Duty Cycling Research Articles

A Cooperative Clustering Protocol With Duty Cycling for Energy Harvesting Enabled Wireless Sensor Networks

This paper proposes a cooperative clustering protocol based on the low energy adaptive clustering hierarchy approach to enhance the longevity of energy harvesting-based wireless sensor networks (EH-WSN). In the proposed protocol, to ensure that any energy consumption associated with the role of the cluster head (CH) is shared between the nodes, the CH role is alternated between the nodes using duty cycling as a function of their individual energy harvesting capabilities. Furthermore, to maintain an energy neutral operation when not acting as a CH, the nodes adopt a data transmission duty cycle and any excess energy is invested in relaying other nodes’ packets. To optimize the relaying performance, a novel cross-layer cooperative TDMA scheme is also presented. The optimal number of clusters in an EH-WSN is analyzed in terms of energy consumption, latency, and bandwidth utilization. Simulations, performed using GreenCastalia, demonstrate tangible performance enhancements in adopting the proposed protocol over benchmark schemes in terms of throughput and lifetime, particularly under highly constrained energy conditions.

Analysis of Latency and MAC-Layer Performance for Class A LoRaWAN

We propose analytical models that allow us to investigate the performance of long range wide area network (LoRaWAN) uplink in terms of latency, collision rate, and throughput under the constraints of the regulatory duty cycling, when assuming exponential inter-arrival times. Our models take into account sub-band selection and the case of sub-band combining. Our numerical evaluations consider specifically the European ISM band, but the analysis is applicable to any coherent band. Protocol simulations are used to validate the proposed models. We find that sub-band selection and combining have a large effect on the quality of service (QoS) experienced in an LoRaWAN cell for a given load. The proposed models allow for the optimization of resource allocation within a cell given a set of QoS requirements and a traffic model.

Realization of a Self Powered Road Side Unit Using Network Processor Technology

Background: Vehicular ad hoc networks (VANET) is a talented system which allows different applications such as road traffic safety, Internet access, advertising and multimedia streaming, as described in the various patents as well. VANETs can work according to two modes of communications, Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I). In the second case, a permanent communication infrastructure, i.e. Road Side Units (RSUs) can be used to undertake the various safety messages or to act as a gateway to the Internet. From the roadside infrastructure viewpoint, the majority of the previous works suppose metropolitan situation where the conventional wired power is offered at a rational rate. However, this assumption is not always true in practical. Our goal here is to propose a self powered VANET infrastructure and the major player in such an infrastructure is the road side unit. We propose that the RSUs can gather the energy required for their work from the surrounding environment, particularly solar energy. Such a proposal allows to set up the RSUs in any location without taking into consideration the power supply availability and hence, a wider area is covered by the VANET infrastructure. Keywords: Network processer, Vehicular Ad Hoc Network (VANET), Road Side Unit (RSU), solar energy harvesting, researchable batteries, duty cycling.

Guided-Processing Outperforms Duty-Cycling for Energy-Efficient Systems

Energy efficiency is highly desirable for sensing systems in the Internet of Things. A common approach to achieve low-power systems is duty cycling, where components in a system are turned OFF periodically to meet an energy budget. However, this paper shows that such an approach is not necessarily optimal in energy efficiency, and proposes guided processing as a fundamentally better alternative. The proposed approach offers: 1) explicit modeling of performance uncertainties in system internals; 2) a realistic resource consumption model; and 3) a key insight into the superiority of guided processing over duty cycling. Generalization from the cascade structure to the more general graph-based one is also presented. Once applied to optimize a large-scale audio sensing system with a practical detection application, empirical results show that the proposed approach significantly improves the detection performance (up to 1.7 times and 4 times reduction in false alarm and miss rate, respectively) for the same energy consumption, when compared with the duty-cycling approach.

