Stephan Robert

Dynamic tuning of the maximum contention window (CWmax) for enhanced service differentiation in IEEE 802.11 wireless ad-hoc networks

The proposed IEEE 802.11e draft standard defines new MAC protocols for QoS in wireless networks, mainly EDCF and HCF. In this paper, we propose to extend EDCF with a dynamic adaptation algorithm of the maximum contention window (CWmax) that enables each station to tune the size of the CWmax used in its back-off algorithm at run time. The purpose of our scheme is to reduce delay and jitter and increases the efficiency of the transmission channel. Priorities between access categories are provisioned by updating the size of the CWmax according to application requirements and channel conditions. The performance of the enhanced EDCF are extensively investigated by simulation. Results obtained indicate that the delay and jitter for high priority traffic, i.e., audio traffic, improve and delay decreases by up to 43%. Furthermore, delay for lower priority traffic, e.g., video traffic, remains stable. Throughput in CWmax adaptation, compared to EDCF, is stable in light and medium system load and increases by up to 7% especially at high system load.

Can Self-Similar Traffic Be Modeled by Markovian Processes?

In this paper, we compare high time resolution local area network (LAN) traffic with three different traffic models: Poisson, ON-OFF and 5-state Markov process. Due to the measured datas extreme variability on time scales ranging from milliseconds to days, it is difficult to find a model for it, especially a Markovian one. Recent studies show that conventional models do not capture the characteristics of the observed traffic. Fractal-based models have already been built to characterize such a traffic but they are not easily tractable tractability of them is not great. Through a new method which integrates different time scales in the model, we have tried to find a quite simple Markovian process having the same behavior as the measured traffic on the LAN. We show in particular that a simple 5-state Markov process integrating different time scales can reasonably model the behavior of measured traffic up to a certain time interval.

Dynamic tuning of the contention window minimum (CW/sub min/) for enhanced service differentiation in IEEE 802.11 wireless ad-hoc networks

The proposed IEEE 802.11e draft standard defines new MAC protocols for QoS in wireless networks, mainly HCF (hybrid coordination function) and EDCF (enhanced distributed coordination function). EDCF is a contention-based channel access scheme and is part of HCF for infrastructure networks and may be used as a separate coordination function for wireless ad-hoc networks. We propose to extend EDCF with a dynamic adaptation algorithm for the minimum contention window (CW/sub min/) that enables each station to tune the size of the CW/sub min/ used in its back-off algorithm at run time. The purpose of our scheme is to reduce delay and jitter and increase the efficiency of the transmission channel. Priorities between access categories are provisioned by tuning the size of the CW/sub min/ according to application requirements and channel conditions. The performances of the IEEE 802.11e EDCF, enhanced with our adaptation algorithm, are extensively investigated by simulation. Results obtained indicate that the CW/sub min/ adaptation scheme outperforms the 802.11e EDCF standard in terms of channel utilization, throughput, and packet delay. Indeed, the delay for the high priority access category decreases by up to 30%, total throughput increases by up to 18%, and channel capacity is at least 15% higher.

Which Arrival Law Parameters Are Decisive for Queueing System Performance

Abstract This paper addresses the problem of finding the decisive parameters, the so-called key parameters, of a queueing system which most significantly influence expected occupation and loss of a finite capacity queue. It is shown that the key parameters of observational data, which are the expected arrival rate, the expected service rate and the spectral density at the frequency zero of the difference between arrivals and service time most significantly influence the performance of the queueing system. An algorithm is developed which shows that it is mostly possible to fit an MMPP(2) to the key parameters. A numerical example illustrates the importance of the key parameters and also shows the accuracy of the proposed fitting procedure.

Toward the Deployment of an Ultra-Wideband Localization Test Bed

The design, development, and deployment of Ultra-Wideband (UWB) localization systems involves digital and Radio-Frequency (RF) hardware, embedded software, localization algorithms, security and reliability aspects, electromagnetics, and others. Design and integration decisions affect the performance of an UWB system, in particular the most important metrics: localization accuracy and position update rate. To facilitate further development of UWB localization systems and to analyze some of the major trade-offs we share our experience in deploying the EPFL UWB-Lite test bed (U-Lite). We describe an approach to numerical simulation modeling that can help in the design and evaluation of UWB localization systems. To validate our approach we show experimental results with one transmitter and one receiver. Our UWB test bed includes a mobile robot platform, so we can study and evaluate the UWB performance trade-offs in real-world conditions.

