Disaster Resilient Optical Core Networks

During the past few years, the number of catastrophic disasters has increased and its impact sometimes incapacitates the infrastructures within a region. The communication network infrastructure is one of the affected systems during these events. Thus, building a resilient network backbone is essential due to the big role of networks during disaster recovery operations. In this thesis, the research efforts in building a disaster-resilient network are reviewed and open issues related to building disaster-resilient networks are discussed. Large size disasters not necessarily impact the communication networks, but instead it can stimulate events that cause network performance degradation. In this regard, two open challenges that arise after disasters are considered one is the short-term capacity exhaustion and the second is the power outage. First, the post-disaster traffic floods phenomena is considered. The impact of the traffic floods on the optical core network performance is studied. Five mitigation approaches are proposed to serve these floods and minimise the incurred blocking. The proposed approaches explore different technologies such as excess or overprovisioned capacity exploitation, traffic filtering, protection paths rerouting, rerouting all traffic and finally using the degrees of freedom offered by differentiated services. The mitigation approaches succeeded in reducing the disaster induced traffic blocking. Second, advance reservation provisioning in an energy-efficient approach is developed. Four scenarios are considered to minimise power consumption. The scenarios exploit the flexibility provided by the sliding-window advance reservation requests. This flexibility is studied through scheduling and rescheduling scenarios. The proposed scenarios succeeded in minimising the consumed power. Third, the sliding-window flexibility is exploited for the objective of minimising network blocking during post-disaster traffic floods. The scheduling and rescheduling scenarios are extended to overcome the capacity exhaustion and improve the network blocking. The proposed schemes minimised the incurred blocking during traffic floods by exploiting sliding window. Fourth, building blackout resilient networks is proposed. The network performance during power outages is evaluated. A remedy approach is suggested for maximising network lifetime during blackouts. The approach attempts to reduce the required backup power supply while minimising network outages due to limited energy production. The results show that the mitigation approach succeeds in keeping the network alive during a blackout while minimising the required backup power

Towards Scalable Design of Future Wireless Networks

Wireless operators face an ever-growing challenge to meet the throughput and processing requirements of billions of devices that are getting connected. In current wireless networks, such as LTE and WiFi, these requirements are addressed by provisioning more resources: spectrum, transmitters, and baseband processors. However, this simple add-on approach to scale system performance is expensive and often results in resource underutilization. What are, then, the ways to efficiently scale the throughput and operational efficiency of these wireless networks? To answer this question, this thesis explores several potential designs: utilizing unlicensed spectrum to augment the bandwidth of a licensed network; coordinating transmitters to increase system throughput; and finally, centralizing wireless processing to reduce computing costs. First, we propose a solution that allows LTE, a licensed wireless standard, to co-exist with WiFi in the unlicensed spectrum. The proposed solution bridges the incompatibility between the fixed access of LTE, and the random access of WiFi, through channel reservation. It achieves a fair LTE-WiFi co-existence despite the transmission gaps and unequal frame durations. Second, we consider a system where different MIMO transmitters coordinate to transmit data of multiple users. We present an adaptive design of the channel feedback protocol that mitigates interference resulting from the imperfect channel information. Finally, we consider a Cloud-RAN architecture where a datacenter or a cloud resource processes wireless frames. We introduce a tree-based design for real-time transport of baseband samples and provide its end-to-end schedulability and capacity analysis. We also present a processing framework that combines real-time scheduling with fine-grained parallelism. The framework reduces processing times by migrating parallelizable tasks to idle compute resources, and thus, decreases the processing deadline-misses at no additional cost. We implement and evaluate the above solutions using software-radio platforms and off-the-shelf radios, and confirm their applicability in real-world settings.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133358/1/gkchai_1.pd

Networks, Communication, and Computing Vol. 2

Networks, communications, and computing have become ubiquitous and inseparable parts of everyday life. This book is based on a Special Issue of the Algorithms journal, and it is devoted to the exploration of the many-faceted relationship of networks, communications, and computing. The included papers explore the current state-of-the-art research in these areas, with a particular interest in the interactions among the fields

Development and management of collective network and cloud computing infrastructures

