To be neutral or not neutral? the in-network caching dilemma

Caching allows Internet Service Providers (ISPs) to reduce network traffic and Content Providers (CPs) to increase the offered QoS. However, when contents are encrypted, effective caching is possible only if ISPs and CPs cooperate. We suggest possible forms of non-discriminatory cooperation that make caching compliant with the principles of Net-Neutrality (NN

A Privacy-Preserving Protocol for Network-Neutral Caching in ISP Networks

By performing in-network caching, Internet Service Providers (ISPs) allow Content Providers (CPs) to serve contents from locations closer to users. In this way, the pressure of content delivery on ISPs’ network is alleviated, and the users’ Quality-of-Experience (QoE) improved. Due to its impact on QoE, caching has been recently considered as a form of traffic prioritization in the debate on Network Neutrality (NN). A possible approach to perform NN-compliant caching consists in assigning the same portion of cache storage to all the CPs. However, this static subdivision does not consider the different popularities of the CPs’ contents and is therefore inefficient. Alternatively, the cache can be subdivided among the CPs proportionally to the popularity of their contents. However, CPs consider this information private and are reluctant to disclose it. In this work, we propose a protocol to perform a popularity-driven subdivision of the caches’ storage in a privacy-preserving and network-neutral fashion. The protocol is based on the Shamir Secret Sharing (SSS) scheme and is designed to ensure a NN-compliant subdivision of the caches while preserving the privacy of both CPs and ISP (i.e., contents’ popularity and caches’ size are not disclosed). Through dynamic simulation, we show that the popularity-driven cache subdivision (enforced by using our protocol) outperforms several baseline approaches in terms of overall network Resource Occupation (RO) and caching Hit-Ratios. Thanks to our numerical results, we observe that the frequency of execution of the protocol has a significant impact on the RO, and that the ISP can tune this frequency to minimize its RO while introducing an acceptable data overhead. Because of this tuning, several CPs may experience a loss with respect to the hit-ratio that they would obtain by independently choosing the frequency of execution. This loss is very limited, and the employment of the protocol is therefore beneficial to all the involved parties, especially since, by using it, CPs are guaranteed that the ISP behaves in a network-neutral manner

To be neutral or not neutral? The in-network caching dilemma

Caching strategies have been always regarded as an important tool to reduce network traffic and to guarantee an improved Quality of Service (QoS) to customers. However, being an inherently selective process, it results in service differentiation and, potentially, discriminatory treatment of user-requested content. Despite of this, in-network caching is not generally regarded as a traffic differentiation technique and, therefore, is not considered by Net-Neutrality (NN) regulations. In this paper, we look at this problem from a different perspective: the characteristics of today's Internet, such as the wide use of encryption, prevent Internet Service Providers (ISPs) from applying in-network caching without cooperating with Content Providers (CPs). Hence, a rigorous definition of NN-compliant caching is needed to agree upon the effective neutrality of ISPs. We compare different caching frameworks under the lens of NN and conclude that caching may lead to discrimination. Finally, we suggest a few research directions towards non-discriminatory in-network caching

Effective techniques for detecting and locating traffic differentiation in the internet

