Annals of Telecommunications

An international journal publishing original peer-reviewed papers

Open Topics

Vol. 74, n° 5-6, May-June 2019
Content available on Springerlink

 

Distributed scheduling with efficient collision detection for end-to-end delay optimization in 6TiSCH multi-hop wireless networks

Inès Hosni1,2
1 University of Tunis El Manar, National Engineering School of Tunis, Communications Systems Laboratory, LR-99-ES21, 1002, Tunis, Tunisia
2 College of Computer and Information Sciences, Jouf University, Sakakah, Saudi Arabia

Abstract It is expected that the IEEE 802.15.4e-TSCH designed for wireless industrial sensor networks will be used in IoT systems. This standard relies on techniques such as channel hopping and bandwidth reservation to ensure both energy savings and reliable transmissions. Since many applications may require low end-to-end delay (e.g., alarms), we propose here a distributed algorithm to schedule the transmissions while upper bounding the end-to-end source-sink delay. Our strategy constructs stratums, regrouping all the nodes with the same depth in the DODAG Destination Oriented Directed Acyclic Graph constructed by RPL. Then, different time-frequency blocks(bands) are assigned deterministically to each stratum. By appropriately tuning the size of each block and chronologically organizing them, we are able to guarantee any packet is delivered along the path length to the border router before the end of the slotframe. We also provide self-healing mechanism to detect and alleviate local collisions. Experiments on a large-scale testbed prove the relevance of this approach to reduce the end-to-end delay while minimizing the number of collisions, prejudicial to the reliability in multihop networks.

Keywords IEEE 802.15.4-TSCH – End-to-end delay – Self-healing – Distributed scheduling – Autonomous – Large-scale experiments

Measurement and security trust in WSNs: a proximity deviation based approach

Noureddine Boudriga1,2, Paulvanna N. Marimuthu3, Sami J. Habib3
1 SUPCOM, University of Carthage, Tunis, Tunisia
2 CS Dep., University of the Western Cape, Bellville, South Africa
3 Computer Engineering Department, Kuwait University, Kuwait City, Kuwait

Abstract Quality of communication and measurement accuracy are of prime importance in WSN-based applications, as the sensors have to report real-time measurements to enable efficient decision-making. These sensors are often subject to measurement errors, such as noise, nonlinearity, and deviation caused by rapid changes. Sensors are prone to failures and can be targeted by attacks that aim to modify their outputs. To address these drawbacks, measurement should be checked, sensor functions should be protected, and accuracy should be analyzed all the time. In this paper, we propose a trust management framework based on three metrics: the true measurement deviation, group deviation, and security metrics to analyze the accuracy and trustworthiness of sensor data. The third metric considers the attacks detectable at the communication architecture layers. We have derived an analytical model (i) to calibrate the sensors periodically by deciding on their trustworthiness, and (ii) to modify their outputs periodically, whenever needed based on the deviation in measurement. Our simulation results for a real-time fire monitoring system show that the proposed trust framework is efficient in producing 95% accurate and trusted measurements by limiting the frequency of sensor calibrations to a minimal value and by setting a lower boundary of 5% deviation from the true and group value metrics with its added trust at the micro-level by disproving attacks at the protocol layer.

Keywords Wireless sensor network – Sensor calibration – Sensor security – Group deviation – True value deviation – Trust management

Universal secret payload location identification in spatial LSB stego images

S. T. Veena1, S. Arivazhagan2
1 Department of Computer Science and Engineering, Kamaraj College of Engineering and Technology, Virudhunagar, India
2 Centre for Image Processing and Pattern Recognition, Department of Electronics and Communication, Mepco Schlenk Engineering College, Mepco Nagar, Amathur Post, Sivakasi, Tamilnadu, India

Abstract Locating steganographic payload is an important aspect of active steganalysis which deals with finding the pixel locations of the embedded secret message (payload) in the stego image. The residual-based payload location detectors are well suited for this purpose. In this paper, an improved universal, blind method of precisely identifying locations in the spatial domain using enhanced weighted residuals with only a few known stego images is proposed. This is done by estimating the cover from the available stego image using the proposed novel locally weighted bivariate shrinkage function in the transform domain. The enhanced weighted residuals ensure that the proposed method is universally applicable for detecting payload locations in spatial least significant bit stego images. The added advantage of the proposed method is that it does not require any prior knowledge of the cover source or the embedding algorithm to determine the exact locations. Experiments conducted on five spatial LSB domain algorithms show that the payload locations can be precisely estimated with a minimum accuracy of 90% with 100 known stego images.

