Michele Papalini

Optimal multipath congestion control and request forwarding in Information-Centric Networks

The evolution of the Internet into a distributed Information access system calls for a paradigm shift to enable an evolvable future network architecture. Information-Centric Networking (ICN) proposals rethink the communication model around named data, in contrast with the host-centric transport view of TCP/IP. Information retrieval is natively pull-based, driven by user requests, point-to-multipoint and intrinsically coupled with in-network caching. In this paper, we tackle the problem of joint multipath congestion control and request forwarding in ICN for the first time. We formulate it as a global optimization problem with the twofold objective of maximizing user throughput and minimizing overall network cost. We solve it via decomposition and derive a family of optimal congestion control strategies at the receiver and of distributed algorithms for dynamic request forwarding at network nodes. An experimental evaluation of our proposal is carried out in different network scenarios to assess the performance of our design and to highlight the benefits of an ICN approach.

Content-based publish/subscribe networking and information-centric networking

On-line information comes in different forms and is accessed in different ways and for different purposes. For example, a recording of Beethovens Ninth Symphony differs from a storm warning from the local weather service. Beethovens Ninth is a large media file with perpetual validity that is typically accessed on demand by users. By contrast, a storm warning is a small ephemeral message typically pushed by the weather service to all users in a specific geographic area. We argue that both should and would be well supported by an information-centric network. More specifically we argue three points. First, modern applications, reflecting the nature of human communications, use and transmit large and long-lived files as well as small ephemeral messages. Second, accessing those two types of information involves significantly different operations within the network. Third, despite their differences, both types of information would benefit from an addressing scheme based on content rather than on more or less flat identifiers, which means that both should be integrated to some extent within a unified content-based routing infrastructure.

Scalable routing for tag-based information-centric networking

Routing in information-centric networking remains an open problem. The main issue is scalability. Traditional IP routing can be used with name prefixes, but it is believed that the number of prefixes will grow too large. A related problem is the use of per-packet in-network state (to cut loops and return data to consumers). We develop a routing scheme that solves these problems. The service model of our information-centric network supports information pull and push using tag sets as information descriptors. Within this service model, we propose a routing scheme that supports forwarding along multiple loop-free paths, aggregates addresses for scalability, does not require per-packet network state, and leads to near-optimal paths on average. We evaluate the scalability of our routing scheme, both in terms of memory and computational complexity, on the full Internet AS-level topology and on the internal networks of representative ASes using realistic distributions of content and users extrapolated from traces of popular applications. For example, a population of 500 million users requires a routing information base of 3.8GB with an almost flat growth and, in this case, a routing update (one content descriptor) can be processed in 2ms on commodity hardware. We conclude that information-centric networking is feasible, even with (or perhaps thanks to) addresses consisting of expressive content descriptors.

Dynamic Adaptive Video Streaming: Towards a Systematic Comparison of ICN and TCP/IP

Streaming of video content over the Internet is experiencing an unprecedented growth. While video permeates every application, it also puts tremendous pressure in the network—to support users having heterogeneous accesses and expecting a high quality of experience, in a furthermore cost-effective manner. In this context, future internet paradigms, such as information centric networking (ICN), are particularly well suited to not only enhance video delivery at the client (as in the dynamic adaptive streaming over HTTP (DASH) approach), but to also naturally and seamlessly extend video support deeper in the network functions. In this paper, we contrast ICN and transmission control protocol/internet protocol (TCP/IP) with an experimental approach, where we employ several state-of-the-art DASH controllers (PANDA, AdapTech, and BOLA) on an ICN versus TCP/IP network stack. Our campaign, based on tools that we developed and made available as open-source software, includes multiple clients (homogeneous vesrus heterogeneous mixture and synchronous vesrus asynchronous arrivals), videos (up to 4k resolution), channels (e.g., DASH profiles, emulated WiFi and LTE, and real 3G/4G traces), and levels of integration with an ICN network (i.e., vanilla named data networking (NDN), wireless loss detection and recovery at the access point, and load balancing). Our results clearly illustrate, as well as quantitatively assess, the benefits of ICN-based streaming, warning about potential pitfalls that are however easy to avoid.