Orientador: Elias P. Duarte Jr.Coorientador: Luis C. E. BonaTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa : Curitiba, 24/09/2019Inclui referências: p. 115-126Área de concentração: Ciência da ComputaçãoResumo: A Neutralidade da Rede torna-se cada vez mais relevante conforme se intensifica o debate global e diversos governos implementam regulações. Este princípio diz que todo tráfego deve ser processado sem diferenciação, independentemente da origem, destino e/ou conteúdo. Práticas de diferenciação de tráfego (DT) devem ser transparentes, independentemente de regulações, pois afetam significativamente usuários finais. Assim, é essencial monitorar DT na Internet. Várias soluções já foram propostas para detectar DT. Essas soluções baseiam-se em medições de rede e inferência estatística. Porém, existem desafios em aberto. Esta tese tem três objetivos principais: (i) consolidar o estado da arte referente ao problema de detectar DT; (ii) investigar a DT em contextos ainda não explorados, especificamente a Internet das Coisas (IoT); e (iii) propor novas soluções para detecção de DT que solucionem alguns dos desafios em aberto, em particular localizar a fonte de DT. Primeiramente descrevemos o atual estado da arte, incluindo várias soluções de detecção de DT. Também propomos uma taxonomia para os diferentes tipos de DT e de detecção, e identificamos desafios em aberto. Em seguida, avaliamos o impacto da DT na IoT, simulando DT de diferentes padrões de tráfego IoT. Resultados mostram que mesmo uma priorização pequena pode ter um impacto significativo no desempenho de dispositivos de IoT. Propomos então uma solução para detectar DT na Internet, que baseia-se em uma nova estratégia que combina diversas métricas para detectar tipos diferente de DT. Resultados de simulação mostram que esta estratégia é capaz de detectar DT em diversas situações. Em seguida, propomos um modelo geral para monitoramento contínuo de DT na Internet, que se propõe a unificar as soluções atuais e futuras de detecção de DT, ao mesmo tempo que tira proveito de tecnologias atuais e emergentes. Neste contexto, uma nova solução para identificar a fonte de DT na Internet é proposta. O objetivo desta proposta é tanto viabilizar a implementação do nosso modelo geral quanto solucionar o problema de localizar DT. A proposta tira proveito de propriedades de roteamento da Internet para identificar em qual Sistema Autônomo (AS) DT acontece. Medições de vários pontos de vista são combinadas, e a fonte de DT é inferida com base nos caminhos em nível de AS entre os pontos de medição. Para avaliar esta proposta, primeiramente executamos experimentos para confirmar que rotas na Internet realmente apresentam as propriedades requeridas. Diversas simulações foram então executadas para avaliar a eficiência da proposta de localização de DT. Resultados mostram que em diversas situações, efetuar medições a partir de poucos nodos no núcleo da Internet obtém resultados similares a efetuar medições a partir de muitos nodos na borda. Palavras-chave: Neutralidade da Rede, Diferenciação de Tráfego, Medição de Rede.Abstract: Network Neutrality is becoming increasingly important as the global debate intensifies and governments worldwide implement and withdraw regulations. According to this principle, all traffic must be processed without differentiation, regardless of origin, destination and/or content. Traffic Differentiation (TD) practices should be transparent, regardless of regulations, since they can significantly affect end-users. It is thus essential to monitor TD in the Internet. Several solutions have been proposed to detect TD. These solutions are based on network measurements and statistical inference. However, there are still open challenges. This thesis has three main objectives: (i) to consolidate the state of the art regarding the problem of detecting TD; (ii) to investigate TD on contexts not yet explored, in particular the Internet of Things (IoT); and (iii) to propose new solutions regarding TD detection that address open challenges, in particular locating the source of TD. We first describe the current state of the art, including a description of multiple solutions for detecting TD. We also propose a taxonomy for the different types of TD and the different types of detection, and identify open challenges. Then, we evaluate the impact of TD on IoT, by simulating TD on different IoT traffic patterns. Results show that even a small prioritization may have a significant impact on the performance of IoT devices. Next, we propose a solution for detecting TD in the Internet. This solution relies on a new strategy of combining several metrics to detect different types of TD. Simulation results show that this strategy is capable of detecting TD under several conditions. We then propose a general model for continuously monitoring TD on the Internet, which aims at unifying current and future TD detection solutions, while taking advantage of current and emerging technologies. In this context, a new solution for locating the source of TD in the Internet is proposed. The goal of this proposal is to both enable the implementation of our general model and address the problem of locating TD. The proposal takes advantage of properties of Internet peering to identify in which Autonomous System (AS) TD occurs. Probes from multiple vantage points are combined, and the source of TD is inferred based on the AS-level routes between the measurement points. To evaluate this proposal, we first ran several experiments to confirm that indeed Internet routes do present the required properties. Then, several simulations were performed to assess the efficiency of the proposal for locating TD. The results show that for several different scenarios issuing probes from a few end-hosts in core Internet ASes achieves similar results than from numerous end-hosts on the edge. Keywords: Network Neutrality, Traffic Differentiation, Network Measurement