Minimum-Cost Virtual Network Function Resilience

International audienceIn the future 5G networks, a wide range of new services with strong requirements will be delivered in the form of chains of service functions on independent virtual networks. These virtual networks will be deployed on demand, each one adapted to the specific service requirements. For infrastructure providers a real challenge consists in providing and setting up the required virtual networks (network slices) while guaranteeing strict Service Level Agreements. One of the major stakes is to be able to provide failure protection for the service function chains at minimal cost. In this work, we consider a set of deployed service chains, and we study the best strategy to protect them at minimal cost. We propose mathematical formulations that provide optimal backup functions placement over a network, and the associated backup paths for each VNF of all the chains. We develop an efficient ILP-based heuristic relying on a separation of the problem into smaller ones to solve large scale instances. We show that our heuristic is competitive, both regarding the solution quality and the solving time

Liability-aware security management for 5G

​© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Multi-party and multi-layer nature of 5G networks implies the inherent distribution of management and orchestration decisions across multiple entities. Therefore, responsibility for management decisions concerning end-to-end services become blurred if no efficient liability and accountability mechanism is used. In this paper, we present the design, building blocks and challenges of a Liability-Aware Security Management (LASM) system for 5G. We describe how existing security concepts such as manifests and Security-by-Contract, root cause analysis, remote attestation, proof of transit, and trust and reputation models can be composed and enhanced to take risk and responsibilities into account for security and liability management

The owner, the provider and the subcontractors : how to handle accountability and liability management for 5G end to end service

The adoption of 5G services depends on the capacity to provide high-value services. In addition to enhanced performance, the capacity to deliver Security Service Level Agreements (SSLAs) and demonstrate their fulfillment would be a great incentive for the adoption of 5G services for critical 5G Verticals (e.g., service suppliers like Energy or Intelligent Transportation Systems) subject to specific industrial safety, security or service level rules and regulations (e.g., NIS or SEVESO Directives). Yet, responsibilities may be difficult to track and demonstrate because 5G infrastructures are interconnected and complex, which is a challenge anticipated to be exacerbated in future 6G networks. This paper describes a demonstrator and a use case that shows how 5G Service Providers can deliver SSLAs to their customers (Service Owners) by leveraging a set of network enablers developed in the INSPIRE-5Gplus project to manage their accountability, liability and trust placed in subcomponents of a service (subcontractors). The elaborated enablers are in particular a novel sTakeholder Responsibility, AccountabIity and Liability deScriptor (TRAILS), a Liability-Aware Service Management Referencing Service (LASM-RS), an anomaly detection tool (IoT-MMT), a Root Cause Analysis tool (IoT-RCA), two Remote Attestation mechanisms (Systemic and Deep Attestation), and two Security-by-Orchestration enablers (one for the 5G Core and one for the MEC)

Agamben’s Grammar of the Secret Under the Sign of the Law

This paper suggests that a grammar of the secret forms a concept in Agamben’s work, a gap that grounds the enigma of sovereignty. Between the Indo-European *krei, *se, and *per themes, the secret is etymologically linked to the logics of separation and potentiality that together enable the pliant and emergent structure of sovereignty. Sovereignty’s logic of separation meets the logic of relation in the form of abandonment: the point at which division has exhausted itself and reaches an indivisible element, bare life, the exception separated from the form of life and captured in a separate sphere. The arcanum imperii of sovereignty and the cipher of bare life are held together in the relation of the ban as the twin secrets of biopower, maintained by the potentiality of law that works itself as a concealed, inscrutable force. But the ‘real’ secret of sovereignty, I suggest, is its dialectical reversibility, the point at which the concept of the secret is met by its own immanent unworking by the critic and scribe under the *krei theme, and subject to abandonment through the work of profanation; here, different species of the secret are thrown against one another, one order undoing the other. The secret founded upon the sacred is displaced by Agamben’s critical orientation toward the immanent: what is immanent is both potential and hiddenness

Stratégies de génération de colonnes en programmation entière pour le problème de découpe et ses variantes