CCDC: A Congestion Control Technique for Duty Cycling WSN MAC Protocols

Wireless Sensor Networks hold the limelight because of significant potential for distributed sensing of large geographical areas. The radio duty cycling mechanism that turns off the radio periodically is necessary for the energy conservation, but it deteriorates the network congestion when the traffic load is high, which increases the packet loss and the delay too. Although many papers for WSNs have tried to mitigate network congestion, none of them has mentioned the congestion problem caused by the radio duty cycling of MAC protocols. In this paper, we present a simple and efficient congestion control technique that operates on the radio duty cycling MAC protocol. It detects the congestion by checking the current queue size. If it detects the congestion, it extends the network capacity by adding supplementary wakeup times. Simulation results show that our proposed scheme highly reduces the packet loss and the delay.

Reliable Data Collection with Mobile Sink Using Seamless Handover in Duty Cycled Based WSNs

Providing successful data collection in transmitter-initiated wireless sensor networks with mobile Sink (WSN-MS) scenarios is a primary goal of a myriad of critical applications in real world. Unfortunately, the problem of broken links which may occur during data transmission between a source node and a mobile Sink may cause inevitably incomplete data collection. To overcome this challenging issue, we propose in this paper a seamless handover mechanism performed on asynchronous duty cycled MAC protocol on the basis of neighborhood information. By measuring continuously the signal quality of ACKnowledgment messages of transmitted Data during a 1-hop communication, this mechanism allows the source node to continue transmitting data to the mobile Sink using a suitable neighbor node as relay in the case where the Sink node leaves the radio range in direction of that neighbor node. The asynchronous protocol XMAC (without handover) has been chosen as a basic protocol on which we designed our contribution named HXMAC (XMAC with handover). The later was implemented and evaluated using a powerful simulation tool. Experimental results based on the comparison between HXMAC and XMAC clearly showed that handover mechanism is a suitable technique to promote significantly reliability in WSN-MS data collection operation.

Experimental Comparison of Radio Duty Cycling Protocols for Wireless Sensor Networks

The performances of three different asynchronous radio duty cycling protocols available in the Contiki lightweight operating system have been compared experimentally in view of their adoption in medium sized wireless sensor networks integrated in the Internet of Things. This study unveils some of the subtleties of those protocols, allowing an improved tuning of their parameters, as well as the identification of overlooked shortcomings and implementation flaws. To ensure fair comparisons default options have been unified and small implementation and design problems have been tackled. Besides the previously mentioned interventions, default values for parameters were kept. The results of the comparison can help designers of wireless sensor networks with their choices and guide designers of protocols to overcome some critical issues.

ZeroMAC: Toward a zero sleep delay and zero idle listening media access control protocol with ultralow power radio frequency wakeup sensor

In wireless sensor networks, duty cycling has been an imperative choice to reduce idle listening but it introduces sleep delay. To break through the energy-latency tradeoff, we propose a pair of a radio wave sensor called radio frequency wakeup sensor and an on-demand media access control protocol called ZeroMAC. Radio frequency wakeup sensor is dedicated to sense the presence of a signal. The distinctive feature is that the sensor can provide the same sensitivity while it consumes only two orders of magnitude less energy than the underlying radio frequency module. With the sensor, a node no longer requires duty cycling. We also propose an on-demand media access control protocol called ZeroMAC that can effectively utilize the on-demand wakeup functionality of a radio frequency wakeup sensor by broadcasting a dedicated signal to wake up nodes before starting a communication. Since each node can notify neighbor nodes of a communication immediately, ZeroMAC can eliminate both idle listening and sleep delay. ZeroMAC wakes up only the nodes on the communication path by propagating wakeup signals in a hop-by-hop manner, avoiding unnecessary signal flooding. To further save energy, ZeroMAC can turn off radio frequency module as soon as it detects the end of communication. According to packet level simulation results, ZeroMAC can deliver data packets at least 1.87 times faster by eliminating both idle listening and sleep delay while it consumes only 3% of the energy compared to X-MAC and A-MAC.

Dual-Source Linear Energy Prediction (LINE-P) Model in the Context of WSNs.

