Dataplane languages like P4 enable flexible and efficient packet-processing using domain-specific primitives such as programmable parsers and match-action tables. Unfortunately, P4 programs tend to be monolithic and tightly coupled to the hardware architecture, which makes it hard to write programs in a portable and modular way-e.g., by composing reusable libraries of standard protocols. To address this challenge, we present the design and implementation of a novel framework (mu P4) comprising a lightweight logical architecture that abstracts away from the structure of the underlying hardware pipelines and naturally supports powerful forms of program composition. Using examples, we show how mu P4 enables modular programming. We present a prototype of the mu P4 compiler that generates code for multiple lower-level architectures, including Barefoot's Tofino Native Architecture. We evaluate the overheads induced by our compiler on realistic examples.

Network operators are facing great challenges in terms of cost and complexity in order to incorporate new communication technologies (e.g., 4G, 5G, fiber) and to keep up with increasing demands of new network services to address emerging use cases. Softwarizing the network operations using SoftwareDefined Networking (SDN) and Network Function Virtualization (NFV) paradigms can simplify control and management of networks and provide network services in a cost effective way. SDN decouples control and data traffic processing in the network and centralizes the control traffic processing to simplify the network management, but may face scalability issues due to the same reasons. NFV decouples hardware and software of network appliances for cost effective operations of network services, but faces performance degradation issues due to data traffic processing in software. In order to address scalability and performance issues in SDN/NFV, we propose in the first part of the thesis, a modular network control and management architecture, in which the SDN controller delegates part of its responsibilities to specific network functions instantiated in network devices at strategic locations in the infrastructure. We have chosen to focus on a modern application using an IP multicast service for live video streaming applications (e.g., Facebook Live or Periscope) that illustrates well the SDN scalability problems. Our solution exploits benefits of the NFV paradigm to address the scalability issue of centralized SDN control plane by offloading processing of multicast service specific control traffic to Multicast Network Functions (MNFs) implemented in software and executed in NFV environment at the edge of the network. Our approach provides smart, flexible and scalable group management and leverages centralized control of SDN for Lazy Load Balance Multicast (L2BM) traffic engineering policy in software defined ISP networks. Evaluation of this approach is tricky, as real world SDN testbeds are costly and not easily available for the research community. So, we designed a tool that leverages the huge amount of resources available in the grid, to easily emulate such scenarios. Our tool, called DiG, takes into account the physical resources (memory, CPU, link capacity) constraints to provide a realistic evaluation environment with controlled conditions. Our NFV-based approach requires multiple application specific functions (e.g., MNFs) to control and manage the network devices and process the related data traffic in an independent way. Ideally, these specific functions should be implemented directly on hardware programmable routers. In this case, new routers must be able to execute multiple independently developed programs. Packet-level programming language P4, one of the promising SDN-enabling technologies, allows applications to program their data traffic processing on P4 compatible network devices. In the second part of the thesis, we propose a novel approach to deploy and execute multiple independently developed and compiled applications programs on the same network device. This solution, called P4Bricks, allows multiple applications to control and manage their data traffic, independently. P4Bricks merges programmable blocks (parsers/deparsers and packet processing pipelines) of P4 programs according to processing semantics (parallel or sequential) provided at the time of deployment.

Packet-level programming languages such as P4 usually require to describe all packet processing functionalities for a given programmable network device within a single program. However, this approach monopolizes the device by a single large network application program, which prevents possible addition of new functionalities by other independently written network applications. 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 pro-grammable 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. This paper presents the initial design of our system with an ongoing implementation and studies P4 language's fundamental constructs facilitating merging of independently written programs.

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. In this paper, we propose a Network Function Virtualization based solution for Software Defined ISP networks to implement scalable multicast group management. Then, we propose the Lazy Load balancing Multicast (L2BM) routing algorithm 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 is used to study the performance of L2BM.

We are witnessing a considerable amount of research work related to data center and cloud infrastructures but evaluations are often limited to small-scale scenarios as very few researchers have access to a real infrastructure to confront their ideas to reality. In this demo we will reveal our experiment automation tool, DiG (Data centers in the Grid), which explicitly allocates physical resources in grids to emulate data center and cloud networks. DiG allows one to utilize grid infrastructures to evaluate research ideas pertaining to data centers and cloud environments at massive scale and with real traffic workload. We have automated the procedure of building target network topologies while respecting available physical resources in the grid against the demand of links and hosts in the experiment. We will present a showcase where DiG automatically builds a large data center topology composed of hundreds of servers executing various Hadoop intensive workloads.

We propose to demonstrate Direct Code Execution (DCE), a framework that enables to execute nearly unmodified applications and Linux Kernel code jointly with the ns-3 simulator. DCE allows therefore fully deterministic reproducibility of network experiments. DCE also supports larger scale scenarios than real-time emulators by using simulation time dilatation. In this demonstration, we will showcase two main scenarios: (1) a basic example describing how to integrate in DCE the Data Center TCP (DCTCP) Linux kernel patch, and then how to customize this protocol and run it on different scenarios; (2) a more advanced use case demonstrating how to benefit from DCE to build a rich and realistic evaluation environment for Software Defined Wireless Networks based on Open vSwitch and the NOX SDN controller.