This thesis gives a comprehensive view of the scope of formulations andrelated solution approaches for the cutting stock problem (CSP) and its variants. The focus is on branch-and-price approaches. Specialized algorithms are developed for knapsack subproblems that arise in thecourse of the algorithm. Thorough numerical tests are used to identify good strategies for initialization, stabilization, branching, and producing primal solutions. Industrial variants of the problem are shown to be tractable for a branch-and-price approach.The models studied are the following: the standard cutting stock andbin packing problems, a variant in which the production levels lie ina prescribed interval of tolerance, the multiple width cutting stockproblem in which stock pieces are of different size, a variant with additional technical constraints that arise typically in industrial applications, and a variant where the number of distinct cutting patterns used is minimized given a waste threshold. First, we consider various formulation of the Cutting Stock Problem(CSP): different models of the knapsack subproblem can be exploited to reformulate the CSP. Moreover, we introduce different ways ofmodeling local exchanges in the solution (primal exchanges imply dual constraints that stabilize the column generation procedure). Some models are shown to be valid integer programming (IP) reformulations while others define relaxations. The dual bounds defined by their LP solution are compared theoretically.Then, we study the variants of the knapsack subproblem that arise in a column generation approach to the CSP. The branching constraints used in the branch-and-price algorithm can result in class bound and setup cost or the need for a binary decomposition in the subproblem. We show how standard knapsack solvers (dynamic programming approach and specialized branch-and-bound algorithm) can be extended to these variants of the knapsack problem.Next, we discuss some branch-and-price implementation strategies. We compare different modes of initialization of the column generation procedure, we present our numerical study of various stabilization strategies to accelerate convergence of the procedure. We compare in particular the impact of the various ways of introducinglocal exchanges in our primal model and other stabilization techniquessuch as dual solution smoothing techniques or penalization from astability center that prevent the fluctuation of the dual variables. To generate the columns we study different strategies based on the use of heuristic columns or on a multiple generation of columns.We also consider the use of heuristics based on column generation to find a primal bound. These are compared to a classic constructive heuristic. Then, we compare the different branching rules that are used in the branch-and-price procedure. Finally, we present numerical results on two industrial applications thatcorrespond to the variant with technical restrictions for which we minimize first the waste and then the number of setups

Stratégies de génération de colonnes en programmation entière pour le problème de découpe et ses variantes

This thesis gives a comprehensive view of the scope of formulations andrelated solution approaches for the cutting stock problem (CSP) and itsvariants. The focus is on branch-and-price approaches. Specializedalgorithms are developed for knapsack subproblems that arise in thecourse of the algorithm. Thorough numerical tests are used to identify good strategiesfor initialization, stabilization, branching, and producingprimal solutions. Industrial variants of the problem are shown to be tractable for a branch-and-price approach.The models studied are the following: the standard cutting stock andbin packing problems, a variant in which the production levels lie ina prescribed interval of tolerance, the multiple width cutting stockproblem in which stock pieces are of different size, a variant withadditional technical constraints that arise typically in industrialapplications, and a variant where the number of distinct cuttingpatterns used is minimized given a waste threshold. First, we consider various formulation of the Cutting Stock Problem(CSP): different models of the knapsack subproblem can be exploited toreformulate the CSP. Moreover, we introduce different ways ofmodeling local exchanges in the solution (primal exchanges imply dualconstraints that stabilize the column generation procedure). Somemodels are shown to be valid integer programming (IP) reformulations while others definerelaxations. The dual bounds defined by their LP solution are comparedtheoretically.Then, we study the variants of the knapsack subproblem that arisein a column generation approach to the CSP. The branching constraintsused in the branch-and-price algorithm can result in class bound andsetup cost or the need for a binary decomposition in the subproblem. We show how standard knapsack solvers (dynamic programming approach and specializedbranch-and-bound algorithm) can be extended to these variants of theknapsack problem.Next, we discuss some branch-and-price implementation strategies. We compare different modes of initialization of the column generation procedure, we present our numerical study of various stabilizationstrategies to accelerate convergence of the procedure. We compare in particular the impact of the various ways of introducinglocal exchanges in our primal model and other stabilization techniquessuch as dual solution smoothing techniques or penalization from astability center that prevent the fluctuation of the dual variables. To generate the columns we study different strategies based on the use of heuristic columns or on a multiple generation of columns.We also consider the use of heuristics based on column generation to find a primal bound. These are compared to a classic constructive heuristic. Then, we compare the different branching rules that are used in the branch-and-price procedure. Finally, we present numerical results on two industrial applications thatcorrespond to the variant with technical restrictions for which weminimize first the waste and then the number of setups

Integer programming column generation strategies for the cutting stock problem and its variants

