This thesis investigates an approach that simplifies the development of Semantic Web services (SWS) by removing the need for additional semantic descriptions. The most actively researched approaches to Semantic Web services introduce explicit semantic descriptions of services that are in addition to the existing semantic descriptions of the service domains. This increases their complexity and design overhead. The need for semantically describing the services in such approaches stems from their foundations in service-oriented computing, i.e. the extension of already existing service descriptions. This thesis demonstrates that adopting a resource-oriented approach based on REST will, in contrast to service-oriented approaches, eliminate the need for explicit semantic service descriptions and service vocabularies. This reduces the development efforts while retaining the significant functional capabilities. The approach proposed in this thesis, called EXPRESS (Expressing RESTful Semantic Services), utilises the similarities between REST and the Semantic Web, such as resource realisation, self-describing representations, and uniform interfaces. The semantics of a service is elicited from a resource’s semantic description in the domain ontology and the semantics of the uniform interface, hence eliminating the need for additional semantic descriptions. Moreover, stub-generation is a by-product of the mapping between entities in the domain ontology and resources. EXPRESS was developed to test the feasibility of eliminating explicit service descriptions and service vocabularies or ontologies, to explore the restrictions placed on domain ontologies as a result, to investigate the impact on the semantic quality of the description, and explore the benefits and costs to developers. To achieve this, an online demonstrator that allows users to generate stubs has been developed. In addition, a matchmaking experiment was conducted to show that the descriptions of the services are comparable to OWL-S in terms of their ability to be discovered, while improving the efficiency of discovery. Finally, an expert review was undertaken which provided evidence of EXPRESS’s simplicity and practicality when developing SWS from scratch.

The question of how neural systems encode memories in one-shot without immediately disrupting previously stored information has puzzled theoretical neuroscientists for years and it is the central topic of this thesis. Previous attempts on this topic, have proposed that synapses probabilistically update in response to plasticity inducing stimuli to effectively delay the degradation of old memories in the face of ongoing memory storage. Indeed, experiments have shown that synapses do not immediately respond to plasticity inducing stimuli, since these must be presented many times before synaptic plasticity is expressed. Such a delay could be due to the stochastic nature of synaptic plasticity or perhaps because induction signals are integrated before overt strength changes occur. The later approach has been previously applied to control fluctuations in neural development by low-pass filtering induction signals before plasticity is expressed. In this thesis we consider memory dynamics in a mathematical model with synapses that integrate plasticity induction signals to a threshold before expressing plasticity. We report novel recall dynamics and considerable improvements in memory lifetimes against a prominent model of synaptically stored memory. With integrating synapses the memory trace initially rises before reaching a maximum and then falls. The memory signal dissociates into separate oblivescence and reminiscence components, with reminiscence initially dominating recall. Furthermore, we find that integrating synapses possess natural timescales that can be used to consider the transition to late-phase plasticity under spaced repetition patterns known to lead to optimal storage conditions. We find that threshold crossing statistics differentiate between massed and spaced memory repetition patterns. However, isolated integrative synapses obtain an insufficient statistical sample to detect the stimulation pattern within a few memory repetitions. We extend the modelto consider the cooperation of well-known intracellular signalling pathways in detecting storage conditions by utilizing the profile of postsynaptic depolarization. We find that neuron wide signalling and local synaptic signals can be combined to detect optimal storage conditions that lead to stable forms of plasticity in a synapse specific manner. These models can be further extended to consider heterosynaptic and neuromodulatory interactions for late-phase plasticity.

