DOH: A Content Delivery Peer-to-Peer Network

Many SMEs and non-pro¯t organizations su®er when their Web servers become unavailable due to °ash crowd e®ects when their web site becomes popular. One of the solutions to the °ash-crowd problem is to place the web site on a scalable CDN (Content Delivery Network) that replicates the content and distributes the load in order to improve its response time. In this paper, we present our approach to building a scalable Web Hosting environment as a CDN on top of a structured peer-to-peer system of collaborative web-servers integrated to share the load and to improve the overall system performance, scalability, availability and robustness. Unlike clusterbased solutions, it can run on heterogeneous hardware, over geographically dispersed areas. To validate and evaluate our approach, we have developed a system prototype called DOH (DKS Organized Hosting) that is a CDN implemented on top of the DKS (Distributed K-nary Search) structured P2P system with DHT (Distributed Hash table) functionality [9]. The prototype is implemented in Java, using the DKS middleware, the Jetty web-server, and a modi¯ed JavaFTP server. The proposed design of CDN has been evaluated by simulation and by evaluation experiments on the prototype

Building Robust Distributed Infrastructure Networks

Many competing designs for Distributed Hash Tables exist exploring multiple models of addressing, routing and network maintenance. Designing a general theoretical model and implementation of a Distributed Hash Table allows exploration of the possible properties of Distributed Hash Tables. We will propose a generalized model of DHT behavior, centered on utilizing Delaunay triangulation in a given metric space to maintain the networks topology. We will show that utilizing this model we can produce network topologies that approximate existing DHT methods and provide a starting point for further exploration. We will use our generalized model of DHT construction to design and implement more efficient Distributed Hash Table protocols, and discuss the qualities of potential successors to existing DHT technologies

Search strategies in unstructured overlays

Trabalho de projecto de mestrado em Engenharia Informática, apresentado à Universidade de Lisboa, através da Faculdade de Ciências, 2008Unstructured peer-to-peer networks have a low maintenance cost, high resilience and tolerance to the continuous arrival and departure of nodes. In these networks search is usually performed by flooding, which generates a high number of duplicate messages. To improve scalability, unstructured overlays evolved to a two-tiered architecture where regular nodes rely on special nodes, called supernodes or superpeers, to locate resources, thus reducing the scope of flooding based searches. While this approach takes advantage of node heterogeneity, it makes the overlay less resilient to accidental and malicious faults, and less attractive to users concerned with the consumption of their resources and who may not desire to commit additional resources that are required by nodes selected as superpeers. Another point of concern is churn, defined as the constant entry and departure of nodes. Churn affects both structured and unstructured overlay networks and, in order to build resilient search protocols, it must be taken into account. This dissertation proposes a novel search algorithm, called FASE, which combines a replication policy and a search space division technique to achieve low hop counts using a small number of messages, on unstructured overlays with nonhierarquical topologies. The problem of churn is mitigated by a distributed monitoring algorithm designed with FASE in mind. Simulation results validate FASE efficiency when compared to other search algorithms for peer-to-peer networks. The evaluation of the distributed monitoring algorithm shows that it maintains FASE performance when subjected to churn.Os sistemas peer-to-peer, como aplicações de partilha e distribuição de conteúdos ou voz-sobre-IP, são construídos sobre redes sobrepostas. Redes sobrepostas são redes virtuais que existem sobre uma rede subjacente, em que a topologia da rede sobreposta não tem de ter uma correspondência com a topologia da rede subjacente. Ao contrário das suas congéneres estruturadas, as redes sobrepostas não-estru-turadas não restringem a localização dos seus participantes, ou seja, não limitam a escolha de vizinhos de um dado nó, o que torna a sua manutenção mais simples. O baixo custo de manutenção das redes sobrepostas não-estruturadas torna estas especialmente adequadas para a construção de sistemas peer-to-peer capazes de tolerar o comportamento dinâmico dos seus participantes, uma vez que estas redes são permanentemente afectadas pela entrada e saída de nós na rede, um fénomeno conhecido como churn. O algoritmo de pesquisa mais comum em redes sobrepostas não-estruturadas consiste em inundar a rede, o que origina uma grande quantidade de mensagens duplicadas por cada pesquisa. A escalabilidade destes algoritmos é limitada porque consomem demasiados recursos da rede em sistemas com muitos participantes. Para reduzir o número de mensagens, as redes sobrepostas não-estruturadas podem ser organizadas em topologias hierárquicas. Nestas topologias alguns nós da rede, chamados supernós, assumem um papel mais importante, responsabilizando-se pela localização de objectos. A utilização de supernós cria novos problemas, como a sua selecção e a dependência da rede de uma pequena percentagem dos nós. Esta dissertação apresenta um novo algoritmo de pesquisa, chamado FASE, criado para operar sobre redes sobrepostas não estruturadas com topologias não-hierárquicas. Este algoritmo combina uma política de replicação com uma técnica de divisão do espaço de procura para resolver pesquisas ao alcançe de um número reduzido de saltos com o menor custo possível. Adicionalmente, o algoritmo procura nivelar a contribuição dos participantes, já que todos contribuem de uma forma semelhante para o desempenho da pesquisa. A estratégia seguida pelo algo- ritmo consiste em dividir tanto os nós da rede como as chaves dos seus conteúdos por diferentes “frequências” e replicar chaves nas respectivas frequências, sem, no entanto, limitar a localização de um nó ou impor uma estrutura à rede ou mesmo aplicar uma definição rígida de chave. Com o objectivo de mitigar o problema do churn, é apresentado um algoritmo de monitorização distribuído para as réplicas originadas pelo FASE. Os algoritmos propostos são avaliados através de simulações, que validam a eficiência do FASE quando comparado com outros algoritmos de pesquisa em redes sobrepostas não-estruturadas. É também demonstrado que o FASE mantém o seu desempenho em redes sob o efeito do churn quando combinado com o algoritmo de monitorização

