Wireless sensor networks (WSN) have played a role in various fields. In-network data processing is one of the most important and challenging techniques as it affects the key features of WSNs, which are energy consumption, nodes life circles and network performance. In the form of in-network processing, an intermediate node or aggregator will fuse or aggregate sensor data, which are collected from a group of sensors before transferring to the base station. The advantage of this approach is to minimize the amount of information transferred due to lack of computational resources. This thesis introduces the development of a hybrid in-network data processing for WSNs to fulfil the WSNs constraints. An architecture for in-network data processing were proposed in clustering level, data compression level and data mining level. The Neighbour-aware Multipath Cluster Aggregation (NMCA) is designed in the clustering level, which combines cluster-based and multipath approaches to process different packet loss rates. The data compression schemes and Optimal Dynamic Huffman (ODH) algorithm compressed data in the cluster head for the compressed level. A semantic data mining for fire detection was designed for extracting information from the raw data by the semantic data-mining model is developed to improve data accuracy and extract the fire event in the simulation. A demo in-door location system with in-network data processing approach is built to test the performance of the energy reduction of our designed strategy. In conclusion, the added benefits that the technical work can provide for in-network data processing is discussed and specific contributions and future work are highlighted.

Network functionalities play a major role in the connectivity and routing in an Ad-hoc networks because end user devices must contribute in routing and therefore maintain connectivity. In dynamic environments with mobile nodes, routing becomes very challenging; this challenge becomes even more burdensome if a network is deployed in larger areas. Therefore, in order to avoid centralisation and bottlenecks, routing algorithms in Ad-hoc networks should not depend on any specific node. Furthermore, these algorithms should be able to support routing in sparse topologies when the density of the nodes is very low in a large deployment area. The rationale behind this research project stems from the lack of sufficiently effective solutions for wireless networks deployed in large areas where the node's mobility creates what is called the Loosely Coupled Nodes Problem. Therefore, this gap in knowledge needs to be addressed by developing a novel and scalable routing protocol, which can utilise application characteristics to stabilise routing between loosely coupled nodes in a large deployment area. This research proposes a new routing protocol to address this gap by increasing the number of packets delivered to their final destinations in an Ad-hoc networks. As another gap, very few current approaches deal with realistic situations, based on real-life case scenarios, in order to evaluate and enhance the accuracy of their Ad-hoc network protocols, and thus they cannot accurately approximate common real world environments [1]. Therefore, this project addresses research issues directly linked to evaluation of protocols and architectures in use cases and applications in real life scenarios. The novel routing algorithm, Ferry-Assisted Greedy Perimeter Stateless Routing (FA-GPSR), proposed in this thesis demonstrates the benefits of extracting information from the application to support communication between the nodes in the network topology. In addition, this approach highlights the advantages and disadvantages of the efficiency and reliability of communication in open large areas of deployment. A simulation model of the proposed algorithm has been implemented and its features investigated through simulation runs. The communication between nodes in the topology show that FA-GPSR outperforms the other routings in terms of packet delivery ratio, especially in sparse networks, where the density of nodes is low. The mobility of the destination nodes affected the packets delivery ratio by decreasing the ratio, compared to other cases because of the changes in the location and node velocity. By increasing the number of packets and source nodes, FA-GPSR outperformed the other algorithms because of the efficient use of the patrol node (ferry). Thus, the comparison of FA-GPSR to these algorithms supports the conclusion that FA-GPSR is suitable for use in large open areas with the effect of node density and packet load.

This thesis investigates the application of Reinforcement Learning (RL) on Medium Access Control (MAC) for Wireless Sensor Networks (WSNs). RL is applied as an intelligent slot selection strategy to Framed ALOHA, along with analytical and experimental performance evaluation. Informed Receiving (IR) and ping packets are applied to multi-hop WSNs to avoid idle listening and overhearing, thereby further improving the energy efficiency. The low computational complexity and signalling overheads of the ALOHA schemes meet the design requirement of energy constraint WSNs, but suffer collisions from the random access strategy. RL is applied to solve this problem and to achieve perfect scheduling. Results show that the RL scheme achieves over 0.9 Erlangs maximum throughput in single-hop networks. For multi-hop WSNs, IR and ping packets are applied to appropriately switch the relay nodes between active and sleep state, to reserve as much energy as possible while ensuring no information loss. The RL algorithms require certain time to converge to steady state to achieve the optimum performance. The convergence behaviour is investigated in this thesis. A Markov model is proposed to describe a learning process, and the model produces the proof of the convergence of the learning process and the estimated convergence time. The channel performance before convergence is also evaluated.