Energy harvesting technologies such as miniature power solar panels and micro wind turbines are increasingly used to help power wireless sensor network nodes. However, a major drawback of energy harvesting is its varying and intermittent characteristic, which can negatively affect the quality of service. This calls for careful design and operation of the nodes, possibly by means of, e.g., dynamic duty cycling and/or dynamic frequency and voltage scaling. In this context, various energy prediction models have been proposed in the literature; however, they are typically compute-intensive or only suitable for a single type of energy source. In this paper, we propose Linear Energy Prediction “LINE-P”, a lightweight, yet relatively accurate model based on approximation and sampling theory; LINE-P is suitable for dual-source energy harvesting. Simulations and comparisons against existing similar models have been conducted with low and medium resolutions (i.e., 60 and 22 min intervals/24 h) for the solar energy source (low variations) and with high resolutions (15 min intervals/24 h) for the wind energy source. The results show that the accuracy of the solar-based and wind-based predictions is up to approximately 98% and 96%, respectively, while requiring a lower complexity and memory than the other models. For the cases where LINE-P’s accuracy is lower than that of other approaches, it still has the advantage of lower computing requirements, making it more suitable for embedded implementation, e.g., in wireless sensor network coordinator nodes or gateways.

Distributed Routing and Channel Selection for Multi-Channel Wireless Sensor Networks

We propose a joint channel selection and quality aware routing scheme for multi-channel wireless sensor networks that apply asynchronous duty cycling to conserve energy, which is common in many environmental monitoring applications. Energy resources may vary from node to node due to differential consumption as well as availability, as observed in rechargeable sensor networks. A data collection traffic pattern is assumed, where all sensor nodes periodically forward sensor data to a centralized base station (sink). Under these assumptions, the effect of overhearing dominates the energy consumption of the nodes. The proposed scheme achieves lifetime improvement by reducing the energy consumed in overhearing and also by dynamically balancing the lifetimes of nodes. Performance evaluations are presented from experimental tests as well as from extensive simulation studies, which show that the proposed scheme reduces overhearing by ∼60% with just 2 channels without significantly affecting the network performance.

Energy efficient LoRa GPS tracker for dementia patients.

Continuous GPS tracking devices always suffer short battery life when used by caregivers to reduce the risk of wandering to dangerous areas by dementia patients. Currently the best existing tracker for dementia patients on the market only supports less than 10 hours battery life with a gigantic battery. It not only requires daily battery charging from patients/caregivers, but also becomes a very restrictive device. In this paper we inspected individual energy consumption of the components in a GPS tracker and proposed a novel energy efficient, small wristband by integrating the latest LoRa communication and GPS duty cycling technologies. We verify our prototype's communication distance and energy efficiency through extensive experiments in the real world. Our model and data show the GPS wristband is able to support up to 40 hours continuous GPS tracking with a frequent 60 seconds location update rate. Its range also spans 3km, effectively monitoring patient locations.

Interference Resilient Duty Cycling for Sensor Networks Under Co-Existing Environments

To save energy, wireless sensor networks often run in a low-duty-cycle mode, where the radios of sensor nodes are scheduled between ON and OFF states. For nodes to communicate with each other, low power listening (LPL) and low power probing (LPP) are two types of rendezvous mechanisms. Nodes with LPL or LPP rely on signal strength or probe packets to detect potential transmissions, and then keep the radio-ON for communications. Unfortunately, in co-existing environments, signal strength and probe packets are susceptible to interference, resulting in undesirable radio ON time when the signal strength of interference is above a threshold or a probe packet is interfered. To address the issue, we propose ZiSense, a low duty cycling mechanism resilient to interference. Instead of checking the signal strength or decoding the probe packets, ZiSense detects the ZigBee signals and wakes up nodes accordingly. On sensor nodes with limited information and resource, we carefully study and extract short-term features purely from the time-domain RSSI sequence, and design a rule-based approach to efficiently identify the existence of ZigBee. We theoretically analyze the benefit of ZiSense in different environments and implement a prototype in TinyOS with TelosB motes. We examine ZiSense performance under controlled interference and office environments. The evaluation results show that, compared with the state-of-the-art rendezvous mechanisms, ZiSense significantly reduces the energy consumption.

