Efficient Security Protocols for Fast Handovers in Wireless Mesh Networks

Wireless mesh networks (WMNs) are gaining popularity as a flexible and inexpensive replacement for Ethernet-based infrastructures. As the use of mobile devices such as smart phones and tablets is becoming ubiquitous, mobile clients should be guaranteed uninterrupted connectivity and services as they move from one access point to another within a WMN or between networks. To that end, we propose a novel security framework that consists of a new architecture, trust models, and protocols to offer mobile clients seamless and fast handovers in WMNs. The framework provides a dynamic, flexible, resource-efficient, and secure platform for intra-network and inter-network handovers in order to support real-time mobile applications in WMNs. In particular, we propose solutions to the following problems: authentication, key management, and group key management. We propose (1) a suite of certificate-based authentication protocols that minimize the authentication delay during handovers from one access point to another within a network (intra-network authentication). (2) a suite of key distribution and authentication protocols that minimize the authentication delay during handovers from one network to another (inter-network authentication). (3) a new implementation of group key management at the data link layer in order to reduce the group key update latency from linear time (as currently done in IEEE 802.11 standards) to logarithmic time. This contributes towards minimizing the latency of the handover process for mobile members in a multicast or broadcast group

Reconfigurable middleware architectures for large scale sensor networks

Wireless sensor networks, in an effort to be energy efficient, typically lack the high-level abstractions of advanced programming languages. Though strong, the dichotomy between these two paradigms can be overcome. The SENSIX software framework, described in this dissertation, uniquely integrates constraint-dominated wireless sensor networks with the flexibility of object-oriented programming models, without violating the principles of either. Though these two computing paradigms are contradictory in many ways, SENSIX bridges them to yield a dynamic middleware abstraction unifying low-level resource-aware task reconfiguration and high-level object recomposition. Through the layered approach of SENSIX, the software developer creates a domain-specific sensing architecture by defining a customized task specification and utilizing object inheritance. In addition, SENSIX performs better at large scales (on the order of 1000 nodes or more) than other sensor network middleware which do not include such unified facilities for vertical integration

A Unified Framework for Solving Multiagent Task Assignment Problems

Multiagent task assignment problem descriptors do not fully represent the complex interactions in a multiagent domain, and algorithmic solutions vary widely depending on how the domain is represented. This issue is compounded as related research fields contain descriptors that similarly describe multiagent task assignment problems, including complex domain interactions, but generally do not provide the mechanisms needed to solve the multiagent aspect of task assignment. This research presents a unified approach to representing and solving the multiagent task assignment problem for complex problem domains. Ideas central to multiagent task allocation, project scheduling, constraint satisfaction, and coalition formation are combined to form the basis of the constrained multiagent task scheduling (CMTS) problem. Basic analysis reveals the exponential size of the solution space for a CMTS problem, approximated by O(2n(m+n)) based on the number of agents and tasks involved in a problem. The shape of the solution space is shown to contain numerous discontinuous regions due to the complexities involved in relational constraints defined between agents and tasks. The CMTS descriptor represents a wide range of classical and modern problems, such as job shop scheduling, the traveling salesman problem, vehicle routing, and cooperative multi-object tracking. Problems using the CMTS representation are solvable by a suite of algorithms, with varying degrees of suitability. Solution generating methods range from simple random scheduling to state-of-the-art biologically inspired approaches. Techniques from classical task assignment solvers are extended to handle multiagent task problems where agents can also multitask. Additional ideas are incorporated from constraint satisfaction, project scheduling, evolutionary algorithms, dynamic coalition formation, auctioning, and behavior-based robotics to highlight how different solution generation strategies apply to the complex problem space

Contributions to topology discovery, self-healing and VNF placement in software-defined and virtualized networks

The evolution of information and communication technologies (e.g. cloud computing, the Internet of Things (IoT) and 5G, among others) has enabled a large market of applications and network services for a massive number of users connected to the Internet. Achieving high programmability while decreasing complexity and costs has become an essential aim of networking research due to the ever-increasing pressure generated by these applications and services. However, meeting these goals is an almost impossible task using traditional IP networks. Software-Defined Networking (SDN) is an emerging network architecture that could address the needs of service providers and network operators. This new technology consists in decoupling the control plane from the data plane, enabling the centralization of control functions on a concentrated or distributed platform. It also creates an abstraction between the network infrastructure and network applications, which allows for designing more flexible and programmable networks. Recent trends of increased user demands, the explosion of Internet traffic and diverse service requirements have further driven the interest in the potential capabilities of SDN to enable the introduction of new protocols and traffic management models. This doctoral research is focused on improving high-level policies and control strategies, which are becoming increasingly important given the limitations of current solutions for large-scale SDN environments. Specifically, the three largest challenges addressed in the development of this thesis are related to the processes of topology discovery, fault recovery and Virtual Network Function (VNF) placement in software-defined and virtualized networks. These challenges led to the design of a set of effective techniques, ranging from network protocols to optimal and heuristic algorithms, intended to solve existing problems and contribute to the deployment and adoption of such programmable networks.For the first challenge, this work presents a novel protocol that, unlike existing approaches, enables a distributed layer 2 discovery without the need for previous IP configurations or controller knowledge of the network. By using this mechanism, the SDN controller can discover the network view without incurring scalability issues, while taking advantage of the shortest control paths toward each switch. Moreover, this novel approach achieves noticeable improvement with respect to state-of-the-art techniques. To address the resilience concern of SDN, we propose a self-healing mechanism that recovers the control plane connectivity in SDN-managed environments without overburdening the controller performance. The main idea underlying this proposal is to enable real-time recovery of control paths in the face of failures without the intervention of a controller. Obtained results show that the proposed approach recovers the control topology efficiently in terms of time and message load over a wide range of generated networks. The third contribution made in this thesis combines topology knowledge with bin packing techniques in order to efficiently place the required VNF. An online heuristic algorithm with low-complexity was developed as a suitable solution for dynamic infrastructures. Extensive simulations, using network topologies representative of different scales, validate the good performance of the proposed approaches regarding the number of required instances and the delay among deployed functions. Additionally, the proposed heuristic algorithm improves the execution times by a fifth order of magnitude compared to the optimal formulation of this problem.Postprint (published version