With the extensive deployment of 802.11 wireless local area networks (WLANs) and the need for better quality of service (QoS), the 802.11e MAC with service differentiation was developed. In practical WLAN deployments, the capture effect has been shown to enhence the throughput performance of the network. Analysing the effect of fading and near–far effect on the performance of 802.11 is a fundamental consideration in practical situations since the wireless channels are error-prone. Developing an accurate closed form solution of the throughput/delay is a crucial task for the network planning and design. This thesis develops a physical/medium-access-control (PHY/MAC) cross-layer model to characterise the throughput and delay performance of WLANs in error-prone wireless environments. The developed model incorporates the capture effect and channel errors from the PHY-layer perspective, while from the MAC perspective the approach considers the QoS differentiated p-persistent CSMA protocol. This research develops PHY/MAC models that accurately calculate the saturated and non-saturated throughput/delay of p-persistent CSMA protocol with multiple traffic types which can be used to model 802.11e. The developed model expresses the saturated and non-saturated throughput/delay as a function of the number of terminals, packet error rates and capture threshold. The work shows that the PHY layer effects have a significant impact on the throughput/delay performance of WLANs and their dimensioning. The anomaly effect also has a significant impact on performance of 802.11 WLANs which affects the calculation of the network capacity during the network planning phase. This research develops an adaptive QoS differentiated p-persistent CSMA protocol with multirate capability that can be used to resolve the performance anomaly of 802.11 DCF and 802.11e EDCA. The developed models can be applied to the QoS differentiated systems such as 802.11e EDCA with significantly less complexity than Markovian models. The adaptive protocol improves the network capacity which leads to more efficient network deployments in terms of capacity, spectral efficiency and energy consumption.

The exponential growth in the number of users of cellular mobile networks (and their requirements) has created a massive challenge for network operators to cope with demands for coverage and data rates. Among the possible solutions for the ever increasing user needs, the deployment of Heterogeneous Networks (HetNets) constitutes both a practical and an economical solution. Moreover, while the typical approach for network operators has been to consider the coverage and data rates as design parameters in a network, a major concern for next generation networks is the efficiency in the power usage of the network. Therefore, in recent years the energy efficiency parameter has gathered a great deal of attention in the design of next generation networks. In the context of HetNets, while the densification of the network in terms of the number of base stations deployed can potentially increase the coverage and boost the data rates, it can also lead to a huge power consumption as the energy used escalates with the number of base stations deployed. To this end, the purpose of this thesis is to investigate the energy efficiency performance of different deployment strategies in a HetNet consisting of macro- and femtocells. We make use of well established tools from stochastic geometry to model the different strategies, as it provides a theoretical framework from which the scalability of the network in terms of the design parameters can be taken into account. Those strategies consisted first, on the analysis of the effect of using multiple antennas and diversity schemes on both, the throughput and the energy efficiency of the network. The optimum diversity schemes and antenna configurations were found for an optimal energy efficiency while keeping constraints on the quality of Service of both tiers. Then, the effect of the vertical antenna tilt was analyzed for both, a traditional macrocell only network and a two-tier network. The optimum antenna tilt in terms of energy efficiency was found while keeping constraints on the Quality of Service required. Finally, an energy efficient deployment of femtocells was proposed where the smart positioning of femtocells derived into improvements of coverage probability, effective throughput and energy efficiency of the network. The proposed model also improved in general the performance of the cell edge user which in turn resulted in a more balanced network in terms of the overall performance.

Since its inception, the Internet witnessed two major approaches to communicate digital content to end users: peer to peer (P2P) and client/server (C/S) networks. Both approaches require high bandwidth and low latency physical underlying networks to meet the users’ escalating demands. Network operators typically have to overprovision their systems to guarantee acceptable quality of service (QoS) and availability while delivering content. However, more physical devices led to more ICT power consumption over the years. An effective approach to confront these challenges is to jointly optimise the energy consumption of content providers and transportation networks. This thesis proposes a number of energy efficient mechanisms to optimise BitTorrent based P2P networks and clouds based C/S content distribution over IP/WDM based core optical networks. For P2P systems, a mixed integer linear programming (MILP) optimisation, two heuristics and an experimental testbed are developed to minimise the power consumption of IP/WDM networks that deliver traffic generated by an overlay layer of homogeneous BitTorrent users. The approach optimises peers’ selection where the goal is to minimise IP/WDM network power consumption while maximising peers download rate. The results are compared to typical C/S systems. We also considered Heterogeneous BitTorrent peers and developed models that optimise P2P systems to compensate for different peers behaviour after finishing downloading. We investigated the impact of core network physical topology on the energy efficiency of BitTorrent systems. We also investigated the power consumption of Video on Demand (VoD) services using CDN, P2P and hybrid CDN-P2P architectures over IP/WDM networks and addressed content providers efforts to balance the load among their data centres. For cloud systems, a MILP and a heuristic were developed to minimise content delivery induced power consumption of both clouds and IP/WDM networks. This was done by optimally determining the number, location and internal capability in terms of servers, LAN and storage of each cloud, subject to daily traffic variation. Different replication schemes were studied revealing that replicating content into multiple clouds based on content popularity is the optimum approach with respect to energy. The model was extended to study Storage as a Service (StaaS). We also studied the problem of virtual machine placement in IP/WDM networks and showed that VM Slicing is the best approach compared to migration and replication schemes to minimise energy. Finally, we have investigated the utilisation of renewable energy sources represented by solar cells and wind farms in BitTorrent networks and content delivery clouds, respectively. Comprehensive modelling and simulation as well as experimental demonstration were developed, leading to key contributions in the field of energy efficient telecommunications.

