The 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.

The evolution of the Internet of Things (IoT) allows the development of new services and applications but triggers as well a full set of new issues to be solved. Among them, there are the problems related to the integration of the WSNs in the IoT realm including those related to data access. In this paper, we address more precisely the in-network data storage and data retrieval performed in a WSN integrated in the IoT realm. In order to develop an adequate data storage scheme for this scenario, we first design a system that integrates the Virtual Broking Coding (VBC) data storage scheme in the IoT realm. Then, we propose an algorithm called Dynamic Adaptive Virtual Broking Coding (DA-VBC) that adapts dynamically the packet redundancy level adopted in VBC to the optimal redundancy level, regarding the actual condition of the network, in order to ensure a reliable data storage and data retrieval. To do so, we model the choice of the optimal redundancy level as a Markov Decision Process (MDP) problem. Using the optimal policy found by the MDP, DA-VBC always performs with the minimum costbenefit for the network which means allowing more packet to be retrieved without overload the energy consumption. The simulation results confirm that the dynamic adaptation of the redundancy level improves the reliability of the data storage scheme while achieving an energy consumption comparable to the solution that does not use any redundancy. Besides, they show that the optimization of the cost-benefit metric is far more efficient than optimizing only one metric (for instance the cost or the packet delivery ratio), or using a fixed redundancy level.

The emerging Internet of Things (IoT) paradigm makes Wireless Sensor and Actuator Networks (WSANs) seem as a central element for data production and consumption. In this realm, where data are produced and consumed within the network, WSANs have as a challenge to perform in-network data storage considering their resource shortage. In this paper, we propose the Virtual Broking Coding (VBC) as a data storage scheme compliant with WSANs constraints. As such, VBC ensures a reliable data storage and an efficient mechanism for data retrievability. To evaluate our proposed solution, we present a theoretical analysis as well as a simulation study. Using both, we show that VBC reduces the cost incurred by the coding techniques; and increases the delivery ratio of the requested data. The results presented by VBC suggest this solution as a new direction on how to use network coding based schemes to address the WSAN in-network storage problem.

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