Algorithmic Reason

Are algorithms ruling the world today? Is artificial intelligence making life-and-death decisions? Are social media companies able to manipulate elections? As we are confronted with public and academic anxieties about unprecedented changes, this book offers a different analytical prism to investigate these transformations as more mundane and fraught. Aradau and Blanke develop conceptual and methodological tools to understand how algorithmic operations shape the government of self and other. While disperse and messy, these operations are held together by an ascendant algorithmic reason. Through a global perspective on algorithmic operations, the book helps us understand how algorithmic reason redraws boundaries and reconfigures differences. The book explores the emergence of algorithmic reason through rationalities, materializations, and interventions. It traces how algorithmic rationalities of decomposition, recomposition, and partitioning are materialized in the construction of dangerous others, the power of platforms, and the production of economic value. The book shows how political interventions to make algorithms governable encounter friction, refusal, and resistance. The theoretical perspective on algorithmic reason is developed through qualitative and digital methods to investigate scenes and controversies that range from mass surveillance and the Cambridge Analytica scandal in the UK to predictive policing in the US, and from the use of facial recognition in China and drone targeting in Pakistan to the regulation of hate speech in Germany. Algorithmic Reason offers an alternative to dystopia and despair through a transdisciplinary approach made possible by the authors’ backgrounds, which span the humanities, social sciences, and computer sciences

Application of service composition mechanisms to Future Networks architectures and Smart Grids

Aquesta tesi gira entorn de la hipòtesi de la metodologia i mecanismes de composició de serveis i com es poden aplicar a diferents camps d'aplicació per a orquestrar de manera eficient comunicacions i processos flexibles i sensibles al context. Més concretament, se centra en dos camps d'aplicació: la distribució eficient i sensible al context de contingut multimèdia i els serveis d'una xarxa elèctrica intel·ligent. En aquest últim camp es centra en la gestió de la infraestructura, cap a la definició d'una Software Defined Utility (SDU), que proposa una nova manera de gestionar la Smart Grid amb un enfocament basat en programari, que permeti un funcionament molt més flexible de la infraestructura de xarxa elèctrica. Per tant, revisa el context, els requisits i els reptes, així com els enfocaments de la composició de serveis per a aquests camps. Fa especial èmfasi en la combinació de la composició de serveis amb arquitectures Future Network (FN), presentant una proposta de FN orientada a serveis per crear comunicacions adaptades i sota demanda. També es presenten metodologies i mecanismes de composició de serveis per operar sobre aquesta arquitectura, i posteriorment, es proposa el seu ús (en conjunció o no amb l'arquitectura FN) en els dos camps d'estudi. Finalment, es presenta la investigació i desenvolupament realitzat en l'àmbit de les xarxes intel·ligents, proposant diverses parts de la infraestructura SDU amb exemples d'aplicació de composició de serveis per dissenyar seguretat dinàmica i flexible o l'orquestració i gestió de serveis i recursos dins la infraestructura de l'empresa elèctrica.Esta tesis gira en torno a la hipótesis de la metodología y mecanismos de composición de servicios y cómo se pueden aplicar a diferentes campos de aplicación para orquestar de manera eficiente comunicaciones y procesos flexibles y sensibles al contexto. Más concretamente, se centra en dos campos de aplicación: la distribución eficiente y sensible al contexto de contenido multimedia y los servicios de una red eléctrica inteligente. En este último campo se centra en la gestión de la infraestructura, hacia la definición de una Software Defined Utility (SDU), que propone una nueva forma de gestionar la Smart Grid con un enfoque basado en software, que permita un funcionamiento mucho más flexible de la infraestructura de red eléctrica. Por lo tanto, revisa el contexto, los requisitos y los retos, así como los enfoques de la composición de servicios para estos campos. Hace especial hincapié en la combinación de la composición de servicios con arquitecturas Future Network (FN), presentando una propuesta de FN orientada a servicios para crear comunicaciones adaptadas y bajo demanda. También se presentan metodologías y mecanismos de composición de servicios para operar sobre esta arquitectura, y posteriormente, se propone su uso (en conjunción o no con la arquitectura FN) en los dos campos de estudio. Por último, se presenta la investigación y desarrollo realizado en el ámbito de las redes inteligentes, proponiendo varias partes de la infraestructura SDU con ejemplos de aplicación de composición de servicios para diseñar seguridad dinámica y flexible o la orquestación y gestión de servicios y recursos dentro de la infraestructura de la empresa eléctrica.This thesis revolves around the hypothesis the service composition methodology and mechanisms and how they can be applied to different fields of application in order to efficiently orchestrate flexible and context-aware communications and processes. More concretely, it focuses on two fields of application that are the context-aware media distribution and smart grid services and infrastructure management, towards a definition of a Software-Defined Utility (SDU), which proposes a new way of managing the Smart Grid following a software-based approach that enable a much more flexible operation of the power infrastructure. Hence, it reviews the context, requirements and challenges of these fields, as well as the service composition approaches. It makes special emphasis on the combination of service composition with Future Network (FN) architectures, presenting a service-oriented FN proposal for creating context-aware on-demand communication services. Service composition methodology and mechanisms are also presented in order to operate over this architecture, and afterwards, proposed for their usage (in conjunction or not with the FN architecture) in the deployment of context-aware media distribution and Smart Grids. Finally, the research and development done in the field of Smart Grids is depicted, proposing several parts of the SDU infrastructure, with examples of service composition application for designing dynamic and flexible security for smart metering or the orchestration and management of services and data resources within the utility infrastructure