Concurrent transmissions in IR-UWB networks: an experimental validation

We demonstrate and validate that concurrent and parallel transmissions are feasible for low data-rate impulse-radio ultra-wide band (IR-UWB) physical layers. The optimal organization for a low data-rate IR-UWB network is to allow for concurrent transmissions at the link layer, and to use interference mitigation techniques at the physical layer. Indeed, low data-rate IR-UWB physical layers can suffer from multi-user interference (MUI), especially in near-far scenarios. Therefore, we perform an experimental validation with a packet-based, low data-rate IR-UWB physical layer testbed. Our results clearly demonstrate that concurrent IR-UWB transmissions are possible. This shows that completely uncoordinated low data-rate IR-UWB networks are feasible. We also demonstrate that, in the presence of MUI, an interference mitigation scheme at the physical layer is indeed necessary. In particular, because it is the first component for the proper reception of a packet, we focus on packet detection and timing acquisition. We show that a traditional scheme is not robust against multi-user interference and prevents concurrent transmissions. On the contrary, a scheme designed to take MUI into account, even with a very simple interference mitigation scheme, allows for concurrent transmissions, even in strong near-far scenarios.

Modeling and benchmarking Ultra-Wideband localization for mobile robots

Ultra-Wideband Impulse Radio (UWB-IR) is a technology that has great potential to solve numerous mobile robotic and asset tracking problems in GPS-denied environments. Our goal is to help software and hardware designers in improving the state-of-the-art in UWB-based robotic localization. We developed a test-bed where an UWB transmitter is attached to a mobile robot. By combining the received signals with the robots position log acquired through the dead-reckoning sensors, we obtain UWB signals which are well referenced with respect to the transmitter-receiver distance and orientation. In addition, we provide a model for every component of the setup. The entire setup allows us to simulate from first principles every aspect of an UWB localization system and then to implement low-level signal processing as well as higher-level modulation and localization techniques. We implement an Automatic Gain Control (AGC) algorithm to demonstrate the rapid proto-typing capabilities of the test-bed. Our work shows how an UWB robotic system and its models can be involved in all phases of the development of a technology that can help robots navigation, localization and communication algorithms.

Predictive Caching in Computer Grids

We present a model for predictive caching where a shared cache is used to improve performance across a grid. Unlike local caching mechanisms, shared, grid or cloud-based caches incur high costs or latency associated with the additional data transfer. Our proposed caching model, which is dynamically optimized and constantly updated over time, determines the optimal allocation of objects into the shared cache, in such a way that the total cost or latency is minimized. This is achieved by including in the caching algorithm design measures of grid latency, data retrieval costs and a predictive component based on the probability of cached objects being requested in the near future.

A Cloud data center optimization approach using dynamic data interchanges

Distributed data center architectures have been recently developed for a more efficient and economical storage of data. In many models of distributed storage, the aim is to store the data in such a way so that the storage costs are minimized and increased redundancy requirements are maintained. However, many approaches do not fully consider issues relating to delivering the data to the end user and the associated costs that this creates. We present an integer programming optimization model for determining the optimal allocation of data components among a network of Cloud data servers in such a way that the total costs of additional storage, estimated data retrieval costs and network delay penalties is minimized. The method is suitable for periodic dynamic reconfiguration of the Cloud data servers, so that the when localized data request spikes occur the data can be moved to a closer or cheaper data server for cost reduction and increased efficiency.

Decisive arrival law parameters and a general finite capacity queueing problem

This paper addresses the problem of finding the parameters of the arrival law which most significantly influence expected occupation and loss of a finite capacity queue. The input process is supposed to be ergodic and wide sense stationary. We show that it is mostly possible to fit an MMPP(2) to the decisive parameters of observational data. Numerical examples illustrate the importance of the decisive parameters, called key parameters, and also show the accuracy of the proposed fitting procedure. Finally, in the appendix we present the solution of the finite capacity queueing problem with Special Semi Markov Process (SSMP) arrivals and a general service strategy.