Routing and caching on DHTS

L'obiettivo della tesi e' quello di analizzare i principali meccanismi di caching e routing implementati oggigiorno nelle DHT piu' utilizzate. In particolare, la nostra analisi mostra come tali meccanismi siano sostanzialmente inefficaci nel garantire un adeguato load balancing tra i peers; le principali cause di questo fenomeno sono individuate nella struttura, eccessivamente rigida, adottata dalle DHT e nella mancanza di correlazione tra meccanismi di routing e di caching. Viene quindi proposto un diverso overlay, organizzato in base a una struttura ipercubica, che permetta di adottare un algoritmo di routing piu' flessibile e di sviluppare due meccanismi di caching e routing strettamente interconnessi. In particolare, l'overlay ottenuto riesce a garantire che ogni nodo subisca un carico al piu' costante, con una taglia di cache costante e una complessita' di routing polilogaritmica nel caso peggior

Multi-dimensional range queries in sensor networks

In many sensor networks, data or events are named by attributes. Many of these attributes have scalar values, so one natural way to query events of interest is to use a multi-dimensional range query. An example is: "List all events whose temperature lies between 50° and 60°, and whose light levels lie between 10 and 15." Such queries are useful for correlating events occurring within the network.In this paper, we describe the design of a distributed index that scalably supports multi-dimensional range queries. Our distributed index for multi-dimensional data (or DIM) uses a novel geographic embedding of a classical index data structure, and is built upon the GPSR geographic routing algorithm. Our analysis reveals that, under reasonable assumptions about query distributions, DIMs scale quite well with network size (both insertion and query costs scale as O(√N)). In detailed simulations, we show that in practice, the insertion and query costs of other alternatives are sometimes an order of magnitude more than the costs of DIMs, even for moderately sized network. Finally, experiments on a small scale testbed validate the feasibility of DIMs

Replica Placement and Location using Distributed Hash Tables

Abstract—Interest in distributed storage is fueled by demand for reliability and resilience combined with decreasing hardware costs. Peer-to-peer storage networks based on distributed hash tables are attractive for their efficient use of resources and result-ing performance. The placement and subsequent efficient location of replicas in such systems remain open problems, especially (1) the requirement to update replicated content, (2) working in the absence of global information, and (3) determination of the locations in a dynamic system without introducing single points of failure. We present and evaluate a novel and versatile technique, replica enumeration, which allows for controlled replication and replica access. The possibility of enumerating and addressing individual replicas allows dynamic updates as well as superior performance without burdening the network with state informa-tion, yet taking advantage of locality information when available. We simulate, analyze, and prove properties of the system, and discuss some applications. I

