A survey on energy efficient techniques in wireless sensor networks

International audienceThe myriad of potential applications supported by wireless sensor networks (WSNs) has generated much interest from the research community. Various applications range from small size low industrial monitoring to large scale energy constrained environmental monitoring. In all cases, an operational network is required to fulfill the application missions. In addition, energy consumption of nodes is a great challenge in order to maximize network lifetime. Unlike other networks, it can be hazardous, very expensive or even impossible to charge or replace exhausted batteries due to the hostile nature of environment. Researchers are invited to design energy efficient protocols while achieving the desired network operations. This paper focuses on different techniques to reduce the consumption of the limited energy budget of sensor nodes. After having identified the reasons of energy waste in WSNs, we classify energy efficient techniques into five classes, namely data reduction, control reduction, energy efficient routing, duty cycling and topology control. We then detail each of them, presenting subdivisions and giving many examples. We conclude by a recapitulative table

GREEN COMPUTING FOR IOT – SOFTWARE APPROACH

More efficient usage of limited energy resources on embedded platforms, found in various IoT applications, is identified as a universal challenge in designing such devices and systems. Although many power management techniques for control and optimization of device power consumption have been introduced at the hardware and software level, only few of them are addressing device operation at the application level. In this paper, a software engineering approach for managing the operation of IoT edge devices is presented. This approach involves a set of the application-level software parameters that affect consumption of the IoT device and its real-time behavior. To investigate and illustrate the impact of the introduced parameters on the device performance and its energy footprint, we utilize a custom-built simulation environment. The simulation results obtained from analyzing simplified data producer-consumer configuration of IoT edge tier, under push-based communication model, confirm that careful tuning of the identified set of parameters can lead to more energy efficient IoT end-device operation

Data-aided Sensing for Gaussian Process Regression in IoT Systems

In this paper, for efficient data collection with limited bandwidth, data-aided sensing is applied to Gaussian process regression that is used to learn data sets collected from sensors in Internet-of-Things systems. We focus on the interpolation of sensors' measurements from a small number of measurements uploaded by a fraction of sensors using Gaussian process regression with data-aided sensing. Thanks to active sensor selection, it is shown that Gaussian process regression with data-aided sensing can provide a good estimate of a complete data set compared to that with random selection. With multichannel ALOHA, data-aided sensing is generalized for distributed selective uploading when sensors can have feedback of predictions of their measurements so that each sensor can decide whether or not it uploads by comparing its measurement with the predicted one. Numerical results show that modified multichannel ALOHA with predictions can help improve the performance of Gaussian process regression with data-aided sensing compared to conventional multichannel ALOHA with equal uploading probability.Comment: 10 pages, 8 figures, to appear in IEEE IoT

Service-Oriented Node Scheduling Scheme for Wireless Sensor Networks Using Markov Random Field Model

Future wireless sensor networks are expected to provide various sensing services and energy efficiency is one of the most important criterions. The node scheduling strategy aims to increase network lifetime by selecting a set of sensor nodes to provide the required sensing services in a periodic manner. In this paper, we are concerned with the service-oriented node scheduling problem to provide multiple sensing services while maximizing the network lifetime. We firstly introduce how to model the data correlation for different services by using Markov Random Field (MRF) model. Secondly, we formulate the service-oriented node scheduling issue into three different problems, namely, the multi-service data denoising problem which aims at minimizing the noise level of sensed data, the representative node selection problem concerning with selecting a number of active nodes while determining the services they provide, and the multi-service node scheduling problem which aims at maximizing the network lifetime. Thirdly, we propose a Multi-service Data Denoising (MDD) algorithm, a novel multi-service Representative node Selection and service Determination (RSD) algorithm, and a novel MRF-based Multi-service Node Scheduling (MMNS) scheme to solve the above three problems respectively. Finally, extensive experiments demonstrate that the proposed scheme efficiently extends the network lifetime.This work is supported by the National Science Foundation of China under Grand No. 61370210 and the Development Foundation of Educational Committee of Fujian Province under Grand No. 2012JA12027.Cheng, H.; Su, Z.; Lloret, J.; Chen, G. (2014). Service-Oriented Node Scheduling Scheme for Wireless Sensor Networks Using Markov Random Field Model. Sensors. 14(11):20940-20962. https://doi.org/10.3390/s141120940S2094020962141

Ordonnancement de l'activité des noeuds dans les réseaux ad hoc et les réseaux de capteurs sans fil

