Tag Archives: scientific

Accelerating Network Measurement in Software

Yang ZhouOmid Alipourfard, Minlan YuTong Yang
Abstract

Network measurement plays an important role for many network functions such as detecting network anomalies and identifying big flows. However, most existing measurement solutions fail to achieve high performance in software as they often incorporate heavy computations and a large number of random memory accesses. We present Agg-Evict, a generic framework for accelerating network measurement in software. Agg-Evict aggregates the incoming packets on the same flows and sends them as a batch, reducing the number of computations and random memory accesses in the subsequent measurement solutions. We perform extensive experiments on top of DPDK with 10G NIC and observe that almost all the tested measurement solutions under Agg-Evict can achieve 14.88 Mpps throughput and see up to 5.7× lower average processing latency per packet.

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Looking for Hypergiants in PeeringDB

Timm Böttger, Felix Cuadrado, Steve Uhlig
Abstract

Hypergiants, such as Google or Netflix, are important organisations in the Internet ecosystem, due to their sheer impact in terms of traffic volume exchanged. However, the research community still lacks a sufficiently crisp definition for them, beyond naming specific instances of them. In this paper we analyse PeeringDB data and identify features that differentiate hypergiants from the other organisations. To this end, we first characterise the organisations present in PeeringDB, allowing us to identify discriminating properties of these organisations. We then use these properties to separate the data in two clusters, differentiating hypergiants from other organisations. We conclude this paper by investigating how hypergiants and other organisations exploit the IXP ecosystem to reach the global IPv4 space.

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Practical Challenge-Response for DNS

Rami Al-Dalky, Michael RabinovichMark Allman
Abstract

Authoritative DNS servers are susceptible to being leveraged in denial of service attacks in which the attacker sends DNS queries while masquerading as a victim—and hence causing the DNS server to send the responses to the victim. This reflection off innocent DNS servers hides the attackers identity and often allows the attackers to amplify their traffic by employing small requests to elicit large responses. Several challenge-response techniques have been proposed to establish a requester’s identity before sending a full answer. However, none of these are practical in that they do not work in the face of “resolver pools”—or groups of DNS resolvers that work in concert to lookup records in the DNS. In these cases a challenge transmitted to some resolver R1 may be handled by a resolver R2, hence leaving an authoritative DNS server wondering whether R2 is in fact another resolver in the pool or a victim. We offer a practical challenge-response mechanism that uses challenge chains to establish identity in the face of resolver pools. We illustrate that the practical cost of our scheme in terms of added delay is small.

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On the Evolution of ndnSIM: an Open-Source Simulator for NDN Experimentation

Spyridon Mastorakis, Alexander Afanasyev, Lixia Zhang.
Abstract

As a proposed Internet architecture, Named Data Networking (NDN) takes a fundamental departure from today’s TCP/IP architecture, thus requiring extensive experimentation and evaluation. To facilitate such experimentation, we have developed ndnSIM, an open-source NDN simulator based on the NS-3 simulation framework. Since its first release in 2012, ndnSIM has gone through five years of active development and integration with the NDN prototype implementations, and has become a popular platform used by hundreds of researchers around the world. This paper presents an overview of the ndnSIM design, the ndnSIM development process, the design tradeoffs, and the reasons behind the design decisions. We also share with the community a number of lessons we have learned in the process.

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Geohyperbolic Routing and Addressing Schemes

Ivan Voitalov, Rodrigo Aldecoa, Lan Wang, Dmitri Krioukov.
Abstract

The key requirement to routing in any telecommunication network, and especially in Internet-of-Things (IoT) networks, is scalability. Routing must route packets between any source and destination in the network without incurring unmanageable routing overhead that grows quickly with increasing network size and dynamics. Here we present an addressing scheme and a coupled network topology design scheme that guarantee essentially optimal routing scalability. The FIB sizes are as small as they can be, equal to the number of adjacencies a node has, while the routing control overhead is minimized as nearly zero routing control messages are exchanged even upon catastrophic failures in the network. The key new ingredient is the addressing scheme, which is purely local, based only on geographic coordinates of nodes and a centrality measure, and does not require any sophisticated non-local computations or global network topology knowledge for network embedding. The price paid for these benefits is that network topology cannot be arbitrary but should follow a specific design, resulting in Internet-like topologies. The proposed schemes can be most easily deployed in overlay networks, and also in other network deployments, where geolocation information is available, and where network topology can grow following the design specifications.

