Massey Documents by Type

Permanent URI for this communityhttps://mro.massey.ac.nz/handle/10179/294

Browse

Subject: search.filters.subject.Internet of things

Search Results

Now showing 1 - 5 of 5
  • Thumbnail Image
    Item
    Improving network lifetime through energy-efficient protocols for IoT applications : thesis submitted to the School of Food and Advanced Technology, Massey University New Zealand, in partial fulfilment of the requirements for the degree of Doctor of Philosophy
    (Massey University, 2022) Mishra, Mukesh
    Sensors are ubiquitous. They can be found in homes, factories, farms, and just about everywhere else. To meet distributed sensing requirements several sensors are deployed and connected on a wireless media to form a Wireless Sensor Network (WSN). Sensor nodes exchange information with one another and with a base station (BS). We begin with a review of recent work on cross-layer WSN design techniques based on the Open System Interconnection (OSI) model. The distributed sensor nodes are often grouped in clusters and a cluster head (CH) is chosen and used to route data from the sensor nodes to the BS. The thesis evaluates constraints-based routing algorithms, which choose a routing path that satisfies administrative or Quality of Service (QoS) constraints. Different algorithms reduce costs, balance network load, and improve security. Clustering sensor nodes in a wireless sensor network is an important technique for lowering sensor energy consumption and thus extending the network's lifetime. The cluster head serves as a router in a network. Furthermore, the cluster head is in charge of gathering and transmitting sensed information from cluster members to a destination node or base station/sink. To safely elect a cluster head, an efficient clustering approach is required. It continues to be an important task for overall network performance. As a result, in this study, we propose a scheme for cluster head selection based on a trust factor that ensures all nodes are trustworthy and authentic during communication. Direct trust is calculated using parameters such as residual energy and node distance. Further, K-means clustering algorithm has been employed for cluster head selection. The simulation results show that the proposed solution outperforms the LEACH (Low-Energy Adaptive Clustering Hierarchy) protocol in improving network lifetime, packet delivery ratio, and energy consumption. Furthermore, this strategy can significantly improve performance while discriminating between legitimate and malicious (or compromised) nodes in the network. The use of the IoT in wireless sensor networks (WSNs) presents substantial issues in ensuring network longevity due to the high energy requirements of sensing, processing, and data transmission. Thus, multiple conventional algorithms with optimization methodologies have been developed to increase WSN network performance. These algorithms focus on network layer routing protocols for dependable, energy-efficient communication, extending network life. This thesis proposes multi-objective optimization strategy. It calculates the optimum path for packets from the source to the sink or base station. The proposed model works in two-steps. First, a trust model selects cluster head to control data connection between the BS and cluster nodes. To determine data transmission routes, a novel hybrid algorithm is proposed that combines a particle swarm optimization (PSO) algorithm and a genetic algorithm (GA) .The obtained results validate the proposed approach's efficiency, as it outperforms existing methods in terms of increased energy efficiency, increased network throughput, high packet delivery ratio, and high residual energy across all iterations. Sensor nodes (SNs) have very constrained memory, energy, and computational resources.The limitations are further exacerbated due to the large volume of sensing data generated in a distributed IoT application . Energy can be saved by compressing data at the sensor node or CH level before transmission. The majority of data compression research has been motivated by image and video compression; however, the vast majority of these algorithms are inapplicable on sensor nodes due to memory restrictions, energy consumption, and processing speed. To address this issue, we chose established data compression techniques such as Run Length Encoding (RLE) and Adaptive Huffman Encoding (AHE), which require much less resources and can be executed on sensor nodes. Both RLE and AHE can negotiate compression ratio and energy utilisation effectively. This thesis initially evaluates RLE and AHE data compression efficiency. Hybrid-RLEAHE (H-RLEAHE) is then suggested and tested for sensor nodes. Simulations were run to validate the efficacy of the proposed hybrid algorithm, and the results were compared to compression methods using RLE, AHE, and without the use of any compression technique for five different cases. RLE data compression outperforms H-RLEAHE and AHE in energy efficiency, network performance, packet delivery ratio, and energy across all iterations.
  • Thumbnail Image
    Item
    Blockchain for secured IoT and D2D applications over 5G cellular networks : a thesis by publications presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer and Electronics Engineering, Massey University, Albany, New Zealand
    (Massey University, 2021) Honar Pajooh, Houshyar
