Optimal Orchestration of Virtual Network Functions

-The emergence of Network Functions Virtualization (NFV) is bringing a set of novel algorithmic challenges in the operation of communication networks. NFV introduces volatility in the management of network functions, which can be dynamically orchestrated, i.e., placed, resized, etc. Virtual Network Functions (VNFs) can belong to VNF chains, where nodes in a chain can serve multiple demands coming from the network edges. In this paper, we formally define the VNF placement and routing (VNF-PR) problem, proposing a versatile linear programming formulation that is able to accommodate specific features and constraints of NFV infrastructures, and that is substantially different from existing virtual network embedding formulations in the state of the art. We also design a math-heuristic able to scale with multiple objectives and large instances. By extensive simulations, we draw conclusions on the trade-off achievable between classical traffic engineering (TE) and NFV infrastructure efficiency goals, evaluating both Internet access and Virtual Private Network (VPN) demands. We do also quantitatively compare the performance of our VNF-PR heuristic with the classical Virtual Network Embedding (VNE) approach proposed for NFV orchestration, showing the computational differences, and how our approach can provide a more stable and closer-to-optimum solution

Error Estimate and Fairness in Resource Allocation with Inaccurate Information Sharing

International audienceIn resource allocation systems, inaccurate information sharing situations are such that users can be aware, up to a small error, about the other users' demands and the available global resource (which can be insufficient to meet the overall demand). Consequently, given an allocation rule, users can predict an allocation that will not necessarily coincide with the actual one. In this work, we provide an estimation of the error for a number of allocation rules and compare their robustness in inaccurate information sharing settings

Game Theoretical Framework for Analyzing Blockchains Robustness

In this paper we propose a game theoretical framework in order to formally characterize the robustness of blockchains systems in terms of resilience to rational deviations and immunity to Byzantine behaviors. Our framework includes necessary and sufficient conditions for checking the immunity and resilience of games and an original technique for composing games that preserves the robustness of individual games. We prove the practical interest of our formal framework by characterizing the robustness of various blockchain protocols: Bitcoin (the most popular permissionless blockchain), Tendermint (the first permissioned blockchain used by the practitioners), Lightning Network, a side-chain protocol and a cross-chain swap protocol. For each one of the studied protocols we identify upper and lower bounds with respect to their resilience and immunity (expressed as no worse payoff than the initial state) face to rational and Byzantine behaviors

Brief Announcement: Game Theoretical Framework for Analyzing Blockchains Robustness

Blockchains systems evolve in complex environments that mix classical patterns of faults (e.g crash faults, transient faults, Byzantine faults, churn) with selfish, rational or irrational behaviors typical to economical systems. In this paper we propose a game theoretical framework in order to formally characterize the robustness of blockchains systems in terms of resilience to rational deviations and immunity to Byzantine behaviors. Our framework includes necessary and sufficient conditions for checking the immunity and resilience of games and a new technique for composing games that preserves the robustness of individual games. We prove the practical interest of our formal framework by characterizing the robustness of three different protocols popular in blockchain systems: a HTLC-based payment scheme (a.k.a. Lightning Network), a side-chain protocol and a cross-chain swap protocol

LISP-MSX: Decentralized Interconnection of Independent LISP Mapping Systems

International audienceWe present in this paper a novel solution for the interconnection of LISP (Locator/Identifier Separation Protocol) mapping systems. Our solution, named LISP-MSX, differs from existing approaches in that it allows for complete mapping systems technology independence and for their decentralized interconnection, by means of novel control-plane primitives to LISP and routing protocols, hence guaranteeing faster mappings resolutio

MPTCP Robustness Against Large-Scale Man-in-the-Middle Attacks

International audienceMultipath communications at the Internet scale have been a myth for a long time, with no actual protocol being deployed at large scale. Recently, the Multipath Transmission Control Protocol (MPTCP) extension was standardized and is undergoing rapid adoption in many different use-cases, from mobile to fixed access networks, from data-centers to core networks. Among its major benefits-i.e., reliability thanks to backup path rerouting, through-put increase thanks to link aggregation, and confidentiality being more difficult to intercept a full connection-the latter has attracted lower attention. How effective would be to use MPTCP, or an equivalent multipath transport layer protocol, to exploit multiple Internet-scale paths and decrease the probability of Man-in-the-Middle (MITM) attacks is a question which we try to answer. By analyzing the Autonomous System (AS) level graph, we identify which countries and regions show a higher level of robustness against MITM AS-level attacks, for example due to core cable tapping or route hijacking practices.

Going beyond diffServ in IP traffic classification

Quality of Service (QoS) management in IP networks today relies on static configuration of classes of service definitions and related forwarding priorities. Packets are actually classified according to the DiffServ architecture based on the RFC 4594, typically thanks to static configuration or filters matching packet features, at network access equipment. In this paper, we propose a dynamic classification procedure, referred to as Learning-powered DiffServ (L-DiffServ), able to detect the distinctive characteristics of traffic and to dynamically assign service classes to IP packets. The idea is to apply semi-unsupervised Machine Learning techniques, such as Linear Discriminant Analysis (LDA) and K-Means, with a proper customization to take into account the issues related to packet-level analysis, i.e. unbalanced distribution of traffic among classes and selection of proper IP header related features. The performance evaluation highlights that L-DiffServ is able to change dynamically the classification outcome, providing an higher number of classes than DiffServ. This last result represents the first step toward a more granular differentiation of IP traffic

4-(3-Nitrophenyl)thiazol-2-ylhydrazone derivatives as antioxidants and selective hMAO-B inhibitors: synthesis, biological activity and computational analysis

A new series of 4-(3-nitrophenyl)thiazol-2-ylhydrazone derivatives were designed, synthesised, and evaluated to assess their inhibitory effect on the human monoamine oxidase (hMAO) A and B isoforms. Different (un)substituted (hetero)aromatic substituents were linked to N1 of the hydrazone in order to establish robust structure–activity relationships. The results of the biological testing demonstrated that the presence of the hydrazothiazole nucleus bearing at C4 a phenyl ring functionalised at the meta position with a nitro group represents an important pharmacophoric feature to obtain selective and reversible human MAO-B inhibition for the treatment of neurodegenerative disorders. In addition, the most potent and selective MAO-B inhibitors were evaluated in silico as potential cholinesterase (AChE/BuChE) inhibitors and in vitro for antioxidant activities. The results obtained from molecular modelling studies provided insight into the multiple interactions and structural requirements for the reported MAO inhibitory properties

Content consumption cartography of the Paris urban region using cellular probe data

A present issue in the evolution of mobile cellular networks is determining whether, how and where to deploy adaptive content and cloud distribution solutions at base station and back-hauling network level. In order to answer these questions, in this paper we document the content consumption in Orange cellular network for Paris metropolitan area. From spatial and application-level extensive analysis of real data, we numerically and statistically quantify the geographical distribution of content consumption with per-service classifications. We provide experimental statistical distributions usable for further research in the area