This dissertation studies a type theory to guarantee communication-safety in sessions of an arbitrary number of participants, typically represented as communication patterns, of mobile processes in the context of multiparty session types— a well-established type theory that describes the interactive structure of a fixed number of processes from a global point of view and type-checks the processes through projection of the global type onto the participants of the session. Communication-safety is the property that mobile processes exchange values of the same set without deadlocking and data races. Our study introduces a programming idiom of roles— a concept that describes the nature of a communication pattern in a similar way to classes in Java and C#, offering a design on how to incorporate parameterised session types into a mainstream language. The formal model (1) preserves multiparty session types’ syntax and type-checking strategy, and (2) allows the number of participants to range over infinite sets of natural numbers, providing full computation power of programs. A series of communication patterns and real-world examples from parallel algorithms and data exchange protocols demonstrate the expressiveness and practicality of the formal model, comparing the model with the only mature implementation of (binary) session types. We proved that type preservation under reduction and communication-safety hold in the type system. The study of parameterised session types is supported by the examination of multiparty session types for synchronous communications. We extended the initial work on multiparty session types with a simpler calculus, multicast send of values and labels, a practical form of higher-order communication and a more intuitive, elegant linearity property; we proved that (a) type preservation and communication-safety hold in the type system, and (b) interactions of a typeable process follow exactly the description of the global type.

Networks form an indispensable part of our lives. In particular, computer networks have ranked amongst the most influential networks in recent times. In such an ever-evolving and fast growing network, the primary concern is to understand and analyse different aspects of the network behaviour, such as the quality of service and efficient information propagation. It is also desirable to predict the behaviour of a large computer network if, for example, one of the computers is infected by a virus. In all of the aforementioned cases, we need protocols that are able to make local decisions and handle the dynamic changes in the network topology. Here, randomised algorithms are preferred because many deterministic algorithms often require a central control. In this thesis, we investigate three network-based randomised algorithms, threshold load balancing with weighted tasks, the pull-Moran process and the coalescing-branching random walk. Each of these algorithms has extensive applicability within networks and computational complexity within computer science. In this thesis we investigate threshold-based load balancing protocols. We introduce a generalisation of protocols in [2, 3] to weighted tasks. This thesis also analyses an evolutionary-based process called the death-birth update, defined here as the Pull-Moran process. We show that a class of strong universal amplifiers does not exist for the Pull-Moran process. We show that any class of selective amplifiers in the (standard) Moran process is a class of selective suppressors under the Pull-Moran process. We then introduce a class of selective amplifiers called Punk graphs. Finally, we improve the broadcasting time of the coalescing-branching (COBRA) walk analysed in [4], for random regular graphs. Here, we look into the COBRA approach as a randomised rumour spreading protocol.

Wireless Sensor Networks (WSNs) have been an exciting topic in recent years. The services offered by a WSN can be classified into three major categories: monitoring, alerting, and information on demand. WSNs have been used for a variety of applications related to the environment (agriculture, water and forest fire detection), the military, buildings, health (elderly people and home monitoring), disaster relief, and area or industrial monitoring. In most WSNs tasks like processing the sensed data, making decisions and generating emergency messages are carried out by a remote server, hence the need for efficient means of transferring data across the network. Because of the range of applications and types of WSN there is a need for different kinds of MAC and routing protocols in order to guarantee delivery of data from the source nodes to the server (or sink). In order to minimize energy consumption and increase performance in areas such as reliability of data delivery, extensive research has been conducted and documented in the literature on designing energy efficient protocols for each individual layer. The most common way to conserve energy in WSNs involves using the MAC layer to put the transceiver and the processor of the sensor node into a low power, sleep state when they are not being used. Hence the energy wasted due to collisions, overhearing and idle listening is reduced. As a result of this strategy for saving energy, the routing protocols need new solutions that take into account the sleep state of some nodes, and which also enable the lifetime of the entire network to be increased by distributing energy usage between nodes over time. This could mean that a combined MAC and routing protocol could significantly improve WSNs because the interaction between the MAC and network layers lets nodes be active at the same time in order to deal with data transmission. In the research presented in this thesis, a cross-layer protocol based on MAC and routing protocols was designed in order to improve the capability of WSNs for a range of different applications. Simulation results, based on a range of realistic scenarios, show that these new protocols improve WSNs by reducing their energy consumption as well as enabling them to support mobile nodes, where necessary. A number of conference and journal papers have been published to disseminate these results for a range of applications.

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