Datacenters have traditionally been architected as a collection of servers wherein each server aggregates a fixed amount of computing, memory, storage, and communication resources. In this paper, we advocate an alternative construction in which the resources within a server are disaggregated and the datacenter is instead architected as a collection of standalone resources.

The applications of the Internet have evolved from being host-centric to being more content-oriented, such as file sharing, online audio and video applications, which constitute the majority of Internet traffic [1]. Several future Internet architectures, putting the content (or information) in the fore-front, have lately been proposed in order to solve the limitations of the current architecture (i.e. insufficient bandwidth to servers, lack of security, mobility, virtualization, user/data centricity, etc.). However, one of the greatest challenges of a novel content-oriented Internet architecture lies in the complexity of looking up long, variable length names compared to the current 32 bit long IPv4 (or even 128 bit IPv6) addresses of today's networks. The success of widely adopting any content-oriented architecture highly depends on the success of designing algorithms that allow these complex names to be looked up at high-speed. Ternary Content Addressable Memories (TCAMs) are widely used in high-speed routers to find matching routes for packets in a routing table. They enable the longest prefix matching (LPM) operation on fixed length addresses to complete in a single clock cycle, however, they are not efficient to store and lookup name prefixes with variable lengths such as the ones proposed in name-based routing [2]-[9]. In this paper, we propose an efficient name-based longest prefix matching algorithm for information-centric networks using TCAMs. In our algorithm, we split incoming prefixes in fixed blocks and subsequently hash these blocks for fixed length storage. Our approach is flexible to support both hierarchical name based routing lookup and flat name based routing lookup. In addition, our approach can be easily modified to support multiple matchings instead of the longest prefix matching. The simulation results demonstrate that our approach is able to provide efficient name-based routing lookup even for the fastest backbone routers (i.e. 100+ Gbps).

Most network deployments respond to changing application, workload, and policy requirements via the deployment of specialized network appliances or "middleboxes". Despite the critical role that middleboxes play in introducing new network functionality, they have been surprisingly ignored in recent efforts for designing networks that are amenable to innovation. We make the case that enabling innovation in middleboxes is at least as important, if not more important, as that for traditional switches and routers. To this end, our vision is a world with software-centric middlebox implementations running on general-purpose hardware platforms that are managed via open and extensible management APIs. While these principles have been applied in other contexts, they introduce unique opportunities and challenges in the context of middleboxes that we highlight in this paper.

Recent technological advances in commodity server architectures, with multiple multi-core CPUs, integrated memory controllers, high-speed interconnects and enhanced network interface cards, provide substantial computational capacity and thus an attractive platform for packet forwarding. However, to exploit this available capacity, we need a suitable software platform that allows effective parallel packet processing and resource management. In this paper, we at first introduce an improved forwarding architecture for software routers that enhances parallelism by exploiting hardware classification and multi-queue support, already available in recent commodity network interface cards. After evaluating the original scheduling algorithm of the widely-used Click modular router, we propose solutions for extending this scheduler for improved fairness, throughput and more precise resource management. To illustrate the potential benefits of our proposal, we implement and evaluate a few key elements of our overall design.

We revisit the problem of scaling software routers, motivated by recent advances in server technology that enable high-speed parallel processing--a feature router workloads appear ideally suited to exploit. We propose a software router architecture that parallelizes router functionality both across multiple servers and across multiple cores within a single server. By carefully exploiting parallelism at every opportunity, we demonstrate a 35Gbps parallel router prototype; this router capacity can be linearly scaled through the use of additional servers. Our prototype router is fully programmable using the familiar Click/Linux environment and is built entirely from off-the-shelf, general-purpose server hardware.

Modern commodity hardware architectures, with their multiple multi-core CPUs and high-speed system interconnects, exhibit tremendous power. In this paper, we study performance limitations when building both software routers and software virtual routers on such systems. We show that the fundamental performance bottleneck is currently the memory system, and that through careful mapping of tasks to CPU cores, we can achieve forwarding rates of 7 million minimum-sized packets per second on mid-range server-class systems, thus demonstrating the viability of software routers. We also find that current virtualisation systems, when used to provide forwarding engine virtualisation, yield aggregate performance equivalent to that of a single software router, a tenfold improvement on current virtual router platform performance. Finally, we identify principles for the construction of high-performance software router systems on commodity hardware, including full router virtualisation support.

In this paper, we evaluate the performance of a software IP router forwarding plane inside the Xen virtual machine monitor environment with a view to identifying (some) design issues in Virtual Routers. To this end, we evaluate and compare the forwarding performance of two identical Linux software router configurations, run either above the Xen hypervisor or within vanilla Linux. Even with minimal sized packets, we show that the Xen DomO privileged domain offers near native forwarding performance at the condition that the sollicitation to unpriviledged domains stay minimal, whereas Xen unprivileged domains offer very poor performance in every cases. This shows that an important design principle for virtual router platforms must be to handle all forwarding, for all virtual routers, onto the same forwarding engine, in order to avoid much detrimental per-packet context switching.

In this paper, we present a thorough and realistic analysis of voice (i.e. audio conferencing) over application-level multicast (ALM). Through flexibility and ease-of-deployment, ALM is a compelling alternative group-communication technique to IP multicast-which has yet to see wide-scale deployment in the Internet. However, proposed ALM techniques suffer from inherent latency inefficiencies, which we show, through realistic simulation and exploration of perceived quality in multi-party conversation, to be greatly problematic for the realisation of truly-scalable audio-conferencing systems over ALM. By incorporating talkspurt data from a large and detailed corpus of multi-party conversation, and through using network-simulation techniques based on actual Internet latency measurements, we develop our previous work on the application-level network audio-conferencing (ALNAC) routing protocol into a thorough analysis of the problem, leading to a novel model for assessing the perceptual quality of multi-party conversation and to novel techniques for speaker prediction. We show that through adaptation to conversational patterns, the ALNAC protocol can achieve perceptual quality for large-scale audio conferencing that, with little cost to each end-system node, is comparable to IP multicast.