Proposal For 6LoWPAN Wireless Network Protocol-Based Street-Light-As-A-Service (SLaaS) Framework To Power Campus Parking Services

A novel IPv6 Over Low Power Wireless Personal Area Network (6LoWPAN) protocol-based Street-Light-As-A-Service (SLaaS) research framework for an integrated cloud-based smart university campus parking platform is being proposed. The Intelligent Connected Street Light infrastructure currently in existence at University Sains Malaysia (USM) is being redesigned. As part of overall parking proposal, approaching object image and video data are being acquired using a range of sensors, including the  passive infrared (PIR) and 3-D Light Detection and Ranging (LIDAR) motion sensors. To acquire and transmit vehicle instrumentation data, ELM327 Onboard Diagnostics 2 (OBD-II) Wi-Fi adapter is being used. For edge computing-based intelligent object detection model processing to synchronize license plate and facial recognition data with USM databases, Nvidia® Jetson Nano is being used. The framework is developed to effect multiple services, including to track and manage university vehicles, to detect and secure pedestrian movement, to trigger lighting commands based on approaching vehicle movement for on-demand parking illumination, to partition digital bounding box perimeter to predict potential vehicle collisions, to detect unregistered and excessive parking time to monitor unattended and illegal vehicles, to enable street-light-located parking-related kiosk services, and consolidate cloud-based human and vehicle data analytics into mobile form-factor dashboards. The proposed design will be evaluated and validated for end-to-end average data propagation rate, data integrity, object-to-human and object-to-vehicle synchronization success rate, electrical power consumption reduction and potential surface attack mitigation and avoidance throughout the network

ENABLING SMART CITY SERVICES FOR HETEROGENEOUS WIRELESS NETWORKS

A city can be transformed into a smart city if there is a resource-rich and reliable communication infrastructure available. A smart city in effect improves the quality of life of citizens by providing the means to convert the existing solutions to smart ones. Thus, there is a need for finding a suitable network structure that is capable of providing sufficient capacity and satisfactory quality-of-service in terms of latency and reliability. In this thesis, we propose a wireless network structure for smart cities. Our proposed network provides two wireless interfaces for each smart city node. One is supposed to connect to a public WiFi network, while the other is connected to a cellular network (such as LTE). Indeed, Multi-homing helps different applications to use the two interfaces simultaneously as well as providing the necessary redundancy in case the connection of one interface is lost. The performance of our proposed network structure is investigated using comprehensive ns-2 computer simulations. In this study, high data rate real-time and low data rate non-real-time applications are considered. The effect of a wide range of network parameters is tested such as the WiFi transmission rate, LTE transmission rate, the number of real-time and non-real-time nodes, application traffic rate, and different wireless propagation models. We focus on critical quality-of-service (QoS) parameters such as packet delivery delay and packet loss. We also measured the energy consumed in packet transmission. Compared with a single-interface WiFi-based or an LTE-based network, our simulation results show the superiority of the proposed network structure in satisfying QoS with lower latency and lower packet loss. We found also that the proposed multihoming structure enables the smart city sensors and other applications to realize a greener communication by consuming a lesser amount of transmission power rather than single interface-based networks

PERFORMANCE STUDY FOR CAPILLARY MACHINE-TO-MACHINE NETWORKS

Communication technologies witness a wide and rapid pervasiveness of wireless machine-to-machine (M2M) communications. It is emerging to apply for data transfer among devices without human intervention. Capillary M2M networks represent a candidate for providing reliable M2M connectivity. In this thesis, we propose a wireless network architecture that aims at supporting a wide range of M2M applications (either real-time or non-real-time) with an acceptable QoS level. The architecture uses capillary gateways to reduce the number of devices communicating directly with a cellular network such as LTE. Moreover, the proposed architecture reduces the traffic load on the cellular network by providing capillary gateways with dual wireless interfaces. One interface is connected to the cellular network, whereas the other is proposed to communicate to the intended destination via a WiFi-based mesh backbone for cost-effectiveness. We study the performance of our proposed architecture with the aid of the ns-2 simulator. An M2M capillary network is simulated in different scenarios by varying multiple factors that affect the system performance. The simulation results measure average packet delay and packet loss to evaluate the quality-of-service (QoS) of the proposed architecture. Our results reveal that the proposed architecture can satisfy the required level of QoS with low traffic load on the cellular network. It also outperforms a cellular-based capillary M2M network and WiFi-based capillary M2M network. This implies a low cost of operation for the service provider while meeting a high-bandwidth service level agreement. In addition, we investigate how the proposed architecture behaves with different factors like the number of capillary gateways, different application traffic rates, the number of backbone routers with different routing protocols, the number of destination servers, and the data rates provided by the LTE and Wi-Fi technologies. Furthermore, the simulation results show that the proposed architecture continues to be reliable in terms of packet delay and packet loss even under a large number of nodes and high application traffic rates