Utilização do protocolo anycast em ambientes virtuais distribuídos visando à escalabilidade do sistema

Distributed Virtual Environments (DVE) allow multiple users interact with a virtual world by sharing, manipulating objects. Each user has his/her own vision of this world and every changes of state of the environment are distributed among other users. Due to technological constraints, most systems for distributed virtual environments support a limited number of users. The major limitation for development of DVE scale are imposed by the communication system. As the number of users grows, the amount of bandwidth required to exchange information in real time among stations to upgrade the environment and keep it in a consistent state for all connected users. Based on this situation is proposed a framework that uses the protocol anycast in the application layer that provides a load balancing among servers in the region and aims at reducing the latency of message delivery between participants selecting the DVE server best suited for the region participant to connect to the environment

Reconfiguração de sistemas de distribuição operando em vários níveis de demanda através de uma meta-heurística de busca em vizinhança variável

Pós-graduação em Engenharia Elétrica - FEIS

Secure gossiping techniques and components

Gossip protocols have proved to be a viable solution to set-up and manage largescale P2P services or applications in a fully decentralised scenario. The gossip or epidemic communication scheme is heavily based on stochastic behaviors and it is the fundamental idea behind many large-scale P2P protocols. It provides many remarkable features, such as scalability, robustness to failures, emergent load balancing capabilities, fast spreading, and redundancy of information. In some sense, these services or protocols mimic natural system behaviors in order to achieve their goals. The key idea of this work is that the remarkable properties of gossip hold when all the participants follow the rules dictated by the actual protocols. If one or more malicious nodes join the network and start cheating according to some strategy, the result can be catastrophic. In order to study how serious the threat posed by malicious nodes can be and what can be done to prevent attackers from cheating, we focused on a general attack model aimed to defeat a key service in gossip overlay networks (the Peer Sampling Service [JGKvS04]). We also focused on the problem of protecting against forged information exchanged in gossip services. We propose a solution technique for each problem; both techniques are general enough to be applied to distinct service implementations. As gossip protocols, our solutions are based on stochastic behavior and are fully decentralized. In addition, each technique’s behaviour is abstracted by a general primitive function extending the basic gossip scheme; this approach allows the adoptions of our solutions with minimal changes in different scenarios. We provide an extensive experimental evaluation to support the effectiveness of our techniques. Basically, these techniques aim to be building blocks or P2P architecture guidelines in building more resilient and more secure P2P services.

Diseño e instalación de un servicio web de tienda virtual en alta disponibilidad

[ES]Diseño e instalación de un servicio web de tienda virtual en un entorno de computación en clúster para proporcionar alta disponibilidad y balanceo de carga del mencionado servicio. La infraestructura requerida para este despliegue será virtual, utilizándose como plataforma de virtualización KVM. Las tareas se organizan en : 1.Tareas para la creación de un clúster de balanceo de carga donde una máquina será la encargada de recibir las peticiones de los clientes y de redirigirlas a los servidores web según la carga de éstos. 2. Tareas para la creación de un clúster de alta disponibilidad para que en caso de fallo siempre haya un servidor de base de datos que pueda atender a las peticiones de los servidores web.

Cross-layer optimizations in multi-hop ad hoc networks

Unlike traditional wireless networks, characterized by the presence of last-mile, static and reliable infrastructures, Mobile ad Hoc Networks (MANETs) are dynamically formed by collections of mobile and static terminals that exchange data by enabling each other's communication. Supporting multi-hop communication in a MANET is a challenging research area because it requires cooperation between different protocol layers (MAC, routing, transport). In particular, MAC and routing protocols could be considered mutually cooperative protocol layers. When a route is established, the exposed and hidden terminal problems at MAC layer may decrease the end-to-end performance proportionally with the length of each route. Conversely, the contention at MAC layer may cause a routing protocol to respond by initiating new routes queries and routing table updates. Multi-hop communication may also benefit the presence of pseudo-centralized virtual infrastructures obtained by grouping nodes into clusters. Clustering structures may facilitate the spatial reuse of resources by increasing the system capacity: at the same time, the clustering hierarchy may be used to coordinate transmissions events inside the network and to support intra-cluster routing schemes. Again, MAC and clustering protocols could be considered mutually cooperative protocol layers: the clustering scheme could support MAC layer coordination among nodes, by shifting the distributed MAC paradigm towards a pseudo-centralized MAC paradigm. On the other hand, the system benefits of the clustering scheme could be emphasized by the pseudo-centralized MAC layer with the support for differentiated access priorities and controlled contention. In this thesis, we propose cross-layer solutions involving joint design of MAC, clustering and routing protocols in MANETs. As main contribution, we study and analyze the integration of MAC and clustering schemes to support multi-hop communication in large-scale ad hoc networks. A novel clustering protocol, named Availability Clustering (AC), is defined under general nodes' heterogeneity assumptions in terms of connectivity, available energy and relative mobility. On this basis, we design and analyze a distributed and adaptive MAC protocol, named Differentiated Distributed Coordination Function (DDCF), whose focus is to implement adaptive access differentiation based on the node roles, which have been assigned by the upper-layer's clustering scheme. We extensively simulate the proposed clustering scheme by showing its effectiveness in dominating the network dynamics, under some stressing mobility models and different mobility rates. Based on these results, we propose a possible application of the cross-layer MAC+Clustering scheme to support the fast propagation of alert messages in a vehicular environment. At the same time, we investigate the integration of MAC and routing protocols in large scale multi-hop ad-hoc networks. A novel multipath routing scheme is proposed, by extending the AOMDV protocol with a novel load-balancing approach to concurrently distribute the traffic among the multiple paths. We also study the composition effect of a IEEE 802.11-based enhanced MAC forwarding mechanism called Fast Forward (FF), used to reduce the effects of self-contention among frames at the MAC layer. The protocol framework is modelled and extensively simulated for a large set of metrics and scenarios. For both the schemes, the simulation results reveal the benefits of the cross-layer MAC+routing and MAC+clustering approaches over single-layer solutions.

