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    On the challenges of mobility prediction in smart cities
    (Copernicus Publications, 2020) Boukhedouma, H.; Meziane, Abdelkrim; Hammoudi, S.; Benna, Amel
    The mass of data generated from people’s mobility in smart cities is constantly increasing, thus making a new business for large companies. These data are often used for mobility prediction in order to improve services or even systems such as the development of location-based services, personalized recommendation systems, and mobile communication systems. In this paper, we identify the mobility prediction issues and challenges serving as guideline for researchers and developers in mobility prediction. To this end, we first identify the key concepts and classifications related to mobility prediction. We then, focus on challenges in mobility prediction from a deep literature study. These classifications and challenges are for serving further understanding, development and enhancement of the mobility prediction vision.
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    Evaluation of the impacts of Sybil attacks against RPL under mobility
    (CERIST, 2014-06) Medjek, Faiza; Tandjaoui, Djamel; Djedjig, Nabil
    The Routing Protocol for Low-Power and Lossy Networks (RPL) is the routing protocol standardized for constrained environments such as 6LoWPAN networks, and is considered as the routing protocol of the Internet of Things (IoT). However, this protocol is subject to several attacks that have been analyzed on static case. Nevertheless, IoT will likely present dynamic and mobile applications. In this paper, we introduce potential security threats on RPL, in particular Sybil attacks when the Sybil nodes are mobile. In addition, we present an analysis and a discussion on how network performances can be affected. Our analysis shows, under Sybil attacks while nodes are mobile, that the performances of RPL are highly affected compared to the static case. In fact, we notice a decrease in the rate of packet delivery, and an increase in control messages overhead. As a result, energy consumption at constrained nodes increases. Our proposed attacks demonstrate that Sybil mobile nodes can easily disrupt RPL and overload the network with fake messages making it unavailable. Based on the obtained results we provide some recommendations to tackle this issue.
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    A Resource-based Mutual Exclusion Algorithm supporting Dynamic Acting Range and Mobility for Wireless Sensor and Actor Networks
    (CERIST, 2010-05) Derhab, Abdelouahid; Zair, Mustapha
    Achieving optimal actor resources usage is one of the fundamental issues in Wireless sensor and Actor Networks (WSANs). One solution is to maximize the mutually exclusive regions (i.e., regions covered by one actor). In this paper, we take a novel approach to define and resolve the mutual exclusion problem. We propose CRMEA, (Centralized Resource-based Mutual Exclusion Algorithm), that constructs an actor cover set whose cost is less than the sole mutual exclusion algorithm existing in the literature. In addition, extensions supporting dynamic acting range and mobility are added to CRMEA. Simulation results show that the proposed extensions can save up to 50%¡90% of actor resources when compared with CRMEA. In addition, the mobility extension can overcome the large event-to-action delay problem and meet the requirements of the delay-sensitive applications.
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    Locating Emergency Responders using Mobile Wireless Sensor Networks
    (ISCRAM, 2013-05) Benkhelifa, Imane; Moussaoui, Samira; Nouali-Taboudjemat, Nadia
    Emergency response in disaster management using wireless sensor networks has recently become an interest of many researchers in the world. This interest comes from the growing number of disasters and crisis (natural or man-made) affecting millions of lives and the easy-use of new and cheap technologies. This paper details another application of WSN in the post disaster scenario and comes up with an algorithm for localization of sensors attached to mobile responders (firefighters, policemen, first aid agents, emergency nurses, etc) while assisted by a mobile vehicle (fire truck, police car, or aerial vehicle like helicopters) called mobile anchor, sent to supervise the rescue operation. This solution is very efficient and rapidly deployable since no pre-installed infrastructure is needed. Also, there is no need to equip each sensor with a GPS receiver which is very costly and may increase the sensor volume. The proposed technique is based on the prediction of the rescuers velocities and directions considering previous position estimations. The evaluation of our solution shows that our technique takes benefit from prediction in a more effective manner than previous solutions. The simulation results show that our algorithm outperforms conventional Monte Carlo localization schemes by decreasing estimation errors with more than 50%.