Evolutionary Game Theory Perspective on Dynamic Spectrum Access Etiquette

In this paper, we describe the long-term evolution of societies of secondary users in dynamic spectrum access networks. Such an understanding is important to help us anticipate future trends in the organization of large-scale distributed networked deployments. Such deployments are expected to arise in support of a wide variety of applications, including vehicular networks and the Internet of Things. Two new biologically-inspired spectrum access strategies are presented here, and compared with a random access baseline strategy. The proposed strategies embody a range of plausible assumptions concerning the sensing capabilities and social characteristics of individual secondary users. Considering these strategies as the basis of a game against the field, we use replicator dynamics within an evolutionary game-theoretic analysis to derive insights into the physical conditions necessary for each of the strategies to be evolutionarily stable. Somewhat surprisingly, we find that the physical channel conditions almost always uniquely determine which one of the three (pure) strategies is selected, and that no mixed strategy ever survives. We show that social tendencies naturally become advantageous for secondary users as they find themselves situated in network environments with heterogeneous channel resources. Hardware test-bed experiments confirm the validity of the analytic conclusions. Taken together, these results predict the emergence of social behavior in the spectrum access etiquette of secondary users as cognitive radio technology continues to advance and improve. The experimental results show an increase in the throughput of up to 90%, when strategy evolution is continuously operational, compared with any static strategy. We present use cases to envision the potential application of the proposed evolutionary framework in real-world scenarios

Personal mobile grids with a honeybee inspired resource scheduler

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The overall aim of the thesis has been to introduce Personal Mobile Grids (PMGrids) as a novel paradigm in grid computing that scales grid infrastructures to mobile devices and extends grid entities to individual personal users. In this thesis, architectural designs as well as simulation models for PM-Grids are developed. The core of any grid system is its resource scheduler. However, virtually all current conventional grid schedulers do not address the non-clairvoyant scheduling problem, where job information is not available before the end of execution. Therefore, this thesis proposes a honeybee inspired resource scheduling heuristic for PM-Grids (HoPe) incorporating a radical approach to grid resource scheduling to tackle this problem. A detailed design and implementation of HoPe with a decentralised self-management and adaptive policy are initiated. Among the other main contributions are a comprehensive taxonomy of grid systems as well as a detailed analysis of the honeybee colony and its nectar acquisition process (NAP), from the resource scheduling perspective, which have not been presented in any previous work, to the best of our knowledge. PM-Grid designs and HoPe implementation were evaluated thoroughly through a strictly controlled empirical evaluation framework with a well-established heuristic in high throughput computing, the opportunistic scheduling heuristic (OSH), as a benchmark algorithm. Comparisons with optimal values and worst bounds are conducted to gain a clear insight into HoPe behaviour, in terms of stability, throughput, turnaround time and speedup, under different running conditions of number of jobs and grid scales. Experimental results demonstrate the superiority of HoPe performance where it has successfully maintained optimum stability and throughput in more than 95% of the experiments, with HoPe achieving three times better than the OSH under extremely heavy loads. Regarding the turnaround time and speedup, HoPe has effectively achieved less than 50% of the turnaround time incurred by the OSH, while doubling its speedup in more than 60% of the experiments. These results indicate the potential of both PM-Grids and HoPe in realising futuristic grid visions. Therefore considering the deployment of PM-Grids in real life scenarios and the utilisation of HoPe in other parallel processing and high throughput computing systems are recommended

Structure and topology of transcriptional regulatory networks and their applications in bio-inspired networking

Biological networks carry out vital functions necessary for sustenance despite environmental adversities. Transcriptional Regulatory Network (TRN) is one such biological network that is formed due to the interaction between proteins, called Transcription Factors (TFs), and segments of DNA, called genes. TRNs are known to exhibit functional robustness in the face of perturbation or mutation: a property that is proven to be a result of its underlying network topology. In this thesis, we first propose a three-tier topological characterization of TRN to analyze the interplay between the significant graph-theoretic properties of TRNs such as scale-free out-degree distribution, low graph density, small world property and the abundance of subgraphs called motifs. Specifically, we pinpoint the role of a certain three-node motif, called Feed Forward Loop (FFL) motif in topological robustness as well as information spread in TRNs. With the understanding of the TRN topology, we explore its potential use in design of fault-tolerant communication topologies. To this end, we first propose an edge rewiring mechanism that remedies the vulnerability of TRNs to the failure of well-connected nodes, called hubs, while preserving its other significant graph-theoretic properties. We apply the rewired TRN topologies in the design of wireless sensor networks that are less vulnerable to targeted node failure. Similarly, we apply the TRN topology to address the issues of robustness and energy-efficiency in the following networking paradigms: robust yet energy-efficient delay tolerant network for post disaster scenarios, energy-efficient data-collection framework for smart city applications and a data transfer framework deployed over a fog computing platform for collaborative sensing --Abstract, page iii

