Link Quality Estimation Research Articles

MCLMR: A Multicriteria Based Multipath Routing in the Mobile Ad Hoc Networks

In Mobile Ad hoc Networks (MANETs), nodes’ mobility, traffic congestion, and link quality estimation of the intermediate nodes are very crucial factors for establishing a reliable forwarding path between a source and destination node pairs. The unpredictable movement of nodes and random data traffic flow at a single node can cause congestion and network topology instability, which significantly lowers the performance of the ad hoc network. Indeed, the above-highlighted issues can be mitigated by implementing a more reliable mobility-centric, contention, and link quality-aware routing protocol for efficient data transmissions in a mobile network. This paper proposes a routing strategy called Mobility, Contention window, and Link quality sensitive multipath Routing (MCLMR) in MANETs, which considers the nodes mobility, contention window size, and link quality estimated value of the intermediate nodes in the optimal route selection. Also, Technique for Order of Preference by Similarity to Ideal Solution; a multicriteria decision-making technique, which provides weights according to node mobility, contention window size, and link quality estimated values, is also employed for the selection of intermediate nodes, whereas the Expected Number of Transmissions metric is used to minimize the effect of control message storm. The extensive simulations results prove that the proposed MCLMR routing scheme outperforms the conventional Multipath Optimized Link State Routing (MP-OLSR) and MP-OLSRv2 routing schemes in terms of network throughput, end-to-end delay, energy consumption, and packets loss ratio.

Lightweight, Fluctuation Insensitive Multi-Parameter Fusion Link Quality Estimation for Wireless Sensor Networks

Accurate and agile link quality estimation is essential for wireless sensor networks. Using the mapping models between physical layer parameters and packet reception ratio, link quality can be estimated with advantages of high agility and low overhead. However, existing estimators based on physical layer parameters fail to utilize link quality information carried by different physical layer parameters efficiently and effectively and fail to effectively solve the problem that physical layer parameters fluctuate greatly, which makes them difficult to describe link conditions really. In this study, a lightweight, fluctuation insensitive multi-parameter fusion link quality estimator is proposed. Two physical layer parameters, Signal-to-Noise Ratio and Link Quality Indicator are preprocessed by exponential weighted Kalman filtering to get more stable estimation values. Then, these two parameters are fused using lightweight weighted Euclidean distance to fully utilize link quality information carried by them. On this basis, link quality is estimated quantitatively with the mapping model of the fused parameter and packet reception ratio, which is constructed by logistic regression. Experimental results show that the proposed estimator could reflect link quality more realistically. Compared with similar estimators, estimate error of the proposed one is reduced by 18.32% to 60.11% under moderate and bad links with large fluctuations, by 1.42% to 83.43% under sudden changed links, and by 16.64% to 65.61% under a long-time link. More importantly, computation overhead of the proposed estimator is equivalent to that of single-parameter estimators, but much less than other multi-parameter fusion estimators. Compared with the later, computation overhead is reduced by 72.36% to 95.61%.

Efficient Multipath Routing to Increase QoS by Link Estimation and Minimum Interference path in MANET'S

Many significant techniques have been developed for real time transmission to meet stringent QoS for various applications of wireless sensor network. However routing in MANET’s still a challenging issue to achieve QoS due to frequent topology changes and its dynamic nature. For majority MANET applications, on demand multi path data routing protocols have been modelled to transfer data in multiple routes to prove its effectiveness on link disjoints and high packet delivery ratio. However due to mobility and underlying medium, multiple routes are exposed to interference and low power unstable link quality which are essential to guarantee QoS in routing. In this paper we propose link quality estimation and minimum path interference based on Geographic adhoc on demand multi path distance vector (GAOMDV) an adaptation of AOMDV routing protocol. To ensure the reliability of MANET’s this adaptation is done by considering routing metrics. GAOMDV selects forwarding neighbour nodes based on link quality and minimum path interference across multiple paths and ensures high stable links between nodes. Extensive simulation is carried on discrete event simulation tool and performance of GAOMDV is analysed in terms of network QoS parameters.