Content Distribution in P2P Systems

The report provides a literature review of the state-of-the-art for content distribution. The report's contributions are of threefold. First, it gives more insight into traditional Content Distribution Networks (CDN), their requirements and open issues. Second, it discusses Peer-to-Peer (P2P) systems as a cheap and scalable alternative for CDN and extracts their design challenges. Finally, it evaluates the existing P2P systems dedicated for content distribution according to the identied requirements and challenges

Distributed k-ary System: Algorithms for Distributed Hash Tables

This dissertation presents algorithms for data structures called distributed hash tables (DHT) or structured overlay networks, which are used to build scalable self-managing distributed systems. The provided algorithms guarantee lookup consistency in the presence of dynamism: they guarantee consistent lookup results in the presence of nodes joining and leaving. Similarly, the algorithms guarantee that routing never fails while nodes join and leave. Previous algorithms for lookup consistency either suffer from starvation, do not work in the presence of failures, or lack proof of correctness. Several group communication algorithms for structured overlay networks are presented. We provide an overlay broadcast algorithm, which unlike previous algorithms avoids redundant messages, reaching all nodes in O(log n) time, while using O(n) messages, where n is the number of nodes in the system. The broadcast algorithm is used to build overlay multicast. We introduce bulk operation, which enables a node to efficiently make multiple lookups or send a message to all nodes in a specified set of identifiers. The algorithm ensures that all specified nodes are reached in O(log n) time, sending maximum O(log n) messages per node, regardless of the input size of the bulk operation. Moreover, the algorithm avoids sending redundant messages. Previous approaches required multiple lookups, which consume more messages and can render the initiator a bottleneck. Our algorithms are used in DHT-based storage systems, where nodes can do thousands of lookups to fetch large files. We use the bulk operation algorithm to construct a pseudo-reliable broadcast algorithm. Bulk operations can also be used to implement efficient range queries. Finally, we describe a novel way to place replicas in a DHT, called symmetric replication, that enables parallel recursive lookups. Parallel lookups are known to reduce latencies. However, costly iterative lookups have previously been used to do parallel lookups. Moreover, joins or leaves only require exchanging O(1) messages, while other schemes require at least log(f) messages for a replication degree of f. The algorithms have been implemented in a middleware called the Distributed k-ary System (DKS), which is briefly described

Self-management for large-scale distributed systems

Autonomic computing aims at making computing systems self-managing by using autonomic managers in order to reduce obstacles caused by management complexity. This thesis presents results of research on self-management for large-scale distributed systems. This research was motivated by the increasing complexity of computing systems and their management. In the first part, we present our platform, called Niche, for programming self-managing component-based distributed applications. In our work on Niche, we have faced and addressed the following four challenges in achieving self-management in a dynamic environment characterized by volatile resources and high churn: resource discovery, robust and efficient sensing and actuation, management bottleneck, and scale. We present results of our research on addressing the above challenges. Niche implements the autonomic computing architecture, proposed by IBM, in a fully decentralized way. Niche supports a network-transparent view of the system architecture simplifying the design of distributed self-management. Niche provides a concise and expressive API for self-management. The implementation of the platform relies on the scalability and robustness of structured overlay networks. We proceed by presenting a methodology for designing the management part of a distributed self-managing application. We define design steps that include partitioning of management functions and orchestration of multiple autonomic managers. In the second part, we discuss robustness of management and data consistency, which are necessary in a distributed system. Dealing with the effect of churn on management increases the complexity of the management logic and thus makes its development time consuming and error prone. We propose the abstraction of Robust Management Elements, which are able to heal themselves under continuous churn. Our approach is based on replicating a management element using finite state machine replication with a reconfigurable replica set. Our algorithm automates the reconfiguration (migration) of the replica set in order to tolerate continuous churn. For data consistency, we propose a majority-based distributed key-value store supporting multiple consistency levels that is based on a peer-to-peer network. The store enables the tradeoff between high availability and data consistency. Using majority allows avoiding potential drawbacks of a master-based consistency control, namely, a single-point of failure and a potential performance bottleneck. In the third part, we investigate self-management for Cloud-based storage systems with the focus on elasticity control using elements of control theory and machine learning. We have conducted research on a number of different designs of an elasticity controller, including a State-Space feedback controller and a controller that combines feedback and feedforward control. We describe our experience in designing an elasticity controller for a Cloud-based key-value store using state-space model that enables to trade-off performance for cost. We describe the steps in designing an elasticity controller. We continue by presenting the design and evaluation of ElastMan, an elasticity controller for Cloud-based elastic key-value stores that combines feedforward and feedback control