Swarm-inspired solution strategy for the search problem of unmanned aerial vehicles

Learning from the emergent behaviour of social insects, this research studies the influences of environment to collective problem-solving of insect behaviour and distributed intelligent systems. Literature research has been conducted to understand the emergent paradigms of social insects, and to investigate current research and development of distributed intelligent systems. On the basis of the literature investigation, the environment is considered to have significant impact on the effectiveness and efficiency of collective problem-solving. A framework of collective problem-solving is developed in an interdisciplinary context to describe the influences of the environment to insect behaviour and problem-solving of distributed intelligent systems. The environment roles and responsibilities are transformed into and deployed as a problem-solving mechanism for distributed intelligent systems. A swarm-inspired search strategy is proposed as a behaviour-based cooperative search solution. It is applied to the cooperative search problem of Unmanned Aerial Vehicles (UAVs) with a series of experiments implemented for evaluation. The search environment represents the specification and requirements of the search problem; defines tasks to be achieved and maintained; and it is where targets are locally observable and accessible to UAVs. Therefore, the information provided through the search environment is used to define rules of behaviour for UAVs. The initial detection of target signal refers to modified configurations of the search environment, which mediates local communications among UAVs and is used as a means of coordination. The experimental results indicate that, the swarm-inspired search strategy is a valuable alternative solution to current approaches of cooperative search problem of UAVs. In the proposed search solution, the diagonal formation of two UAVs is able to produce superior performance than the triangular formation of three UAVs for the average detection time and the number of targets located within the maximum time length

Personal mobile grids with a honeybee inspired resource scheduler

The overall aim of the thesis has been to introduce Personal Mobile Grids (PMGrids) as a novel paradigm in grid computing that scales grid infrastructures to mobile devices and extends grid entities to individual personal users. In this thesis, architectural designs as well as simulation models for PM-Grids are developed. The core of any grid system is its resource scheduler. However, virtually all current conventional grid schedulers do not address the non-clairvoyant scheduling problem, where job information is not available before the end of execution. Therefore, this thesis proposes a honeybee inspired resource scheduling heuristic for PM-Grids (HoPe) incorporating a radical approach to grid resource scheduling to tackle this problem. A detailed design and implementation of HoPe with a decentralised self-management and adaptive policy are initiated. Among the other main contributions are a comprehensive taxonomy of grid systems as well as a detailed analysis of the honeybee colony and its nectar acquisition process (NAP), from the resource scheduling perspective, which have not been presented in any previous work, to the best of our knowledge. PM-Grid designs and HoPe implementation were evaluated thoroughly through a strictly controlled empirical evaluation framework with a well-established heuristic in high throughput computing, the opportunistic scheduling heuristic (OSH), as a benchmark algorithm. Comparisons with optimal values and worst bounds are conducted to gain a clear insight into HoPe behaviour, in terms of stability, throughput, turnaround time and speedup, under different running conditions of number of jobs and grid scales. Experimental results demonstrate the superiority of HoPe performance where it has successfully maintained optimum stability and throughput in more than 95% of the experiments, with HoPe achieving three times better than the OSH under extremely heavy loads. Regarding the turnaround time and speedup, HoPe has effectively achieved less than 50% of the turnaround time incurred by the OSH, while doubling its speedup in more than 60% of the experiments. These results indicate the potential of both PM-Grids and HoPe in realising futuristic grid visions. Therefore considering the deployment of PM-Grids in real life scenarios and the utilisation of HoPe in other parallel processing and high throughput computing systems are recommended.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

STOCHASTIC MOBILITY MODELS IN SPACE AND TIME

An interesting fact in nature is that if we observe agents (neurons, particles, animals, humans) behaving, or more precisely moving, inside their environment, we can recognize - tough at different space or time scales - very specific patterns. The existence of those patterns is quite obvious, since not all things in nature behave totally at random, especially if we take into account thinking species like human beings. If a first phenomenon which has been deeply modeled is the gas particle motion as the template of a totally random motion, other phenomena, like foraging patterns of animals such as albatrosses, and specific instances of human mobility wear some randomness away in favor of deterministic components. Thus, while the particle motion may be satisfactorily described with a Wiener Process (also called Brownian motion), the others are better described by other kinds of stochastic processes called Levy Flights. Minding at these phenomena in a unifying way, in terms of motion of agents \u2013 either inanimate like the gas particles, or animated like the albatrosses \u2013 the point is that the latter are driven by specific interests, possibly converging into a common task, to be accomplished. The whole thesis work turns around the concept of agent intentionality at different scales, whose model may be used as key ingredient in the statistical description of complex behaviors. The two main contributions in this direction are: 1. the development of a \u201cwait and chase\u201d model of human mobility having the same two-phase pattern as animal foraging but with a greater propensity of local stays in place and therefore a less dispersed general behavior; 2. the introduction of a mobility paradigm for the neurons of a multilayer neural network and a methodology to train these new kind of networks to develop a collective behavior. The lead idea is that neurons move toward the most informative mates to better learn how to fulfill their part in the overall functionality of the network. With these specific implementations we have pursued the general goal of attributing both a cognitive and a physical meaning to the intentionality so as to be able in a near future to speak of intentionality as an additional potential in the dynamics of the masses (both at the micro and a the macro-scale), and of communication as another network in the force field. This could be intended as a step ahead in the track opened by the past century physicists with the coupling of thermodynamic and Shannon entropies in the direction of unifying cognitive and physical laws