    The Internet of things (IoT) is in continuous development with ever-growing popularity. It brings significant benefits through enabling humans and the physical world to interact using various technologies from small sensors to cloud computing. IoT devices and networks are appealing targets of various cyber attacks and can be hampered by malicious intervening attackers if the IoT is not appropriately protected. However, IoT security and privacy remain a major challenge due to characteristics of the IoT, such as heterogeneity, scalability, nature of the data, and operation in open environments. Moreover, many existing cloud-based solutions for IoT security rely on central remote servers over vulnerable Internet connections. The decentralized and distributed nature of blockchain technology has attracted significant attention as a suitable solution to tackle the security and privacy concerns of the IoT and device-to-device (D2D) communication. This thesis explores the possible adoption of blockchain technology to address the security and privacy challenges of the IoT under the 5G cellular system. This thesis makes four novel contributions. First, a Multi-layer Blockchain Security (MBS) model is proposed to protect IoT networks while simplifying the implementation of blockchain technology. The concept of clustering is utilized to facilitate multi-layer architecture deployment and increase scalability. The K-unknown clusters are formed within the IoT network by applying a hybrid Evolutionary Computation Algorithm using Simulated Annealing (SA) and Genetic Algorithms (GA) to structure the overlay nodes. The open-source Hyperledger Fabric (HLF) Blockchain platform is deployed for the proposed model development. Base stations adopt a global blockchain approach to communicate with each other securely. The quantitative arguments demonstrate that the proposed clustering algorithm performs well when compared to the earlier reported methods. The proposed lightweight blockchain model is also better suited to balance network latency and throughput compared to a traditional global blockchain. Next, a model is proposed to integrate IoT systems and blockchain by implementing the permissioned blockchain Hyperledger Fabric. The security of the edge computing devices is provided by employing a local authentication process. A lightweight mutual authentication and authorization solution is proposed to ensure the security of tiny IoT devices within the ecosystem. In addition, the proposed model provides traceability for the data generated by the IoT devices. The performance of the proposed model is validated with practical implementation by measuring performance metrics such as transaction throughput and latency, resource consumption, and network use. The results indicate that the proposed platform with the HLF implementation is promising for the security of resource-constrained IoT devices and is scalable for deployment in various IoT scenarios. Despite the increasing development of blockchain platforms, there is still no comprehensive method for adopting blockchain technology on IoT systems due to the blockchain's limited capability to process substantial transaction requests from a massive number of IoT devices. The Fabric comprises various components such as smart contracts, peers, endorsers, validators, committers, and Orderers. A comprehensive empirical model is proposed that measures HLF's performance and identifies potential performance bottlenecks to better meet blockchain-based IoT applications' requirements. The implementation of HLF on distributed large-scale IoT systems is proposed. The performance of the HLF is evaluated in terms of throughput, latency, network sizes, scalability, and the number of peers serviceable by the platform. The experimental results demonstrate that the proposed framework can provide a detailed and real-time performance evaluation of blockchain systems for large-scale IoT applications. The diversity and the sheer increase in the number of connected IoT devices have brought significant concerns about storing and protecting the large IoT data volume. Dependencies of the centralized server solution impose significant trust issues and make it vulnerable to security risks. A layer-based distributed data storage design and implementation of a blockchain-enabled large-scale IoT system is proposed to mitigate these challenges by using the HLF platform for distributed ledger solutions. The need for a centralized server and third-party auditor is eliminated by leveraging HLF peers who perform transaction verification and records audits in a big data system with the help of blockchain technology. The HLF blockchain facilitates storing the lightweight verification tags on the blockchain ledger. In contrast, the actual metadata is stored in the off-chain big data system to reduce the communication overheads and enhance data integrity. Finally, experiments are conducted to evaluate the performance of the proposed scheme in terms of throughput, latency, communication, and computation costs. The results indicate the feasibility of the proposed solution to retrieve and store the provenance of large-scale IoT data within the big data ecosystem using the HLF blockchain.
  • Thumbnail Image
    Item
    Novel lightweight ciphertext-policy attribute-based encryption for IoT applications : a thesis presented in partial fulfilment of the requirements for the degree of Master of Information Science at Massey University, Auckland, New Zealand