Logical Correlation-Based Sleep Scheduling for WSNs in Ambient-Assisted Homes

This paper proposes a logical correlation-based sleep scheduling mechanism (LCSSM) to implement energy-efficient wireless sensor networks (WSNs) in ambient-assisted homes (AAHs). LCSSM analyzes sensory data generated by different human behaviors to detect the logical correlations between sensor nodes in an AAH. By utilizing the particular logical correlations of an AAH to predict its usage status, LCSSM deactivates sensor nodes accordingly to save energy when they are not expected to sense any valuable event. Evaluation results based on real life-logs have validated that LCSSM not only reduces the energy consumption of WSNs significantly, but also retains their quality of sensing successfully, e.g., with a moderate assumption on the duty cycling ratio and hardware configuration of sensor nodes, LCSSM successfully senses 98.7% valuable events with an average of 37.0% usual energy consumption, and extends the life time of WSNs by 63.4%.

Adaptive Sleep Efficient Hybrid Medium Access Control algorithm for next-generation wireless sensor networks

The scheduling algorithm is a fundamental design problem to allocate resources amongst different entities in distributive wireless sensor networks (WSNs). These sensor nodes have limited power and non-replenishable energy resources. In WSNs, the duty cycling mechanism is commonly used to save energy due to idle listening. On the other hand, a fixed duty cycling mechanism increases transmission latency in WSNs. Therefore, in order to ensure the prolonged network-life of WSNs, the medium access control (MAC) protocol should be tackled in an efficient manner to improve energy efficiency by minimizing idle listening, maximizing sleep duration, and eliminating data collision. This paper proposes a practical Adaptive Sleep Efficient Hybrid Medium Access Control (AEH-MAC) algorithm in which the key idea is to dynamically adjust nodes’ sleep time to improve the scheduling in WSNs. The AEH-MAC allows nodes to adjust sleep time dynamically according to the traffic load and coordinate wakeup time with neighbour nodes. A series of short taken packets are transmitted to wake the receiver, and a prediction field is introduced in the ACK packets (GRANT/RELEASE) to reduce the waiting time of the source node. In the proposed algorithm, each node maps a conflict-free time slot for itself up to two-hop neighbouring nodes. The simulation results show that the AEH-MAC algorithm achieves high performance in terms of runtime, number of rounds, energy consumption, and slot reservation.

Energy efficient context aware traffic scheduling for IoT applications

The evolution of Internet of Things (IoT) has increased the appetite for the energy efficient wireless infrastructures. Most of the IoT devices are inherently resource constrained and heterogeneous in respect of their traffic demand. Moreover, these devices need to be made adaptable to the varying environmental conditions. However, existing traffic scheduling and duty cycling algorithms lack the capability to meet the dynamic service quality requirements of IoT applications with variable context information. Specifically, they are infeasible for IoT use-cases where multi-hop communication is required. This paper strives to realize efficient resource allocation to the Wi-Fi based IoT devices in multi-hop IoT infrastructures. Firstly, IoT applications are characterized as per their heterogeneous traffic demand and mapped to the distinct weighted quality classes. Then, context awareness is introduced for IoT devices and an optimization model constrained by their service quality requirements and context priorities is presented. Further, an energy efficient context aware traffic scheduling (EE-CATS) algorithm is proposed wherein the convergence of model is specified by a sub-gradient projection method. The EE-CATS algorithm efficiently allocates resources to multi-hop IoT devices and reduce their total awake time by employing adaptive duty cycling. The performance evaluation is done for various IoT use-cases through simulations in Network Simulator (ns-2) and testbed implementation in Contiki operating system. The results suggest substantial improvements in the energy efficiency of IoT devices while ensuring their dynamic service requirements. In addition, the proposed algorithm minimizes the end-to-end delays in overall IoT networks.

Requirements, Design Challenges, and Review of Routing and MAC Protocols for CR-Based Smart Grid Systems

Cognitive radio technology can facilitate communication in smart grid applications through dynamic spectrum access. However, traditional routing and MAC protocols adopted for cognitive radio networks may not be beneficial in CR-based smart grid environments due to large data sizes and variable link quality among different functional blocks of smart grids. The interference and fading in wireless links necessitate efficient routing for reliable low-latency data delivery of smart grid applications. This low-latency data delivery must be achieved while protecting the legitimate primary users. Besides efficient routing, MAC layer protocols should be enhanced to achieve successful data delivery with simultaneous spectrum sensing and duty cycling for energy-efficient operation. In this article, we evaluate the requirements and key design challenges for routing and MAC protocols in the CR-based smart grid. We also provide a review of research carried out to date for routing and MAC protocols for the CR-based smart grid.

