Hervé Rivano

Optimal positioning of active and passive monitoring devices

Network measurement is essential for assessing performance issues, identifying and locating problems. Two common strategies are the passive approach that attaches specific devices to links in order to monitor the traffic that passes through the network and the active approach that generates explicit control packets in the network for measurements. One of the key issues in this domain is to minimize the overhead in terms of hardware, software, maintenance cost and additional traffic.In this paper, we study the problem of assigning tap devices for passive monitoring and beacons for active monitoring. Minimizing the number of devices and finding optimal strategic locations is a key issue, mandatory for deploying scalable monitoring platforms. In this article, we present a combinatorial view of the problem from which we derive complexity and approximability results, as well as efficient and versatile Mixed Integer Programming (MIP) formulations.

Optimization method for the joint allocation of modulation schemes, coding rates, resource blocks and power in self-organizing LTE networks

This article investigates the problem of the allocation of modulation and coding, subcarriers and power to users in LTE. The proposed model achieves inter-cell interference mitigation through the dynamic and distributed self-organization of cells. Therefore, there is no need for any a prior frequency planning. Moreover, a two-level decomposition method able to find near optimal solutions is proposed to solve the optimization problem. Finally, simulation results show that compared to classic reuse schemes the proposed approach is able to pack more users into the same bandwidth, decreasing the probability of user outage.

Shared risk resource group complexity and approximability issues

This article investigates complexity and approximability properties of combinatorial optimization problems yielded by the notion of Shared Risk Resource Group (SRRG). SRRG has been introduced in order to capture network survivability issues where a failure may break a whole set of resources, and has been formalized as colored graphs, where a set of resources is represented by a set of edges with same color. We consider here the analogous of classical problems such as determining paths or cuts with the minimum numbers of colors or color disjoint paths. These optimization problems are much more difficult than their counterparts in classical graph theory. In particular standard relationship such as the Max Flow - Min Cut equality do not hold any longer. In this article we identify cases where these problems are polynomial, for example when the edges of a given color form a connected subgraph, and otherwise give hardness and non approximability results for these problems.

An optimization framework for the joint routing and scheduling in Wireless Mesh Networks

In this paper, we address the problem of computing the transport capacity of Wireless Mesh Networks dedicated to Internet access. Routing and transmission scheduling have a major impact on the capacity provided to the clients. A cross-layer optimization of these problems allows the routing to take into account contentions due to radio interferences. We develop exact linear programs and provide an efficient column generation process computing a relaxation of the problem. It allows to work around the combinatoric of simultaneously achievable transmissions, hence computing solutions on large networks. Our approach is validated through extensive simulations. Evolution of the capacity of a mesh network with its parameters, as well as the algorithmic complexity are then discussed. We conjecture that the problem can be solved in polynomial time and that the gateway placement problem is only subject to localized constraints.

Fractional Path Coloring with Applications to WDM Networks

This paper addresses the natural relaxation of the path coloring problem, in which one needs to color directed paths on a symmetric directed graph with a minimum number of colors, in such a way that paths using the same arc of the graph have different colors. This classic combinatorial problem finds applications in the minimization of the number of wavelengths in wavelength division multiplexing (WDM) all-optical networks.

Lightpath assignment for multifibers WDM networks with wavelength translators

We consider the problem of finding a lightpath assignment for a given set of communication requests on a multifiber WDM optical network with wavelength translators. Given such a network and w, the number of wavelengths available on each fiber, k, the number of fibers per link, and c, the number of partial wavelength translations available on each node, our problem stands for deciding whether it is possible to find a w-lightpath for each request in the set such that there is no link carrying more that k lightpaths using the same wavelength nor node where more than c wavelength translations take place. Our main theoretical result is the writing of this problem as a particular instance of integral multicommodity flow, hence integrating routing and wavelength assignment in the same model. We then provide three heuristics mainly based upon randomized rounding of fractional multicommodity flow and enhancements that are three different answers to the trade-off between efficiency and tightness of approximation, and discuss their practical performances on both theoretical and real-world instances.

Models, Complexity and Algorithms for the Design of Multi-fiber WDM Networks

In this paper, we study multi-fiber optical networks with wavelength division multiplexing (WDM). We extend the definition of the well-known Wavelength Assignment Problem (WAP) to the case of k fibers per link and w wavelengths per fiber, generalization that we will call (k,w)-WAP. We develop a new model for the (k,w)-WAP based on conflict hypergraphs. Furthermore, we consider two natural optimization problems that arise from the (k,w)-WAP: minimizing the number of fibers k given a number of wavelengths w, on one hand, and minimizing w given k, on the other. We develop and analyze the practical performance of two methodologies based on hypergraph coloring.

Capillary networks: a novel networking paradigm for urban environments

In this paper, we present our vision of the networking challenges that are yielded by the rise of Smart Cities. Smart Cities leverage massive data collected by sensors, connected devices, social applications,... for proving a whole set a new services to the citizens. However, there is a lack of reflexion on the networking solutions that enable these services, from the gathering of sensed data to the dissemination of digital services. We identify the emerging needs of Smart Cities, focus on the capillary networks paradigm which unify the wealth of wireless connectivity available in urban environment, and present the research issues it yields.

Power-efficient radio configuration in fixed broadband wireless networks

In this work, we investigate on determining feasible radio configurations in fixed broadband wireless networks, focusing on power efficiency. Under this scenario, a power-efficient configuration can be characterized by a modulation constellation size and a transmission power level. Every link holds a set of power-efficient configurations, each of them associating a capacity with its energy cost. We introduce a joint optimization of data routing and radio configuration that minimizes the total energy consumption while handling all the traffic requirements simultaneously. An exact mathematical formulation of the problem is presented. It relies on a minimum cost multicommodity flow with step increasing cost functions, which is very hard to optimize. We then propose a piecewise linear convex function, obtained by linear interpolation of power-efficient points, that provides a good approximation of the energy consumption on the links, and present a relaxation of the previous formulation that exploits the convexity of the cost functions. This yields lower bounds on the total energy expenditure, and finally heuristic algorithms based on the fractional optimum are employed to produce feasible configuration solutions. Our models are validated through extensive experiments that are reported and discussed. The results testify the potentialities behind this novel approach.

Energy and Throughput Optimization of Wireless Mesh Networks With Continuous Power Control

Providing high data rates with minimum energy consumption is a crucial challenge for next generation wireless networks. There are few papers in the literature which combine these two issues. This paper focuses on multi-hop wireless mesh networks using a MAC layer based on Spatial Time Division Multiple Access (S-TDMA). We develop an optimization framework based on linear programming to study the relationship between throughput and energy consumption. Our contributions are two-fold. First, we formulate and solve, using column generation, a new MILP to compute offline energy-throughput tradeoff curve. We use a physical interference model where the nodes can perform continuous power control and can use a discrete set of data rates. Second, we highlight network engineering insights. We show, via numerical results, that power control and multi-rate functionalities allow optimal throughput to be reached, with lower energy consumption, using a mix of single hop and multi-hop routes.