In the search and development of more participatory models for infrastructure development and management, in this dissertation, we investigate models for the financing, deployment, and operation of network and cloud computing infrastructures. Our main concern is to overcome the inherent exclusion in participation in the processes of development and management and in the right of use in the current dominant models. Our work starts by studying in detail the model of Guifi.net, a successful bottom-up initiative for building network infrastructure, generally referred to as a community networks. We pay special attention to its governance system and economic organisation because we argue that these are the key components of the success of this initiative. Then, we generalise our findings for any community network, aiming at becoming sustainable and scalable, and we explore the suitability of the Guifi.net model to the cloud computing infrastructure. As a result of both, we coin the attribute extensible to refer to infrastructure that is relatively easy to expand and maintain in contrast to those naturally limited or hard to expand, such as natural resources or highly complex or advanced artificial systems. We conclude proposing a generic model which, in our opinion, is suitable, at least, for managing extensible infrastructure. The Guifi.net model is deeply rooted in the commons; thus, the research in this field, in general, and Elinor Ostrom’s work, in particular, have left a profound imprint in our work. Our results show that the \guifinet model meets almost entirely the principles of long-enduring commons identified by E. Ostrom. This work has been developed as an industrial doctorate. As such, it combines academic research with elements of practice and pursues an effective knowledge transfer between academia and the private sector. Given that the private sector’s partner is a not-for-profit organisation, the effort to create social value has prevailed over the ambition to advance the development of a specific industrial product or particular technology.En la recerca i desenvolupament de models més participatius per al desenvolupament i gestió d'infraestructura, en aquesta tesi investiguem sobre models per al finançament, desplegament i operació d'infraestructures de xarxa i de computació al núvol. La nostra preocupació principal és fer front a l’exclusió inherent dels models dominants actualment pel que fa a la participació en els processos de desenvolupament i gestió i, també, als drets d’us. El nostre treball comença amb un estudi detallat del model de Guifi.net, un cas d'èxit d'iniciativa ciutadana en la construcció d'infraestructura de xarxa, iniciatives que es coneixen com a xarxes comunitàries. En fer-ho, parem una atenció especial al sistema de governança i a l’organització econòmica perquè pensem que són els dos elements claus de l'èxit d'aquesta iniciativa. Tot seguit passem a analitzar d'altres xarxes comunitàries per abundar en la comprensió dels factors determinants per a la seva sostenibilitat i escalabilitat. Després ampliem el nostre estudi analitzant la capacitat i el comportament del model de Guifi.net en el camp de les infraestructures de computació al núvol. A resultes d'aquests estudis, proposem l'atribut extensible per a descriure aquelles infraestructures que són relativament fàcil d'ampliar i gestionar, en contraposició a les que o bé estan limitades de forma natural o be són difícils d'ampliar, com ara els recursos naturals o els sistemes artificials avançats o complexos. Finalitzem aquest treball fent una proposta de model genèric que pensem que és d'aplicabilitat, com a mínim, a tot tipus d'infraestructura extensible. El model de Guifi.net està fortament vinculat als bens comuns. És per això que la recerca en aquest àmbit, en general, i els treballs de Elinor Ostrom en particular, han deixat una forta empremta en el nostre treball. Els resultats que hem obtingut mostren que el model Guifi.net s'ajusta molt bé als principis que segons Ostrom han de complir els béns comuns per ser sostenibles. Aquest treball s'ha desenvolupat com a doctorat industrial. Com a tal, combina la investigació acadèmica amb elements de practica i persegueix una transferència efectiva de coneixement entre l'àmbit acadèmic i el sector privat. Ates que el soci del sector privat és una organització sense ànim de lucre, l’esforç per crear valor social ha prevalgut en l’ambició d’avançar en el desenvolupament d'un producte industrial específic o d'una tecnologia particula

Development and management of collective network and cloud computing infrastructures