This thesis gives a comprehensive view of the scope of formulations andrelated solution approaches for the cutting stock problem (CSP) and itsvariants. The focus is on branch-and-price approaches. Specializedalgorithms are developed for knapsack subproblems that arise in thecourse of the algorithm. Thorough numerical tests are used to identify good strategiesfor initialization, stabilization, branching, and producingprimal solutions. Industrial variants of the problem are shown to be tractable for a branch-and-price approach.The models studied are the following: the standard cutting stock andbin packing problems, a variant in which the production levels lie ina prescribed interval of tolerance, the multiple width cutting stockproblem in which stock pieces are of different size, a variant withadditional technical constraints that arise typically in industrialapplications, and a variant where the number of distinct cuttingpatterns used is minimized given a waste threshold. First, we consider various formulation of the Cutting Stock Problem(CSP): different models of the knapsack subproblem can be exploited toreformulate the CSP. Moreover, we introduce different ways ofmodeling local exchanges in the solution (primal exchanges imply dualconstraints that stabilize the column generation procedure). Somemodels are shown to be valid integer programming (IP) reformulations while others definerelaxations. The dual bounds defined by their LP solution are comparedtheoretically.Then, we study the variants of the knapsack subproblem that arisein a column generation approach to the CSP. The branching constraintsused in the branch-and-price algorithm can result in class bound andsetup cost or the need for a binary decomposition in the subproblem. We show how standard knapsack solvers (dynamic programming approach and specializedbranch-and-bound algorithm) can be extended to these variants of theknapsack problem.Next, we discuss some branch-and-price implementation strategies. We compare different modes of initialization of the column generation procedure, we present our numerical study of various stabilizationstrategies to accelerate convergence of the procedure. We compare in particular the impact of the various ways of introducinglocal exchanges in our primal model and other stabilization techniquessuch as dual solution smoothing techniques or penalization from astability center that prevent the fluctuation of the dual variables. To generate the columns we study different strategies based on the use of heuristic columns or on a multiple generation of columns.We also consider the use of heuristics based on column generation to find a primal bound. These are compared to a classic constructive heuristic. Then, we compare the different branching rules that are used in the branch-and-price procedure. Finally, we present numerical results on two industrial applications thatcorrespond to the variant with technical restrictions for which weminimize first the waste and then the number of setups

Integer programming column generation strategies for the cutting stock problem and its variants

Cette thèse traite du problème de découpe uni-dimentionnel et de ses variantes. Une revue compréhensive des différentes formulations et approches de résolution associées y est complètée par des résultats sur les relations théoriques d'équivalence ou de dominance qui existent entre ces formulations et des comparaisons sur des questions pratiques telles que la symétrie dans la représentation des solutions et les schémas de branchement qu'elles induisent. La thèse se poursuit par la comparaison numérique de stratégies d'implémentation pour une approche de branch-and-price avec des résultats en matière d'initialisation, de stabilisation, de stratégie de branchements et sur l'obtention de solutions primales. Ces stratégies sont ensuite utilisées pour résoudre des problèmes industriels. La thèse montre aussi comment le sous-problème de sac-à-dos avec coût fixe peut être résolu exactement et efficacement.BORDEAUX1-BU Sciences-Talence (335222101) / SudocSudocFranceF

Knapsack Problems with Setups

Knapsack problems with setups find their application in many concrete industrial and financial problems. Moreover, they also arise as subproblems in a Dantzig-Wolfe decomposition approach to more complex combinatorial optimization problems, where they need to be solved repeatedly and therefore efficiently. Here, we consider the multiple-class integer knapsack problem with setups. Items are partitioned into classes whose use implies a setup cost and associated capacity consumption. Item weights are assumed to be a multiple of their class weight. The total weight of selected items and setups is bounded. The objective is to maximize the difference between the profits of selected items and the fixed costs incurred for setting-up classes. A special case is the bounded integer knapsack problem with setups where each class holds a single item and its continuous version where a fraction of an item can be selected while incurring a full setup. The paper shows the extent to which classical results for the knapsack problem can be generalized to these variants with setups. In particular, an extension of the branch-and-bound algorithm of Horowitz and Sahni is developed for problems with positive setup costs. Our direct approach is compared experimentally with the approach proposed in the literature consisting in converting the problem into a multiple choice knapsack with pseudo-polynomial size