented to show that the new model is a significant improvement but more work is needed to analyse more complex scenarios.

A Wireless Sensor Network (WSN) consists of spatially distributed autonomous sensors that monitor environmental data such as temperature, humidity, light, speed and sound. WSNs pose new security challenges because of their unattended nature and limited resources. Although prevention measures such as encryption and firewalls have been successfully applied, the attacker can physically access the node and modify it. Intrusion Detection Systems (IDSs) are a second line of defence that can be used to mitigate this problem. Building IDSs for WSNs is a new challenge because of the limited resources of the WSN nodes. IDS solutions for sensor networks should try to minimise the use of battery of the sensor nodes in order to prolong the network lifetime. In this paper we analyse different solutions that have been proposed for intrusion detection in wireless sensor networks. More specifically we analyse the impact of popular intrusion detection systems on the life time of the WSNs. Our study is quite general since we consider IDSs that are distributed on the sensor nodes and continuously monitor the networks for evidence of attacks. We also consider IDSs that are event triggered, which means that they require agreement between nodes when a suspicious activity is detected. The agreement is used to detect the attack and isolate the attacker. We analyse the effects of IDSs on battery life. The results show that, popular oral message algorithm of Byzantine generals problem should be considered for small scale WSNs because of the overhead introduced in terms of messages exchanged for decision. We conclude our paper with properties and recommendations for IDSs working for WSNs and some future works.

The main feature of the next generation wireless communication systems is the ability to establish ubiquitous and seamless access to various radio access technologies (RATs) and standards. For this reason the integration of cellular and wireless local area networks (WLANs) and performance evaluation of the interaction between these technologies is now an important research area. Modelling such systems for performance evaluation is essential to improve the architecture according to the quality of service (QoS) requirements and performance characteristics. In this paper, an analytical model for performance evaluation of an integrated cellular network and a WLAN is considered. WLAN is deployed inside of the cellular network to support handoffs between cellular networks with higher bandwidth. Such an integrated system can be modelled as a two stage open network. An analytical model is proposed together with an exact solution technique in order to evaluate the performance of an integrated system consisting of a cellular network and a WLAN. A two stage queuing system is considered for this purpose. Numerical results are presented for mean queue length values of cellular system as well as the WLAN.

Networks of queues are extensively used in modelling transaction processing systems and nodes in communication networks. Today, many practical queuing systems with finite queuing capacity are widely used in communication and computing. In such systems, servers are prone to failures. In this paper, the performance modelling of a multi-node system, with finite capacity heterogeneous nodes, serving internal and external arrivals of jobs is considered. An analytical model has been developed, and solved for performability measures. Joint-state modelling approach is used for this purpose. In an attempt to improve accuracy in performability evaluation, assumptions made have been minimised and a series of computations have been performed for open queuing networks with breakdowns, repairs, and finite queuing capacity. Results obtained from the analytical model are presented comparatively with simulation results and IPP modelling.