TAMU‐RPL: Thompson sampling‐based multichannel RPL

AbstractFor the success of critical applications in the IoT, there is a need to counteract the effects of external interference, especially when the unlicensed spectrum is used. One way of improving the performance is with a routing protocol that quickly reacts to changes in the environment and avoids path and/or frequencies with higher interference. In this paper, we propose an optimization to the RPL protocol, called TAMU‐RPL, that can keep a more accurate estimation of link quality to the neighbors and quickly react to degradation on the links. TAMU‐RPL also uses the quality of links at different frequencies and opportunistically avoids the ones with bad quality. It is evaluated through simulations with connectivity traces from a 40‐node test bed and in a real 5‐node deployment. We compare TAMU‐RPL with a baseline RPL protocol and a Dijkstra‐based shortest‐path algorithm. Results show that TAMU‐RPL can successfully explore the neighbors and obtain ETX values much closer to the ones obtained with a shortest‐path tree, even when link quality changes over time. In the simulation evaluation, TAMU‐RPL was able to double the number of packets received at the sink compared to RPL and reduced the average delay of packets (in time slots) by more than 10%. In the real deployment, the number of packets received at the sink was increased by more than 33%.

Hybrid Cross Layer Fault Resilient Energy Efficient Data Transmission for Underwater Acoustic Sensor Networks

Under water acoustic sensor network is the unique case of wireless sensor network in which the physical characteristics limits the capability of sensor network due to various problems like Doppler-spreads, medium significnt delay, Double-side spreading, limited bandwidth and frequency-selective fading. Ensuring QOS is very challenging problem in acoustic sensor networks. In this work, a QOS centric hybrid routing protocol with consideration of fault resilience is proposed. The solution use the parameters of the network at all Application Layer, Network Layer, MAC Layer, and PHY Layer, which are the different layers of IEEE 802.15.4 protocol stack, thus calculating Node selection score which helps in identifying the best forwarding node for a constrained reliable data transmission. The solution involves dynamic link quality estimation, congestion awareness, packet injection ratio estimation and physical switching that cumulatively ensures fault-resilient and QoS delivery over acoustic sensor network.

Efficient on Demand Routing Protocol to Optimize Throughput in Manet

Throughput oriented route selection is still a challenging task due to several constraints of ad-hoc networks such as absence of central control, dynamic network topology, selfish nature of nodes, etc. A routing protocol produce optimum results if it prioritizes wireless links on the basis of link quality and consider high quality/ efficient links at the time of path selection. Proposed protocol discovers high quality/ efficient links and connects those links to establish efficient route in mobile ad-hoc network that leads to high Aggregate Network Throughput. This work has been done by estimating every link’s ENT (Expected Number of Transmission) value as QoS parameter and considering qualifying high capacity/efficient links to communicate data packets. To estimate ENT value of each link, variability in packet loss rate on that link is observed in simulation experiments. Probability of errors in transmission is estimated at bit level. Results are stochastic and high fluctuations observed in packet loss rate hence (i.e. packet loss variance on a wireless link) included in link quality estimation. In proposed protocol EODRP (Efficient On Demand Routing Protocol) link quality based route metric ENT, selects QoS qualified wireless links during route computation and routing information disperse through reactive routing protocol. Simulation results have been analyzed and compared with MXAODV [7] which indicates significant improvement in network efficiency in terms of throughput and other parameters.

Enhanced Routing for Low Power and Lossy Network Based on Link Quality Estimation

Internet of Things (IoT) network is designed using a set of wireless sensor nodes connected together through a Base station. The sensor nodes capture the data about the surrounding environment and forward it to the base station (BS) along with the geotag and timestamp. For a better quality of service in a IoT network the intelligent routing becomes essential factor. The routing protocol must be energy efficient to prevent packet loss or packet drop, and early dying of certain nodes. Hence it also becomes necessary to balance the energy spending in the network by implementing optimal routing decisions derived from intelligent machine learning techniques. Many researchers have provided solutions for energy efficient routing in IoT network. However the solutions provided need to be enhanced or redesigned to address other challenges and issues in an IoT network. This paper proposes a link quality estimation mechanism when a node is considering it neighboring node as a parent node. Based upon the experiments conducted in this research by implementing the proposed routing protocol it is observed that the routing algorithm exhibits better performance with respect to the following performance metrics including average energy consumption, packet drop rate, overall network life time, and average end to end delay.

Link quality estimation for arbitrary packet sizes over wireless links using packet reception events

SummaryThe packet error rate of wireless links is known to increase with the length of packets. Yet, packet length is rarely taken into account in protocols and algorithms estimating the packet error rate. Still, it is an important factor that higher layer protocols need to be aware of. In this article, we systematically measure the relationship between packet length and packet error rate over a wide range of wireless links and technologies. On the basis of our measurements, we propose a simple empirical model that can capture this behavior. Using this model, multiple methods are proposed that can estimate the packet error rate for any packet length by sampling the link. We consider methods based on hello packets with controlled packet lengths as well as data packets, where the transmitted packet lengths cannot be controlled. We investigate the accuracy of the different estimation methods in various situations and show how they are able to predict the delivery ratio for different packet sizes.

