Link Quality Estimation Research Articles

Distance based Reliable and Energy Efficient (DREE) Routing Protocol for Underwater Acoustic Sensor Networks

The distinctive features of Underwater Acoustic Sensor Networks (UW-ASN) such as high propagation delay, asymmetric channels, high errors rates and limited bandwidth cause significant issues due to the use of acoustic medium as a method of communication. Therefore, designing an efficient underwater protocol that make efficient use of available battery resources and provides reliability in unreliable acoustic environment is a challenging task. In this paper, we therefore present a distance based reliable and energy efficient routing protocol (DREE). The contribution in this routing protocol is twofold 1) DREE actually takes in to account physical distance unlike similar protocol R-ERP 2 R where physical distance has not been utilized 2) DREE utilizes Fuzzy logic based link Quality Estimator (F-LQE) which has not been put on the test before in underwater networks. Moreover, DREE extends network lifetime not only by providing energy balancing but by reducing number of transmissions required to deliver a packet successfully. Experiments performed in NS2 simulator prove that DREE contributes to improve results in comparison with R-ERP 2 R which is the similar and only distance based reliable protocol present in literature and well known depth based routing protocol DBR

SLQE: An Improved Link Quality Estimation based on Four-bit LQE

Link quality estimation (LQE) is an effective basic building block in wireless sensor networks (WSNs) and higher cross layer design of network protocol. Some researchers have investigated the statistical properties of the link quality estimators independently from higher-layer protocols, and their impact on the Collection Tree Routing Protocol (CTP). Then they set up a dedicated LQE, independent of the protocol interface, which has in total of four bits information: one from the physical layer, one from the link layer, and two from the network layer. Four-bit has been found to be a good estimator; however its performance heavily depends on the tuning of its parameters. But we found that Fourbit couldn’t be working effectively in responding to the burst situation after repeated experiments. So we redesigned the link estimation method, called Stable Link Quality Estimation (SLQE), which combines active probing with passive snooping to make estimation more stable. We have found that the new design can cope with the emergency. Moreover it also enhances the robustness of the network, and saves the overall energy consumption of the network.

Toward Stable Network Performance in Wireless Sensor Networks: A Multilevel Perspective

Many applications in wireless sensor networks require communication performance that is both consistent and of high quality. Unfortunately, performance of current network protocols can vary significantly because of various interferences and environmental changes. Current protocols estimate link quality based on the reception of probe packets over a short time period. This method is neither efficient nor accurate enough to capture the dramatic variations of link quality. Therefore, we propose a link metric called competence that characterizes links over a longer period of time. We combine competence with current short-term estimations in routing algorithm designs. To further improve network performance, we have designed a distributed route maintenance framework based on feedback control solutions. This framework allows every link along an end-to-end (E2E) path to adjust its link protocol parameters, such as transmission power and number of retransmissions, to ensure specified E2E reliability and latency under dynamic link qualities. Our solutions are evaluated in both extensive simulations and real system experiments. In real system evaluations with 48 T-Motes, our overall solution improves E2E packet delivery ratio over existing solutions by up to 40% while reducing transmission energy consumption by up to 22%. Importantly, our solution also achieves more stable and better transient performance than current approaches.

Estimating Packet Delivery Ratio for Arbitrary Packet Sizes Over Wireless Links

Real life measurements show that on a given wireless link, the packet delivery ratio of different packet lengths varies with longer packets experiencing lower delivery ratios. In this letter, we measure this effect in detail over several different wireless links and technologies. Our results show that the current models are not entirely correct. Hence, we propose a simple modification that rectifies this behavior. Using this new model, we look at how link quality estimation methods can be enhanced to include this modification. Our study shows that the use of two different packet lengths or simple compensation can be used to achieve significantly better estimation of link quality.