In this thesis, we propose a suite of schemes for wireless multiuser relay networks, where multiple source nodes (SNs) and relay nodes (RNs) share the spectral resources and hence we take into the account the co-channel interference (CCI). Our objective is to deal with both the channel fading and CCI in order to improve the attainable outage performance. Firstly, we consider the opportunistic relay selection (ORS) design in the scenario, where multiple RNs are available for assisting the transmission of a single SN, while CCI is imposed by other SNs in the network. We design the single-user-detection-aided (SUD-aided) and multi-user-detection based successive interference-cancellation-aided (MUD-SIC-aided) systems, where multiple-user detection (MUD) receivers using successive interference cancellation (SIC) at the destination node (DN) are adopted to combat co-channel interference. In SUD-aided system, we employ single-user detection (SUD) at the RNs and MUD SIC at the DN. In MUD-SIC-aided system, we employ MUD-SIC at both the RNs and DN. We present the outage analysis of both systems based on an outage-optimised ORS scheme, implying that the proposed ORS scheme provides the best outage performance. We show that the traditional ORS scheme proposed for SUD receivers based on the highest SNR criterion is not outage-optimal, when employing MUD-SIC in the presence of CCI. Hence, we propose a novel ORS scheme based on a best-effort detection (BED) criterion that outperforms the traditional ORS scheme. Furthermore, considering the effects of the outdated channel state information (CSI), an improved BED-ORS is proposed for enhancing the robustness towards CSI imperfections. Then, we study the scenario, where multiple SNs are coordinated to share a RN. In this case, network coding (NC) may be invoked at the RN, which treats the CCI from other SNs as useful messages and superimposes them to reduce the time slots required for relaying, therefore achieving higher spectral efficiency. However, NC systems may not always be beneficial in cooperative communications, where the detrimental interference of the undesired SNs, often referred to as network coding noise (NC noise), may outweigh the benefits of NC. In previous works, the outage performance was only evaluated numerically for several case studies. Against this background, we propose a systematically analytical framework for evaluating the outage performance for a multi-unicast NC-aided network, where each DN extracts the information of the desired SN from the NC signal forwarded by the RN. As our main contribution, we present the outage analysis of this system in the presence of NC noise and the closed-form analytical outage probability expressions are derived for an arbitrary number of SN-DN pairs. We show that if NC is employed, the quality of the worst SN-DN link may dominate the outage performance of every SNs. We then consider a two-hop network, where multiple SNs transmit to a DN with the aid of a RN and we assume the direct link between the SNs and the DN is weak. In this scenario, we show that the NC-aided relaying is not preferred and hence the buffer-aided relaying (BAR) is advocated for improving the uplink. The RN is equipped with a buffer, which is capable of storing multiple frames received from the SNs. During each time slot, the proposed protocol activates either the SNRN hop or the RN-DN hop, depending on the channel quality of each hop and the buffer state at the RN. In order to optimise the hop selection for the network, we design a hop quality metric (HQM) and propose a multi-user buffer-aided-relaying uplink (MU-BR-UL) protocol. The benefits of the proposed protocol is analysed in terms of the end-to-end outage probability and the end-to-end transmission delay. Then, the optimal power allocation is proposed for minimizing the end-to-end outage probability under the total power constraint. Furthermore, the impact of the buffer size, the number of users and the relay position on the achievable outage performance are characterized. The results indicate that the outage performance is significantly improved when theproposed power allocation is utilized in the MU-BR-UL protocol. Finally, we consider a new family of networks, in which the SNs and RNs have energy harvesting (EH) capability, which allows the nodes to harvest energy from the environments and convert it to electrical energy for wireless transmissions. The EH removes the constraints of relying on a battery for constant power supply, but also demands novel energy usage policy (EUP) design for effectively utilizing the random power supply gleaned from the EH system. We start with the point-to-point (P2P) network and by effectively exploiting the statistics of the energy arrival rates, we propose novel search algorithms for designing the EUP, which achieve a significantly better outage performance than the state-of-the-art designs reported in the literature. Based on the proposed methods in P2P network, we design novel EUPs for spacedivision- multiple-access (SDMA) and SDMA-based relay sharing networks. We show that the proposed EUPs significantly outperforms the state-of-the-art benchmarks in terms of outage performance.

