Section: New Results

Open Network Architecture

Controller load in SDN networks

Participant: Damien Saucez.

In OpenFlow, a centralized programmable controller installs forwarding rules into switches to implement policies. However, this flexibility comes at the expense of extra overhead in signalling and number of rules to install. The community considered that it was essential to install all rules and strictly respect routing requirements, hence working on making extra fast and large memory switches and controllers. Instead we took an opposite direction and came with a new vision that leverages the SDN concept and considers the network as a black box where tailored rules should be used only for network traffic that really matters while for the rest a good-enough (sub-optimal but cheap) default behaviour should be enough. In the past, we applied this vision to limit the needed memory on network switches in [5]. Lately, we proposed solutions to limit the number of exchanged messages between the switches and the controller. More precisely, in [31], [16] we developed a distributed sampling adaptive algorithm that allows switches to locally decide if they can contact the controller or if instead they should make their own decision locally. Numerical evaluation and emulation in Mininet demonstrate the benefit of the approach. The results were published in the PGMO (Gaspard Monge Program for Optimisation) days, Nov 2017, Paris, France.

Traceroute facility for Content-Centric Network

Participant: Thierry Turletti.

In the context of the UHD-on-5G associated team with our colleagues at NICT, Japan, we have proposed the Contrace tool for Measuring and Tracing Content-Centric Networks (CCNs). CCNs are fundamental evolutionary technologies that promise to form the cornerstone of the future Internet. The information flow in these networks is based on named data requesting, in-network caching, and forwarding – which are unique and can be independent of IP routing. As a result, common IP-based network tools such as ping and traceroute can neither trace a forwarding path in CCNs nor feasibly evaluate CCN performance. We designed Contrace, a network tool for CCNs (particularly, CCNx implementation running on top of IP) that can be used to investigate 1) the Round-Trip Time (RTT) between content forwarder and consumer, 2) the states of in-network cache per name prefix, and 3) the forwarding path information per name prefix. This tool can estimate the content popularity and design more effective cache control mechanisms in experimental networks. We have published an Internet-Draft [30] describing the specification of Contrace.

Message Dissemination in Intelligent Transport Systems

Participant: Thierry Turletti.

We proposed D2-ITS, a flexible and extensible framework to dynamically distribute network control to enable message dissemination in Intelligent Transport Systems (ITS). By decoupling the control from the data plane, D2-ITS leverages network programmability to address ITS scalability, delay intolerance and decentralization. It uses a distributed control plane based on a hierarchy of controllers that can dynamically adjust to environment and network conditions in order to satisfy ITS application requirements. We demonstrate the benefits of D2-ITS through a proof-of-concept prototype using the ns-3 simulation platform. Results indicate lower message delivery latency with minimal additional overhead. This work has been presented at the IEEE/ACM Symposium on Distributed Simulation and Real Time Applications (DS-RT) in October 2017 [18].

Peer-assisted Information-Centric Network

Participant: Thierry Turletti.

Information-Centric Networking (ICN) is a promising solution for most of Internet applications where the content represents the core of the application. However, the proposed solutions for the ICN architecture are associated with many complexities including pervasive caching in the Internet and incompatibility with legacy IP networks, so the deployment of ICN in real networks is still an open problem. In this work, we proposed a backward compatible ICN architecture to address the caching issue in particular. The key idea is implementing edge caching in ICN, using a coalition of end clients and edge servers. Our solution can be deployed in IP networks with HTTP requests. We performed a trace-driven simulation for analyzing PICN benefits using IRCache and Berkeley trace files. The results showed that in average, PICN decreases the latency for 78% and increases the content retrieval speed for 69% compared to a direct download from the original web servers. When comparing PICN with a solution based on central proxy servers, we showed that the hit ratio obtained using a small cache size in each PICN client is almost 14% higher than the hit ratio obtained with a central proxy server using an unlimited cache storage. This work has been published in the IEEE Access journal [14].

Streaming using In-Network Coding and Caching

Participant: Thierry Turletti.

With the rapid growth in high-quality video streaming over the Internet, preserving high-level robustness against data loss and low latency, while maintaining higher data transmission rates, is becoming an increasingly important issue for high-quality real-time delay-sensitive streaming. We have proposed a low latency, low loss streaming mechanism, L4C2, specialized for high-quality delay-sensitive streaming. Using L4C2, nodes in a network estimate the acceptable delay and packet loss probability in their uplinks, aiming at retrieving lost data packets from in-network cache and/or coded data packets using in-network coding within an acceptable delay, by extending the Content-Centric Networking (CCN) approach. Further, L4C2 naturally provides multiple path and multicast technologies to efficiently utilize network resources while sharing network resources fairly with competing data flows by adjusting the video quality as necessary. We validate through comprehensive simulations that L4C2 achieves a high success probability of data transmission considering the acceptable one-way delay and outperforms the existing solution. This work has been presented at the IEEE Infocom conference in May 2017 [23].