Keywords Active steganalysis – Stego key – Wavelet transform – Known stego image

An evaluation methodology to assess the accuracy of a tracking system in the case of horse races description and experimental validation

Céline Blache1, Geneviève Baudoin2, Marc Somson3,  Thierry Taillandier-Loize4, Alexandre Versvisch-Picois5, Nel Samama5
1 PMU, Paris, France
2 ESIEE, Marne La Vallée, France
3 Hippodrome de Paris-Vincennes, Vincennes, France
4 Laboratoire SAMOVAR, Télécom SudParis, CNRS, Université Paris-Saclay, Evry, France
5 EPH, Institut Mines-Telecom/Telecom SudParis, 9 rue Charles Fourier, 91000 Evry, France

Abstract All sorts of positioning systems exist and there is a growing demand nowadays in order to provide users with additional data in many activities. Horse racing is no exception and the PMU (Paris Mutuel Urbain) is in charge of driving the project concerning the deployment of a tracking system. PMU is Europe’s largest betting operator. It is an Economic Interest Grouping (EIG), whose mission is to finance the French horse racing industry. The specifications of the tracking system to be implemented are quite tough: an accuracy of positioning of 25 cm for more than 98% of the time during races for all the horses. A call for proposals has been issued and a few competitors have been hired in order to demonstrate the real performances of their system in a so-called “pilot” phase. The problem we now have is how to evaluate the real accuracy of the system in real conditions, i.e., during “simulated races”. Additional aspects are also of uppermost importance, such as the latency and the way data are displayed, but the present paper will only focus on the evaluation methodology used for the positioning accuracy assessment. An incremental validation approach was set up in order to allow the competitors to gradually improve their solutions, from the “easiest” tests (with cars) to the “most difficult” ones on horses during simulated races. Note that all competitors proposed a GNSS (Global Navigation Satellite System)-based solution using an RTK (Real-Time Kinematic) approach.

Keywords Horse races – Tracking system – Accuracy evaluation – Methodology

Optimal data collection in wireless sensor networks with correlated energy harvesting

Kishor Patil1, Koen De Turck2, Dieter Fiems1
1 Department of Telecommunications and Information Processing, Ghent University, Sint-Pietersnieuwstraat 41, 9000 Ghent, Belgium
2 Central Supelec, Laboratoire des Signaux et Systèmes, 3, Rue Joliot-Curie, 91192 Gif-sur-Yvette, France

Abstract We study the optimal data collection rate in a hybrid wireless sensor network where sensor data is collected by mobile sinks. In such networks, there is a trade-off between the cost of data collection and the timeliness of the data. We further assume that the sensor node under study harvests its energy from its environment. Such energy harvesting sensors ideally operate energy neutral, meaning that they can harvest the necessary energy to sense and transmit data, and have on-board rechargeable batteries to level out energy harvesting fluctuations. Even with batteries, fluctuations in energy harvesting can considerably affect performance, as it is not at all unlikely that a sensor node runs out of energy, and is neither able to sense nor to transmit data. The energy harvesting process also influences the cost vs. timeliness trade-off as additional data collection requires additional energy as well. To study this trade-off, we propose an analytic model for the value of the information that a sensor node brings to decision-making. We account for the timeliness of the data by discounting the value of the information at the sensor over time, we adopt the energy chunk approach (i.e. discretise the energy level) to track energy harvesting and expenditure over time, and introduce correlation in the energy harvesting process to study its influence on the optimal collection rate.

