RadiaLE: A framework for designing and assessing link quality estimators in wireless sensor networks

Abstract

Stringent cost and energy constraints impose the use of low-cost and low-power radio transceivers in large-scale wireless sensor networks (WSNs). This fact, together with the harsh characteristics of the physical environment, requires a rigorous WSN design. Mechanisms for WSN deployment and topology control, MAC and routing, resource and mobility management, greatly depend on reliable link quality estimators (LQEs). This paper describes the RadiaLE framework, which enables the experimental assessment, design and optimization of LQEs. RadiaLE comprises (i) the hardware components of the WSN testbed and (ii) a software tool for setting-up and controlling the experiments, automating link measurements gathering through packets-statistics collection, and analyzing the collected data, allowing for LQEs evaluation. We also propose a methodology that allows (i) to properly set different types of links and different types of traffic, (ii) to collect rich link measurements, and (iii) to validate LQEs using a holistic and unified approach. To demonstrate the validity and usefulness of RadiaLE, we present two case studies: the characterization of low-power links and a comparison between six representative LQEs. We also extend the second study for evaluating the accuracy of the TOSSIM 2 channel model.

Introduction

Wireless sensor networks (WSNs) typically have severe constraints on energy consumption since nodes have to survive on a limited battery energy for extended periods of time, up to several years. This fact brings network protocols designers to provide energy-efficient solutions, namely in what concerns medium-access control (MAC), routing, mobility management, and topology control protocols. One of the most important requirements to achieve this goal is to avoid excessive retransmissions over low quality links. Therefore, link quality estimation emerges as a fundamental building block for network protocols to maximize the lifetime, the reliability, and the throughput of WSNs.

Several link quality estimators (LQEs) have been reported in the literature (e.g. [1], [2], [3], [4], [5]). They can be classified as either hardware-based or software-based. Hardware-based LQEs, such as Link Quality Indicator (LQI), Received Signal Strength Indicator (RSSI) and Signal to Noise Ratio (SNR) are directly read from the radio transceiver (e.g. the CC2420) upon packet reception. Most software-based LQEs enable to either count or approximate the packet reception ratio or the average number of packet transmissions/retransmissions.

The accuracy of link quality estimation greatly impacts the efficiency of network protocols. For instance, many routing protocols, e.g. [2], [6], [7], rely on link quality estimation to select high quality routes for communication. The more accurate the link quality estimation is, the more correct the decision made by routing protocols in selecting such routes. This is just one example on how important it is to assess the performance of the LQE before integrating it into a particular network protocol.

The experimental performance evaluation of LQEs requires performing link measurements through packet-statistics collection. Several testbeds have been designed for the experimentation (test, validation, performance evaluation, etc.) of WSNs [8], [9], [10], [11], [12], but only [13], [14] targeted link measurements. However, these were exploited for analyzing low-power link characteristics rather than for the performance evaluation of LQEs. Namely, they do not provide sufficient data to compute most LQEs, especially sender-side ones (refer to Section 3.2 for further intuition on sender-side and receiver-side LQEs).

Despite its importance, the experimental performance evaluation of LQEs remains an open problem. One of the reasons is the impossibility, or at least the difficulty, to provide a quantitative evaluation of the accuracy of LQEs. In fact, there is no objective link quality metric to which the link quality estimate can be compared. Furthermore, there are LQEs that are based on the packet reception ratio (PRR), some others are based on packet retransmission count (i.e. RNP) and some others are hybrid and more complex. Thus, comparing their performance becomes challenging as they have different natures. These facts motivated us to build a framework – RadiaLE, aiming at the experimental evaluation, design and optimization of LQEs.

The RadiaLE framework [15] comprises (i) hardware components of the WSN testbed and (ii) a software tool for setting-up and controlling the experiments and also for analyzing the collected data, allowing for LQEs evaluation. In fact, RadiaLE is much more than an experimental testbed. It stands for a methodology that allows researchers (i) to properly set different types of links and different types of traffics, (ii) to collect a rich database of link measurements, and (iii) to validate their solutions using a holistic and unified approach. Furthermore, RadiaLE can be used to validate the accuracy of the channel model of network simulators by replaying the performed experiments using the simulator under consideration and comparing the simulation results against the experimental results.

This paper makes the following three main contributions:

• First, we propose RadiaLE, a new experimental testbed dedicated to perform the empirical evaluation of link quality estimators (Sections 3 Methodology, 4 RadiaLE implementation).

• Second, we present an empirical study demonstrating the capabilities of RadiaLE for the characterization of low-power links and the performance evaluation of LQEs (Section 5).

• Third, we examine the accuracy of the wireless channel model of TOSSIM 2 by comparing simulation results with empirical results obtained with RadiaLE (Section 6).