Individuals are typically members of a variety of web-based social networks (both explicit and implied), but existing trust inference mechanisms typically draw on only a single network to calculate trust between any two individuals. This reduces both the likelihood that a trust value can be calculated (as both people have to be members of the same network), and the quality of any trust inference that can be drawn (as it will be based on only a single network, typically representing a single type of relationship). To make trust calculations on Multiple Distributed (MuDi) social networks, those networks must first be consolidated into a single network. Two challenges that arise when consolidating MuDi networks are their heterogeneity, due to different name representation techniques used for participants, and the variability of trust information, due to the different trust evaluation criteria, across the different candidate networks. Semantic technologies are vital to deal with the heterogeneity issues as they permit data to be linked from multiple resources and help them to be modelled in a uniform representation using ontologies. The inconsistency of multiple trust values from different networks is handled using data fusion techniques, as simpler aggregation techniques of summation and weighted averages tend to distort trust data. To test the proposed semantic framework, two set of experiments were run. Simulation experiments generated pairs of networks with varying percentages of Participant Overlap (PO) and Tie Overlap (TO), with trust values added to the links between participants in the networks. It analysed different data fusion techniques aiming to identify which best preserved the integrity of trust from each individual network with varying values of PO and TO. A real world experiment used the findings of the simulation experiment on the best trust aggregation techniques and applied the framework to real trust data between participants that was extracted from a pair of professional social networks. The trust values generated from consolidated MuDi networks were then compared with the real life trust between users, collected using a survey, with the aim of analysing whether aggregated trust is closer to real life trust than using each of the individual networks. Analysis of the simulation experiment showed that the Weighted Ordered Weighted Averaging (WOWA) data fusion technique better aggregated trust data and, unlike the other techniques, preserved the integrity of trust from each individual network for varying PO and TO (p � 0.05). The real world experiment partially proved the hypothesis of generating better trust values from consolidated MuDi networks and showed improved results for participants who are part of both networks (p � 0.05), while disproving the claim for those in the cross-region (with one user present in both networks and the other in a single network) and single-network users (p > 0.05).

Crosslinked polyethylene (XLPE) is widely used for high voltage insulation in power transmission systems. However, it has been found that, after crosslinking with Dicumyl Peroxide (DCP), the crosslinking byproducts such as acetophenone, α-methylstyrene and cumyl alcohol have a significant influence on electrical properties of XLPE power cables. This thesis distinguished the individual contribution of the crosslinking byproducts on space charge formation, dielectric properties, dc conductivity as well as the ac breakdown strength. Percentage weight increases as well as the Fourier Transform Infrared (FTIR) spectrum were used to monitor the chemical level in the soaked samples. Despite high concentration of byproducts in the LDPE film compared to practical, the measurement results have successfully reveal the contribution of each byproduct on the electrical properties. It should be noted that some consideration should be taken when taking the quantitative value from the result obtained. Space charge accumulation was measured using the pulsed electroacoustic (PEA) technique. Homocharges are observed in acetophenone and α-methylstyrene soaked LDPE. Meanwhile heterocharge formed in cumyl alcohol soaked LDPE. From the charge decay profile in dc condition, these chemicals are observed to assist the transportation of the charges in the sample bulk due to shallow traps from the byproducts. These shallow traps assist the trapping process into deep traps when ac field is applied to the byproduct soaked LDPE. As a result, more charges trapped in deep traps were found in soaked LDPE compared to clean LDPE. In addition, from the space charge measurement in ac condition, it is proved that the amount of charge trapped in deep traps also depends on the population of shallow traps in the polymer which is contradicted to the literature where the byproducts are normally associated to the deep traps. Permittivity values of acetophenone, α-methylstyrene soaked LDPE and cumyl alcohol are slightly higher than permittivity value of the clean untreated LDPE. Cumyl alcohol soaked LDPE has higher dielectric loss at lower frequency due to Maxwell-Wagner-Sillars polarisation as well as space charge polarisation effect. In contrast, acetophenone does not change the dielectric loss value and α-methylstyrene gives very little effect. These byproducts have very high dc conductivity values. It is also proposed that the chemicals provide shallow traps that aid the charge movement and this is consistent with the mobility values that calculated from the conduction current result. The ac breakdown results however show no significant difference from the breakdown strength of clean LDPE. Based on ac space charge results and ac breakdown test results, it is concluded that the byproducts have little effects in ac condition