Pla de Doctorat industrial de la Generalitat de CatalunyaIn the search and development of more participatory models for infrastructure development and management, in this dissertation, we investigate models for the financing, deployment, and operation of network and cloud computing infrastructures. Our main concern is to overcome the inherent exclusion in participation in the processes of development and management and in the right of use in the current dominant models. Our work starts by studying in detail the model of Guifi.net, a successful bottom-up initiative for building network infrastructure, generally referred to as a community networks. We pay special attention to its governance system and economic organisation because we argue that these are the key components of the success of this initiative. Then, we generalise our findings for any community network, aiming at becoming sustainable and scalable, and we explore the suitability of the Guifi.net model to the cloud computing infrastructure. As a result of both, we coin the attribute extensible to refer to infrastructure that is relatively easy to expand and maintain in contrast to those naturally limited or hard to expand, such as natural resources or highly complex or advanced artificial systems. We conclude proposing a generic model which, in our opinion, is suitable, at least, for managing extensible infrastructure. The Guifi.net model is deeply rooted in the commons; thus, the research in this field, in general, and Elinor Ostrom’s work, in particular, have left a profound imprint in our work. Our results show that the \guifinet model meets almost entirely the principles of long-enduring commons identified by E. Ostrom. This work has been developed as an industrial doctorate. As such, it combines academic research with elements of practice and pursues an effective knowledge transfer between academia and the private sector. Given that the private sector’s partner is a not-for-profit organisation, the effort to create social value has prevailed over the ambition to advance the development of a specific industrial product or particular technology.En la recerca i desenvolupament de models més participatius per al desenvolupament i gestió d'infraestructura, en aquesta tesi investiguem sobre models per al finançament, desplegament i operació d'infraestructures de xarxa i de computació al núvol. La nostra preocupació principal és fer front a l’exclusió inherent dels models dominants actualment pel que fa a la participació en els processos de desenvolupament i gestió i, també, als drets d’us. El nostre treball comença amb un estudi detallat del model de Guifi.net, un cas d'èxit d'iniciativa ciutadana en la construcció d'infraestructura de xarxa, iniciatives que es coneixen com a xarxes comunitàries. En fer-ho, parem una atenció especial al sistema de governança i a l’organització econòmica perquè pensem que són els dos elements claus de l'èxit d'aquesta iniciativa. Tot seguit passem a analitzar d'altres xarxes comunitàries per abundar en la comprensió dels factors determinants per a la seva sostenibilitat i escalabilitat. Després ampliem el nostre estudi analitzant la capacitat i el comportament del model de Guifi.net en el camp de les infraestructures de computació al núvol. A resultes d'aquests estudis, proposem l'atribut extensible per a descriure aquelles infraestructures que són relativament fàcil d'ampliar i gestionar, en contraposició a les que o bé estan limitades de forma natural o be són difícils d'ampliar, com ara els recursos naturals o els sistemes artificials avançats o complexos. Finalitzem aquest treball fent una proposta de model genèric que pensem que és d'aplicabilitat, com a mínim, a tot tipus d'infraestructura extensible. El model de Guifi.net està fortament vinculat als bens comuns. És per això que la recerca en aquest àmbit, en general, i els treballs de Elinor Ostrom en particular, han deixat una forta empremta en el nostre treball. Els resultats que hem obtingut mostren que el model Guifi.net s'ajusta molt bé als principis que segons Ostrom han de complir els béns comuns per ser sostenibles. Aquest treball s'ha desenvolupat com a doctorat industrial. Com a tal, combina la investigació acadèmica amb elements de practica i persegueix una transferència efectiva de coneixement entre l'àmbit acadèmic i el sector privat. Ates que el soci del sector privat és una organització sense ànim de lucre, l’esforç per crear valor social ha prevalgut en l’ambició d’avançar en el desenvolupament d'un producte industrial específic o d'una tecnologia particularPostprint (published version

EFFICIENT DATA PROTECTION BY NOISING, MASKING, AND METERING

Protecting data secrecy is an important design goal of computing systems. Conventional techniques like access control mechanisms and cryptography are widely deployed, and yet security breaches and data leakages still occur. There are several challenges. First, sensitivity of the system data is not always easy to decide. Second, trustworthiness is not a constant property of the system components and users. Third, a system’s functional requirements can be at odds with its data protection requirements. In this dissertation, we show that efficient data protection can be achieved by noising, masking, or metering sensitive data. Specifically, three practical problems are addressed in the dissertation—storage side-channel attacks in Linux, server anonymity violations in web sessions, and data theft by malicious insiders. To mitigate storage side-channel attacks, we introduce a differentially private system, dpprocfs, which injects noise into side-channel vectors and also reestablishes invariants on the noised outputs. Our evaluations show that dpprocfs mitigates known storage side channels while preserving the utility of the proc filesystem for monitoring and diagnosis. To enforce server anonymity, we introduce a cloud service, PoPSiCl, which masks server identifiers, including DNS names and IP addresses, with personalized pseudonyms. PoPSiCl can defend against both passive and active network attackers with minimal impact to web-browsing performance. To prevent data theft from insiders, we introduce a system, Snowman, which restricts the user to access data only remotely and accurately meters the sensitive data output to the user by conducting taint analysis in a replica of the application execution without slowing the interactive user session.Doctor of Philosoph

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

Proceedings of the 2nd Conference on Production Systems and Logistics (CPSL 2021)

Proceedings of the CPSL 202

Bioinspired metaheuristic algorithms for global optimization

This paper presents concise comparison study of newly developed bioinspired algorithms for global optimization problems. Three different metaheuristic techniques, namely Accelerated Particle Swarm Optimization (APSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO) are investigated and implemented in Matlab environment. These methods are compared on four unimodal and multimodal nonlinear functions in order to find global optimum values. Computational results indicate that GWO outperforms other intelligent techniques, and that all aforementioned algorithms can be successfully used for optimization of continuous functions

Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF