Modelling the Integrated QoS for Wireless Sensor Networks with Heterogeneous Data Traffic

The future of Internet of Things (IoT) is envisaged to consist of a high amount of wireless resource-constrained devices connected to the Internet. Moreover, a lot of novel real-world services offered by IoT devices are realized by wireless sensor networks (WSNs). Integrating WSN to the Internet has therefore brought forward the requirements of an end-to-end quality of service (QoS) guarantee. In this paper, the QoS requirements for the WSN-Internet integration are investigated by first distinguishing the Internet QoS from the WSN QoS. Next, this study emphasizes on WSN applications that involve traffic with different levels of importance, thus the way realtime traffic and delay-tolerant traffic are handled to guarantee QoS in the network is studied. Additionally, an overview of the integration strategies is given, and the delay-tolerant network (DTN) gateway, being one of the desirable approaches for integrating WSNs to the Internet, is discussed. Next, the implementation of the service model is presented, by considering both traffic prioritization and service differentiation. Based on the simulation results in OPNET Modeler, it is observed that real-time traffic achieve low bound delay while delay-tolerant traffic experience a lower packet dropped, hence indicating that the needs of real-time and delay-tolerant traffic can be better met by treating both packet types differently. Furthermore, a vehicular network is used as an example case to describe the applicability of the framework in a real IoT application environment, followed by a discussion on the future work of this research

Adaptive Quality of Service for IoT-based Wireless Sensor Networks

The future of the Internet of Things (IoT) is envisaged to consist of a high amount of wireless resource-constrained devices connected to the Internet. Moreover, a lot of novel real-world services offered by IoT devices are realised by wireless sensor networks (WSNs). Integrating WSNs to the Internet has therefore brought forward the requirements of an end-to-end quality of service (QoS) guarantees. In this thesis, a QoS framework for integrating WSNs with heterogeneous data traffic is proposed. The concept of Adaptive Service Differentiation for Heterogeneous Data in WSN (ADHERE) is proposed based on the varying QoS factors and requirements analysis of mixed traffic within an IoT-based WSN. The objective of the QoS framework is to meet the requirements of heterogeneous data traffic in the WSN - in the domain of timeliness and reliability. Another objective is to implement an adaptive QoS scheme that can react to dynamic network changes. This thesis provides the literature analysis and background study for integrating a WSN which contains heterogeneous data traffic with the Internet. In the discussion of network modelling and implementation tools for the testing, this thesis provides an insight into the different tools that are available and their ability to investigate the concept of service differentiation among heterogeneous traffic within the IoT-based WSN network. Furthermore, the major components of ADHERE are presented in the Concept chapter. The major components are: a heterogeneous traffic class queuing model that encompasses a service differentiation policy, a congestion control unit and a rate adjustment unit that supports the adaptive mechanism. Network modelling and the simulation of an ADHERE QoS framework which is carried out primarily using the network simulation tool, Riverbed Modeler, are also presented. Additionally, a proposed co-simulation between Riverbed Modeler and MATLAB is introduced, which aims to provide a seamless QoS monitoring using the ADHERE concept. The simulation results suggest that real-time traffic achieves low bound delay while delay-tolerant traffic experiences a lower packet drop. This indicates that the needs for real-time and delay-tolerant traffic can be better met by treating both packet types differently using ADHERE. Furthermore, a verification and added-value to the ADHERE QoS model using a neural network is also presented. The learning capabilities in ADHERE optimise the QoS framework’s performance by accommodating the QoS requirements of the network through the unpredictable traffic dynamics and when complex network behaviour takes place. Before concluding the thesis, the implementation of ADHERE QoS as a use-case on a physical test environment is also discussed. The test environment offers a flexible system that is capable of reacting to the dynamic changes of process demands. Physical network performance can be predicted by analysing the historical data in the background on a network simulator or virtual network. Finally, this thesis offers a conclusion with an indication of our future research work

Bandwidth Performance Analysis of a Remote Monitoring Surveillance System

Conventional security surveillance systems require the constant attention of security personnel, to monitor several locations concurrently. With the declining cost of computing power and widespread acceptance of the Internet as a viable communication medium, a low-cost and effective web-based surveillance system becomes an attractive alternative to conventional system. Apart from the increased availability of inexpensive computing power and image sensors, the inefficiency of manual surveillance and monitoring system has also become the contributing factor towards the growth of motion detection application. The aim of this research is to study and develop a web-based surveillance system consisting of a motion detection technique. By adopting WebCam Monitor as the motion detection tool, the thesis describes the construction of the remote monitoring surveillance system consisting of webcam technology. This thesis discusses the system and network performances evaluated from the developed surveillance system. Network Quality of Service (QoS) is implemented in system design, by means of bandwidth management appliance, Packet Shaper. The research results describe the findings in the QoS implementation on the proposed system, focusing on bandwidth requirements, bandwidth utilization, and network efficiencies