Performance Optimization of the IEEE 802.15.4-Based Link Quality Protocols for WBASNs/IoTs in a Hospital Environment Using Fuzzy Logic

The link quality protocols of the IEEE 802.15.4 show low performance in terms of reliability in a hospital environment. To achieve the optimal performance of these protocols, this paper proposes a fuzzy logic-based solution using a detailed empirical reliability assessment. This paper provides a solution through four steps: 1) identifying the suitable IEEE 802.15.4 protocols and validating their suitability for patient monitoring systems through simulation in Castalia 3.2 with the OMNet++ platform; 2) providing a detailed discussion and analysis regarding link quality mechanisms used; 3) creating a real-time test bed to perform the empirical experiments to find the actual link quality estimation for different hospital environments; and 4) proposing a fuzzy logic system (FLS), which maps the results of empirical experiments with the proposed FLS to obtain the optimal results. For empirical experiments, we divide the communication in the hospital into four environmental scenarios, including inside ward, corridor, ward to corridor, and ward to ward. Both mobile and static scenarios are considered with line of sight and non-line of sight. Different link quality threshold values for link quality indicator (LQI) and received signal strength indicator (RSSI) are found for the variety of hospital scenarios. A strong correlation is noticed between LQI and packet reception rate in most of the scenarios, whereas a weak correlation is found between RSSI and packet reception rate. Finally, the results are mapped to our proposed FLS to obtain the optimal performance.

CL-mWSNs: Cross Layer Model-Based QoS Centric Routing Protocol for Mission-Critical Cooperative Communication in Mobile WSNs

The paper presents a robust QoS centric routing protocol for mission-critical communication over mobile Wireless Sensor Networks (CL-mWSN) that exploits dynamic network states from the different layers of the IEEE 802.15.4 protocol stack to make the routing decision. The CL-mWSN protocol exploits three key layers: application layer, network layer and MAC layer. It exhibits proactive network and node table management, service differentiation, fair resource scheduling and congestion detection, avoidance at the network layer, as well as dynamic link quality estimation and packet injection rate estimation at the MAC layer to assess its candidature as the best forwarding node for QoS-centric mission-critical communication. Simulation reveals that the proposed routing model exhibits higher throughput, minimum loss and deadline miss ratio that augments QoS provision in mobile WSNs.

Quality of Information Analysis in WSN: An Application in BASN

Topology control deals with reducing the power consumption of WSN nodes by making use of quality of information parameters such as Received Signal Strength (RSSI) and Link Quality Indicator (LQI). This paper deals with Link Quality Estimation(LQE), which is a prominent criterion in designing a Topology Control aware higher layer routing protocol for WSN. An improved LQE is designed for the AODV routing protocol, which has been applied in Body Area Sensor Networks. Simulation study shows that the proposed estimator gives an enhanced performance in terms of packet delivery ratio and energy consumption. Empirical analysis using TelosB motes are carried out to estimate distance from RSSI measurements, using log normal path loss model. The experiments are performed both in the indoor and outdoor scenario and the amount of error deviation of the estimated distance is calculated. The root mean square of the distance error value obtained can be used as a threshold value in the distance noise model used in localization. Localized sensor nodes is widely used in BASN applications for mapping the exact user location and the routing of packets also will be more accurate.

Exploiting Concurrency for Opportunistic Forwarding in Duty-Cycled IoT Networks

Due to limited energy supply of Internet of Things (Zhao et al. 2018) (IoT) devices, asynchronous duty cycle radio management is widely adopted to save energy. Since the sleep schedules of nodes are unsynchronized, a sender has to repeatedly send frames to coordinate with its receiver or keep sleeping until the receiver’s wake-up time will come according to receiver’s sleep-wake schedule. In such contexts, opportunistic forwarding, which takes the earliest forwarding opportunity instead of a deterministic forwarder, shows great advantage in utilizing channel resource for duty-cycled IoT networks. The multiple forwarding choices with temporal and spatial diversity increase the chance of collision tolerance in opportunistic forwarding, potentially enhancing the overall performance of duty-cycled multi-hop networks. However, since the current channel contention mechanisms mainly focus on collision avoidance, it is too conservative to exploit concurrency. To address this problem, in this article, we propose COF to fully exploit the potential Concurrency for Opportunistic Forwarding in duty-cycled IoT networks. COF achieves concurrent transmission by: (i) measuring conditional link quality under the interference of on-going transmissions, and then (ii) further modeling the benefit of potential concurrency opportunities. According to the expected benefit of concurrency, COF decides whether or not to transmit in concurrent way. COF also adopts concurrency flag and signal features to avoid data collision caused by disordered concurrent transmissions and enhance the accuracy of conditional link quality estimation. COF can be easily integrated into the conventional unsynchronized and duty-cycled protocols. We have implemented COF and evaluated its performance on a 40-node testbed. The results show that COF can effectively exploit potential concurrency in opportunistic forwarding and COF outperforms the state-of-art protocols under diverse traffic load and network density.