A Link Quality Estimation model of Wireless Sensor Networks for Smart Distribution Grid

Recent advances in Micro-electro-mechanical Systems made Wireless Sensor Network (WSN) a viable solution for Smart Distribution Grid communication. However, the transitional and environmentrelated features seriously affect communication link quality in Wireless-Sensor-Network-based smart distribution grid application. In this paper, a novel Link Quality Estimation model is presented to estimate link quality in harsh Distribution Grid environments. By theoretical analysis, background noise fluctuation and signal strength attenuation are considered as main factors affecting link quality. Consequently, Alpha-stable distribution fitting is used for modeling background noise, and Log-distance path loss model is adopted for received signal strength model. In addition, the method of estimating parameters in presented Link Quality Estimation model is introduced along. The experiment result demonstrates that, Link Quality Estimation model is a better and more realistic and accuracy choice.

Link quality estimation in VANETs for multi-hop alert messages dissemination

Reception of alert messages by endangered vehicles at time of an emergency event e.g., a traffic accident is a prime objective of alert messaging protocols in vehicular ad hoc networks VANETs. This work proposes a new bi-directional stable communication BDSC protocol for relay nodes selection in multi-hop alert messages propagation in VANETs. The BDSC protocol is based on a dynamic link quality estimation algorithm. The proposed protocol is evaluated by assessing the alert messages reachability in varying network size and traffic densities. Results obtained from extensive simulation experiments favour the performance of the proposed protocol with a large margin of reachability improvement compared to conventional furthest distance relay selection protocols. In a multi-lane road segment with dense traffic scenario, reachability improvement of approximately 25% is noticed over the furthest distance protocols. This reachability improvement is achieved with comparable end-to-end communication delays to those exhibited by furthest distance-based solutions.

Impact of Energy and Link Quality Indicator with Link Quality Estimators in Wireless Sensor Networks

The Link Quality Indicator (LQI) and Residual Energy have a fundamental impact on the network performance in Wireless Sensor Networks (WSNs) and affects as well in the life time of nodes. This paper will provide a comparative of Link Quality Estimator, the Link Quality Estimator with Link Quality Indicator and Link Quality Estimator with Residual Energy. In this paper we develop a Collect Tree Protocol (CTP) and compare the performance of LQI and Residual Energy, and show their effect on the packet delivery ratio and throughput, covering the characteristics of low-power links, and their performance to the best of our knowledge, we believe that our efforts would have implementations on embedded application.

Cross-Layer QoS Optimization of Wireless Sensor Network for Smart Grid

Wireless Sensor Network (WSN) has been considered as a promising solution for Smart Grid due to the significant advantages over traditional communication technologies. However, as a necessary function for monitoring, diagnosing, and controlling of remote electrical equipment, Quality of Service (QoS) is still a challenging problem in applying WSN in Smart Grid. This paper presents a comprehensive experimental study on optimization of multiobject QoS in cross-layers of WSN protocol. In PHY layer, a Link Quality Estimator is studied for the purpose of evaluating link quality under harsh Smart Grid environments. In MAC layer, a QoS Enhanced MAC algorithm is used to prevent disorderly contentions among nodes and to allocate more channel resources for critical traffic; in NWK layer, a routing algorithm is introduced for multiobject QoS optimization. All the algorithms are cooperated with each other in cross-layer manner to improve end-to-end reliability and latency. In comparison with other counterparts, the proposed algorithms achieve preferable performances. Finally, field experiments were conducted, the result of which showed that the proposed algorithms outperform the ZigBee protocol and the original Distribution Grid wireless communication technology in terms of the QoS performance of critical traffic.