Performance evaluation of a parallel algorithm for simultaneous untangling and smoothing of tetrahedral meshes

[EN]A new parallel algorithm for simultaneous untangling and smoothing of tetrahedral meshes is proposed in this paper. We provide a detailed analysis of its performance on shared-memory many-core computer architectures. This performance analysis includes the evaluation of execution time, parallel scalability, load balancing, and parallelism bottlenecks. Additionally, we compare the impact of three previously published graph coloring procedures on the performance of our parallel algorithm. We use six benchmark meshes with a wide range of sizes. Using these experimental data sets, we describe the behavior of the parallel algorithm for different data sizes. We demonstrate that this algorithm is highly scalable when it runs on two different high-performance many-core computers with up to 128 processors...

A Routing Protocol Based on Energy and Link Quality for Internet of Things Applications

The Internet of Things (IoT) is attracting considerable attention from the universities, industries, citizens and governments for applications, such as healthcare, environmental monitoring and smart buildings. IoT enables network connectivity between smart devices at all times, everywhere, and about everything. In this context, Wireless Sensor Networks (WSNs) play an important role in increasing the ubiquity of networks with smart devices that are low-cost and easy to deploy. However, sensor nodes are restricted in terms of energy, processing and memory. Additionally, low-power radios are very sensitive to noise, interference and multipath distortions. In this context, this article proposes a routing protocol based on Routing by Energy and Link quality (REL) for IoT applications. To increase reliability and energy-efficiency, REL selects routes on the basis of a proposed end-to-end link quality estimator mechanism, residual energy and hop count. Furthermore, REL proposes an event-driven mechanism to provide load balancing and avoid the premature energy depletion of nodes/networks. Performance evaluations were carried out using simulation and testbed experiments to show the impact and benefits of REL in small and large-scale networks. The results show that REL increases the network lifetime and services availability, as well as the quality of service of IoT applications. It also provides an even distribution of scarce network resources and reduces the packet loss rate, compared with the performance of well-known protocols.