In this thesis, we propose a series of cross-layer aided routing algorithms for ad hocnetworks by jointly exploiting the characteristics of the physical layer, of the data link layer and of the network layer, for the sake of improving the network's throughput, while reducing the normalized energy consumption. Since the node mobility in dynamic self organizing ad hoc networks may render the routing information gathered during the route discovery process invalid and hence may disrupt the current data transmission, a fuzzy logic aided technique is incorporated into the routing algorithm for mitigating the influence of imprecise routing information. Both the expected route life time and the number of hops are used as the input parameters of the Fuzzy Logic System (FLS), which outputs the `stability' of a route. Hence, the specific route having the highest route `stability' is finally selected for data transmission. The proposed fuzzy logic based routing outperforms the conventional Dynamic Source Routing (DSR) in terms of the attainable network throughput. Moreover, since near-capacity channel coding aided Multiple Input Multiple- Output (MIMO) schemes allow a single link to communicate using the lowest possible transmit power at a given Frame Error Rate (FER), multi antenna aided routing was proposed for reducing the system's total energy consumption, which relied on a three-stage concatenated transceiver constituted by an Irregular Convolutional Code, Unity-Rate Code and Space-Time Trellis Code (IrCC-URC-STTC) equipped with two antennas. It is demonstrated that in a high-node-density scenario the average energy consumption per information bit and per node becomes about a factor two lower than that in the equivalent Single-Antenna Relay Node (SA-RNs) aided networks. Finally, we further exploit the benefits of cross-layer information exchange, including the knowledge of the FER in the physical layer, the maximum number of retransmissions in the data link layer and the number of RNs in the network layer. Energy-consumption-based Objective Functions (OF) are invoked for calculating the end-to-end energy consumption of each potentially available route for both Traditional Routing (TR) and for Opportunistic Routing (OR), respectively. We also improve the TR and the OR with the aid of efficient Power Allocation (PA) for further reducing the energy consumption. Moreover, two energy-efficient routing algorithms are designed based on Dijkstra's algorithm. The algorithms based on the energy-consumption OF provide the theoretical bounds, which are shown to be close to the bound found by exhaustive search, despite the significantly reduced complexity of the former. Finally,the end-to-end throughput and the end-to-end delay of this system are analyzed theoretically. The simulation results show that our energy-efficient OR outperforms the TR and that their theoretical analysis accurately matches the simulation results.

Thanks to the rapid development of the wireless Internet, numerous mobile applications provide platforms for Mobile Users (MUs) to share any Information of Common Interest (IoCI) with their friends. For example, mobile applications of Facebook and Twitter enableMUs to share information via posts and status updates. Similarly, the mobile application of Wase (http://www.waze.com/) enables the drivers to share the real-time traffic information collected by themselves. However, at the time of writing, the dissemination process of the IoCI is predominantly supported by the Centralised Infrastructure (CI) based communication. In order to receive the IoCI, the mobile devices of MUs have to be connected either to a Base Station (BS) or to a Wi-Fi hotspot. However, the CI-based information dissemination faces the following three limitations: i) intermittent connectivity in rural areas; ii) overloaded CI-based network; iii) inefficient data service in densely populated areas. Due to the rapid development of the powerful mobile computing technique, mobile devices are typically equipped with large storage capacity, say dozens or possibly hundreds of Giga Bytes. Furthermore, they support multiple communication standards, such as Infrared, Bluetooth and Wi-Fi modules, in support of direct peer-to-peer communications. As a result, this treatise contributed towards mitigating the above-mentioned design problems in the conventional CI-based information dissemination by seeking assistance both from the opportunistic contacts and opportunistic multicast amongst MUs, who share common interest in the same information. This results in an integrated cellular and opportunistic network. Since mobile devices are carried by MUs, exploring the social behaviours exhibited by individuals and the social relationships amongst MUs may assist us in enhancing the communication experience. We firstly study an integrated cellular and large-scale opportunistic network, where theMUs are sparsely distributed within a large area. Due to the large size of the area and the sparse distribution of the MUs, the connectivity between a BS and a MU as well as that between a pair of MUs exhibit an intermittent nature. As a result, the information delivery has to be realised by the opportunistic contact between a transmitter and receiver pair, when the receiver enter the range of the transmitter. However, successful information delivery requires that the duration of this opportunistic contact has to be longer than the downloading period of the information. This integrated network is relied upon for disseminating delay-tolerant IoCI amongst the MUs. We model the information dissemination in this integrated network by a Continuous-Time-Pure-Birth-Markov-Chain (CT-PBMC) and further derive its relevant delay metrics and information delivery ratio. With the assistance of large-scale opportunistic networks, the information delivery ratio before the IoCI expires may be doubled, when compared to the conventional CI-based information dissemination. Furthermore, upon modelling the contact history of the MUs as a social network, social centrality based schemes are proposed for the sake of off-loading tele-traffic from the potentially congested CI to the large-scale opportunistic network. As demonstrated by our simulation results, in the scenario considered, as many as 58% MUs can be served by