In the past few years, accelerated by Covid-19 pandemic, real-time services based on RTC (Real-Time Communications) have become pervasive, and their performance has become critical for a wide range of business and entertainment applications. The diffusion of RTC services beyond controlled enterprise network perimeters poses the challenge of guaranteeing high-quality, reliable, in-time delivery over the Internet and at global, worldwide scale. In this paper, we address such a problem by proposing ROBUST, a Reliable and Flexible Media Transport based on Pub/Sub Information-Centric Networking (ICN) principles. ROBUST brings enhanced reliability and flexibility to RTC applications over varying network environments and conditions. ROBUST initial design is experimentally assessed on three popular Video Conferencing applications (Jitsi Meet, Cisco Webex, and Zoom) with encouraging improvements in terms of objective Quality of Experience (QoE) metrics: e.g., we observe at least 91% loss recovery in the most challenging experimental settings, an improved video smoothness for Zoom up to 160%, a higher resolution for Webex up to 16%, while Jitsi with ROBUST works in conditions where the original application does not.

In this article, we consider security aspects of online meeting applications based on protocols such as WebRTC that leverage the Information-centric Networking (ICN) architecture to make the system fundamentally more scalable. If the scalability properties provided by ICN have been proved in recent literature, the security challenges and implications for real-time applications have not been reviewed. We show that this class of applications can benefit from strong security and scalability jointly without any major tradeoff and with significant performance improvements over traditional WebRTC systems. To achieve this goal, some modifications to the current ICN architecture must be implemented in the way integrity and authentication are verified. Extensive performance analysis of the architecture based on the open source implementation of Hybrid-ICN proves that real-time applications can greatly benefit from this novel network architecture in terms of strong security and scalable communications.

WebRTC is increasingly adopted by real-time streaming applications beyond traditional multiparty collaboration, in virtue of its low-latency capabilities. To support large scale deployments, the WebRTC architecture has evolved from the original peer-to-peer design to a centralized MCU-based (Multipoint Control Unit) system first, then to a lighter, SFU-based (Selective Forwarding Unit) system where media encoding/decoding and rate selection is delegated to the clients.In this paper we present ICN-RTC, a real time communication architecture build on the latest SFU-based proposal that exploits the scalability benefits provided by Information-Centric Networking (ICN). We also propose the ICN-RTC synchronization protocol, a protocol that allows to use the pull-based transport of ICN without introducing additional latency to media distribution.We implemented ICN-RTC using Hybrid ICN, an incrementally deployable ICN implementation using IP. Preliminary results are encouraging: ICN-RTC scales with the number of active speakers rather than the total number of users in the conference. This allows for calls with ten times more participants with respect to the standard WebRTC, reducing the resources needed for the call by more than a hundred times.

Information-Centric Networking (ICN) is a novel network architecture designed to replace the current IP-based architecture. In ICN, contents are identified based on unique names and can be cached in-network in order to immediately serve subsequent requests. These characteristics are particularly important in the context of the Internet of Things (IoT), where they allow to heavily reduce loads on the things, as well as increase content availability and decrease energy consumption. In this paper we address the open problem of providing access control for IoT deployments in ICN. Our protocol takes advantage of the reliance of IoT on Infrastructure-as-a-Service and provides confidentiality, traitor tracing and revocation of an unbound number of users. At the same time, our protocol preserves both network caching and location-independent content retrieval. To the best of our knowledge, our protocol is the first access control protocol for ICN providing all these advantages. We provide an extensive analysis of the security properties of our protocol, as well as a thorough experimental evaluation. Our evaluation shows that our protocol does not pose significant over-head with respect to published content size nor computational time required. Considering a popular IoT camera, our evaluation shows that our protocol introduces 0.27% size overhead and 150ms of computational overhead for a 7 seconds stream.

Mobility has become a basic premise of network communications, thereby requiring a native integration into 5G networks. Despite numerous efforts to propose and standardize effective mobility-management models for IP, the result is a complex, poorly flexible set of mechanisms. The natural support for mobility offered by information centric networking (ICN) makes it a good candidate to define a radically new solution relieving limitations of the traditional approaches. If consumer mobility is supported in ICN by design, in virtue of its connectionless pull-based communication model, producer mobility is still an open challenge. In this paper, we look at two prominent ICN architectures, content centric networking (CCN) and named data networking (NDN) and we propose MAP-Me, an anchor-less solution to manage micro-mobility of content producers via a name-based CCN/NDN data plane, with support for latency-sensitive streaming applications. We analyze MAP-Me performance and provide guarantees of correctness, stability, and bounded stretch, which we verify on real ISP topologies. Finally, we set up a comprehensive simulation environment in NDNSim 2.1 for MAP-Me evaluation and comparison against the existing classes of solutions, including a realistic trace-driven car-mobility pattern under a 802.11n radio access. The results are encouraging and highlight the superiority of MAP-Me in terms of user performance and network cost metrics. All the code is available as open-source.

