Mathieu Bouet

RFID tags: Positioning principles and localization techniques

RFID is an automatic identification technology that enables tracking of people and objects. Both identity and location are generally key information for indoor services. An obvious and interesting method to obtain these two types of data is to localize RFID tags attached to devices or objects or carried by people. However, signals in indoor environments are generally harshly impaired and tags have very limited capabilities which pose many challenges for positioning them. In this work, we propose a classification and survey the current state-of-art of RFID localization by first presenting this technology and positioning principles. Then, we explain and classify RFID localization techniques. Finally, we discuss future trends in this domain.

DISCO: Distributed multi-domain SDN controllers

Software-Defined Networking (SDN) is now envisioned for Wide Area Networks (WAN) and constrained overlay networks. Such networks require a resilient, scalable and easily extensible SDN control plane. In this paper, we propose DISCO, an extensible DIstributed SDN COntrol plane able to cope with the distributed and heterogeneous nature of modern overlay networks. A DISCO controller manages its own network domain and communicates with other controllers to provide end-to-end network services. This east-west communication is based on a lightweight and highly manageable control channel. We implemented DISCO on top of the Floodlight OpenFlow controller and the AMQP protocol and we evaluated it through an inter-domain topology disruption use case.

Monitoring latency with OpenFlow

Software Defined Networking, especially through protocols like OpenFlow, is becoming more and more present in networks. It aims at separating the data plane from the control plane for more network programmability, serviceability, heterogeneity and maintainability. Even if mobile applications and multimedia are often pointed at to show the demise of current network architectures, there are currently no ways to efficiently dynamically obtain the latency in an OpenFlow network to efficiently apply QoS policies. In this paper, we propose a mechanism to measure link latencies from an OpenFlow controller with high accuracy and a low footprint. We implemented it and present the performance evaluation. A monitoring packet consumes only 24 Bytes, which is 81% less than the ping utility, for an average accuracy of 99.25% compared to the ping values.

Cost‐based placement of vDPI functions in NFV infrastructures

Network Functions Virtualization (NFV) is transforming how networks are architected and network services delivered. The network is more flexible and adaptable, it can scale with traffic demands. To manage video traffic in the network, or get protection from cyber-attacks, Deep Packet Inspection is increasingly deployed at specific locations in the network. The virtual Deep Packet Inspection (vDPI) engines can be dynamically deployed as software on commodity servers within emerging NFV infrastructures. For a network operator, deploying a set of vDPIs over the network is a matter of finding the appropriate placement that meets the traffic management or cyber-security targets (such as the number of inspected flows) and operational cost constraints (license fees, network efficiency or power consumption). In this work, we formulate the vDPI placement problem as a cost minimization problem. The cost captures the different objectives the operator is pursuing. A placement of vDPIs on the network nodes realizes a trade-off between these possibly conflicting goals. We cast the problem as a multi-commodity flow problem and solve it as an Integer Linear Program (ILP). We then devise a centrality-based greedy algorithm and assess its validity by comparing it with the ILP optimal solution on a real data set (GEANT network with 22 nodes and real traffic matrix). We further analyze the scalability of the heuristic by applying it to larger random networks of up to 100 nodes. The results show the network structure and the costs strongly influence time performance. They also show that after a size limit (between 40 to 80 nodes in our case), the execution time increases exponentially due to combinatorial issues. Finally, they demonstrate that the heuristic well approximate the optimal on smaller problem instances.

Cost-Based Placement of Virtualized Deep Packet Inspection Functions in SDN

In todays IT systems, cyber security requires fine-grained, flexible, adaptable and cost optimized monitoring mechanisms. The emergence of new networking technologies, like Network Function Virtualization (NFV) and Software Defined Networking (SDN), opens up new venues for large scale adoption of these cyber security tools. In particular, Deep Packet Inspection (DPI) engines can be virtualized and dynamically deployed as pieces of software on commodity hardware. Deploying such software DPI engines is costly in terms of license fees and power consumption. Designing cost effective DPI engine deployment strategies that meet the cybersecurity operational constraints is thus mandatory for the adoption of this approach. For this purpose, we propose a method, based on genetic algorithms, that optimizes the cost of DPI engine deployment, minimizing their number, the global network load and the number of unanalyzed flows. We conduct several experiments with different types of traffic and different cost structures. The results show that the method is able to reach a trade-off between the number of DPI engines and network load. Furthermore, the global cost can be reduced up to 58% when relaxing the constraint on the used link capacity, that is the provisioning rate.

Cost-based placement of vDPI functions in NFV infrastructures

Network Functions Virtualization (NFV) is transforming how networks are architected and network services delivered. The network is more flexible and adaptable, it can scale with traffic demands. To manage video traffic in the network, or get protection from cyber-attacks, Deep Packet Inspection is increasingly deployed at specific locations in the network. The virtual Deep Packet Inspection (vDPI) engines can be dynamically deployed as software on commodity servers within emerging NFV infrastructures. For a network operator, deploying a set of vDPIs over the network is a matter of finding the appropriate placement that meets the traffic management or cyber-security targets (such as the number of inspected flows) and operational cost constraints (license fees, network efficiency or power consumption). In this work, we formulate the vDPI placement problem as a cost minimization problem. The cost captures the different objectives the operator is pursuing. A placement of vDPIs on the network nodes realizes a trade-off between these possibly conflicting goals. We cast the problem as a multi-commodity flow problem and solve it as an Integer Linear Program (ILP). We then devise a centrality-based greedy algorithm and assess its validity by comparing it with the ILP optimal solution on a real data set (GEANT network with 22 nodes and real traffic matrix). We further analyze the scalability of the heuristic by applying it to larger random networks of up to 100 nodes. The results show the network structure and the costs strongly influence time performance. They also show that after a size limit (between 40 to 80 nodes in our case), the execution time increases exponentially due to combinatorial issues. Finally, they demonstrate that the heuristic well approximate the optimal on smaller problem instances.

Improving SDN with InSPired Switches

In SDN, complex protocol interactions that require forging network packets are handled on the controller side. While this ensures flexibility, both performance and scalability are impacted, introducing serious concerns about the applicability of SDN at scale. To improve on these issues, without infringing the SDN principles of control and data planes separation, we propose an API for programming the generation of packets in SDN switches. Our InSP API allows a programmer to define in-switch packet generation operations, which include the specification of triggering conditions, packets content and forwarding actions. To validate our design, we implemented the InSP API in an OpenFlow software switch and in a controller, requiring only minor modifications. Finally, we demonstrate that the application of the InSP API, for the implementation of a typical ARP-handling use case, is beneficial for the scalability of both switches and controller.

DISCO: Distributed SDN controllers in a multi-domain environment

Software-Defined Networking (SDN) is now envisioned for Wide Area Networks (WAN) and deployed constrained networks. Such networks require a resilient, scalable and easily extensible SDN control plane. In this paper, we propose DISCO, a DIstributed SDN COntrol plane able to cope with the distributed and heterogeneous nature of modern overlay networks and deployed networks. A DISCO controller manages its own network domain, communicates with other DISCO controllers to provide end-to-end network services and share aggregated network-wide information. This east-west communication is based on a lightweight and highly manageable control channel which can self-adapt to network conditions.

Operator-driven framework for establishing and unifying autonomic network and service management solutions

It is commonly recognized that the technology progress, dynamism but also complexity of telecommunication networks and services increase with rapid paces. Such challenges cannot be efficiently handled by traditional networking and management schemes. Autonomics in network and services management appear as the most viable way out. However, despite the significant research efforts and achievements in this field, a few and only recently start to convince operators for their deployability. In this direction, UniverSelf is a research initiative which proposes a pragmatic solution for overcoming the increasing complexity a) by consolidating and capitalizing on lessons learnt and b) by identifying and solving actual, first-priority, immediate and mid-term manageability problems encountered by operators. The cornerstone of UniverSelf approach is the Unified Management Framework (UMF), an operator-driven framework that designates processes, tools and methods for establishing (legacy, emerging and yet undiscovered) autonomic solutions in the joint management of networks and services. This paper provides a first concise description of the UMF design in terms of core, reusable and cohesive functional blocks and interfaces, as derives from the elaboration of requirements elicited from a set of operator problems (use cases). The design is complemented by principles and goals that address important high-level challenges such as the unification/federation of diverse autonomic solutions and technology domains, the governance of autonomic infrastructures and services, as well as the embodiment of autonomic solutions (intelligence) into the management ecosystem.

Failover mechanisms for distributed SDN controllers

Distributed SDN controllers have been proposed to address performance and resilience issues. While approaches for datacenters are built on strongly-consistent state sharing among controllers, others for WAN and constrained networks rely on a loosely-consistent distributed state. In this paper, we address the problem of failover for distributed SDN controllers by proposing two strategies for neighbor active controllers to take over the control of orphan OpenFlow switches: (1) a greedy incorporation and (2) a pre-partitioning among controllers. We built a prototype with distributed Floodlight controllers to evaluate these strategies. The results show that the failover duration with the greedy approach is proportional to the quantity of orphan switches while the pre-partitioning approach, introducing a very small additional control traffic, enables to react quicker in less than 200ms.