A Comprehensive Survey on RPL: Evolution and Challenges

LLNs (Low Power and Lossy Networks) are becoming hot research topics due to challenges posed by their limited battery life, computing power, memory and transmission power. LLNs require a routing protocol which can perform efficiently with their limitations. IETF has come up with RPL as standard routing protocol for LLNs. It builds energy efficient network. But it also has major limitations and several research have happened to overcome the same. This paper is survey of RPL challenges and recent research on RPL extensions. Major RPL limitations include packet loss under noisy scenario, increased DODAG depth causing high energy consumption. TTA (Trickle Timer Algorithm) is important part of RPL. It is used to manage control messages flow. Limitation of trickle algorithm results in problem of short time for listening and it can make few nodes crave for delay and higher latency. E-Trickle is proposed to overcome the listen only period, improve convergence time and energy consumption. QOI (Quality of Information) aware RPL reduces the energy consumption with less data transmission. RPL operates under one sink. Entire data flows towards the single sink. RPL doesn’t specify when, where and how more number of sinks need to be used. Dynamic rescue sink is RPL enhancement built with real timetracking of nodes’ performance in RPL networks to propose new sinks when required. AMI (Advanced metering infrastructure) is one of the application in smart grid for connecting smart metering devices at homes. It is critical to have efficient routing protocol for AMI as the smart meter nodes are resource constrained. AMI with high density networks suffer from high packet loss, network congestion retransmissions, increased latency, control traffic overhead and power consumption. LQE (Link Quality Estimation) influences quality of selected route and energy consumption. RL-probe measures link quality precisely with small overhead and energy consumption. RL-probe reduces packet loss by reacting to link quality variations and link failures due to mobility. Communication overhead needs to be as minimal as possible inLLNs with limited resources. Adaptive timing model uses dynamic method to decide frequency of executing objective function to construct DODAG based on degree of surrounding changes and reduces the control messages overhead. Objective is to bring down the PLR (packet loss ratio), overhead of control messages and battery usage. RPL doesn’t give good results for high throughput and changes in network conditions. This prevents use of RPL in high speed sensors and mobile sensing applications. BRPL is extension to RPL which combines RPL objective function (OF) with back pressure routing to handle dynamic traffic load and mobility.

Improving the Accuracy Rate of Link Quality Estimation Using Fuzzy Logic in Mobile Wireless Sensor Network

Link quality estimation is essential for improving the performance of a routing protocol in a wireless sensor network. Many methods have been proposed to increase the performance of the link quality estimation; however, most of them are not able to evaluate link quality accurately. In this study, a method that uses fuzzy logic to combine both hardware-based and software-based metrics is proposed to improve the accuracy rate for evaluating a link quality. This proposed method consists of three types of modules, the Fuzzifier module, the Inference module, and the Defuzzifier module. The Fuzzifier module is used to determine the degree to which input link quality metrics belong to each fuzzy set through proposed membership functions. The Inference module obtains the rule outputs based on the proposed fuzzy rules and the given inputs acquired from the Fuzzifier module. The Defuzzifier module is used to aggregate the rule outputs inferred from the Inference module. The result from the Defuzzifier module is then used to evaluate the link quality. A simulation conducted to compare the accuracy rates of the proposed method and those found in related works showed that the proposed method had higher accuracy rates for evaluating a link quality.

Link Quality Estimation in Industrial Temporal Fading Channel With Augmented Kalman Filter

Wireless networks attract increasing interests from a variety of industry communities. However, the wide applications of wireless industrial networks are still challenged by unreliable services due to severe multipath fading effects. Such effects are not only caused by massive metal surfaces but also moving operators and logistical vehicles, which will lead to temporal fading effects. A three-layer impulse response framework is proposed to characterize such effects, in which both the specular and scattered components vary with the spacial movement of nearby objects. In this context, a received signal strength indicator will be a noisy estimation only on the specular power and fail to describe the link quality accurately without the aid of scattered power. Consequently, an augmented Kalman-filter-based link quality estimator has been designed to track both the specular and scattered power in the distribution parameter space with constant noise covariance matrices. Experiments from industrial sites show significantly increased accuracy.