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.

Named Data Networking (NDN) ambitions the rank of Future Internet Architecture in uniquely addressing content items by their name. In NDN, routers forward Interests for content after finding Longest-Prefix Matches (LPM) of content names in their Forwarding Information Base (FIB). However, the scalability of this structure is challenged by the huge global Internet namespace. In this paper, we propose a novel approach to interest forwarding that compresses the FIB data structure into Artificial Neural Networks (ANNs). A bitwise trie splits the namespace and indexes ANNs. ANNs are offline trained by the control plane from the Routing Information Base and matching Interests. Then, they are made available to the data plane for interrogation. We demonstrate that this approach accelerates packet forwarding by several orders of magnitude. Noteworthily, leveraging ANNs as memory and processor for directing packets towards next hops reminds of Asking For Directions to people in the street, incurring similar reliability regards.

The rapid traffic growth fueled by mobile devices spread and high speed network access calls for substantial innovation at network layer. The content-centric nature of Internet usage highlights the limitations of the host-centric model in coping with dynamic content-to-location binding, mobility, multicast, multi-homing, etc. If transmission capacity speedups in the backhaul may hide inefficiencies in the short term, the hostcentric communication model needs to be revisited to sustain future mobile demand. In this paper, we first identify and quantify the opportunities for backhaul evolution by analyzing a large set of traffic measurements collected between mobile core and backhaul of Orange France. The analysis reveals that 50% of HTTP requests are cacheable and traffic can be reduced from 60% to 95% during the peak hour by using 350GBs to 1TB of memory overall. Motivated by such significant opportunities for latency reduction and network cost savings, we present a solution based on Information-Centric Networking (ICN). First results of a large scale experimentation with 100 Linux servers and customized software, in a realistic network setting, provide a glimpse into ICN gains even under naive caching: a factor three reduction in delivery time and almost 40% bandwidth savings, when compared to existing alternatives.

Latency-minimization is recognized as one of the pillars of 5G network architecture design. Information-Centric Networking (ICN) appears a promising candidate technology for building an agile communication model that reduces latency through in-network caching. However, no proposal has developed so far latency-aware cache management mechanisms for ICN. In the paper, we investigate the role of latency awareness on data delivery performance in ICN and introduce LAC, a new simple, yet very effective, Latency-Aware Cache management policy. The designed mechanism leverages in a distributed fashion local latency observations to decide whether to store an object in a network cache. The farther the object, latency-wise, the more favorable the caching decision. By means of simulations, show that LAC outperforms state of the art proposals and results in a reduction of the content mean delivery time and standard deviation by up to 50%, along with a very fast convergence to these figures.

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.

Caching is a key component for Content Distribution Networks and new Information-Centric Network architectures. In this paper, we address performance issues of caching networks running the RND replacement policy. We first prove that when the popularity distribution follows a general power-law with decay exponent α > 1, the miss probability is asymptotic to O( C1-α) for large cache size C. We further evaluate network of caches under RND policy for homogeneous tree networks and extend the analysis to tandem cache networks where caches employ either LRU or RND policies.

Internet performance is tightly related to the properties of TCP and UDP protocols, jointly responsible for the delivery of the great majority of Internet traffic. It is well understood how these protocols behave under first-in-first-out (FIFO) queuing and what are the network congestion effects. However, no comprehensive analysis is available when flow-aware mechanisms such as per-flow scheduling and dropping policies are deployed. Previous simulation and experimental results leave a number of unanswered questions. In this paper, we tackle this issue by modeling via a set of fluid nonlinear ordinary differential equations (ODEs) the instantaneous throughput and the buffer occupancy of long-lived TCP sources under three per-flow scheduling disciplines (Fair Queuing, Longest Queue First, Shortest Queue First) and with longest queue drop buffer management. We study the system evolution and analytically characterize the stationary regime: Closed-form expressions are derived for the stationary throughput/sending rate and buffer occupancy, which give a thorough understanding of short/long-term fairness for TCP traffic. Similarly, we provide the characterization of the loss rate experienced by UDP flows in the presence of TCP traffic. As a result, the analysis allows to quantify benefits and drawbacks related to the deployment of flow-aware scheduling mechanisms in different networking contexts. The model accuracy is confirmed by a set of simulations and by the evaluation of the three scheduling disciplines in a real implementation in the Linux kernel.

We present a packet scheduler called "shortest queue first" (SQF) that aims at protecting audio and video traffic from the congestion caused by data traffic. Unlike standard solutions, the services to be handled with priority are not known in advance. It is rather the traffic characteristics of audio and video applications that are used to detect their delay sensitivity. The SQF algorithm does not require any prior configuration of the network and, as such, adapts to the fast evolution of traffic and usage. The performance of the proposed solution is demonstrated using both analysis and experiments on a testbed emulating a residential access line.