the large-scale opportunistic network before the oCI expires. In the above-mentioned large-scale networks, the MUs tend to be dispersed. By contrast, in the densely populated scenario, where numerous MUs can be found within a small area, classic BS-aided multicast is often invoked as a traditional measure of disseminating the IoCI by relying on the broadcast nature of the wireless channels. However, BS-aided multicasting becomes inefficient, when the number of MUs is high. If we efficiently exploit the redundant copies of the IoCI held by the already served MUs and activate these IoCI holders as potential relays for the next stage of cooperative multicast, the resultant diversity gain beneficially accelerates the information dissemination process. This approach may be regarded as opportunistic cooperative multicast, since no deterministic relay selection scheme is required. Its promising advantages experienced during disseminating the delay-sensitive IoCI across the densely populated area considered motivate us to study an integrated cellular and small-scale opportunistic network. By jointly considering both the effects of the channel model in the physical layer, as well as the resource scheduling in the Medium Access-Control (MAC) layer and the information dissemination protocol in the network layer, we model the information dissemination process by a Discrete-Time-Pure-Birth-Markov-Chain (DT PBMC). Apart from the above-mentioned factors related to wireless transmission, we also consider various MUs’ social characteristics, such as their altruistic behaviours and their geographic social relationships. Relying upon the above-mentioned DT-PBMC, we are capable of studying the delay versus energy dissipation trade-off during the information dissemination process. As demonstrated by our simulation results, the integrated cellular and small-scale opportunistic network considered is capable of substantially reducing the total information dissemination delay and the total energy dissipation of the classic BS-aided multicast. However, these benefits are achieved at the cost of the additional energy dissipated by the individual MUs. In order to further reduce both the information dissemination delay and the energy dissipation, Social Network Analysis (SNA) tools are relied upon for proposing a range of efficient resource scheduling approaches in the MAC layer. As demonstrated by our simulation results, the so-called shortest-shortest-distance scheduling regime outperforms its counterparts in terms of both its delay and energy metrics. Since the distance-related path-loss predetermines the successful information delivery in the scenario of the integrated cellular and small-scale opportunistic network, it is crucial for us to study the statistical properties of the random distance between a transmitter and receiver pair. As a result, we derive the closedform distributions of both the random distance between a pair of MUs and that between a BS and MU pair for different scenarios. Apart from assisting us in analysing the information dissemination process, these results may be further relied upon for evaluating the path loss, the throughput, the spectral efficiency and the outage probability in mobile networks. Although mobile communication techniques evolved from the well known analog ‘1G’ mobile networks to the emerging heterogeneous ‘5G’ mobile networks, the operational systems still rely on the CI-dominated ‘Comm 1.0’ era. Explicitly, direct interaction amongst the MUs without any aid of the CI is rare. Since powerfulmobile devices and pervasive social networking services are popular amongst theMUs, more direct interaction amongst theMUs would be advocated for the sake of achieving a more reliable, more prompt, and more energy-efficient communication experience. This treatise may contribute in a modest way towards the new ‘Comm 2.0’ era and may inspire further efforts from both the industrial and academic communities so as to embrace both the opportunities and the challenges of this new era from both the technical and economic perspectives.

Cryptographic algorithms have always relied on stored keys for the provision of security services. Since these keys are stored on a system this makes them prone to attack. Efforts to increase the key size makes brute forcing difficult but does not eliminate key theft. This thesis proposes a comprehensive security framework for groups of devices. The research makes four major contributions to improve the security of devices in the multiparty environment. The proposed framework uses the novel Integrated Circuit Metric (ICMetric) technology which proposes utilizing measurable properties and features of a device to create a device identification. This device identification called the ICMetric is used to create cryptographic keys which are then used in the designed cryptosystems. The first contribution of the thesis is the creation of an ICMetric using sensors found in modern smart devices. The research explores both explicit and implicit features which can be used to generate of an ICMetric. The second contribution of this research is the creation of a group ICMetric which is computed using the device ICMetric. The computation of the device ICMetric is a particular challenge as it has to be computed without violating the properties of the ICMetric technology. The third contribution is the demonstration that an ICMetric can be used for the creation of symmetric key. The fourth contribution of this research is an efficient RSA based asymmetric key generation scheme for the multiparty environment. Designing a system using widely accepted cryptographic primitives does not guarantee a secure system therefore the security of proposed schemes has been studied under the standard model. The schemes presented in this thesis attempt to improve the security of devices in the group environment. The schemes demonstrate that key theft deterrent technologies can be incorporated into cryptographic schemes to offer higher levels of security and privacy.