Keywords Value of information – Correlated energy harvesting – Markov process – Sensor networks

Mobility support enhancement for RPL with multiple sinks

Jinpeng Wang1, Gerard Chalhoub1
1 University of Clermont Auvergne, Clermont-Ferrand, France

Abstract In recent years, low power and lossy networks (LLNs) have attracted the attention of researchers. They typically operate with strict resource constraints in communication, computation, memory, and energy. Routing protocol for LLNs (RPL) is an ad-hoc distance vector routing protocol for LLNs that adapts IPv6 and runs on top of IEEE 802.15.4 standard. Although RPL was originally designed for static topologies, for many applications mobility support has been a major requirement in LLNs. In addition, part of these applications requires multiple sink nodes rather than one sink node. This is due to the fact that in a data collection wireless sensor network (WSN), only one sink easily leads to a faster energy depletion, more packet loss, higher latency, and smaller network range. Deploying multiple sinks in the network can help solve these problems. This paper focuses on addressing mobility support in RPL with multiple sinks. We propose an enhancement based on signal strength monitoring and rank updating in order to improve the network performance in mobility scenarios where all nodes except sink nodes are moving. This enhancement helps RPL to better cope with mobility scenarios and to make faster decisions on updating next-hop neighbors. Moreover, we propose a dynamic management of control messages in order to reduce the overhead in the network. Simulation results show that our technique outperforms the standard RPL in different
network configurations.

Keywords Wireless sensor networks – LLN – RPL – Mobility – Multiple sinks

Discovering the right place to check-in using web-based proximate selection

Rui José1, Ana Inês Xavier1 
1 Algoritmi Research Centre, University of Minho, Guimarães, Portugal

Abstract With information technology becoming increasingly embedded in our everyday physical world, there is a growing set of mobile applications that involve a connection with the digital representation of physical places. This association is normally initiated with a check-in procedure, through which a person asserts her presence at a particular place and determines the context for subsequent interactions. The common assumption is that a mobile application will be able to search the surrounding environment and present the user with the intended check-in target; however, in a world of ubiquitous place-based services, this assumption may no longer hold. A person in an urban environment would, at any moment, be surrounded by a large number of places, all of which could be regarded as possible interaction contexts for that person. In this work, we investigate the real-word challenges associated with wide-scale place selection and how the process can be affected by the place environment, by the position of the person in relation to the target place and by positioning errors. To study this reality, we used Google Places as a directory of georeferenced places. We conducted 14,400 nearby place queries structured around different combinations of our three independent variables. The results suggest that the overall performance is poor, except for low-density scenarios, and that this discovery process, albeit relevant, should always be combined with other place discovery approaches. The results also help to understand how this performance is affected by check-in positions and by the properties of the place environment.

Keywords Proximate selection – Place-based – Google places – Mobile check-in

Discovering the right place to check-in using web-based proximate selection

Rui José1, Ana Inês Xavier1 
1 Algoritmi Research Centre, University of Minho, Guimarães, Portugal

Abstract With information technology becoming increasingly embedded in our everyday physical world, there is a growing set of mobile applications that involve a connection with the digital representation of physical places. This association is normally initiated with a check-in procedure, through which a person asserts her presence at a particular place and determines the context for subsequent interactions. The common assumption is that a mobile application will be able to search the surrounding environment and present the user with the intended check-in target; however, in a world of ubiquitous place-based services, this assumption may no longer hold. A person in an urban environment would, at any moment, be surrounded by a large number of places, all of which could be regarded as possible interaction contexts for that person. In this work, we investigate the real-word challenges associated with wide-scale place selection and how the process can be affected by the place environment, by the position of the person in relation to the target place and by positioning errors. To study this reality, we used Google Places as a directory of georeferenced places. We conducted 14,400 nearby place queries structured around different combinations of our three independent variables. The results suggest that the overall performance is poor, except for low-density scenarios, and that this discovery process, albeit relevant, should always be combined with other place discovery approaches. The results also help to understand how this performance is affected by check-in positions and by the properties of the place environment.

