Subsampling for Chain-Referral Methods

International audienceWe study chain-referral methods for sampling in social networks. These methods rely on subjects of the study recruiting other participants among their set of connections. This approach gives us the possibility to perform sampling when the other methods, that imply the knowledge of the whole network or its global characteristics, fail. Chain-referral methods can be implemented with random walks or crawling in the case of online social networks. However, the estimations made on the collected samples can have high variance, especially with small sample size. The other drawback is the potential bias due to the way the samples are collected. We suggest and analyze a sub-sampling technique, where some users are requested only to recruit other users but do not participate to the study. Assuming that the referral has lower cost than actual participation, this technique takes advantage of exploring a larger variety of population, thus decreasing significantly the variance of the estimator. We test the method on real social networks and on synthetic ones. As by-product, we propose a Gibbs like method for generating synthetic networks with desired properties

ns-3 Based Framework for Simulating Communication Based Train Control (CBTC) Systems

International audienceIn a Communication Based Train Control System (CBTC), a central zone controller server (ZC) exchanges signaling messages with on-board carborne controllers (CC) inside the trains through a wireless technology. The ZC calculates and sends periodically to each train its Limit of Movement Authority (LMA), i.e. how far the train can proceed. A CC triggers an emergency break (EB) if no message is received within a certain time interval to avoid collision. Clearly, it is not desired to have an EB due to signaling messages losses (called spurious EB) and not to real risks for the trains. Quantifying the rate of spurious EBs and predicting correctly CBTC system performance are hard tasks with important industrial relevance.This work aims at filling this gap using simulation to better predict CBTC system performance and avoid extra provisioning before deployment. A typical CBTC system implementation for metro by Alstom Transport is considered. New ns-3 modules (CBTC protocol, Video traffic generator, multi-channel scanning mechanism, 3D antennas patterns) are developed and a piece of existing code is enhanced. The simulation is also used to investigate the dimension of the radio access networks in a realistic environment (specific modems and access point antennas, radio frequencies, train and track models), another aspect also ignored in the previous literature. Last, our approach can be useful to validate some analytical works

Performance Evaluation of Train Moving-Block Control

In moving block systems for railway transportationa central controller periodically communicates to the train how far it can safely advance.On-board automatic protection mechanisms stop the train if no message is received during a given time window.In this report we consider as reference a typical implementation of moving-block control for metro and quantify the rate of spurious Emergency Brakes (EBs), i.e.~of train stops due to communication losses and not to an actual risk of collision. Such unexpected EBs can happen at any point on the track and are a major service disturbance. Our general formula for the EB rate requires a probabilistic characterization of losses and delays. We derive an exact formula for the case of homogeneous and independent packet losses and we use the results of this analysis to design an efficient Monte Carlo method that takes into account correlated losses due to handovers. We validate our approach via discrete-event simulations, including simulations with ns-3 for which we have developed additional modules for train systems.Our approach is computationally efficient even when emergency brakes are very rare (as they should be) and can no longer be estimated via discrete-event simulations

Performance Evaluation of Train Moving-Block Control

International audienceIn moving block systems for railway transportation a central controller periodically communicates to the train how far it can safely advance. On-board automatic protection mechanisms stop the train if no message is received during a given time window. In this paper we consider as reference a typical implementation of moving-block control for metro and quantify the rate of spurious Emergency Brakes (EBs), i.e. of train stops due to communication losses and not to an actual risk of collision. Such unexpected EBs can happen at any point on the track and are a major service disturbance. Our general formula for the EB rate requires a probabilistic characterization of losses and delays. Calculations are surprisingly simple in the case of homogeneous and independent packet losses. Our approach is computationally efficient even when emergency brakes are very rare (as they should be) and can no longer be estimated via discrete-event simulations

Performance Evaluation of Train Moving-Block Control

International audienceIn this work we provide a model-based analysis of the moving block control and quantify the rate of spurious emergency brakes (EBs). We consider as a reference a typical implementation for metro by Alstom Transport. We derive the general formula for the EB rate, that requires to provide the loss and delay model. The delay model considers processing delays, computation times and communication delays. For the loss model we start with the case when packet losses are independent and homogeneous. By developing the general formula we derive an exact expression for the EB rate. We proceed then with a more elaborate loss model, when losses are no longer independent.As it becomes hard to derive a closed-form expression for the EB rate, we evaluate it using efficient Monte Carlo simulations. The theoretical results are validated via discrete-event simulations, including simulations with ns-3 for which we have developed additional modules for train systems

Optimal Cache Allocation for Femto Helpers with Joint Transmission Capabilities

International audienceAs cellular network operators are struggling to keep up with the rapidly increasing traffic demand, two key directions are deemed necessary for beyond 4G networks: (i) extensive cell densification to improve spatial reuse, and (ii) storage of content as close to the user as possible to cope with the backhaul constraints and increased interference. However, caching has mostly been studied with an exclusive focus either on the backhaul network (e.g. the "femto-caching" line of work) or on the radio access (e.g. through coded caching or cache-aided CoMP). As a result, an understanding of the impact of edge caching on network-wide and end-to-end performance is lacking. In this paper we investigate the problem of optimal caching in a context where nearby small cells ("femto-helpers") can coordinate not just in terms of what to cache but also to perform Joint Transmission (a type of CoMP). We show that interesting tradeoffs arise between caching policies that improve radio access and ones that improve backhaul, and propose an algorithm that provably achieves an 1/2-approximation ratio to the optimal one (which is NP-hard), and performs well in simulated scenarios

Caching Policies for Delay Minimization in Small Cell Networks with Coordinated Multi-Point Joint Transmissions

International audienceIn 5G and beyond network architectures, operators and content providers base their content distribution strategies on Heterogeneous Networks, where macro and small cells are combined to offer better Quality of Service to wireless users. On top of such networks, edge caching and Coordinated Multi-Point (CoMP) joint transmissions are used to further improve performance. In this paper, we address the average delay minimization problem by first formulating it as a static optimization problem. Even though the problem is NP-hard we are able to solve it via an efficient algorithm that guarantees a 1 2-approximation ratio. We then proceed to propose two fully distributed and dynamic caching policies for the same problem. The first one asymptotically converges to the static optimal solution under the Independent Reference Model (IRM). The second one provides better results in practice under real (nonstationary) request processes. Our online policies outperform existing dynamic solutions that are PHY-unaware