In the last few years, Wireless Sensor Network (WSN) emerges and appears as an essential platform for prominent concept of Internet of Things (IoT). Their application ranges from so-called "smart cities", "smart homes" over environmental monitoring. The connectivity in IoT mainly relies on RPL (IPv6 Routing Protocol for Low Power and Lossy Network) -a routing algorithm that constructs and maintains DODAGs (Destination Oriented Directed Acyclic Graph) to transmit data from sensors to root over a single path. However, due to the resource constraints of sensor nodes and the unreliability of wireless links, single-path routing approaches cannot be considered effective techniques to meet the performance demands of various applications. In order to overcome these problems, many individuals and group research focuses on multi-path solutions for RPL routing protocol. In this paper, we propose three multipath schemes based on RPL (Energy Load Balancing-ELB, Fast Local Repair-FLR and theirs combination-ELB-FLR) and integrate them in a modified IPv6 communication stack for IoT. These schemes are implemented in OMNET++ simulator and the experiment outcomes show that our approaches have achieved better energy efficiency, better end-to-end delay, packet delivery rate and network load balance compared to traditional solution of RPL.

Target tracking applications in wireless sensor networks need to achieve energy efficiency, tracking accuracy, and certain real-time constraints in response to fast-moving targets. From a layer view, an energy-efficient cross-layer communication protocol that consists of a medium access control layer and network routing layer is necessary for joint optimization. Due to the interference and contention over the wireless medium, the limited resources of battery-operated sensor nodes, and the dynamic topology of large-scale networks, this cross-layer design becomes a challenging task. In this research, we exploit a cluster routing algorithm over large-scale networks and propose a low-duty-cycle medium access control (MAC) algorithm to reduce collision, idle-listening, and overhearing. In addition, our work focuses on the joint optimization of routing and a MAC strategy for achieving a good trade-off between low delay, energy efficiency, and tracking accuracy. To deploy this protocol in a real tracking application, we also propose a clustering synchronization procedure that does not require distributing the global timing information over the complete network to achieve network-wide time synchronization. An analytical model and extensive simulations are proposed to evaluate and compare the performance of our work with existing protocols. Simulation and analysis results show that our approach achieves better communication delay and thus better tracking error while maintaining reasonable energy consumption compared to other cases.

A tracking s y stem can track a moving target, re p ort to the Base Station (BS) and p redict the wake-u p zone while considering the trade-off between energ y consum p tion and the accurac y of tracking p erformance. To estimate and p redict the trajector y of a d y namic target, the use of Ba y esian filter, Kalman filter and its derivations are p ro p osed in [1]. The im p lementation of these different filters for a tracking s y stem is also anal y sed. In this paper, we propose a new method to estimate the trajector y of a target: Lateration estimation. We then continue to simulate and anal y se the p erformance of this method and com p are to extended Kalman filter (EKF) in term of residual energ y and tracking accurac y . Simulation results show that the Lateration estimation method can achieve better energ y consum p tion while maintaining reasonable tracking p erformance.

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