Scalable Multicast Service in Software Defined ISP networks

Participants: Hardik Soni, Thierry Turletti, Walid Dabbous.

In the context of the SDN-based multicast mechanisms activity, we designed an architectural solution to provide scalable multicast service in ISP networks. In fact, new applications where anyone can broadcast video are becoming very popular on smartphones. With the advent of high definition video, ISP providers may take the opportunity to propose new high quality broadcast services to their clients. Because of its centralized control plane, Software Defined Networking (SDN) seems an ideal way to deploy such a service in a flexible and bandwidth-efficient way. But deploying large scale multicast services on SDN requires smart group membership management and a bandwidth reservation mechanism to support QoS guarantees that should neither waste bandwidth nor impact too severely best effort traffic. We have proposed a Network Function Virtualization based solution for Software Defined ISP networks to implement scalable multicast group management. We also proposed a routing algorithm called Lazy Load balancing Multicast (L2BM) for sharing the network capacity in a friendly way between guaranteed-bandwidth multicast traffic and best-effort traffic. Our implementation of the framework made on Floodlight controllers and Open vSwitches has been used to study the performance of L2BM. This work has been presented at the IEEE ICC conference [24] in May 2017 and an extended version has been published to the IEEE TNSM journal [13].

Placement of Virtual Network Function Chains in 5G

Participants: Osama Arouk, Thierry Turletti.

We proposed a novel algorithm, namely Multi-Objective Placement (MOP), for the efficient placement of Virtualized Network Function (VNF) chains in future 5G systems. Real datasets are used to evaluate the performance of MOP in terms of acceptance ratio and embedding time when placing the time critical radio access network (RAN) functions as a chain. In addition, we rely on a realistic infrastructure topology to assess the performance of MOP with two main objectives: maximizing the number of base stations that could be embedded in the Cloud and load balancing. The results reveal that the acceptance ratio of embedding RAN functions is only 5% less than the one obtained with the optimal solution for the majority of considered scenarios, with a speedup factor of up to 2000 times. This work has been presented at the IEEE CloudNet conference in September 2017 [17].

P4Bricks: Enabling multiprocessing using Linker-based network data plane architecture

Participants: Hardik Soni, Thierry Turletti, Walid Dabbous.

In order to realize NFV-based multicast service as an add-on network capability without having knowledge of implementation level details of other network functions, we proposed a novel data plane architecture, P4Bricks, for modularized control and packet processing in the network... We propose P4Bricks, a system which aims to deploy and execute multiple independently developed and compiled P4 programs on the same reconfigurable hardware device. P4Bricks is based on a Linker component that merges the programmable parsers/deparsers and restructures the logical pipeline of P4 programs by refactoring, decomposing and scheduling the pipelines' tables. It merges P4 programs according to packet processing semantics (parallel or sequential) specified by the network operator and runs the programs on the stages of the same hardware pipeline, thereby enabling multiprocessing.  A paper presenting the initial design of our system with an ongoing implementation and studies P4 language's fundamental constructs facilitating merging of independently written programs was submitted to SOSR and publisehd as a research report [37].

Vehicles as a Mobile Cloud: Modelling, Optimization and Performance Analysis

Participants: Luigi Vigneri, Thrasyvoulos Spyropoulos, Chadi Barakat.

The large diffusion of handheld devices is leading to an exponential growth of the mobile traffic demand which is already overloading the core network. To deal with such a problem, several works suggest to store content (files or videos) in small cells or user equipments. In this work, done in collaboration with Eurecom with the support of the UCN@SOPHIA Labex, we push the idea of caching at the edge a step further, and we propose to use public or private transportation as mobile small cells and caches. In fact, vehicles are widespread in modern cities, and the majority of them could be readily equipped with network connectivity and storage. The adoption of such a mobile cloud, which does not suffer from energy constraints (compared to user equipments), reduces installation and maintenance costs (compared to small cells). In our work, a user can opportunistically download chunks of a requested content from nearby vehicles, and be redirected to the cellular network after a deadline (imposed by the operator) or when her playout buffer empties. The main goal of the work is to suggest to an operator how to optimally replicate content to minimize the load on the core network. Our main contributions are: (i) Modelling: We model the above scenario considering heterogeneous content size, generic mobility and a number of other system parameters. (ii) Optimization: We formulate some optimization problems to calculate allocation policies under different models and constraints. (iii) Performance analysis. We build a MATLAB simulator to validate the theoretical findings through real trace-based simulations. We show that, even with low technology penetration, the proposed caching policies are able to offload more than 50 percent of the mobile traffic demand. The results of this work has been published in several papers, and are currently the subject of two submissions to journals. In particular, in [25] we consider the case of per-chunk caching for video streaming, whereas in [26] we consider the case of Quality of Experience-aware caching of files where the Quality of Experience is modeled as the slowdown in the file download time. A thorough presentation of this work and of our contributions can be found in the PhD thesis of Luigi Vigneri defended in July 2017 and available at [12].