Link performance model for filter bank based multicarrier systems

This paper presents a complete link level abstraction model for link quality estimation on the system level of filter bank multicarrier (FBMC)-based networks. The application of mean mutual information per coded bit (MMIB) approach is validated for the FBMC systems. The considered quality measure of the resource element for the FBMC transmission is the received signal-to-noise-plus-distortion ratio (SNDR). Simulation results of the proposed link abstraction model show that the proposed approach is capable of estimating the block error rate (BLER) accurately, even when the signal is propagated through the channels with deep and frequent fades, as it is the case for the 3GPP Hilly Terrain (3GPP-HT) and Enhanced Typical Urban (ETU) models. The FBMC-related results of link level simulations are compared with cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) analogs. Simulation results are also validated through the comparison to reference publicly available results. Finally, the steps of link level abstraction algorithm for FBMC are formulated and its application for system level simulation of a professional mobile radio (PMR) network is discussed.

Reliable link quality estimation in low-power wireless networks and its impact on tree-routing

Radio link quality estimation is essential for protocols and mechanisms such as routing, mobility management and localization, particularly for low-power wireless networks such as wireless sensor networks. Commodity Link Quality Estimators (LQEs), e.g. PRR, RNP, ETX, four-bit and RSSI, can only provide a partial characterization of links as they ignore several link properties such as channel quality and stability. In this paper, we propose F-LQE (Fuzzy Link Quality Estimator, a holistic metric that estimates link quality on the basis of four link quality properties—packet delivery, asymmetry, stability, and channel quality—that are expressed and combined using Fuzzy Logic. We demonstrate through an extensive experimental analysis that F-LQE is more reliable than existing estimators (e.g., PRR, WMEWMA, ETX, RNP, and four-bit) as it provides a finer grain link classification. It is also more stable as it has lower coefficient of variation of link estimates. Importantly, we evaluate the impact of F-LQE on the performance of tree routing, specifically the CTP (Collection Tree Protocol). For this purpose, we adapted F-LQE to build a new routing metric for CTP, which we dubbed as F-LQE/RM. Extensive experimental results obtained with state-of-the-art widely used test-beds show that F-LQE/RM improves significantly CTP routing performance over four-bit (the default LQE of CTP) and ETX (another popular LQE). F-LQE/RM improves the end-to-end packet delivery by up to 16%, reduces the number of packet retransmissions by up to 32%, reduces the Hop count by up to 4%, and improves the topology stability by up to 47%.

COLLECTIVE APPROACH FOR MANETS TO SUPPORT PACKET LOSS AND DELAY SENSITIVE APPLICATIONS IN REAL

Mobile ad hoc network is network with different applications are developing with different service requirement. In particular multimedia applications and other real-time applications e.g. voice transmission. MANET is a autonomous network where communicating entities can communicate without the aid of any downlink power controller called base stations. Therefore there is no centralized control over links. Further the link quality varies due to mobility of the nodes. Existing routing protocols like AODV or any other QoS routing does not account for changes in link quality once the path is established. Therefore the performance of such a system degrades with high mobility. Hence in this work we emphasis on incorporating link quality estimation based on mobility prediction along with Node's geographic location and incorporate same in the routing decision further new routes are accumulated and the primary transmission path is changed in case a better route in terms of link quality is obtained. We mingled the idea of link stability and power consumption with Location aware routing to propose a new technique for MANET that reduces control overhead and provides better performance.

Temporal Adaptive Link Quality Prediction with Online Learning

Link quality estimation is a fundamental component of the low-power wireless network protocols and is essential for routing protocols in Wireless Sensor Networks (WSNs). However, accurate link quality estimation remains a challenging task due to the notoriously dynamic and unpredictable wireless environment. In this article we argue that, in addition to the estimation of current link quality, prediction of the future link quality is more important for the routing protocol to establish low-cost delivery paths. We propose to apply machine learning methods to predict the link quality in the near future to facilitate the utilization of intermediate links with frequent quality changes. Moreover, we show that, by using online learning methods, our adaptive link estimator (TALENT) adapts to network dynamics better than statically trained models without the need of a priori data collection for training the model before deployment. We implemented TALENT in TinyOS with Low-Power Listening (LPL) and conducted extensive experiments in three testbeds. Our experimental results show that the addition of TALENT increases the delivery efficiency 1.95 times on average compared with a 4B, state-of-the-art link quality estimator, as well as improves the end-to-end delivery rate when tested on three different wireless testbeds.

