Sustainable Traffic Aware Duty-Cycle Adaptation in Harvested Multi-Hop Wireless Sensor Networks

International audienceSustainable power management techniques in energy harvesting wireless sensors currently adapt the consumption of sensors to their harvesting rate within the limits of their battery residual energy, but regardless of the traffic profile. To provide a fairer distribution of the energy according to application needs, we propose a new sustainable traffic aware duty-cycle adaptation scheme (STADA) that takes into account the traffic load in addition to previous factors. We evaluate our protocol in the specific context of multi-hop IEEE 802.15.4 beacon-enabled wireless sensor networks powered by solar energy. Simulations show that our solution outperforms traffic-unaware adaptation schemes while minimizing the variance of the quality of service provided to applications

DADC: A Novel Duty-cycling Scheme for IEEE 802.15.4 Cluster-tree-based IoT Applications

[EN] The IEEE 802.15.4 standard is one of the widely adopted specifications for realizing different applications of the Internet of Things. It defines several physical layer options and Medium Access Control (MAC) sublayer for devices with low-power operating at low data rates. As devices implementing this standard are primarily battery-powered, minimizing their power consumption is a significant concern. Duty-cycling is one such power conserving mechanism that allows a device to schedule its active and inactive radio periods effectively, thus preventing energy drain due to idle listening. The standard specifies two parameters, beacon order and superframe order, which define the active and inactive period of a device. However, it does not specify a duty-cycling scheme to adapt these parameters for varying network conditions. Existing works in this direction are either based on superframe occupation ratio or buffer/queue length of devices. In this article, the particular limitations of both the approaches mentioned above are presented. Later, a novel duty-cycling mechanism based on MAC parameters is proposed. Also, we analyze the role of synchronization schemes in achieving efficient duty-cycles in synchronized cluster-tree network topologies. A Markov model has also been developed for the MAC protocol to estimate the delay and energy consumption during frame transmission.This work is supported by Science and Engineering Research Board, Department of Science and Technology, Government of India under ECR 2016, Grant No. 2016/001651. This work has been partially supported by the "Ministerio de Economia y Competitividad" in the "Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia," "Subprograma Estatal de Generacion de Conocimiento," within the project under Grant No. TIN2017-84802-C2-1-P. This work has also been partially supported by European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) Project ERANETMED3-227 SMARTWATIR.Choudhury, N.; Matam, R.; Mukherjee, M.; Lloret, J. (2021). DADC: A Novel Duty-cycling Scheme for IEEE 802.15.4 Cluster-tree-based IoT Applications. ACM Transactions on Internet Technology. 22(2). https://doi.org/10.1145/3409487S22

Pile de protocoles pour des réseaux des capteurs avec récupération d'énergie

This thesis concerns energy efficient protocols for harvested wireless sensor networks. It is a part of an industrial Internet of Things project. STMicroelectronics started the GreenNet project with the objective to develop and design a new generation of harvesting smart objects to be integrated in the Internet of Things. The GreenNet platform is novel with respect to the existing solutions due to its small size that implies a small energy buffer and small harvesting capabilities. This aspect makes the standard protocols and precedent solutions not directly applicable on this extremely low power platform. In this dissertation, we analyse standard protocols and existing solutions to identify their issues in the gn platform. Then, we provide protocol and algorithm adaptations to make feasible the concept of auto configurable and sustainable networks of GreenNet nodes. We proposed MCBT, an energy efficient protocol for the bootstrap procedure. It enables low power nodes to be enrolled in mh mc wireless sensor networks thanks to the network support for enrolling new nodes. It represents an energy efficient solution that extends the standard protocol. We proposed STADA, a sustainable algorithm to adapt the node activity according to the available energy and traffic conditions. STADA is based on a weighted function that takes into account the energy present in the battery, the energy harvesting rate, and network traffic. In this way, the algorithm takes into account all main parameters to adapt the energy consumption and improve the node performance. To make the harvested network more efficient according to light variations, we proposed a novel metric that makes the path choice a simple process. With the Expected Delay, we synthesize all network parameters in a single monotonic variable that facilitates the path choice in mh harvesting wireless sensor networks. All proposed solutions are designed to work with standard beacon-enabled IEEE 802.15.4 protocols and are easily portable on the future version of IEEE 802.15.4e. We validated the proposed protocols with emulations and simulations. The evaluation results shown better performance in terms of energy consumption and quality of service.Cette thèse vise à améliorer la pile de protocoles pour réseaux de capteurs sans fil à récupération d'énergie afin de les rendre autonomes dans un contexte multi-saut. Elle s'inscrit dans le projet GreenNet de STMicroelectronics qui a pour objectif de concevoir et développer une nouvelle génération d'objets intelligent basés sur la récupération d'énergie ambiente en vue de l'intégration dans l'Internet des Objets. L'originalité de la plateforme GreenNet repose sur sa petite taille qui implique une faible capacité de stockage d'énergie ainsi qu'une faible capacité de récupération d'énergie. Avec un si faible budget d'énergie, les protocoles standards ou les solutions proposées par les communautés académique/industrielle ne permettant pas d'assurer un fonctionnement autonome de ces réseaux. Dans cette thèse, nous analysons les protocoles standards et les solutions existantes pour identifier leurs limites avec la plateforme GreenNet. Ensuite, nous proposons 3 contributions afin de permettre cette autonomie. La première contribution est MCBT, un protocole permettant d'accélérer la découverte et le rattachement de nouveaux noeuds à un réseau multi saut et multi-canaux en formation ou existent. Ce protocole réduit efficacement l'énergie dépensée dans cette phase fortement consommatrice. La deuxième contribution est STADA, un algorithme adaptant l'activité des capteurs en fonction des conditions locales de trafic et d'énergie disponible. STADA est basé sur une fonction de pondération qui tient compte de l'énergie présente dans la batterie, du taux de récupération d'énergie et du trafic local. Enfin, notre troisième contribution propose une nouvelle métrique de routage basée sur Expected Delay synthétisant en une seule variable monotone des facteurs tels que l'éloignement au puits, les chemins bénéficiant d'un ordonnancement de relayage de paquet privilégié et de périodes cumulées d'activité des radios sur le chemin favorable. Toutes les solutions proposées sont conçues pour fonctionner avec la norme IEEE 802.15.4 slotté et sont facilement transposables à son évolution définie par la norme IEEE 802.15.4e. Nous avons validé les protocoles proposés grâce à un simulateur émulant des noeuds réels (Cooja) et au simulateur WSNet. Les résultats ont montré de meilleures performances en termes de consommation d'énergie et de qualité de service par rapport à l'existant

A Learning Approach to Decentralised Beacon Scheduling

Accepted for publication in Elsevier Ad-Hoc NetworksBeaconing is usually employed to allow network discovery and to maintain synchronisation in mesh networking protocols, such as those defined in the IEEE 802.15.4e and IEEE 802.11s standards. Thus, avoiding persistent or consecutive collisions of beacons is crucial in order to ensure correct network operation. Beacons are also used in receiver-initiated medium access protocols to advertise that nodes are awake. Consequently, effective beacon scheduling can enable duty-cycle operation and reduce energy consumption. In this work, we propose a completely decentralised and low-complexity solution based on learning techniques to schedule beacon transmissions in mesh networks. We show the algorithm converges to beacon collision-free operation almost surely in finite time and evaluate converge times in different mesh network scenarios