Adaptive and Beacon-based multi-channel protocol for Industrial Wireless Sensor Networks

This paper proposes a novel protocol for Industrial Wireless Sensor Networks (IWSN), which is called Adaptive and Beacon-based Multi-Channel Protocol (ABMP), and combines multi-channel communication, real-time link quality estimation, and dynamic channel allocation, to deal with the problems that affect the link quality in industrial environments. A hybrid channel diversity mechanism is employed, in which the beacon frames are transmitted using channel hopping, and the unicast data packets are transmitted using channel adaptation. The network dynamically allocates the channels to deal with temporal and spatial variations in the channel quality. Referring to ABMP, the end-nodes do not need to receive all the beacons to maintain the communication. As demonstrated in this paper, the proposed approach makes the network more robust against problems related to the beacon reception. The ABMP has been compared to the protocols TSCH, and CSMA/CA for networks with the star and the tree topologies, using theoretical and simulation studies, with a realistic channel model for the IWSN. The results indicate that the proposed protocol presents a better performance in comparison to the MAC protocols defined by the new standards for IWSN, in terms of packet delivery rate, delay, and determinism.

Link Quality Estimation Method for Wireless Sensor Networks Based on Stacked Autoencoder

In wireless sensor networks, effective link quality estimation is the basis of topology management and routing control. Effective link quality estimation can guarantee the transmission of data, as well as improve the throughput rate, and hence, extend the life of the entire network. For this reason, a stacked autoencoder-based link quality estimator (LQE-SAE) is proposed. Specifically, the zero-filling method is developed to process the original missing link information. Then, the SAE model is used to extract the asymmetric characteristics of the uplink and downlink from the received signal strength indicator, link quality indicator, and signal-to-noise ratio, respectively. These characteristics are fused by SAE to construct the link features' vectors, which are given as inputs to the support vector classifier (SVC), for which the link quality grade is taken as its label. The experimental results in different scenarios show that the LQE-SAE has better accuracy than link quality estimators based on the SVC, ELM, and WNN.

Performance evaluation of various link quality metrics using cross layer routing for wireless multimedia sensor networks

For the past few years, link quality estimation has been an active area of research in wireless networks. Low-power wireless links are error-prone, asymmetric and unreliable in nature. Therefore, understanding the behaviour and characteristics of low-power radio links is essential to design effective and efficient routing protocol in wireless networks. The objective of this paper is to estimate and evaluate the quality of a link with single link quality metric and amalgamated link quality metric. In addition, these estimated link quality metrics are respectively used in a generic routing cost function of the proposed link quality-based cross layer routing (LQCLR) protocol. Extensive simulation results are presented, which give insights on how estimated link quality with single and amalgamated link quality metrics affects the performance of routing protocol in wireless multimedia sensor network (WMSN).

Performance evaluation of various link quality metrics using cross layer routing for wireless multimedia sensor networks

For the past few years, link quality estimation has been an active area of research in wireless networks. Low-power wireless links are error-prone, asymmetric and unreliable in nature. Therefore, understanding the behaviour and characteristics of low-power radio links is essential to design effective and efficient routing protocol in wireless networks. The objective of this paper is to estimate and evaluate the quality of a link with single link quality metric and amalgamated link quality metric. In addition, these estimated link quality metrics are respectively used in a generic routing cost function of the proposed link quality-based cross layer routing (LQCLR) protocol. Extensive simulation results are presented, which give insights on how estimated link quality with single and amalgamated link quality metrics affects the performance of routing protocol in wireless multimedia sensor network (WMSN).

Selection of high quality path through MXAODV in mobile ad-hoc network

Selection of high quality path in mobile ad-hoc network is a critical issue due to mobility of nodes and variable channel conditions during data transmission. Path containing smallest number of hops generally performs less due to some links on those paths may have low or marginal quality. Mean loss ratio of link is also not a perfect way to estimate link quality, mean channel condition is not realistic. Hence, link quality estimation on the basis of loss ratio in burst loss conditions of different channels is significant. Incorporation of loss variance for a link in its quality estimation through modified expected transmission count (mETX) is the main aim of the proposed protocol to improve the communication efficiency in mobile ad-hoc networks. This paper describes the design and implementation of proposed routing protocol named as modified expected transmission count enabled ad-hoc on-demand distance vector (MXAODV). Extensive simulation has been done to analyse the performance of MXADOV. Significant improvements found in terms of throughput, packet delivery fraction, normalised routing load and end-to-end delay.