Comparison of QoS-aware single-path vs. multi-path routing protocols for image transmission in wireless multimedia sensor networks

Wireless multimedia sensor network (WMSN) applications require strong multimedia communication competence. Therefore, in WMSN applications, it is necessary to use specific mechanisms in order to handle multimedia communication challenges and address desired energy efficiency and reliability goals. Nevertheless, the existing communication protocols are not suitable for the communication challenges and the desired goals. In this respect, specific mechanisms for prioritization, link-quality estimation and multi-path selection can be employed by quality of service (QoS)-aware routing protocols to meet the reliability and delay requirements of WMSN applications.In this study a novel approach is proposed to set different reliability values for image packets for image transmission in WMSNs. Using this prioritization, important parts of an image are assigned high priority and take priority during data transmission. In order to evaluate the proposed approach, the performance of single-path and multi-path QoS-aware routing protocols has been investigated for WMSN-based image transmission applications. Specifically, comparative performance analysis of single-path routing and multi-path routing in image transmission have been conducted in terms of peak signal-to-noise ratio (PSNR), average delay, reachability, and control overhead. As proven by the results of the performance evaluations in this study, multi-path routing is better than single-path routing in terms of reliability. On the other hand, at high traffic loads, multi-path routing may perform worse in terms of delay due to its associated overhead.

LIPS: Link Prediction as a Service for data aggregation applications

A central component of the design of wireless sensor networks is reliable and efficient transmission of data from source to destination. However, this remains a challenging problem because of the dynamic nature of wireless links, such as interference, diffusion, and path fading. When the link quality gets worse, packets will get lost even with retransmissions and acknowledgments when internal queues become full. For example, in a well-known study to monitor volcano behavior (Werner-Allen et al., 2006), the measured data yield of nodes ranges from 20% to 80%. To address this challenge brought by unreliable links, in this paper, we propose the idea of LIPS, or Link Prediction as a Service. Specifically, we argue that it is beneficial for applications to be aware of link layer variations, so that they can take into account the future link quality estimates based on past measurements. In particular, we present a novel state space based approach for the link quality prediction, and demonstrate that it is possible to integrate this model into operating system interfaces, so that higher layer data aggregation protocols can directly exploit these interfaces to improve their performance. Our intensive evaluation indicates the state space based approach is accurate, stable and lightweight comparing to other strategies such as the autoregressive model (Liu and Cerpa, 2010). We carry out experiments based on the commonly used sensor node hardware including both link layer and operating system measurements.

Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications.

An Analytical Framework for Disconnection Prediction in Wireless Networks

The stability and reliability of links in wireless networks is dependent on a number of factors such as the topology of the area, inter-base station or inter-mobile station distances, weather conditions and so on. Link instability in wireless networks has a negative impact on the data throughput and thus, the overall quality of user experience, even in the presence of sufficient bandwidth. An estimation of link quality and link availability duration can drastically increase the performance of these networks, allowing the network or applications to take proactive measures to handle impending disconnections. In this paper we look at a mathematical model for predicting disconnection in wireless networks. This model is originally intended to be implemented in base stations of cellular networks, but is independent of the wireless technology and can thus be applied to different types of networks with minimum changes.

Determining Fuzzy Link Quality Membership Functions in Wireless Sensor Networks

Wireless Sensor Network routing protocols rely on the estimation of the quality of the links between nodes to determine a suitable path from the data source nodes to a data-collecting node. Several link estimators have been proposed, but most of these use only one link property. Fuzzy logic based link quality estimators have been recently proposed which consider a number of link quality metrics. In this work, we implemented the Fuzzy logic based link estimator in the WiseRoute routing protocol, which is a collection style protocol in MiXiM. We also present an experimental approach to determine a suitable fuzzy membership function based on varying the shape of the fuzzy set for a multipath wireless sensor network scenario and choosing an optimum shape that maximizes the Packet Delivery Ratio of the network. The computed fuzzy set membership functions were evaluated against an existing fuzzy link quality estimator under typical scenarios and it is shown the performance of the experimental optimal membership function was better in terms of packet reception ratio and end-to-end delay.

