Habib Youssef

Radio link quality estimation in wireless sensor networks: A survey

Radio link quality estimation in Wireless Sensor Networks (WSNs) has a fundamental impact on the network performance and also affects the design of higher-layer protocols. Therefore, for about a decade, it has been attracting a vast array of research works. Reported works on link quality estimation are typically based on different assumptions, consider different scenarios, and provide radically different (and sometimes contradictory) results. This article provides a comprehensive survey on related literature, covering the characteristics of low-power links, the fundamental concepts of link quality estimation in WSNs, a taxonomy of existing link quality estimators, and their performance analysis. To the best of our knowledge, this is the first survey tackling in detail link quality estimation in WSNs. We believe our efforts will serve as a reference to orient researchers and system designers in this area.

F-LQE: a fuzzy link quality estimator for wireless sensor networks

Radio Link Quality Estimation (LQE) is a fundamental building block for Wireless Sensor Networks, namely for a reliable deployment, resource management and routing. Existing LQEs (e.g. PRR, ETX, Four-bit, and LQI) are based on a single link property, thus leading to inaccurate estimation. In this paper, we propose F-LQE, that estimates link quality on the basis of four link quality properties: packet delivery, asymmetry, stability, and channel quality. Each of these properties is defined in linguistic terms, the natural language of Fuzzy Logic. The overall quality of the link is specified as a fuzzy rule whose evaluation returns the membership of the link in the fuzzy subset of good links. Values of the membership function are smoothed using EWMA filter to improve stability. An extensive experimental analysis shows that F-LQE outperforms existing estimators.

A comparative simulation study of link quality estimators in wireless sensor networks

Link quality estimation (LQE) in wireless sensor networks (WSNs) is a fundamental building block for an efficient and cross-layer design of higher layer network protocols. Several link quality estimators have been reported in the literature; however, none has been thoroughly evaluated. There is thus a need for a comparative study of these estimators as well as the assessment of their impact on higher layer protocols. In this paper, we perform an extensive comparative simulation study of some well-known link quality estimators using TOSSIM. We first analyze the statistical properties of the link quality estimators independently of higher-layer protocols, then we investigate their impact on the Collection Tree Routing Protocol (CTP). This work is a fundamental step to understand the statistical behavior of LQE techniques, helping system designers choose the most appropriate for their network protocol architectures.

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.

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%.

Confidentiality and Integrity for Data Aggregation in WSN Using Homomorphic Encryption

Data aggregation is an important method to reduce the energy consumption in wireless sensor networks (WSNs), however, performing data aggregation while preserving data confidentiality and integrity is mounting a challenge. The existing solutions either have large communication and computation overheads or produce inaccurate results. This paper proposes a novel secure data aggregation scheme based on homomorphic encryption in WSNs. The scheme adopts a symmetric-key homomorphic encryption to protect data privacy and combines it with homomorphic signature to check the aggregation data integrity. In addition, during the decryption of aggregated data, the base station is able to classify the encrypted and aggregated data based on the encryption keys. Simulation results and performance analysis show that our mechanism requires less communication and computation overheads than previously known methods. It can effectively preserve data privacy, check data integrity, and achieve high data transmission efficiency. Also, it performs accurate data aggregation rate while consuming less energy to prolong network lifetime.

Is QoE estimation based on QoS parameters sufficient for video quality assessment

Internet Service providers offer today a variety of of audio, video and data services. Traditional approaches for quality assessment of video services were based on Quality of Service (QoS) measurement. These measurements are considered as performance measurement at the network level. However, in order to make accurate quality assessment, the video must be assessed subjectively by the user. However, QoS parameters are easier to be obtained than the QoE subjective scores. Therefore, some recent works have investigated objective approaches to estimate QoE scores based on measured QoS parameters. The main purpose is the control of QoE based on QoS measurements. This paper presents several solutions and models presented in the literature. We discuss some other factors that must be considered in the mapping process between QoS and QoE. The impact of these factors on perceived QoE is verified through subjective tests.

A testbed for the evaluation of link quality estimators in wireless sensor networks

Link quality estimation is a fundamental building block for the design of several different mechanisms and protocols in wireless sensor networks. The accuracy of link quality estimation greatly impacts the efficiency of these protocols. Therefore, a thorough experimental evaluation of link quality estimators (LQEs) is mandatory. This motivated us to build a benchmarking testbed - RadiaLE, that automates LQEs evaluation by analyzing their statistical properties. Our testbed includes (i.) hardware components that represent the WSN under test and (ii.) a software tool for setting up and controlling the experiments and also for analyzing the collected data, allowing for LQEs evaluation. To demonstrate the usefulness of RadiaLE, we carried out a comparative performance study of a set of well-known LQEs.

Cyber-physical systems clouds

Cyber-Physical Systems (CPSs) represent systems where computations are tightly coupled with the physical world, meaning that physical data is the core component that drives computation. Industrial automation systems, wireless sensor networks, mobile robots and vehicular networks are just a sample of cyber-physical systems. Typically, CPSs have limited computation and storage capabilities due to their tiny size and being embedded into larger systems. With the emergence of cloud computing and the Internet-of-Things (IoT), there are several new opportunities for these CPSs to extend their capabilities by taking advantage of the cloud resources in different ways. In this survey paper, we present an overview of research efforts on the integration of cyber-physical systems with cloud computing and categorize them into three areas: (1) remote brain, (2) big data manipulation, (3) and virtualization. In particular, we focus on three major CPSs namely mobile robots, wireless sensor networks and vehicular networks.

IKM -- An Identity based Key Management Scheme for Heterogeneous Sensor Networks

Wireless sensor networks applications are growing and so are their security needs. However, due to severe memory, computing and communication limitations, wireless sensor networks security presents tremendous challenges. Central to any security service, key management is a fundamental cryptographic primitive to provide other security operations. In this paper, we propose IKM, an identity based key management scheme designed for heterogeneous sensor networks. This scheme provides a high level of security as it is based on a variant of public key cryptography named pairing identity based cryptography. The IKM scheme supports the establishment of two types of keys, pairwise key to enable point to point communication between pairs of neighbouring nodes, and cluster key to make in-network processing feasible in each cluster of nodes. IKM also supports the addition of new nodes and re-keying mechanism. A security analysis is presented to prove the scheme resilience against several types of attacks especially the node compromise attack. We also perform an overhead analysis of the proposed scheme in terms of storage, communication, and computation requirements. To demonstrate the feasibility of this scheme, we present implementation and performance evaluation of the proposed scheme on Crossbow TelosB motes running TinyOS. The results indicate that it can be deployed efficiently in resource-constrained sensor networks that need a high level of security.