Harvesting-Aware Energy Management for Environmental Monitoring WSN

Wireless sensor networks can be used to collect data in remote locations, especially when energy harvesting is used to extend the lifetime of individual nodes. However, in order to use the collected energy most effectively, its consumption must be managed. In this work, forecasts of diurnal solar energies were made based on measurements of atmospheric pressure. These forecasts were used as part of an adaptive duty cycling scheme for node level energy management. This management was realized with a fuzzy logic controller that has been tuned using differential evolution. Controllers were created using one and two days of energy forecasts, then simulated in software. These controllers outperformed a human-created reference controller by taking more measurements while using less reserve energy during the simulated period. The energy forecasts were comparable to other available methods, while the method of tuning the fuzzy controller improved overall node performance. The combination of the two is a promising method of energy management.

Energy Efficient QoS-Aware Random Network Coding on Smartphones

Random network coding (RNC) technology is known to benefit various facets of information networks; however, there have been concerns for the computational complexity of RNC since its incipience. For instance, RNC's high complexity can be directly translated into high energy consumption and drain fast smartphone batteries, making it unsuitable for mobile environments. In this paper, we optimize the energy consumption of RNC implementations with a given QoS requirement, especially throughput, for smartphone environments. To this end, we propose a duty cycling approach minimizing the energy consumption of RNC with a given throughput constraint. By manipulating the processor clock frequency controlling mechanism (a.k.a. governor) in Android, our approach can indirectly regulate the processor clock frequency and enhance energy efficiency. Real experiments on Android systems with smartphone application processors such as Samsung's Exynos 5410, show that our method can reduce the energy consumption of RNC by up to 67% compared to a RNC implementation relying on ondemand governor for frequency control. Finally, we argue that our method can be applied to a wide range of applications by implementing it with a fast Fourier transform algorithm.

Activity-Aware Sensor Cycling for Human Activity Monitoring in Smart Homes

Smart homes are one of the Internet of Things domains intended to support and aid the residents through various smart services. These services require accurate context inferences using daily activity patterns and environmental properties. To satisfy such a need with battery-powered sensors, various duty cycling schemes were introduced. In this letter, we propose an activity-aware sensor cycling approach that makes the best tradeoff for duty cycle adjustments by exploiting the predictable behavior of residents, thereby significantly improving the activity detection accuracy at a marginal increase of the energy consumption. Evaluation results demonstrate that it achieves up to 99% accuracy of activity detection and extends the network lifetime by supporting balanced energy consumption among sensors.

A Sub-60- $\mu \text{A}$ Multimodal Smart Biosensing SoC With >80-dB SNR, 35- $\mu \text{A}$ Photoplethysmography Signal Chain

A sub-60- $\mu \text{A}$ multimodal analog front-end and ultralow energy biosensing CMOS SoC is presented. A 35- $\mu \text{A}$ photoplethysmography (PPG) signal chain that consumes five times lower power than state of the art has been demonstrated. An SNR of >80 dBFS was achieved using circuit and system techniques that enable sub-1% analog duty cycling. Input signal-aware, on-the-fly, real-time data path adaptation algorithms implemented on an external microcontroller and synchronized by an ultralow power on-chip FSM along with a 1.3- $\mu \text{W}$ , 14-b, 1-kSPS SAR ADC further lower system energy. A programmable, asynchronous reset capacitive amplifier (PARCA) with noise efficiency factor (NEF) of 4.8 and $dx$ / $dt$ analog feature extractor demonstrates energy efficient electrocardiogram (ECG) capture. A wearable platform using this SoC that simultaneously captures ECG plus PPG and wirelessly transmits the heart rate using Bluetooth low energy every 2 s to a smartphone lasts for greater than five days from a 250-mAhr battery.