Fayçal Ait Aoudia

OPWUM: Opportunistic MAC Protocol Leveraging Wake-Up Receivers in WSNs

Opportunistic forwarding has emerged as a promising technique to address the problem of unreliable links typical in wireless sensor networks and improve energy efficiency by exploiting multiuser diversity. Timer-based solutions, such as timer-based contention, form promising schemes to allow opportunistic next hop relay selection. However, they can incur significant idle listening and thus reduce the lifetime of the network. To tackle this problem, we propose to exploit emerging wake-up receiver technologies that have the potential to considerably reduce the power consumption of wireless communications. A careful design of MAC protocols is required to efficiently employ these new devices. In this work, we propose Opportunistic Wake-Up MAC (OPWUM), a novel multihop MAC protocol using timer-based contention. It enables the opportunistic selection of the best receiver among its neighboring nodes according to a given metric (e.g., the remaining energy), without requiring any knowledge about them. Moreover, OPWUM exploits emerging wake-up receivers to drastically reduce nodes power consumption. Through analytical study and exhaustive networks simulations, we show the effectiveness of OPWUM compared to the current state-of-the-art protocols using timer-based contention.

Fuzzy power management for energy harvesting Wireless Sensor Nodes

Power management is an important issue in the design of Energy Harvesting Wireless Sensor Networks (EH-WSNs). In this kind of networks, each Energy Harvesting Node (EH-node) must dynamically adapt its performance in order to avoid power failures while maintaining a good quality of service. The power management policy is implemented on each node by a Power Manager (PM). Designing a PM is challenging because the harvested energy is time varying, and the amount of energy that will be harvested in the future is hard to predict. In this work, we present Fuzzyman, a novel PM based on fuzzy control theory. Because of the unpredictability of the harvested energy, fuzzy control theory constitutes an appropriate framework to tackle the problem of designing PM for EH-nodes. We evaluate the performance of Fuzzyman by comparing it to a state of the art approach via extensive trace-driven network simulations. Results show that Fuzzyman achieves more efficient utilization of the harvested energy.

WULoRa: An energy efficient IoT end-node for energy harvesting and heterogeneous communication

Intelligent connected objects, which build the IoT, are electronic devices usually supplied by batteries that significantly limit their life-time. These devices are expected to be deployed in very large numbers, and manual replacement of their batteries will severely restrict their large-scale or wide-area deployments. Therefore energy efficiency is of the utmost importance in the design of these devices. The wireless communication between the distributed sensor devices and the host stations can consume significant energy, even more when data needs to reach several kilometers of distance. In this paper, we present an energy-efficient multi-sensing platform that exploits energy harvesting, long-range communication and ultra-low-power short-range wake-up radio to achieve self sustainability in a kilometer range network. The proposed platform is designed with power efficiency in mind and exploits the always-on wake-up radio as both receiver and a power management unit to significantly reduce the quiescent current even continuously listening the wireless channel. Moreover the platform allows the building of an heterogeneous long-short range network architecture to reduce the latency and reduce the power consumption in listening phase at only 4.6 μW. Experimental results and simulations demonstrate the benefits of the proposed platform and heterogeneous network.

A Generic Framework for Modeling MAC Protocols in Wireless Sensor Networks

Wireless sensor networks are employed in many applications, such as health care, environmental sensing, and industrial monitoring. An important research issue is the design of efficient medium access control (MAC) protocols, which have an essential role for the reliability, latency, throughput, and energy efficiency of communication, especially as communication is typically one of the most energy consuming tasks. Therefore, analytical models providing a clear understanding of the fundamental limitations of the different MAC schemes, as well as convenient way to investigate their performance and optimize their parameters, are required. In this paper, we propose a generic framework for modeling MAC protocols, which focuses on energy consumption, latency, and reliability. The framework is based on absorbing Markov chains, and can be used to compare different schemes and evaluate new approaches. The different steps required to model a specific MAC using the proposed framework are illustrated through a study case. Moreover, to exemplify how the proposed framework can be used to evaluate new MAC paradigms, evaluation of the novel pure-asynchronous approach, enabled by emerging ultra-low-power wake-up receivers, is done using the proposed framework. Experimental measurements on real hardware were performed to set framework parameters with accurate energy consumption and latency values, to validate the framework, and to support our results.

A Low Latency and Energy Efficient Communication Architecture for Heterogeneous Long-Short Range Communication

Low power communication has evolved towards multi-kilometer ranges and low bit-rate schemes in recent years. LoRa is an example of such a long-range technology that is triggering increasing interest. Using these technologies, a trade-off must be made between power consumption and latency for message transfer from the gateway to the nodes. However, domains such as industrial applications in which sensors and actuators are part of the control loop require predictable latency, as well as low power consumption. These requirements can be fulfilled using pure-asynchronous communication and idle listening elimination, allowed by emerging ultra-low-power wake-up receivers. On the other hand, state-of-the-art wake-up receivers present low sensitivity compared to traditional wireless node receivers and LoRa, which results in the fact that they can operate in short-range in the order of a few tens of meters. In this work, we propose an energy efficient architecture that combines long-range communication with ultra low-power short-range wake-up receivers to achieve both energy efficient and low latency communication in heterogeneous long-short range networks. The proposed hardware architecture uses a single radio transceiver that can communicate using both LoRa and state-of-the-art wake-up receivers while the proposed MAC protocol exploits the benefits of these two communication schemes. Experimental measurements and analytical comparisons show the benefits regarding both energy efficiency and latency enabled by the proposed approach. Analytical comparisons show that the proposed scheme allows up to 3000 times reduction of the power consumption compared to the standard LoRa approach.

