Hierarchical Content Stores in High-speed ICN Routers: Emulation and Prototype Implementation

Recent work motivates the design of Information-centric rou-ters that make use of hierarchies of memory to jointly scale in the size and speed of content stores. The present paper advances this understanding by (i) instantiating a general purpose two-layer packet-level caching system, (ii) investigating the solution design space via emulation, and (iii) introducing a proof-of-concept prototype. The emulation-based study reveals insights about the broad design space, the expected impact of workload, and gains due to multi-threaded execution. The full-blown system prototype experimentally confirms that, by exploiting both DRAM and SSD memory technologies, ICN routers can sustain cache operations in excess of 10Gbps running on off-the-shelf hardware

Paralelizando unidades de cache hierárquicas para roteadores ICN

Um desafio fundamental em ICN (do inglês Information-Centric Networking) é desenvolver Content Stores (ou seja, unidades de cache) que satisfaçam três requisitos: espaço de armazenamento grande, velocidade de operação rápida e custo acessível. A chamada Hierarchical Content Store (HCS) é uma abordagem promissora para atender a esses requisitos. Ela explora a correlação temporal entre requisições para prever futuras solicitações. Por exemplo, assume-se que um usuário que solicita o primeiro minuto de um filme também solicitará o segundo minuto. Teoricamente, essa premissa permitiria transferir proativamente conteúdos de uma área de cache relativamente grande, mas lenta (Layer 2 - L2), para uma área de cache mais rápida, porém menor (Layer 1 - L1). A estrutura hierárquica tem potencial para incrementar o desempenho da CS em uma ordem de grandeza tanto em termos de vazão como de tamanho, mantendo o custo. Contudo, o desenvolvimento de HCS apresenta diversos desafios práticos. É necessário acoplar as hierarquias de memória L2 e L1 considerando as suas taxas de transferência e tamanhos, que dependem tanto de aspectos de hardware (por exemplo, taxa de leitura da L2, uso de múltiplos SSD físicos em paralelo, velocidade de barramento, etc.), como de software (por exemplo, controlador do SSD, gerenciamento de memória, etc.). Nesse contexto, esta tese apresenta duas contribuições principais. Primeiramente, é proposta uma arquitetura para superar os gargalos inerentes ao sistema através da paralelização de múltiplas HCS. Em resumo, o esquema proposto supera desafios inerentes à concorrência (especificamente, sincronismo) através do particionamento determinístico das requisições de conteúdos entre múltiplas threads. Em segundo lugar, é proposta uma metodologia para investigar o desenvolvimento de HCS explorando técnicas de emulação e modelagem analítica conjuntamente. A metodologia proposta apresenta vantagens em relação a metodologias baseadas em prototipação e simulação. A L2 é emulada para viabilizar a investigação de uma variedade de cenários de contorno (tanto em termos de hardware como de software) maior do que seria possível através de prototipação (considerando as tecnologias atuais). Além disso, a emulação emprega código real de um protótipo para os outros componentes do HCS (por exemplo L1, gerência das camadas e API) para fornecer resultados mais realistas do que seriam obtidos através de simulação.A key challenge in Information Centric Networking (ICN) is to develop cache units (also called Content Store - CS) that meet three requirements: large storage space, fast operation, and affordable cost. The so-called HCS (Hierarchical Content Store) is a promising approach to satisfy these requirements jointly. It explores the correlation between content requests to predict future demands. Theoretically, this idea would enable proactively content transfers from a relatively large but slow cache area (Layer 2 - L2) to a faster but smaller cache area (Layer 1 - L1). Thereby, it would be possible to increase the throughput and size of CS in one order of magnitude, while keeping the cost. However, the development of HCS introduces several practical challenges. HCS requires a careful coupling of L2 and L1 memory levels considering their transfer rates and sizes. This requirement depends on both hardware specifications (e.g., read rate L2, use of multiple physical SSD in parallel, bus speed, etc.), and software aspects (e.g., the SSD controller, memory management, etc.). In this context, this thesis presents two main contributions. First, we propose an architecture for overcoming the HCS bottlenecks by parallelizing multiple HCS. In summary, the proposed scheme overcomes racing condition related challenges through deterministic partitioning of content requests among multiple threads. Second, we propose a methodology to investigate the development of HCS exploiting emulation techniques and analytical modeling jointly. The proposed methodology offers advantages over prototyping and simulation-based methods. We emulate the L2 to enable the investigation of a variety of boundary scenarios that are richer (regarding both hardware and software aspects) than would be possible through prototyping (considering current technologies). Moreover, the emulation employs real code from a prototype for the other components of the HCS (e.g., L1, layers management and API) to provide more realistic results than would be obtained through simulation

