On a reliable handoff procedure for supporting mobility in wireless sensor networks

Wireless sensor network (WSN) applications such as patients’ health monitoring in hospitals, location-aware ambient intelligence, industrial monitoring /maintenance or homeland security require the support of mobile nodes or node groups. In many of these applications, the lack of network connectivity is not admissible or should at least be time bounded, i.e. mobile nodes cannot be disconnected from the rest of the WSN for an undefined period of time. In this context, we aim at reliable and real-time mobility support in WSNs, for which appropriate handoff and rerouting decisions are mandatory. This paper1 drafts a mechanism and correspondent heuristics for taking reliable handoff decisions in WSNs. Fuzzy logic is used to incorporate the inherent imprecision and uncertainty of the physical quantities at stake

Demo abstract: RadiaLE: a framework for benchmarking link quality estimators

Link quality estimation is a fundamental building block for the design of several different mechanisms and protocols in wireless sensor networks (WSN). A thorough experimental evaluation of link quality estimators (LQEs) is thus mandatory. Several WSN experimental testbeds have been designed ([1–4]) but only [3] and [2] targeted link quality measurements. However, these were exploited for analyzing low-power links characteristics rather than the performance of LQEs. Despite its importance, the experimental performance evaluation of LQEs remains an open problem, mainly due to the difficulty to provide a quantitative evaluation of their accuracy. This motivated us to build a benchmarking testbed for LQE - RadiaLE, which we present here as a demo. It includes (i.) hardware components that represent the WSN under test and (ii.) a software tool for the set up and control of the experiments and also for analyzing the collected data, allowing for LQEs evaluation

Quality-of-service in wireless sensor networks: state-of-the-art and future directions

Wireless sensor networks (WSNs) are one of today’s most prominent instantiations of the ubiquituous computing paradigm. In order to achieve high levels of integration, WSNs need to be conceived considering requirements beyond the mere system’s functionality. While Quality-of-Service (QoS) is traditionally associated with bit/data rate, network throughput, message delay and bit/packet error rate, we believe that this concept is too strict, in the sense that these properties alone do not reflect the overall quality-ofservice provided to the user/application. Other non-functional properties such as scalability, security or energy sustainability must also be considered in the system design. This paper identifies the most important non-functional properties that affect the overall quality of the service provided to the users, outlining their relevance, state-of-the-art and future research directions

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

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

Radio link quality estimation in low-power wireless networks

This book provides a comprehensive survey on related work for radio link quality estimation, which covers the characteristics of low-power links, the fundamental concepts of link quality estimation in wireless sensor networks, a taxonomy of existing link quality estimators and their performance analysis. It then shows how link quality estimation can be used for designing protocols and mechanisms such as routing and hand-off. The final part is dedicated to radio interference estimation, generation and mitigation

Experiencing Low Power Wireless Links in Distribution Smart Grid Environments

International audienceWireless Sensor Networks (WSNs) have been recognized as a promising communication technology for the Internet of Things (IoT). In particular, smart grid applications rely on WSNs for enabling pervasive monitoring and control of the electric grid. However, these applications are commonly deployed in harsh environments that adversely impact the reliability of low-power wireless links in WSNs. Efficient link quality estimation has been shown as a prerequisite to overcome link unreliability. Several WSN Link Quality Estimators (LQEs) have been proposed in the literature. However, there is a lack of real world experimentations that investigate their adequacy to assess low-power links in smart grid environments. To fill this gap, this paper presents a thorough experimental study of representative LQEs in a smart grid distribution substation. Both single and composite LQEs are evaluated in terms of reliability, stability and reactivity, by analyzing their statistical behavior. This study would help system designers choose the most appropriate estimators for smart grid environments. Especially, it shows that composite LQEs, such as Opt-FLQE, F-LQE, and four-bit, are more reliable than single LQEs, including PRR, WMEWMA, and RNP. Further, experimental results show that Opt-FLQE is found to be the most reliable estimator, F-LQE, PRR, and WMEWMA are the most stable estimators, while Opt-FLQE, RNP, and four-bit are the most reactive LQEs

Holistic link quality estimation-based routing metric for RPL networks in smart grids

International audienceWireless Sensor Networks (WSNs) have been recognized as a promising communication technology for smart grid monitoring and control applications. Unfortunately, environmental conditions in smart grids are complex and harsh (electromagnetic interference, obstructions, fading, etc.), which turns radio links extremely unreliable. Routing protocols play a crucial role to overcome low-power link unreliability in smart grid environments. Especially, RPL (IPv6 Routing Protocol for Low Power and Lossy Networks) is an IETF standard that is supposed to meet the requirements of WSN-based smart grid communications. RPL routing metric relies on link quality estimation through ETX (Expected Transmission Count) assessment, to identify high quality links for data delivery. However, ETX is not sufficiently accurate as it assesses a particular link aspect, number of packet retransmissions over the link, and ignores other important aspects such as channel quality. Consequently, as confirmed by recent experimental studies, RPL can fail to identify routing paths with high quality links leading to high packet loss rates. In this paper, we propose an alternative routing metric for RPL based on holistic link quality estimation, where several link metrics are combined. Based on COOJA simulations, we demonstrate that our proposed routing metric improves RPL performance over traditional routing metrics, including the RPL default metric, mainly in terms of packet loss ratio, end-to-end delay, energy efficiency, and topology stability

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%