GRAPMAN: Gradual power manager for consistent throughput of energy harvesting wireless sensor nodes

In this work, Wireless Sensor Network (WSN) applications that require long-term sustainability are considered. Energy harvesting forms a promising technology to address this challenge, by allowing each node to be entirely powered by energy harvested from its environment. To be sustainable, each node must dynamically adapt its Quality of Service (QoS), regarding the harvested energy using a power management strategy. This strategy is implemented on each node by the Power Manager (PM). In this paper, GRAPMAN (GRAdual Power MANager) is proposed, a novel PM for Energy-Harvesting WSN (EH-WSN) powered by pseudo-periodic energy sources. Unlike most state of the art PMs, GRAPMAN aims to achieve high average throughput while maintaining consistent QoS, i.e. with low fluctuations with respect to time, by looking for the highest throughput that can be supplied by the node over a finite time horizon while remaining sustainable. We show through extensive trace-driven network simulations that GRAPMAN outperforms state of the art PMs in both average throughput and throughput consistency.

Analytical and Experimental Evaluation of Wake-Up Receivers Based Protocols

Achieving energy efficient wireless communication is the most pursued goal in Wireless Sensor Networks (WSNs), as energy consumption is typically a major barrier to long term applications. In recent years, ultra-low power Wake-up Receivers (WuRx) have emerged, enabling pure asynchronous wireless communication that eliminates energy waste due to idle listening. However, to achieve a significant increase of energy efficiency compared to traditional duty-cycling approaches, Medium Access Control (MAC) protocols exploiting WuRx must be carefully designed. Therefore, we propose an analytical framework to model MAC protocols, leveraging WuRx or not, which gives an important evaluation of power consumption, latency and reliability. This framework was used to both model a WuRx-based MAC protocol, and to model two other state-of-the art MAC protocols for WSNs not using WuRx. Experimental power consumption and latency measurements were conducted to validate the proposed framework and the MAC protocol leveraging WuRx. Analytical results show the convenience of using WuRx and quantify the benefits of this emerging technology. These results demonstrate that using WuRx achieves up to 135 times lower power consumption and up to 23 times lower latency compared to traditional approaches in typical low throughput WSNs applications.

Poster Abstract: Wake-Up Receivers for Energy Efficient and Low Latency Communication

Long lifetime is the most pursued goal in Wireless Sensor Networks (WSNs). As communication is typically the most energy consuming task, a lot of effort has been devoted to design energy efficient communication protocols using duty-cycling in the last decades. However, in the recent years, a new kind of Ultra Low Power (ULP) receivers, called Wake-up Receivers (WuRx), is emerging. These devices allow the continuous monitoring of the wireless channel while having a power consumption orders of magnitude less than typical WSNs transceivers. WuRx can wake-up the rest of the system (microcontroller (MCU) and main radio) using interrupts only when needed, minimizing the idle listening. In this work, we present an experimental and an analytical study which ultimately serve as guidelines for the design of communication protocols leveraging WuRx.

Leveraging Energy Harvesting and Wake-Up Receivers for Long-Term Wireless Sensor Networks

Wireless sensor nodes are traditionally powered by individual batteries, and a significant effort has been devoted to maximizing the lifetime of these devices. However, as the batteries can only store a finite amount of energy, the network is still doomed to die, and changing the batteries is not always possible. A promising solution is to enable each node to harvest energy directly in its environment, using individual energy harvesters. Moreover, novel ultra-low power wake-up receivers, which allow continuous listening of the channel with negligible power consumption, are emerging. These devices enable asynchronous communication, further reducing the power consumption related to communication, which is typically one the most energy-consuming tasks in wireless sensor networks. Energy harvesting and wake-up receivers can be combined to significantly increase the energy efficiency of sensor networks. In this paper, we propose an energy manager for energy harvesting wireless sensor nodes and an asynchronous medium access control protocol, which exploits ultra-low power wake-up receivers. The two components are designed to work together and especially to fit the stringent constraints of wireless sensor nodes. The proposed approach has been implemented on a real hardware platform and tested in the field. Experimental results demonstrate the benefits of the proposed approach in terms of energy efficiency, power consumption and throughput, which can be up to more than two-times higher compared to traditional schemes.

Learning to survive: Achieving energy neutrality in wireless sensor networks using reinforcement learning

Energy harvesting is a promising approach to enable autonomous long-life wireless sensor networks. As typical energy sources present time-varying behavior, each node embeds an energy manager, which dynamically adapts the power consumption of the node to maximize the quality of service, while preventing power failure. In this work, RLMan, a novel energy management scheme based on reinforcement learning theory, is proposed. RLMan dynamically adapts its policy to time-varying environment by continuously exploring, while exploiting the current knowledge to improve the quality of service. The proposed energy management scheme has a very low memory footprint, and requires very few computational power, which makes it suitable for online execution on sensor nodes. Moreover, it only necessitates the state of charge of the energy storage device as an input, and therefore is practical to implement. RLMan was compared to three state-of-the-art energy management schemes, using simulations and energy traces from real measurements. Results show that using RLMan can enable almost 70 % gains regarding the average throughput.