Leveraging ICN In-network Control for Loss Detection and Recovery in Wireless Mobile networks

One of the most appealing features of Information-Centric Networking (ICN) is its agile connectionless transport model based on consumer requests and hop-by-hop forwarding. By relaxing end-to-end constraints, ICN empowers a distributed in-network control with the potential to improve congestion management over heterogeneous wired/wireless media and in presence of mobility. However, little effort has been devoted so far to the exploration of ICN capabilities in this space. In this paper, we contribute an understanding of the opportunities for ICN in-network control over wireless mobile networks and a proposal for simple, yet very effective mechanisms for in-network loss detection and recovery to complement receiver-driven control. More precisely, we introduce (i) WLDR, a mechanism for in-network Wireless Loss Detection and Recovery that promptly identifies and recovers channel losses at wireless access point and (ii) MLDR, a mechanism for preventing losses due to consumer/producer mobility via explicit network notification and dynamic on-the-fly request re-routing. We setup a realistic wireless simulation environment in ndn-SIM using IEEE 802.11n connectivity and evaluate WLDR-MLDR performance. The results show significant benefits over consumer-based solutions with or without explicit loss notification, while also removing any dependency from network and application timers.

Fully decentralized estimation of some global properties of a network

It is often beneficial to architect networks and overlays as fully decentralized systems, in the sense that any computation (e.g., routing or search) would only use local information, and no single node would have a complete view or control over the whole network. Yet sometimes it also important to compute global properties of the network. In this paper we propose a fully decentralized algorithm to compute some global properties that can be derived from the spectrum of the network. More specifically, we compute the most significant eigenvalues of a descriptive matrix closely related to the adjacency matrix of the network graph. Such spectral properties can then lead to, for example, the “mixing time” of a network, which can be used to parametrize random walks and related search algorithms typical of peer-to-peer networks. Our key insight is to view the network as a linear dynamic system whose impulse response can be computed efficiently and locally by each node. We then use this impulse response to identify the spectral properties of the network. This algorithm is completely decentralized and requires only minimal local state and local communication. We show experimentally that the algorithm works well on different kinds of networks and in the presence of network instability.

High Throughput Forwarding for ICN with Descriptors and Locators

Application-defined and location-independent addressing is a founding principle of information centric networking (ICN) that is inherently difficult to realize if one also wants scalable routing and forwarding. We propose an ICN architecture, called TagNet, intended to combine expressive application-defined addressing with scalable routing and forwarding. TagNet features two independent delivery services: one with application-defined and possibly location-independent content descriptors, and one with network-defined host locators. In this paper we develop and evaluate specialized forwarding algorithms for TagNet. We then implement and combine these algorithms in a forwarding engine built on a general-purpose commodity CPU, and show experimentally that, thanks to the dual addressing, by descriptor or by locator, this engine can achieve a throughput of over 20Gbps with large forwarding tables corresponding to hundreds of millions of users.

High-Throughput Subset Matching on Commodity GPU-Based Systems

Large-scale information processing often relies on subset matching for data classification and routing. Examples are publish/subscribe and stream processing systems, database systems, social media, and information-centric networking. For instance, an advanced Twitter-like messaging service where users might follow specific publishers as well as specific topics encoded as tag sets must join a stream of published messages with the users and their preferred tag sets so that the user tag set is a subset of the message tags. Subset matching is an old but also notoriously difficult problem. We present TagMatch, a system that solves this problem by taking advantage of a hybrid CPU/GPU stream processing architecture. TagMatch targets large-scale applications with thousands of matching operations per seconds against hundreds of millions of tag sets. We evaluate TagMatch on an advanced message streaming application, with very positive results both in absolute terms and in comparison with existing systems. As a notable example, our experiments demonstrate that TagMatch running on a single, commodity machine with two GPUs can easily sustain the traffic throughput of Twitter even augmented with expressive tag-based selection.

Enhancing Mobile Video Delivery over an Heterogeneous Network Access with Information-Centric Networking

Mobile video delivery drives Internet traffic evolution and puts colossal pressure on future 5G networks to support higher quality and lower latency requirements over an increasingly heterogeneous network access. Future Internet paradigms recentering communication around content, such as Information Centric Networks (ICN), appear as promising candidates to relieve the challenges of a mobility-robust, efficient and cost-effective video delivery, by integrating video-awareness at network layer. In this demo, we focus on ICN-enabled Dynamic Adaptive Streaming (DAS) over an heterogeneous wireless access. We integrate ICN capabilities in DAS clients requesting 4K video content to standard DAS servers. We deploy a virtualized ICN-enabled network slice using LXC containers to connect clients to servers through an heterogeneous wireless access (802.11n and LTE emulated radios) and a simplified backhaul. The contribution of the demo is twofold. First it showcases what ICN can bring to DAS over a mobile heterogeneous access in virtue of its content-awareness at network layer. Second, it offers to the user a rich sandbox where several state-of-the-art DAS controllers are implemented and can be tested over ICN or standard TCP.