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Knowledge-Defined Networking

Albert Mestres, Alberto Rodriguez-Natal, Josep Carner, Pere Barlet-Ros, Eduard Alarcón, Marc Solé, Victor Muntés-Mulero, David Meyer, Sharon Barkai, Mike J. Hibbett, Giovani Estrada, Khaldun Ma, Florin Coras, Vina Ermagan, Hugo Latapie, Chris Cassar, John Evans, Fabio Maino, Jean Walrand.
Abstract

The research community has considered in the past the application of Artificial Intelligence (AI) techniques to control and operate networks. A notable example is the Knowledge Plane proposed by D.Clark et al. However, such techniques have not been extensively prototyped or deployed in the field yet. In this paper, we explore the reasons for the lack of adoption and posit that the rise of two recent paradigms: Software-Defined Networking (SDN) and Network Analytics (NA), will facilitate the adoption of AI techniques in the context of network operation and control. We describe a new paradigm that accommodates and exploits SDN, NA and AI, and provide use-cases that illustrate its applicability and benefits. We also present simple experimental results that support, for some relevant use-cases, its feasibility. We refer to this new paradigm as Knowledge-Defined Networking (KDN).

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A Techno-Economic Approach for Broadband Deployment in Underserved Areas

Ramakrishnan Durairajan, Paul Barford
Abstract

A large body of economic research has shown the strong correlation between broadband connectivity and economic productivity. These findings motivate government agencies such as the FCC in the US to provide incentives to services providers to deploy broadband infrastructure in unserved or underserved areas. In this paper, we describe a framework for identifying target areas for network infrastructure deployment. Our approach considers (i) infrastructure availability, (ii) user demographics, and (iii) deployment costs. We use multi-objective optimization to identify geographic areas that have the highest concentrations of un/underserved users and that can be upgraded at the lowest cost. To demonstrate the efficacy of our framework, we consider physical infrastructure and demographic data from the US and two different deployment cost models. Our results identify a list of counties that would be attractive targets for broadband deployment from both cost and impact perspectives. We conclude with discussion on the implications and broader applications of our framework.
Download the full article DOI: 10.1145/3089262.3089265

Principles for Measurability in Protocol Design

Mark Allman, Robert Beverly, Brian Trammell
Abstract

Measurement has become fundamental to the operation of networks and at-scale services—whether for management, security, diagnostics, optimization, or simply enhancing our collective understanding of the Internet as a complex system. Further, measurements are useful across points of view—from end hosts to enterprise networks and data centers to the wide area Internet. We observe that many measurements are decoupled from the protocols and applications they are designed to illuminate. Worse, current measurement practice often involves the exploitation of side-effects and unintended features of the network; or, in other words, the artful piling of hacks atop one another. This state of affairs is a direct result of the relative paucity of diagnostic and measurement capabilities built into today’s network stack.

Given our modern dependence on ubiquitous measurement, we propose measurability as an explicit low-level goal of current protocol design, and argue that measurements should be available to all network protocols throughout the stack. We seek to generalize the idea of measurement within protocols, e.g., the way in which TCP relies on measurement to drive its end-to-end behavior. Rhetorically, we pose the question: what if the stack had been built with measurability and diagnostic support in mind? We start from a set of principles for explicit measurability, and define primitives that, were they supported by the stack, would not only provide a solid foundation for protocol design going forward, but also reduce the cost and increase the accuracy of measuring the network.
Download the full article DOI: 10.1145/3089262.3089264

Exploring Domain Name Based Features on the Effectiveness of DNS Caching

Shuai Hao, Haining Wang.
Abstract

DNS cache plays a critical role in domain name resolution, providing (1) high scalability at Root and Top-level-domain (TLD) name servers with reduced workloads and (2) low response latency to clients when the resource records of the queried domains are cached. However, the pervasive misuses of domain names, e.g., the domains of “one-time-use” pattern, have negative impact on the effectiveness of DNS caching as the cache has been filled with those entries that are highly unlikely to be retrieved. In this paper, we investigate such misuse and identify domain name-based features to characterize those one-time domains. By leveraging the features that are explicitly available from the domain name itself, we build a classifier to combine these features, propose simple policy modifications on caching resolvers for improving DNS cache performance, and validate their efficacy using real traces.

Download the full article DOI: 10.1145/3041027.3041032