Bioinspired approaches for coordination and behaviour adaptation of aerial robot swarms

Behavioural adaptation is a pervasive component in a myriad of animal societies. A well-known strategy, known as Levy Walk, has been commonly linked to such adaptation in foraging animals, where the motion of individuals couples periods of localized search and long straight forward motions. Despite the vast number of studies on Levy Walks in computational ecology, it was only in the past decade that the first studies applied this concept to robotics tasks. Therefore, this Thesis draws inspiration from the Levy Walk behaviour, and its recent applications to robotics, to design biologically inspired models for two swarm robotics tasks, aiming at increasing the performance with respect to the state of the art. The first task is cooperative surveillance, where the aim is to deploy a swarm so that at any point in time regions of the domain are observed by multiple robots simultaneously. One of the contributions of this Thesis, is the Levy Swarm Algorithm that augments the concept of Levy Walk to include the Reynolds’ flocking rules and achieve both exploration and coordination in a swarm of unmanned aerial vehicles. The second task is adaptive foraging in environments of clustered rewards. In such environments behavioural adaptation is of paramount importance to modulate the transition between exploitation and exploration. Nature enables these adaptive changes by coupling the behaviour to the fluctuation of hormones that are mostly regulated by the endocrine system. This Thesis draws further inspiration from Nature and proposes a second model, the Endocrine Levy Walk, that employs an Artificial Endocrine System as a modulating mechanism of Levy Walk behaviour. The Endocrine Levy Walk is compared with the Yuragi model (Nurzaman et al., 2010), in both simulated and physical experiments where it shows its increased performance in terms of search efficiency, energy efficiency and number of rewards found. The Endocrine Levy Walk is then augmented to consider social interactions between members of the swarm by mimicking the behaviour of fireflies, where individuals attract others when finding suitable environmental conditions. This extended model, the Endocrine Levy Firefly, is compared to the Levy+ model (Sutantyo et al., 2013) and the Adaptive Collective Levy Walk Nauta et al. (2020). This comparison is also made both in simulated and physical experiments and assessed in terms of search efficiency, number of rewards found and cluster search efficiency, strengthening the argument in favour of the Endocrine Levy Firefly as a promising approach to tackle collaborative foragin

Ordonnancement décentralisé au niveau de la couche MAC pour les réseaux maillés radio cognitive

Le réseau maillé sans fil radio cognitive (CWMN) est un type de réseau prometteur qui combine les avantages des réseaux maillés sans fil (WMN) avec l’augmentation de la capacité du réseau grâce à l'utilisation de canaux disponibles découverts grâce à la technologie radio cognitive. Le CWMN nécessite une couche de contrôle d'accès au support (MAC) adapté à ce nouvel environnement. En effet, la couche MAC a pour objectif d’ordonnancer la transmission des trames de données dans un environnement dynamique dans lequel les canaux disponibles varient dans l'espace et le temps. L’ordonnancement dans un CWMN est plus difficile que dans un réseau multicanaux IEEE 802.11 car dans un CWMN, chaque noeud peut avoir un ensemble de canaux disponibles différents de leurs voisins tandis que dans un réseau multicanaux IEEE 802.11, tous les noeuds partagent le même ensemble de canaux disponibles. Dans le cadre de cette maîtrise, on améliore l’ordonnancement au niveau de la couche MAC des réseaux maillés radio cognitive. On propose un algorithme d'ordonnancement de paquets efficace dans une architecture distribuée dans CWMN. La solution utilise l’algorithme de coloration des sommets à deux distances, au niveau des noeuds qui augmente la vitesse de traitement de l'algorithme d’ordonnancement et réduit la quantité de données de contrôle échangées. Les résultats des simulations montrent que l'algorithme proposé améliore le passage à l’échelle, augmente la vitesse d’ordonnancement des liens et réduit la quantité de données de contrôle échangées par rapport à un algorithme existant

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of-the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: quality-of-service and video communication, routing protocol and cross-layer design. A few interesting problems about security and delay-tolerant networks are also discussed. This book is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks