Content Centric Networking represents a paradigm shift in the evolution and definition of modern network protocols. Many research efforts have been made with the purpose of proving the feasibility and the scalability of this proposal. Our main contribution is to provide an analysis of the Pending Interest Table memory requirements in real deployment scenarios, especially considering the impact of distributed denial of service attacks. In fact, the state that the protocol maintains for each resource request makes the routers more prone to resources exhaustion issues than in traditional stateless solutions. Our results are derived by using a full custom simulator and considering the different node architectures that have been proposed as valid reference models. The main outcomes point out differentiated weaknesses in each architecture we investigated and underline the need for improvements in terms of security and scalability.

The role of software and its flexibility is becoming more and more important in todays networks. New emerging paradigms, such as Software Defined Networking (SDN) and Network Function Virtualization (NFV), are changing the rules of the game, shifting the focus on dynamicity and programmability. Perfectly aligned with this new spirit, the FP7 UNIFY European project aims at realizing this appealing vision by applying DevOps concepts to telecom operator networks and supporting the idea of fast network reconfiguration. However, the increased range of possibilities offered by the DevOps approach comes at the cost of designing new processes and toolkits to make SDN and NFV a concrete opportunity. In this paper we specifically focus on the verification process as part of the challenging tasks that must be addressed in this scenario and its fundamental role of automatically checking some desired network properties before deploying a particular configuration. Our preliminary results confirm the feasibility of the approach and encourage future efforts in this direction.

We address the problem of detecting non-stationary effects in time series (in particular fractal time series) by means of the Diffusion Entropy Method (DEM). This means that the experimental sequence under study, of size N , is explored with a window of size L << N . The DEM makes a wise use of the statistical information available and, consequently, in spite of the modest size of the window used, does succeed in revealing local statistical properties, and it shows how they change upon moving the windows along the experimental sequence. The method is expected to work also to predict catastrophic events before their occurrence.

In-network function chaining often involves the deployment of multiple applications into a single, possibly multitenant, middlebox. This approach has gained much interest since new network paradigms, such as Software Defined Networking (SDN) and Network Function Virtualization (NFV), have been proposed to virtualize resources as well as network functions. In this scenario, it is very common to move data (e.g., packets) from an application to another by means of a switching module that is in charge of chaining network functions in the correct order, also ensuring an adequate level of isolation between any two virtualized components. With this purpose in mind, this paper proposes an efficient algorithm to handle the communication between the internal soft-switch and the heterogeneous network functions that are executed on the same server. Our proposal is designed with the aim of dealing with high speed packet processing, hence an extensive performance evaluation is also provided to prove the goodness of our solution in this context.

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