Intrusion detection systems (IDS) designed for conventional computer systems and networks are not necessarily suitable for mobile cyber-physical systems (CPS), such as robots, drones and automobiles. They tend to be geared towards attacks of different nature and do not take into account mobility, energy consumption and other physical aspects that are vital to a mobile cyber-physical system. This work provides two different approaches for addressing the problem of detecting attacks against vehicles, using a small-scale robotic vehicle as a testbed. The first approach is based on decision trees and the second on deep learning. Both use a combination of cyber and physical features that can be measured by its onboard systems and processes. Experimental evaluation on a variety of scenarios involving denial of service, command injection and two different types of malware infections demonstrated the feasibility of the approaches. Decision tree algorithm is one of the most lightweight machine learning techniques, yet sufficiently powerful in many areas of applications, because it can naturally account for non-linearities in the data. Decision trees produce sets of simple rules, which can be easily checked onboard even the most resource-constrained of robotic vehicles. In the case of our vehicle, this approach was able to achieve high accuracy rate for denial of service attacks, but less so for the other attacks tested. Due to their processing resource constraints, cyber-physical systems, such as robotic vehicles, tend to be limited to lightweight mechanisms, such as decision trees and other statistical machine learning techniques. We show that considerably higher accuracy rates can be achieved if one utilises techniques from the field of deep learning. In particular, we use a recurrent neural network architecture, benefiting from a long short-term memory layer, which is highly appropriate for real-time data. To address the processing limitations, we turn to computational offloading, which is a technique particularly common for mobile devices, for largely the same reasons: to save energy and to have access to greater processing resources. We show both experimentally and mathematically in which cases offloading the periodic task of deep learning based intrusion detection to a remote server can be practical, especially in relation to the time the whole process takes.

Recently, the advances in Ubiquitous Computing networks and the increased computational power of network devices have led designers to create more flexible distributed network models using decentralised network management systems. Security, resilience and privacy issues within such distributed systems become more complicated while important tasks such as routing, service access and state management become increasingly challenging. Low-level protocols over ubiquitous decentralised systems, which provide autonomy to network nodes, have replaced the traditional client-server arrangements in centralised systems. Small World networks represent a model that addresses many existing challenges within Ubiquitous Computing networks. Therefore, it is imperative to study the properties of Small World networks to help understanding, modelling and improving the performance, usability and resiliency of Ubiquitous Computing networks. Using the network infrastructure and trusted relationships in the Small World networks, this work proposes a framework to enhance security, resilience and trust within scalable Peer-to-Peer (P2P) networks. The proposed framework consists of three major components namely network-aware topology construction, anonymous global communication using community trust, and efficient search and broadcasting based on granularity and pro-active membership management. We utilise the clustering co-efficient and conditional preferential attachment to propose a novel topology construction scheme that organises nodes into groups of trusted users to improve scalability. Network nodes communicate locally without advertising node identity at a global scale, which ensures user anonymity. The global communication is organised and facilitated by Service Centres to maintain security, privacy and integrity of member nodes. Service Centres are allocated using a novel leader election mechanism within unstructured scalable P2P networks. This allows providing fair and equitable access for existing and new nodes without having to make complex changes to the network topology. Moreover, the scale-free and clustering co-efficient characteristics of Small World networks help organising the network layout to maintain its balance in terms of the nodes distribution. Simulation results show that the proposed framework ensures better scalability and membership management in unstructured P2P networks, and improves the performance of the search and broadcasting in terms of the average shortest path and control overhead while maintaining user anonymity and system resiliency.