Data-driven link quality prediction using link features

As an integral part of reliable communication in wireless networks, effective link estimation is essential for routing protocols. However, due to the dynamic nature of wireless channels, accurate link quality estimation remains a challenging task. In this article, we propose 4C, a novel link estimator that applies link quality prediction along with link estimation. Our approach is data driven and consists of three steps: data collection, offline modeling, and online prediction. The data collection step involves gathering link quality data, and based on our analysis of the data, we propose a set of guidelines for the amount of data to be collected in our experimental scenarios. The modeling step includes offline prediction model training and selection. We present three prediction models that utilize different machine learning methods, namely, naive Bayes classifier, logistic regression, and artificial neural networks. Our models take a combination of PRR and the physical-layer information, that is, Received Signal Strength Indicator (RSSI), Signal-to-Noise Ratio (SNR), and Link Quality Indicator (LQI) as input, and output the success probability of delivering the next packet. From our analysis and experiments, we find that logistic regression works well among the three models with small computational cost. Finally, the third step involves the implementation of 4C, a receiver-initiated online link quality prediction module that computes the short temporal link quality. We conducted extensive experiments in the Motelab and our local indoor testbeds, as well as an outdoor deployment. Our results with single- and multiple-senders experiments show that with 4C, CTP improves the average cost of delivering a packet by 20% to 30%. In some cases, the improvement is larger than 45%.

Fuzzy Logic Based Multidimensional Link Quality Estimation for Multi-Hop Wireless Sensor Networks

In the applications of multi-hop wireless sensor networks, the effective evaluation of wireless link quality which can improve the network reliability is a crucial problem in the design of network protocols. The lossy and dynamic nature of the radio channel, however, makes link quality estimation a great challenge. First, we use data-driven modeling and statistical inference methods to model the burstiness of wireless link packet loss, which reflects the reliability of packet retransmission in the data link layer. Then, from a multidimensional view of characterizing the wireless link quality, we present the fuzzy logic based link quality indicator (FLI), which is a comprehensive reflection of single hop reliability of packet delivery, link volatility, and packet loss burst. Finally, we implement a wireless link quality estimator based on FLI in the collection tree protocol (CTP). Through the experimental comparison with the original link quality estimator in the CTP, the network performance with the new link quality estimator guarantees high end to end delivery reliability, while the average routing depth of the nodes and the dynamic changes of network topology are reduced.

On Adaptive Energy-Efficient Transmission in WSNs

One of the major challenges in design of wireless sensor networks (WSNs) is to reduce energy consumption of sensor nodes to prolong lifetime of finite capacity batteries. In this paper, we propose energy-efficient adaptive scheme for transmission (EAST) in WSNs. EAST is an IEEE 802.15.4 standard compliant. In this scheme, open-looping feedback process is used for temperature-aware link quality estimation and compensation, wherea closed-loop feedback process helps to divide network into three logical regions to minimize overhead of control packets. Threshold on transmitter power loss ([Formula: see text]) and current number of nodes ([Formula: see text]( t)) in each region help to adapt transmit power level ([Formula: see text]) according to link quality changes due to temperature variation. Evaluation of the proposed scheme is done by considering mobile sensor nodes and reference node both static and mobile. Simulation results show that the proposed scheme effectively adapts transmission [Formula: see text] to changing link quality with less control packets overhead and energy consumption as compared to classical approach with single region in which maximum transmitter [Formula: see text] assigned to compensate temperature variation.