Real-Life Experiments based on IQRF IoT Testbed: From Sensors to Cloud

Master's thesis Information- and communication technology IKT590 - University of Agder 2018Internet of things (IoT) is the next generation internet technology which connects devices and objects intelligently to control data collected by diverse types of sensors, radio frequency identification and other physical objects. To address the challenges in IoT such as integrating artificial intelligent techniques with IoT concept, developing green IoT technologies and combining IoT and cloud computing, various platforms which support reliable and low power wireless connectivity are required. IQRF is a recently developed platform for wireless connectivity. It provides low power, low speed, reliable and easy to use wireless connectivity in sub-GHz bands for telemetry and industrial control and building automation. The applications are used for scientific knowledge in practical purposes, especially in industrial usage. It is extensively non-identical from what we are accustomed to nowadays. It has been designed to use IQMESH technology. The purpose for IQMESH is to ensure wireless connectivity wherever it is necessary, covering tens of hundreds of meters up to several kilometers. In this master’s thesis, we implemented an IQRF platform-based testbed for IoT related application scenarios which can measure various environmental conditions and perform required communications. The research work of this thesis is carried out in three directions, i.e., single-hop and multi-hop communication for temperature measurements, light intensity measurements via integrated light dependent resistors and cloud-based connectivity for IQRF sensors. The work performed in this thesis provides a valuable result because IQRF does not only solve problems regarding wireless technology, but it also supports industrial control, remote control and cloud control as well. Also, as the devices come with different input/output pins, they are easily maneuverable to connect different external sensors to get accurate results. In this thesis, the employed research methods, experiments, readings and related discussions have been presented accordingly. Key words: IQRF, IoT, Wireless Sensor Network, Light Dependent Resistor, GSM Gateway, IEEE 802.15.4, IQRF Clou

Energy and throughput efficient strategies for heterogeneous future communication networks

As a result of the proliferation of wireless-enabled user equipment and data-hungry applications, mobile data traffic has exponentially increased in recent years.This in-crease has not only forced mobile networks to compete on the scarce wireless spectrum but also to intensify their power consumption to serve an ever-increasing number of user devices. The Heterogeneous Network (HetNet) concept, where mixed types of low-power base stations coexist with large macro base stations, has emerged as a potential solution to address power consumption and spectrum scarcity challenges. However, as a consequence of their inflexible, constrained, and hardware-based configurations, HetNets have major limitations in adapting to fluctuating traffic patterns. Moreover, for large mobile networks, the number of low-power base stations (BSs) may increase dramatically leading to sever power consumption. This can easily overwhelm the benefits of the HetNet concept. This thesis exploits the adaptive nature of Software-defined Radio (SDR) technology to design novel and optimal communication strategies. These strategies have been designed to leverage the spectrum-based cell zooming technique, the long-term evolution licensed assisted access (LTE-LAA) concept, and green energy, in order to introduce a novel communication framework that endeavors to minimize overall network on-grid power consumption and to maximize aggregated throughput, which brings significant benefits for both network operators and their customers. The proposed strategies take into consideration user data demands, BS loads, BS power consumption, and available spectrum to model the research questions as optimization problems. In addition, this thesis leverages the opportunistic nature of the cognitive radio (CR) technique and the adaptive nature of the SDR to introduce a CR-based communication strategy. This proposed CR-based strategy alleviates the power consumption of the CR technique and enhances its security measures according to the confidentiality level of the data being sent. Furthermore, the introduced strategy takes into account user-related factors, such as user battery levels and user data types, and network-related factors, such as the number of unutilized bands and vulnerability level, and then models the research question as a constrained optimization problem. Considering the time complexity of the optimum solutions for the above-mentioned strategies, heuristic solutions were proposed and examined against existing solutions. The obtained results show that the proposed strategies can save energy consumption up to 18%, increase user throughput up to 23%, and achieve better spectrum utilization. Therefore, the proposed strategies offer substantial benefits for both network operators and users