StreamCloud: An Elastic Parallel-Distributed Stream Processing Engine

In recent years, applications in domains such as telecommunications, network security or large scale sensor networks showed the limits of the traditional store-then-process paradigm. In this context, Stream Processing Engines emerged as a candidate solution for all these applications demanding for high processing capacity with low processing latency guarantees. With Stream Processing Engines, data streams are not persisted but rather processed on the fly, producing results continuously. Current Stream Processing Engines, either centralized or distributed, do not scale with the input load due to single-node bottlenecks. Moreover, they are based on static configurations that lead to either under or over-provisioning. This Ph.D. thesis discusses StreamCloud, an elastic paralleldistributed stream processing engine that enables for processing of large data stream volumes. Stream- Cloud minimizes the distribution and parallelization overhead introducing novel techniques that split queries into parallel subqueries and allocate them to independent sets of nodes. Moreover, Stream- Cloud elastic and dynamic load balancing protocols enable for effective adjustment of resources depending on the incoming load. Together with the parallelization and elasticity techniques, Stream- Cloud defines a novel fault tolerance protocol that introduces minimal overhead while providing fast recovery. StreamCloud has been fully implemented and evaluated using several real word applications such as fraud detection applications or network analysis applications. The evaluation, conducted using a cluster with more than 300 cores, demonstrates the large scalability, the elasticity and fault tolerance effectiveness of StreamCloud. Resumen En los útimos años, aplicaciones en dominios tales como telecomunicaciones, seguridad de redes y redes de sensores de gran escala se han encontrado con múltiples limitaciones en el paradigma tradicional de bases de datos. En este contexto, los sistemas de procesamiento de flujos de datos han emergido como solución a estas aplicaciones que demandan una alta capacidad de procesamiento con una baja latencia. En los sistemas de procesamiento de flujos de datos, los datos no se persisten y luego se procesan, en su lugar los datos son procesados al vuelo en memoria produciendo resultados de forma continua. Los actuales sistemas de procesamiento de flujos de datos, tanto los centralizados, como los distribuidos, no escalan respecto a la carga de entrada del sistema debido a un cuello de botella producido por la concentración de flujos de datos completos en nodos individuales. Por otra parte, éstos están basados en configuraciones estáticas lo que conducen a un sobre o bajo aprovisionamiento. Esta tesis doctoral presenta StreamCloud, un sistema elástico paralelo-distribuido para el procesamiento de flujos de datos que es capaz de procesar grandes volúmenes de datos. StreamCloud minimiza el coste de distribución y paralelización por medio de una técnica novedosa la cual particiona las queries en subqueries paralelas repartiéndolas en subconjuntos de nodos independientes. Ademas, Stream- Cloud posee protocolos de elasticidad y equilibrado de carga que permiten una optimización de los recursos dependiendo de la carga del sistema. Unidos a los protocolos de paralelización y elasticidad, StreamCloud define un protocolo de tolerancia a fallos que introduce un coste mínimo mientras que proporciona una rápida recuperación. StreamCloud ha sido implementado y evaluado mediante varias aplicaciones del mundo real tales como aplicaciones de detección de fraude o aplicaciones de análisis del tráfico de red. La evaluación ha sido realizada en un cluster con más de 300 núcleos, demostrando la alta escalabilidad y la efectividad tanto de la elasticidad, como de la tolerancia a fallos de StreamCloud.

StreamCloud: An elastic and scalable data streaming system

Many applications in several domains such as telecommunications, network security, large scale sensor networks, require online processing of continuous data lows. They produce very high loads that requires aggregating the processing capacity of many nodes. Current Stream Processing Engines do not scale with the input load due to single-node bottlenecks. Additionally, they are based on static con?gurations that lead to either under or over-provisioning. In this paper, we present StreamCloud, a scalable and elastic stream processing engine for processing large data stream volumes. StreamCloud uses a novel parallelization technique that splits queries into subqueries that are allocated to independent sets of nodes in a way that minimizes the distribution overhead. Its elastic protocols exhibit low intrusiveness, enabling effective adjustment of resources to the incoming load. Elasticity is combined with dynamic load balancing to minimize the computational resources used. The paper presents the system design, implementation and a thorough evaluation of the scalability and elasticity of the fully implemented system.

Evaluación de la tecnología CAES como sistema de almacenamiento de energía eólica. Caso de estudio en España

Se presenta a continuación un modelo de una planta del almacenamiento de energía mediante aire comprimido siguiendo un proceso adiabático. En esta planta la energía eólica sobrante se usa para comprimir aire mediante un tren de compresión de 25 MW, el aire comprimido será después almacenado en una caverna de sal a 770 metros de profundidad. La compresión se llevará a cabo por la noche, durante 6 horas, debido a los bajos precios de electricidad. Cuando los precios de la electricidad suben durante el día, el aire comprimido es extraído de la caverna de sal y es utilizado para producir energía en un tren de expansión de 70 MW durante 3 horas. La localización elegida para la planta es el norte de Burgos (Castilla y León, España), debido a la coincidencia de la existencia de muchos parques eólicos y una formación con las propiedades necesarias para el almacenamiento. El aspecto más importante de este proyecto es la utilización de un almacenamiento térmico que permitirá aprovechar el calor de la compresión para calentar el aire a la entrada de la expansión, eliminando combustibles fósiles del sistema. Por consiguiente, este proyecto es una atractiva solución en un posible futuro con emisiones de carbono restringidas, cuando la integración de energía renovable en la red eléctrica supone un reto importante. ABSTRACT: A model of an adiabatic compressed air energy storage plant is presented. In this plant surplus wind energy is used to compress air by means of a 25 MW compression train, the compressed air will be later stored in a salt cavern at 770 meters depth. Compression is carried out at night time, during 6 hours, because power prices are lower. When power prices go up during the day, the compressed air is withdrawn from the salt cavern and is used to produce energy in an expansion train of 70 MW during 3 hours. The chosen location for the plant is in the north of Burgos (Castilla y León, Spain), due to both the existence of several wind farms and a suitable storage facility with good properties at the same place. The relevance of this project is that it is provided with a thermal storage, which allows using the generated heat in the compression for re-heating the air before the expansion, eliminating fossil fuels from the system. Hence, this system is an attractive load balancing solution in a possibly carbon-constrained future, where the integration of renewable energy sources into the electric grid is a major challenge.

