Collaboration has become a key feature of modern software, allowing teams to work together effectively in real-time while in different locations. In order for a user to communicate their intention to several distributed peers, computing devices must exchange high-frequency updates with transient metadata like mouse position, text range highlights, and temporary comments. Current peer-to-peer awareness solutions have high time and space complexity due to the ever-expanding logs that each client must maintain in order to ensure robust collaboration in eventually consistent environments. This paper proposes an awareness Conflict-Free Replicated Data Type (CRDT) library that provides the tooling to support an eventually consistent, decentralized, and robust multi-user collaborative environment. Our library is tuned for rapid iterative updates that communicate fine-grained user actions across a network of collaborators. Our approach holds memory constant for subsequent writes to an existing key on a shared resource and completely prunes stale data from shared documents. These features allow us to keep the CRDT's memory footprint small, making it a feasible solution for memory constrained applications. Results show that our CRDT implementation is comparable to or exceeds the performance of similar data structures in high-frequency read/write scenarios.

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Traditional Machine Learning (ML) methods usually rely on a central server to per-form ML tasks. However, these methods have problems like security risks, datastorage issues, and high computational demands. Federated Learning (FL), on theother hand, spreads out the ML process. It trains models on local devices and thencombines them centrally. While FL improves computing and customization, it stillfaces the same challenges as centralized ML in security and data storage. This thesis introduces a new approach combining Federated Learning and Decen-tralized Machine Learning (DML), which operates on an Ethereum Virtual Machine(EVM) compatible blockchain. The blockchain’s security and decentralized naturehelp improve transparency, trust, scalability, and efficiency. The main contributionsof this thesis include:1. Redesigning a semi-centralized system with enhanced privacy and the multi-KRUM algorithm, following the work of Shayan et al..2. Developing a new decentralized framework that supports both standard anddeep-learning FL, using the InterPlanetary File System (IPFS) and EthereumVirtual Machine (EVM)-compatible Smart Contracts.3. Assessing how well the system defends against common data poisoning attacks,using a version of Multi-KRUM that’s better at detecting outliers.4. Applying privacy methods to securely combine data from different sources.

Polar Spectrum Coding is a novel speech coding algorithm for narrowband voice communications. A polar Fourier transform of the signal is computed, and the magnitude and phase of the speech spectrum is encoded for transmission. The correlation between frames of speech signals is exploited to minimize the transmission rate required for intelligible speech. At the receiver, the encoded words are decoded and the spectrum reconstructed. An inverse Fourier transform is performed, and the result is the reconstructed speech waveform. Polar Spectrum Coding theory is explained. The sensitivities of various parameters on performance are explored, and performance in the presence of channel noise is measured. Directions for future research in the realm of Polar Spectrum Coding is suggested.

This report explains the development of a telephone line multiplexer to be used with a computer based personal paging system. The large geographical area coverage made possible by computer processing results in many calls having to cross telephone tariff boundaries. Since system users cannot be expected to pay long distance charges, dedicated lines which cross tariff boundaries must be leased. Multiplexing applied to those leased lines reduces the cost of data transmission, and is, therefore, justified. The design of the multiplexer proceeds from a specification set which is derived from user response requirements. Fundamentally, the response consists in advising the user, within a reasonable time, that a "page" has been accepted by the system. The specification set is then partitioned into functional blocks which are modeled using flow charts and state diagrams. Logic design follows directly from the models. Production of the multiplexer is followed by field installation. The savings resulting from the multiplexing are considerable.

WiFi networks are susceptible to statistical traffic analysis attacks. Despite encryption, the metadata of encrypted traffic, such as packet inter-arrival time and size, remains visible. This visibility allows potential eavesdroppers to infer private information in the Internet of Things (IoT) environment. For example, it allows for the identification of sleep monitors and the inference of whether a user is awake or asleep. WiFi eavesdropping theoretically enables the identification of IoT devices without the need to join the victim's network. This attack scenario is more realistic and much harder to defend against, thus posing a real threat to user privacy. However, researchers have not thoroughly investigated this type of attack due to the noisy nature of wireless channels and the relatively low accuracy of WiFi sniffers. Furthermore, many countermeasures proposed in the literature are inefficient in addressing side-channel leakage in WiFi networks. They often burden internet traffic with high data overhead and disrupt the user experience by introducing deliberate delays in packet transmission. This dissertation investigates privacy leakage resulting from WiFi eavesdropping and proposes efficient defensive techniques. We begin by assessing the practical feasibility of IoT device identification in WiFi networks. We demonstrate how an eavesdropper can fingerprint IoT devices by passively monitoring the wireless channel without joining the network. After exploring this privacy attack, we introduce a traffic spoofing-based defense within the WiFi channel to protect against such threats. Additionally, we propose a more data-efficient obfuscation technique to counter traffic analytics based on packet size without adding unnecessary noise to the traffic.

