Yvonne Anne Pignolet

Efficiency of Wireless Networks: Approximation Algorithms for the Physical Interference Model

In this monograph we survey results from a newly emerging line of research that targets algorithm analysis in the physical interference model. In the main part of our monograph we focus on wireless scheduling: given a set of communication requests, arbitrarily distributed in space, how can these requests be scheduled efficiently? We study the difficulty of this problem and we examine algorithms for wireless scheduling with provable performance guarantees. Moreover, we present a few results for related problems and give additional context.

Speed Dating Despite Jammers

Many wireless standards and protocols today, such as WLAN and Bluetooth, operate on similar frequency bands. While this permits an efficient usage of the limited medium capacity, transmissions of nodes running different protocols can interfere. This paper studies how to design node discovery algorithms for wireless multichannel networks which are robust against contending protocols on the shared medium. We pursue a conservative approach and consider a Byzantine adversary who prevents the communication of our protocol on t channels in a worst-case fashion. Our model also captures disruptions controlled by an adversarial jammer . This paper presents algorithms for scenarios where t is not known. The analytical findings are complemented by simulations providing evidence that the proposed protocols perform well in practice.

A Note on Uniform Power Connectivity in the SINR Model

In this paper we study the connectivity problem for wireless networks under the Signal to Interference plus Noise Ratio (SINR) model. Given a set of radio transmitters distributed in some area, we seek to build a directed strongly connected communication graph, and compute an edge coloring of this graph such that the transmitter-receiver pairs in each color class can communicate simultaneously. Depending on the interference model, more or less colors, corresponding to the number of frequencies or time slots, are necessary. We consider the SINR model that compares the received power of a signal at a receiver to the sum of the strength of other signals plus ambient noise . The strength of a signal is assumed to fade polynomially with the distance from the sender, depending on the so-called path-loss exponent ?. We show that, when all transmitters use the same power, the number of colors needed is constant in one-dimensional grids if ?> 1 as well as in two-dimensional grids if ?> 2. For smaller path-loss exponents and two-dimensional grids we prove upper and lower bounds in the order of

Distributed minimum dominating set approximations in restricted families of graphs

\mathcal{O}(\log n)

On the Power of Uniform Power: Capacity of Wireless Networks with Bounded Resources

and ?(logn/loglogn) for ?= 2 and ?(n 2/?? 1) for ?< 2 respectively. If nodes are distributed uniformly at random on the interval [0,1], a regular coloring of

Energy-efficiency through micro-managing communication and optimizing sleep

\mathcal{O}(\log n)

Time-optimal information exchange on multiple channels

colors guarantees connectivity, while ?(loglogn) colors are required for any coloring.

Distributed power control in the SINR model

A dominating set is a subset of the nodes of a graph such that all nodes are in the set or adjacent to a node in the set. A minimum dominating set approximation is a dominating set that is not much larger than a dominating set with the fewest possible number of nodes. This article summarizes the state-of-the-art with respect to finding minimum dominating set approximations in distributed systems, where each node locally executes a protocol on its own, communicating with its neighbors in order to achieve a solution with good global properties. Moreover, we present a number of recent results for specific families of graphs in detail. A unit disk graph is given by an embedding of the nodes in the Euclidean plane, where two nodes are joined by an edge exactly if they are in distance at most one. For this family of graphs, we prove an asymptotically tight lower bound on the trade-off between time complexity and approximation ratio of deterministic algorithms. Next, we consider graphs of small arboricity, whose edge sets can be decomposed into a small number of forests. We give two algorithms, a randomized one excelling in its approximation ratio and a uniform deterministic one which is faster and simpler. Finally, we show that in planar graphs, which can be drawn in the Euclidean plane without intersecting edges, a constant approximation factor can be ensured within a constant number of communication rounds.

Adversarial VNet embeddings: A threat for ISPs?

The throughput capacity of arbitrary wireless networks under the physical Signal to Interference Plus Noise Ratio (SINR) model has received much attention in recent years. In this paper, we investigate the question of how much the worst-case performance of uniform and non-uniform power assignments differ under constraints such as a bound on the area where nodes are distributed or restrictions on the maximum power available. We determine the maximum factor by which a non-uniform power assignment can outperform the uniform case in the SINR model. More precisely, we prove that in one-dimensional settings the capacity of a non-uniform assignment exceeds a uniform assignment by at most a factor of O(logL max ) when the length of the network is L max . In two-dimensional settings, the uniform assignment is at most a factor of O(logP max ) worse than the non-uniform assignment if the maximum power is P max . We provide algorithms that reach this capacity in both cases. Due to lower bound examples in previous work, these results are tight in the sense that there are networks where the lack of power control causes a performance loss in the order of these factors. As a consequence, engineers and researchers may prefer the uniform model due to its simplicity if this degree of performance deterioration is acceptable.

Evaluation of RPL for medium voltage power line communication

Energy-efficiency is key to meet lifetime requirements of Wireless Sensor Networks (WSN) applications. Todays run-time platforms and development environments leave it to the application developer to manage power consumption. For best results, the characteristics of the individual hardware platforms must be well understood and minutely directed. An Operating System (OS) with suitable programming abstractions can micro-manage power consumption of resources. We demonstrate with the Mote Runner platform how the inherent overhead of managed application code is compensated for by a platform-independent communication API together with sleep optimizations. The proposed abstractions and optimizations can be applied to other modern sensor network platforms. To quantify the effectiveness of our approach, we measured the energy efficiency of a real-world WSN application using a custom TDMA communication protocol fully implemented on both Mote Runner and TinyOS. Mote Runners power management and sleep phase optimizations outperforms TinyOS in our test application for duty cycles below 10% on the Iris hardware.