Aplicación de la metodología GloBeM al servicio de cloud Hydra

El presente Proyecto de Fin de Máster consiste en crear una herramienta software capaz de monitorizar y gestionar la actividad de Hydra, una herramienta de gestión de entornos distribuidos, para que su estrategia de balanceo de carga se adecúe al modelo creado por GloBeM, una metodología de análisis de entornos distribuidos. GloBeM, que es una metodología externa, puede analizar y crear un modelo de máquina de estados finitos a partir de un sistema distribuido concreto. Hydra, una herramienta también externa, es un sistema de gestión de entornos cloud recientemente desarrollado y de código abierto, con un sistema de balanceo de carga efectivo pero algo limitado. El software construido recoge el modelo creado por GloBeM y lo analiza. A partir de ahí, monitoriza en tiempo real y a una frecuencia determinada la actividad de Hydra y el sistema cloud que ésta gestiona, y reconfigura sus parámetros para que su desempeño se ciña a lo estipulado por el modelo de GloBeM, extendiendo así el sistema de balanceo de carga original de Hydra.---ABSTRACT---This Master's Thesis Project involves creating a software able to monitor and manage the activity of Hydra, a tool for managing distributed environments, in order to adjust its load balancing strategy to the model created by GloBeM, an analysis methodology for distributed environments. GloBeM, which is an external methodology, can analyse and create a finite-state machine model from a particular cloud system. Hydra, also an external tool, is an open source management system for cloud environments recently developed, with a relatively limited system of load balancing. The created software gets the model created by GloBeM as an input and analyses it. From there, it monitors in real time and at a certain frequency Hydra’s activity and the cloud system that it manages, and reconfigures its parameters to adjust its performance to the stipulations by the GloBeM’s model, extending Hydra's original load balancing system.

Submodular Optimization and Data Processing

Thesis (Ph.D.)--University of Washington, 2016-06

Ensuring efficiency and robustness in MANET

This paper introduces a joint load balancing and hotspot mitigation protocol for mobile ad-hoc network (MANET) termed by us as 'load_energy balance + hotspot mitigation protocol (LEB+HM)'. We argue that although ad-hoc wireless networks have limited network resources - bandwidth and power, prone to frequent link/node failures and have high security risk; existing ad hoc routing protocols do not put emphasis on maintaining robust link/node, efficient use of network resources and on maintaining the security of the network. Typical route selection metrics used by existing ad hoc routing protocols are shortest hop, shortest delay, and loop avoidance. These routing philosophy have the tendency to cause traffic concentration on certain regions or nodes, leading to heavy contention, congestion and resource exhaustion which in turn may result in increased end-to-end delay, packet loss and faster battery power depletion, degrading the overall performance of the network. Also in most existing on-demand ad hoc routing protocols intermediate nodes are allowed to send route reply RREP to source in response to a route request RREQ. In such situation a malicious node can send a false optimal route to the source so that data packets sent will be directed to or through it, and tamper with them as wish. It is therefore desirable to adopt routing schemes which can dynamically disperse traffic load, able to detect and remove any possible bottlenecks and provide some form of security to the network. In this paper we propose a combine adaptive load_energy balancing and hotspot mitigation scheme that aims at evenly distributing network traffic load and energy, mitigate against any possible occurrence of hotspot and provide some form of security to the network. This combine approach is expected to yield high reliability, availability and robustness, that best suits any dynamic and scalable ad hoc network environment. Dynamic source routing (DSR) was use as our underlying protocol for the implementation of our algorithm. Simulation comparison of our protocol to that of original DSR shows that our protocol has reduced node/link failure, even distribution of battery energy, and better network service efficiency.

Evolutionary market agents for resource allocation in decentralised systems

We introduce self-interested evolutionary market agents, which act on behalf of service providers in a large decentralised system, to adaptively price their resources over time. Our agents competitively co-evolve in the live market, driving it towards the Bertrand equilibrium, the non-cooperative Nash equilibrium, at which all sellers charge their reserve price and share the market equally. We demonstrate that this outcome results in even load-balancing between the service providers. Our contribution in this paper is twofold; the use of on-line competitive co-evolution of self-interested service providers to drive a decentralised market towards equilibrium, and a demonstration that load-balancing behaviour emerges under the assumptions we describe. Unlike previous studies on this topic, all our agents are entirely self-interested; no cooperation is assumed. This makes our problem a non-trivial and more realistic one.

Dynamic Distribution Simulation Model Objects Based on Knowledge

This paper presents the process of load balancing in simulation system Triad.Net, the architecture of load balancing subsystem. The main features of static and dynamic load balancing are discussed and new approach, controlled dynamic load balancing, needed for regular mapping of simulation model on the network of computers is proposed. The paper considers linguistic constructions of Triad language for different load balancing algorithms description.