Algorithmic Reason

Are algorithms ruling the world today? Is artificial intelligence making life-and-death decisions? Are social media companies able to manipulate elections? As we are confronted with public and academic anxieties about unprecedented changes, this book offers a different analytical prism to investigate these transformations as more mundane and fraught. Aradau and Blanke develop conceptual and methodological tools to understand how algorithmic operations shape the government of self and other. While disperse and messy, these operations are held together by an ascendant algorithmic reason. Through a global perspective on algorithmic operations, the book helps us understand how algorithmic reason redraws boundaries and reconfigures differences. The book explores the emergence of algorithmic reason through rationalities, materializations, and interventions. It traces how algorithmic rationalities of decomposition, recomposition, and partitioning are materialized in the construction of dangerous others, the power of platforms, and the production of economic value. The book shows how political interventions to make algorithms governable encounter friction, refusal, and resistance. The theoretical perspective on algorithmic reason is developed through qualitative and digital methods to investigate scenes and controversies that range from mass surveillance and the Cambridge Analytica scandal in the UK to predictive policing in the US, and from the use of facial recognition in China and drone targeting in Pakistan to the regulation of hate speech in Germany. Algorithmic Reason offers an alternative to dystopia and despair through a transdisciplinary approach made possible by the authors’ backgrounds, which span the humanities, social sciences, and computer sciences

FinBook: literary content as digital commodity

This short essay explains the significance of the FinBook intervention, and invites the reader to participate. We have associated each chapter within this book with a financial robot (FinBot), and created a market whereby book content will be traded with financial securities. As human labour increasingly consists of unstable and uncertain work practices and as algorithms replace people on the virtual trading floors of the worlds markets, we see members of society taking advantage of FinBots to invest and make extra funds. Bots of all kinds are making financial decisions for us, searching online on our behalf to help us invest, to consume products and services. Our contribution to this compilation is to turn the collection of chapters in this book into a dynamic investment portfolio, and thereby play out what might happen to the process of buying and consuming literature in the not-so-distant future. By attaching identities (through QR codes) to each chapter, we create a market in which the chapter can ‘perform’. Our FinBots will trade based on features extracted from the authors’ words in this book: the political, ethical and cultural values embedded in the work, and the extent to which the FinBots share authors’ concerns; and the performance of chapters amongst those human and non-human actors that make up the market, and readership. In short, the FinBook model turns our work and the work of our co-authors into an investment portfolio, mediated by the market and the attention of readers. By creating a digital economy specifically around the content of online texts, our chapter and the FinBook platform aims to challenge the reader to consider how their personal values align them with individual articles, and how these become contested as they perform different value judgements about the financial performance of each chapter and the book as a whole. At the same time, by introducing ‘autonomous’ trading bots, we also explore the different ‘network’ affordances that differ between paper based books that’s scarcity is developed through analogue form, and digital forms of books whose uniqueness is reached through encryption. We thereby speak to wider questions about the conditions of an aggressive market in which algorithms subject cultural and intellectual items – books – to economic parameters, and the increasing ubiquity of data bots as actors in our social, political, economic and cultural lives. We understand that our marketization of literature may be an uncomfortable juxtaposition against the conventionally-imagined way a book is created, enjoyed and shared: it is intended to be