BitTorrent developers have recently introduced a new application layer congestion control algorithm based on UDP framing at transport layer and currently under definition at the IETF ledbat Working Group. Ledbat is a delay-based protocol which aims at offering a ``lower than Best Effort'''' data transfer service, with a lower priority with respect to elastic TCP and interactive traffic (e.g., VoIP, game). However, in its current specification, ledbat is affected by a late-comer advantage: indeed the last flow arriving at the bottleneck is more aggressive due to a wrong estimation of the base delay and finally takes over all resources. In this work, we study several solutions to the late-comer problem by means of packet level simulations and simple analysis: in the investigation process, we individuate the root cause for LEDBAT unfairness and propose effective countermeasures.

A few months ago, BitTorrent developers announced that the transfer of torrent data in the official client was about to switch to a new application-layer congestion-control protocol using UDP at the transport-layer. This announcement immediately raised an unmotivated buzz about a new, imminent congestion collapse of the whole Internet. As the new congestion control aims at offering a lower than best effort transport service, this reaction was not built on solid technical foundation. Nevertheless, a legitimate question remains: whether this new protocol is a necessary building block for future Internet applications, or whether it may result in an umpteenth addition to the already well populated world of Internet congestion control algorithms. To tackle this issue, we implement the novel congestion control algorithm and investigate its performance by means of packet-level simulations. Considering a simple bottleneck scenario, where the new BitTorrent competes against either TCP or other BitTorrent flows, we evaluate the fairness of resource share as well as the protocol efficiency. Our results show that the new protocol successfully meets some of its design goals, as for instance the efficiency one. At the same time, we also identify some potential fairness issues, that need to be dealt with. Finally, we point out that end-users will be the final judges of the new protocol: therefore, further research should evaluate the effects of its adoption on the performance of the applications ultimately relying on it.

Internet performance is tightly related to the properties of TCP and UDP protocols, jointly responsible for the delivery of the great majority of Internet traffic. It is well understood how these protocols behave under FIFO queuing and what are the network congestion effects. However, no comprehensive analysis is available when flow-aware mechanisms such as per-flow scheduling and dropping policies are deployed. Previous simulation and experimental results leave a number of unanswered questions. In the paper, we tackle this issue by modeling via a set of fluid non-linear ODEs the instantaneous throughput and the buffer occupancy of N long-lived TCP sources under three per-flow scheduling disciplines (Fair Queuing, Longest Queue First, Shortest Queue First) and with longest queue drop buffer management. We study the system evolution and analytically characterize the stationary regime: closed-form expressions are derived for the stationary throughput/sending rate and buffer occupancy which give a thorough understanding of short/long-term fairness for TCP traffic. Similarly, we provide the characterization of the loss rate experienced by UDP flows in presence of TCP traffic. As a result, the analysis allows to quantify benefits and drawbacks related to the deployment of flow-aware scheduling mechanisms in different networking contexts. The model accuracy is confirmed by a set of ns2 simulations and by the evaluation of the three scheduling disciplines in a real implementation in the Linux kernel.

Last year, the official BitTorrent client switched to LEDBAT, a new congestion control algorithm targeting a lower-than Best Effort transport service. In this paper, we study this new protocol through packet-level simulations, with a special focus on a performance comparison with other lower-than Best Effort protocols such as TCP-LP and TCP-NICE: our aim is indeed to quantify and relatively weight the level of Low-priority provided by such protocols. Our results show that LEDBAT transport generally achieves the lowest possible level of priority, with the default configurations of TCP-NICE and TCP-LP representing increasing levels of aggressiveness. In addition, we perform a careful sensitivity analysis of LEDBAT performance, by tuning its main parameters in both an inter-protocol (against TCP) and intra-protocol (against LEDBAT itself) scenarios. In the inter-protocol case, even in case of misconfiguration LEDBAT competes as aggressively as TCP, but we show that it is not possible to achieve an arbitrary level of low-priority by merely tuning its parameters. In the intra-protocol case, we show that coexistence of legacy flows with slightly dissimilar settings, or experiencing different network conditions, can result in significant unfairness.

We have currently reached a phase where big shifts in the network traffic might impose to rethink the design of current architectures, and where new technologies, being pushed into market, will act as enabler of such changes. Taking into account the current scenario and its likely evolution as well, in this paper we examine the case for multi-path routing within the metropolitan access network. Through an optimization framework, we undertake the analysis of several interesting aspects of the problem, such as (i) the user access technology, (ii) the topology of the access network and (iii) the traffic locality ratio within the access. By numerical solution of the problem we quantify the potential gain given by path-diversity: our results confirm the appeal of multi-path routing strategies both from the user and the network perspectives.