The role of the South African National Defence Force (SANDF) has changed considerably in the last decade. The emphasis has moved from protecting the country's borders to peacekeeping duties in Central Africa and even further North. Communications between the peacekeeping missions and the military bases back in South Africa is vital to ensure the success of these missions. Currently use is made of satellite as well as High Frequency (HF) communications. There are drawbacks associated with these technologies (high cost and low data rates/interference respectively). Successful long distance ionospheric propagation in the low Very High Frequency (VHF) range will complement the existing infrastructure and enhance the success rate of these missions. This thesis presents a feasibility study to determine under what ionospheric conditions such low VHF communications will be possible. The International Reference Ionosphere (IRI) was used to generate ionospheric data for the reflection point(s) of the signal. The peak height of the ionospheric F2 layer (hmF2) was used to calculate the required antenna elevation angle. Once the elevation angle is known it is possible to calculate the required F2 layer critical frequency (foF2). The required foF2 value was calculated by assuming a Maximum Useable Frequency (MUF) of 20% higher than the planned operational frequency. It was determined that single hop propagation is possible during the daytime if the smoothed sunspot number (SSN) exceeds 15. The most challenging requirement for successful single hop propagation is the need of an antenna height of 23 m. For rapid deployment and semi-mobile operations within a jungle environment it may prove to be a formidable obstacle.

The growth of Asynchronous Transfer Mode (ATM) was considered to be the ideal carrier of the high bandwidth applications like video on demand and multimedia e-learning. ATM emerged commercially in the beginning of the 1990's. It was designed to provide a different quality of service at a speed up 100 Gbps for both real time and non real time application. The turn of the 90's saw a variety of technologies being developed. This project analyzes these technologies, compares them to the Asynchronous Transfer Mode and assesses the future of ATM.

This thesis seeks to identify and explain some technology in order to more fully understand modern communication. This study makes use of metaphoric cluster analysis to examine the technological rhetoric of Nicholas Negroponte.

A thesis submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy in the School of Electrical and Information Engineering, 2016 / Reliable and e cient data transmission have been the subject of current research, most especially in realistic channels such as the Rayleigh fading channels. The focus of every new technique is to improve the transmission reliability and to increase the transmission capacity of the communication links for more information to be transmitted. Modulation schemes such as M-ary Quadrature Amplitude Modulation (M-QAM) and Orthogonal Frequency Division Multiplexing (OFDM) were developed to increase the transmission capacity of communication links without additional bandwidth expansion, and to reduce the design complexity of communication systems. On the contrary, due to the varying nature of communication channels, the message transmission reliability is subjected to a couple of factors. These factors include the channel estimation techniques and Forward Error Correction schemes (FEC) used in improving the message reliability. Innumerable channel estimation techniques have been proposed independently, and in combination with di erent FEC schemes in order to improve the message reliability. The emphasis have been to improve the channel estimation performance, bandwidth and power consumption, and the implementation time complexity of the estimation techniques. Of particular interest, FEC schemes such as Reed-Solomon (RS) codes, Turbo codes, Low Density Parity Check (LDPC) codes, Hamming codes, and Permutation codes, are proposed to improve the message transmission reliability of communication links. Turbo and LDPC codes have been used extensively to combat the varying nature of communication channels, most especially in joint iterative channel estimation and decoding receiver structures. In this thesis, attention is focused on using RS codes to improve the message reliability of a communication link because RS codes have good capability of correcting random and burst errors, and are useful in di erent wireless applications. This study concentrates on symbol level soft decision decoding of RS codes. In this regards, a novel symbol level iterative soft decision decoder for RS codes based on parity-check equations is developed. This Parity-check matrix Transformation Algorithm (PTA) is based on the soft reliability information derived from the channel output in order to perform syndrome checks in an iterative process. Performance analysis verify that this developed PTA outperforms the conventional RS hard decision decoding algorithms and the symbol level Koetter and Vardy (KV ) RS soft decision decoding algorithm. In addition, this thesis develops an improved Distance Metric (DM) method of deriving reliability information over Rayleigh fading channels for combined demodulation with symbol level RS soft decision decoding algorithms. The newly proposed DM method incorporates the channel state information in deriving the soft reliability information over Rayleigh fading channels. Analysis verify that this developed metric enhances the performance of symbol level RS soft decision decoders in comparison with the conventional method. Although, in this thesis, the performance of the developed DM method of deriving soft reliability information over Rayleigh fading channels is only veri ed for symbol level RS soft decision decoders, it is applicable to any symbol level soft decision decoding FEC scheme. Besides, the performance of the all FEC decoding schemes plummet as a result of the Rayleigh fading channels. This engender the development of joint iterative channel estimation and decoding receiver structures in order to improve the message reliability, most especially with Turbo and LDPC codes as the FEC schemes. As such, this thesis develops the rst joint iterative channel estimation and Reed- Solomon decoding receiver structure. Essentially, the joint iterative channel estimation and RS decoding receiver is developed based on the existing symbol level soft decision KV algorithm. Consequently, the joint iterative channel estimation and RS decoding receiver is extended to the developed RS parity-check matrix transformation algorithm. The PTA provides design ease and exibility, and lesser computational time complexity in an iterative receiver structure in comparison with the KV algorithm. Generally, the ndings of this thesis are relevant in improving the message transmission reliability of a communication link with RS codes. For instance, it is pertinent to numerous data transmission technologies such as Digital Audio Broadcasting (DAB), Digital Video Broadcasting (DVB), Digital Subscriber Line (DSL), WiMAX, and long distance satellite communications. Equally, the developed, less computationally intensive, and performance e cient symbol level decoding algorithm for RS codes can be use in consumer technologies like compact disc and digital versatile disc. / GS2016