With predictions suggesting there will be 18 billion Internet of Things (IoT) devices live by 2022, performance of these low powered devices, as well as security is of utmost importance.Managing security and performance is a balancing act.Achieving this balance will always continue to be a challenge.This research presents two main contributions to this area.The first contribution is a framework to measure cryptographic performance of IoT devices.The areas of measurement are power consumption, time cost, energy cost, random access memory (RAM) usage and flash usage.The second contribution is an insightful comparison of the performance of the ATmega328, STM32F103C8T6 and ESP8266 low powered microcontroller devices.Experiments were conducted on these devices running various cryptographic operations.The measured operations are from three encryption algorithms: Advanced Encryption Standard (AES), ChaCha and Acorn.The proposed methods from this research are real-world in nature rather than simulated, and can be used by others wishing to conduct their own IoT performance testing.The results show that the ATmega328 has the lowest overall power consumption.The ESP8266 was generally the fastest performing device.ChaCha outperformed AES in both time cost and energy cost.Both algorithms outperformed Acorn in these metrics.The STM32F103C8T6 device displayed the best overall energy cost, while still performing well in terms of time.The results from the experiments conducted in this study can be used by network designers, developers and others to make appropriate decisions in IoT deployments with regards to balancing performance and security.

The purpose of this study is twofold. First, this study proposes a cost-effective LoRa gateway to improve bandwidth utilisation to achieve optimal network throughput for LoRa networks from a hardware design perspective. Secondly, this study creates a design for adaptive and autonomous algorithm to allocate bandwidth while meeting dynamic throughput demands from a network management perspective. This study conducted actual experiments to evaluate the network throughput capacity of a LoRa gateway based on the SemTech™ SX1301 transceiver chipset (SX1301 gateway). This study also addresses the limitations of the SX1301 gateway by proposing a gateway to improve bandwidth utilisation to increase network throughput. Knowing different packet sizes have an impact on network throughput, this study also set up a series of actual experiments related to the network throughput of the proposed gateway with 40 test combinations based on four different packet sizes and ten configurable bandwidth options. These test results were gathered and analysed to establish the throughput threshold for four different packet size ranges, and then to design an adaptive and autonomous algorithm for dynamic bandwidth allocation without human intervention. Based on the theoretical throughput capacity, the proposed gateway has an average improvement of throughput capacity of 57.73%, compared to the SX1301 gateway. The significance of the proposed adaptive algorithm is its capability for monitoring of the network usage constantly and then allocating the bandwidth on demand in an autonomous, agile and scalable fashion.

This research is intended to provide practical insights to empower designers, developers and management to develop smart cities underpinned by Long Range (LoRa) technology. LoRa, one of most prevalent long-range wireless communication technologies, can be used to underpin the development of smart cities. This study draws upon relevant research to gain an understanding of underlying principles and issues involved in the design and management of long-range and low-power networks such as LoRa. This research uses empirical evidence that has been gathered through experiments with a LoRa network to analyse network design and identify challenges and then proposes cost-effective and timely solutions. Particularly, practical measurements of LoRa network dependencies and performance metrics are used to support our proposals. This research identifies a number of network performance metrics that need to be considered and controlled when designing and managing LoRa-specific networks from the perspectives of hardware, software, networking and security.