    (Massey University, 2018) Li, Ping
    As more sensitive data are frequently shared over the Internet of Things (IoT) network, the confidentiality and security of IoT should be given special consideration. In addition, the property of the resources-constraint nodes raises a rigid lightweight requirement for IoT security system. Currently, the Attribute-Based Encryption (ABE) for fine-grained access control is the state-of-the-art technique to enable the secure data transmission and storage in the distributed case such as IoT. However, most existing ABE schemes are based on expensive bilinear pairing with linear size keys and ciphertexts. This results in the increase of the memory and computational requirement on the devices, which is not suitable for the resource-limited IoT applications. Leveraging on the advantages offered by the Ciphertext-Policy ABE (CP-ABE), this thesis proposes two constructions of lightweight no-paring cryptosystems based on Rivest–Shamir–Adleman (RSA). One realized work is a construction of AND-gate CP-ABE to achieve both constant-size keys and ciphertexts. The result of the evaluation shows that it reduces the storage and computational overhead. The other construction supports an expressive monotone tree access structure to implement the complex access control as a more generic system. Both have respective advantages in different contexts and are provably secure to guarantee the sharing of data, as well as more applicable and efficient than the previous scheme. In this thesis, practical issues are also described about implementations and evaluations of both proposals.
  • Thumbnail Image
    Item
    Gesture and voice control of internet of things : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Electronics and Computer Engineering at Massey University, Auckland, New Zealand
    (Massey University, 2015) Han, Xiao
    Nowadays, people's life has been remarkably changed with various intelligent devices which can provide more and more convenient communication with people and with each other. Gesture and voice control are becoming more and more important and widely used. People feel the control system humanized and individualised using biological control. In this thesis, an approach of combined voice and gesture control of Internet of Things is proposed. A prototype is built to show the accuracy and practicality of the system. A Cortex-A8 processor (S5PV210) is used and the embedded Linux version 3.0.8 has been cross-compiled. Qt 4.8.5 has been ported as a UI (User Interface ) framework and OpenCV 2.4.5 employed as vision processing library. Two ZigBee modules are used to provide wireless communication for device control. The system is divided into control station and appliance station. The control station includes development board, USB camera, voice recognition module, LCD screen and ZigBee module. This station is responsible for receiving input signal (from camera or microphone), analyzing the signal and sending control signal to appliance station. The appliance station consists of relay, ZigBee module and appliances. The ZigBee module in the appliance station is to receive control signal and send digital signal to connected relay. The appliance station is a modular unit that can be expanded for multiple appliances. The system can detect and keep tracking user's hand. After recognizing user's gesture, it can control appliances based on certain gestures. Voice control is included as an additional control approach and voice commands can be adjusted for different devices.
  • Thumbnail Image
    Item
    Design and implementation of Internet of Things for home environment : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Electronics and Computer Systems Engineering at Massey University, Manawatu, New Zealand
    (Massey University, 2013) Kelly, Sean
    An integrated framework for smart home monitoring towards internet of things based on ZigBee and 6LoWPAN wireless sensor networks is presented. The system was developed to retrofit existing sub systems of wireless technologies in order to reduce cost, and complexity. The practical internetworking architecture and the connection procedures for reliable measurement of smart sensors parameters and transmission of sensing data via internet are presented. A ZigBee based sensing system was designed and developed to see the feasibility of the system in home automation for contextual environmental monitoring. The ubiquitous sensing system is based on combination of pervasive distributed sensing units and an information system for data aggregation and analysis. Results related to the home automation parameters and execution of the system running continuously for long durations is encouraging. The prototype system (ZigBee based) was tested to generate real-time graphical information rather than using a simulator or a test bed scenario. A trail has also been performed with 6LoWPAN technology to provide functionality as the ZigBee based system. The overall internetworking architecture describes the integration of a low power consumption wireless sensor network with the internet. The proposed prototype has advantages in terms of low cost, flexibility of usage. The design of the integrated framework provides a template for other applications related to the Internet of Things.