Keywords Proximate selection – Place-based – Google places – Mobile check-in

Collision avoidance in shared slots in wireless devices of the Internet of Things: models and simulations

Pascale Minet1, Paul Muhlethaler1, Ines Khoufi1 
1 Inria, 2 rue Simone Iff, 75589 Paris Cedex 12, France

Abstract In this paper, we propose an analysis of a slot-based protocol designed for devices of the Internet of Things (IoT). In contrast to other TDMA-based protocols, this scheme uses a random technique to access shared slots, similarly to CSMA protocols. In practice, the transmissions are scheduled in a given backoff window of slots whose duration allows the transmission of a packet and its acknowledgment. Therefore, this protocol can be analyzed according to the methodology introduced by Bianchi for the IEEE 802.11 protocol even if the protocol studied differs in many aspects. The model we use is also particular because we succeed in obtaining a Markov model even though the scheme used to send a packet (in a node) may depend on the transmission of the previous packet. We distinguish two protocols; in the first one, at the initial stage or after a successful transmission, the packets are transmitted without any backoff, whereas in the second protocol each transmission is always preceded by the count down of a random backoff. Extensive simulations validate both protocols models. In addition, the performances of these protocols are compared with those of slotted Aloha and a protocol using a constant backoff window.

Keywords Wireless networks – Models – Collision avoidance – Shared slots – Medium access – Markov model – Slotted Aloha

Popularity prediction–based caching in content delivery networks

Nesrine Ben Hassine1, Pascale Minet1, Dana Marinca2, Dominique Barth2 
1  Inria, Paris, France
2 DAVID, University of Versailles, Versailles, France

Abstract In content delivery networks (CDNs), caches are resources that must be allocated. For that purpose, videos’ popularity knowledge helps to make efficient decisions about which videos should be cached. Thus, we must be able to anticipate future needs in terms of requested videos. To do this, we rely on the requests history. This paper focuses on predicting the videos’ popularity: the daily number of requests. For that purpose, we propose a two-level prediction approach. At the first level, the experts compute the videos’ popularity, each expert using its own prediction method with its own parameters. At the second level, the forecasters select the best experts and build a prediction based on the predictions provided by these experts. The prediction accuracy is evaluated by a loss function as the discrepancy between the prediction value and the real number of requests. We use real traces extracted from YouTube to compare different prediction methods and determine the best parameter tuning for experts and forecasters. The goal is to find the best trade-off between complexity and accuracy of the prediction methods used. Finally, we apply these prediction methods to caching. Prediction methods are compared in terms of cache hit ratio and update ratio. The gain brought by this two-level prediction approach is compared with that obtained by a single prediction level. The results show that the choice of a two-level prediction approach is justified.

Keywords Machine learning – Prediction – CDN – Caching – Video popularity – Expert – Forecaster

Capacity optimization of multi-input/multi-output relay channel by SADDE algorithm

Chien-Ching Chiu1, Yu-Ting Cheng1, Cheng-Hwa Yang1 
1 Electrical Engineering Department, Tamkang University, Tamsui, Taipei, Republic of China

Abstract In this paper, we use self-adaptive dynamic differential evolution (SADDE) to search for multi-input/multi-output (MIMO) relay locations and transmitter locations to reduce the outage probability in the indoor ultra-wideband (UWB) environment. Amplifyand-forward (AF) MIMO relay is chosen to improve the performance of the environment. We use the shooting and bouncing ray/ image (SBR/image) method to compute the frequency response, which is used to compute capacity. The channel capacities for the linear antenna with 1 × 1 antenna, 3 3 spaced linear antennas, and 3 × 3 tri-polarized antennas are compared. First, we deploy the relay and transmitter at the equipartition area. It is found that there are some outage receiving points. Thus, the SADDE is employed to optimize the position of the relay and transmitter in order to reduce the outage probability. Numerical results show that the outage probability for the relay and transmitter location is reduced by SADDE. Moreover, it is found that the channel
capacity for the tri-polarized antennas has increased when comparing to 3 × 3 spaced linear antennas. For the zero outage probability requirement, the signal to noise for the tri-polarized antennas is lower 6 dB than that for 3 × 3 spaced linear antennas.

Keywords Capacity optimization – MIMO relay – UWB – SADDE

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