Data Structures and Algorithms for Scalable NDN Forwarding

Named Data Networking (NDN) is a recently proposed general-purpose network architecture that aims to address the limitations of the Internet Protocol (IP), while maintaining its strengths. NDN takes an information-centric approach, focusing on named data rather than computer addresses. In NDN, the content is identified by its name, and each NDN packet has a name that specifies the content it is fetching or delivering. Since there are no source and destination addresses in an NDN packet, it is forwarded based on a lookup of its name in the forwarding plane, which consists of the Forwarding Information Base (FIB), Pending Interest Table (PIT), and Content Store (CS). In addition, as an in-network caching element, a scalable Repository (Repo) design is needed to provide large-scale long-term content storage in NDN networks. Scalable NDN forwarding is a challenge. Compared to the well-understood approaches to IP forwarding, NDN forwarding performs lookups on packet names, which have variable and unbounded lengths, increasing the lookup complexity. The lookup tables are larger than in IP, requiring more memory space. Moreover, NDN forwarding has a read-write data plane, requiring per-packet updates at line rates. Designing and evaluating a scalable NDN forwarding node architecture is a major effort within the overall NDN research agenda. The goal of this dissertation is to demonstrate that scalable NDN forwarding is feasible with the proposed data structures and algorithms. First, we propose a FIB lookup design based on the binary search of hash tables that provides a reliable longest name prefix lookup performance baseline for future NDN research. We have demonstrated 10 Gbps forwarding throughput with 256-byte packets and one billion synthetic forwarding rules, each containing up to seven name components. Second, we explore data structures and algorithms to optimize the FIB design based on the specific characteristics of real-world forwarding datasets. Third, we propose a fingerprint-only PIT design that reduces the memory requirements in the core routers. Lastly, we discuss the Content Store design issues and demonstrate that the NDN Repo implementation can leverage many of the existing databases and storage systems to improve performance

On the design of efficient caching systems

Content distribution is currently the prevalent Internet use case, accounting for the majority of global Internet traffic and growing exponentially. There is general consensus that the most effective method to deal with the large amount of content demand is through the deployment of massively distributed caching infrastructures as the means to localise content delivery traffic. Solutions based on caching have been already widely deployed through Content Delivery Networks. Ubiquitous caching is also a fundamental aspect of the emerging Information-Centric Networking paradigm which aims to rethink the current Internet architecture for long term evolution. Distributed content caching systems are expected to grow substantially in the future, in terms of both footprint and traffic carried and, as such, will become substantially more complex and costly. This thesis addresses the problem of designing scalable and cost-effective distributed caching systems that will be able to efficiently support the expected massive growth of content traffic and makes three distinct contributions. First, it produces an extensive theoretical characterisation of sharding, which is a widely used technique to allocate data items to resources of a distributed system according to a hash function. Based on the findings unveiled by this analysis, two systems are designed contributing to the abovementioned objective. The first is a framework and related algorithms for enabling efficient load-balanced content caching. This solution provides qualitative advantages over previously proposed solutions, such as ease of modelling and availability of knobs to fine-tune performance, as well as quantitative advantages, such as 2x increase in cache hit ratio and 19-33% reduction in load imbalance while maintaining comparable latency to other approaches. The second is the design and implementation of a caching node enabling 20 Gbps speeds based on inexpensive commodity hardware. We believe these contributions advance significantly the state of the art in distributed caching systems