A framework for efficient communication in hybrid sensor and vehicular networks

Fast transmission of event-driven warning messages and energy conservation are primary concerns to design robust Hybrid Sensors and Vehicular Networks (HSVNs). In last few years, several protocols have been proposed to address these issues. However, the tradeoff between energy consumption and latency has not been carefully studied and sometimes it is given higher priority than event detection efficiency which remains the first objective of HSVNs. Unlike the existing works, we propose a framework that provides equilibrium between the following three metrics of HSVNs; dangerous events detection, energy consumption and transmission delay. The main advantage of our framework is its ability to ensure an effective detection of dangers on the road and timely transmission of the corresponding warning messages towards the passing by vehicles. This is achieved through the proposed mechanism to switch the sensors' status between sleep and active modes as well as the devised communication scheme between WSN-Gateway and the vehicles cluster head. The preliminary simulation results confirm the effectiveness of our framework and encourage us to pursue further investigation to extend it. © 2012 IEEE

A robust congestion control scheme for fast and reliable dissemination of safety messages in VANETs

In this paper, we address the beacon congestion issue in Vehicular Ad Hoc Networks (VANETs) due to its devastating impact on the performance of ITS applications. The periodic beacon broadcast may consume a large part of the available bandwidth leading to an increasing number of collisions among MAC frames, especially in case of high vehicular density. This will severely affect the performance of the Intelligent Transportation Systems (ITS) safety based applications that require timely and reliable dissemination of the event-driven warning messages. To deal with this problem, we propose an original solution that consists of three phases as follows; priority assignment to the messages to be transmitted /forwarded according to two different metrics, congestion detection phase, and finally transmit power and beacon transmission rate adjustment to facilitate emergency messages spread within VANETs. Our solution outperforms the existing works since it doesn't alter the performance of the running ITS applications unless a VANET congestion state is detected. Moreover, it ensures that the most critical and nearest dangers are advertised prior to the farther and less damaging events. The simulation results show promising results and validate our solution. © 2012 IEEE

Virtual Broking Coding for Reliable In-Network Storage on WSANs

International audienceThe emerging Internet of Things (IoT) paradigmmakes Wireless Sensor and Actuator Networks (WSANs) seemas a central element for data production and consumption. Inthis realm, where data are produced and consumed within thenetwork, WSANs have as a challenge to perform in-network datastorage considering their resource shortage. In this paper, wepropose the Virtual Broking Coding (VBC) as a data storagescheme compliant with WSANs constraints. As such, VBCensures a reliable data storage and an efficient mechanism fordata retrievability. To evaluate our proposed solution, we presenta theoretical analysis as well as a simulation study. Using both,we show that VBC reduces the cost incurred by the codingtechniques; and increases the delivery ratio of the requesteddata. The results presented by VBC suggest this solution as anew direction on how to use network coding based schemes toaddress the WSAN in-network storage problem

A Duty Cycle Self-adaptation Algorithm for the 802.15.4 Wireless Sensor Networks

International audienceThe IEEE 802.15.4 protocol is widely adopted as the standard for the physical and MAC layers of wireless sensor networks. Among other mechanisms, it implements a mechanism called duty cycle that defines the node's active time during the network lifetime. This paper proposes a dynamic beacon interval and superframe adaptation algorithm (DBSAA) that adjusts the network duty cycle through two MAC layer parameters: the Beacon Order (BO) and the Superframe Order (SO). The parameters adaptation is triggered by the changes in the traffic load (i.e. increase or decrease due to modification in the environment). Using DBSAA, the network coordinator adjust the BO and SO parameters based on four parameter estimations: the superframe occupation ratio, the collision ratio, the number of packets received by the coordinator, and the number of source nodes. Performance evaluation results show that the duty cycle adaptation taking into account the BO and SO values meets the trade-off defined by the application requirements and energy consumption while compared to two other protocols: the standard 802.15.4 protocol, which does not perform duty cycle dynamic adaptation; and the DSAA (Dynamic Superframe Adjustment Algorithm), which adapts the duty cycle by adjusting only the SO parameter

A message-based incentive mechanism for opportunistic networking applications

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QoS-aware Reinforcement Learning for Multimedia Traffic Scheduling in Home Area Networks

Cloud-based interactive multimedia applications such as virtual games and video streaming are gaining high popularity. However, giving the high bandwidth consumption, the remote execution can negatively impact the quality of the multimedia traffic. In such a realm, data travel different communication networks from the cloud to the final users crossing the last meters the home's access point (AP). In such a scenario, the quality-of-service (QoS) support is a challenging task, particularly in the home network environment, with heterogeneous applications simultaneously running and consuming the available bandwidth. To address this issue, we propose ReiLeCS, a Reinforcement Learning-based Controller and Scheduler for interactive multimedia traffic in Home Area Networks (HAN). Through reinforcement learning and the maximization of a reward function, it enables the AP to schedule the arriving multimedia traffic from the cloud according to their required QoS. Simulation results using real multimedia traffic conditions demonstrate that ReiLeCS achieves better performances compared with existing packet scheduling policies

"Scalable and Fast Root Cause Analysis Using Inter Cluster Inference"

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Scalable and Fast Root Cause Analysis Using Inter Cluster Inference

International audienceThe capability to diagnose the root cause of an observed problem precisely and quickly is a desirable feature for large communication networks. However, the design of a technique that is at the same time fast, scalable and accurate is a challenging task. In this paper, we propose a novel method based on inter-cluster inference to overcome the usual limits of fault diagnosis techniques. The approach is based on two important concepts: a cluster decomposition of the dependency graph in order to ensure scalability, and the introduction of duplicated nodes aiming at preserving the end-to-end network view. The evaluation of the proposed approach has demonstrated a significant reduction in the complexity and the computation time of the root cause analysis, since it is based on a set of small-scale dependency graphs