Multi-path routing is a valuable on-line technique to deal with unpredictable and variable traffic patters, mostly for intra-domain TE, multi-homing, wireless mesh networks, metropolitan access networks, and has been shown efficient for a large spectrum of future traffic scenarios. In this paper we analyze the performance of MIRTO, TEXCP and TRUMP, three recently proposed multi-path routing algorithms. Modeling of such algorithms is performed through fluid models, based on ordinary differential equations (ODEs). On a US-like backbone network, with and without in-network fair queuing schedulers, TEXCP and TRUMP show faster convergence times while MIRTO, that relies on simpler feedbacks, consumes less network resources.

In this paper we focus on passive measurements of TCP traffic, main component of nowadays traffic. We propose a heuristic technique for the classification of the anomalies that may occur during the lifetime of a TCP flow, such as out-of-sequence and duplicate segments. Since TCP is a closed-loop protocol that infers network conditions by means of losses and reacts accordingly, the possibility of carefully distinguishing the causes of anomalies in TCP traffic is very appealing, since it may be instrumental to the deep understanding of TCP behavior in real environments and to protocol engineering as well. We apply the proposed heuristic to traffic traces collected at both networks edges and backbone links. By studying the statistical properties of TCP anomalies, we find that their aggregate exhibits Long Range Dependence phenomena, but that anomalies suffered by individual long-lived flows are on the contrary uncorrelated. Interestingly, no dependence to the actual link load is observed.

An enhanced flow-aware Internet is arguably a more effective means of ensuring adequate performance than implementing the complex standardized QoS architectures. This flow-aware network would provide flow-level performance guarantees for real time and data applications by implementing per-flow fair queueing and by limiting the impact of overload through flow level admission control. The paper discusses the feasibility of the implied router mechanisms and proposes original solutions that minimize the necessary overhead with respect to the current best effort network. Preferred solutions significantly reduce requirements for flow state by employing directly addressed bitmaps to record flow status, as necessary for scheduling and admission control, respectively.

We focus on the identification and definition of "Web user-sessions", an aggregation of several TCP connections generated by the same source host on the basis of TCP connection opening time. The identification of a user session is non trivial; traditional approaches rely on threshold based mechanisms, which are very sensitive to the value assumed for the threshold and may be difficult to correctly set. By applying clustering techniques, we define a novel methodology to identify Web user-sessions without requiring an a priori definition of threshold values. We analyze the characteristics of user sessions extracted from real traces, studying the statistical properties of the identified sessions. From the study it emerges that Web user-sessions tend to be Poisson, but correlation may arise during periods of network/hosts anomalous functioning.

Despite its well-known advantages, per-flow fair queueing has not been deployed in the Internet mainly because of the common belief that such scheduling is not scalable. The objective of the present paper is to demonstrate using trace simulations and analytical evaluations that this belief is misguided. We show that although the number of flows in progress increases with link speed, the number that needs scheduling at any moment is largely independent of this rate. The number of such active flows is a random process typically measured in hundreds even though there may be tens of thousands of flows in progress. The simulations are performed using traces from commercial and research networks with quite different traffic characteristics. Analysis is based on models for balanced fair statistical bandwidth sharing and applies properties of queue busy periods to explain the observed behaviour.

In this paper, we propose a MMPP (Markov modulated Poisson process) traffic model that accurately approximates the LRU (long range dependence) characteristics of Internet traffic traces. Using the notion of sessions and flows, the proposed MMPP model mimics the real hierarchical behavior of the packet generation process by Internet users. Thanks to its hierarchical structure, the proposed model is both simple and intuitive: it allows the generation of traffic with the desired characteristics by easily setting a few input parameters which have a clear physical meaning. Results prove that the queuing behavior of the traffic generated by the MMPP model is coherent with the one produced by the real traces collected at our institution edge router under different networking scenarios and loads. Due to its characteristics, the proposed MMPP traffic model can be used as a simple and manageable tool for IP network performance analysis, as well as for network planning and dimensioning.

We study the TCP flow arrival process, starting from the aggregated measurement at the TCP flow level taken from our campus network. In particular, we analyze the statistical properties of the TCP flow arrival process. We define the different traffic aggregates by splitting the original trace, such that i) each of them is constituted by all the TCP flows belonging to the same traffic relation, i.e., with the same source/destination IP addresses and ii) each traffic aggregate has, bytewise, the same amount of traffic. To induce a divisions of TCP-elephants and TCP-mice into different traffic aggregates, the used algorithm packs the largest traffic relations in the first traffic aggregates, so that subsequently generated aggregates are constituted by an increasing number of smaller traffic relations. The long range dependency (LRD) characteristics are presented, showing the possible causes of the LRD of TCP flow arrival process in i) the heavy tailed distribution of the number of flows in a traffic aggregate, and ii) the presence of TCP-elephants within them.