National audienceL'efficacité énergétique est une exigence majeure pour les réseaux sans fil où certains noeuds opèrent sur batterie. L'ordonnancement de l'activité des noeuds permet de distinguer périodes actives où la communication radio est possible et périodes inactives où la radio est arrêtée. Cet ordonnancement contribue largement à améliorer l'efficacité énergétique : d'une part en évitant les collisions entre transmissions conflictuelles et donc les retransmissions associées et d'autre part en permettant aux noeuds non concernés par la transmission de dormir pour économiser leur énergie. Parmi les solutions possibles, nous étudierons plus particulièrement le coloriage des noeuds. Après avoir défini le problème et ses différentes déclinaisons, nous donnerons sa complexité et proposerons SERENA, un algorithme de coloriage distribué qui s'adapte à la collecte de données. Nous présenterons OSERENA, l'optimisation de SERENA pour les réseaux denses et son utilisation dans le réseau de capteurs sans fil OCARI. Lorsque les noeuds ont des charges de trafic fortement hétérogènes, il devient plus intéressant d'effectuer une assignation de slots. Disposer d'un accès au médium multicanal et d'un puits multi-interfaces permet de gagner en nombre de slots nécessaires à la collecte de données, de réduire les interférences et d'améliorer la résistance aux perturbations. Nous présenterons une formalisation en ILP (Integer Linear Programming) du problème d'assignation de slots visant à minimiser le nombre de slots en profitant d'un environnement mono ou multicanal et d'un puits mono ou multi-interfaces. Nous donnerons des bornes théoriques sur le nombre optimal de slots dans diverses configurations et divers environnements (mono ou multicanal, puits mono ou multi-interfaces). Nous présenterons MODESA un algorithme centralisé d'allocatoion conjointe de canaux et slots temporels. Nous terminerons par quelques questions ouvertes

A low power IoT sensor node architecture for waste management within smart cities context

This paper focuses on the realization of an Internet of Things (IoT) architecture to optimize waste management in the context of Smart Cities. In particular, a novel typology of sensor node based on the use of low cost and low power components is described. This node is provided with a single-chip microcontroller, a sensor able to measure the filling level of trash bins using ultrasounds and a data transmission module based on the LoRa LPWAN (Low Power Wide Area Network) technology. Together with the node, a minimal network architecture was designed, based on a LoRa gateway, with the purpose of testing the IoT node performances. Especially, the paper analyzes in detail the node architecture, focusing on the energy saving technologies and policies, with the purpose of extending the batteries lifetime by reducing power consumption, through hardware and software optimization. Tests on sensor and radio module effectiveness are also presented

A Survey on Energy-Efficient Strategies in Static Wireless Sensor Networks

A comprehensive analysis on the energy-efficient strategy in static Wireless Sensor Networks (WSNs) that are not equipped with any energy harvesting modules is conducted in this article. First, a novel generic mathematical definition of Energy Efficiency (EE) is proposed, which takes the acquisition rate of valid data, the total energy consumption, and the network lifetime of WSNs into consideration simultaneously. To the best of our knowledge, this is the first time that the EE of WSNs is mathematically defined. The energy consumption characteristics of each individual sensor node and the whole network are expounded at length. Accordingly, the concepts concerning EE, namely the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective, are proposed. Subsequently, the relevant energy-efficient strategies proposed from 2002 to 2019 are tracked and reviewed. Specifically, they respectively are classified into five categories: the Energy-Efficient Media Access Control protocol, the Mobile Node Assistance Scheme, the Energy-Efficient Clustering Scheme, the Energy-Efficient Routing Scheme, and the Compressive Sensing--based Scheme. A detailed elaboration on both of the basic principle and the evolution of them is made. Finally, further analysis on the categories is made and the related conclusion is drawn. To be specific, the interdependence among them, the relationships between each of them, and the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective are analyzed in detail. In addition, the specific applicable scenarios for each of them and the relevant statistical analysis are detailed. The proportion and the number of citations for each category are illustrated by the statistical chart. In addition, the existing opportunities and challenges facing WSNs in the context of the new computing paradigm and the feasible direction concerning EE in the future are pointed out

Energy efficiency in LEO satellite and terrestrial wired environments

To meet an ever-growing demand for advanced multimedia services and to support electronic connectivity anywhere on the planet, development of ubiquitous broadband multimedia systems is gaining a huge interest at both academic and industry levels. Satellite networks in general and LEO satellite constellations in particular will play an essential role in the deployment of such systems. Therefore, as LEO satellite constellations like Iridium or IridiumNEXT are extremely expensive to deploy and maintain, extending their service lifetimes is of crucial importance. In the main part of this thesis, we propose different techniques for extending satellite service life in LEO satellite constellations. Satellites in such constellations can spend over 30% of their time under the earth’s umbra, time during which they are powered by batteries. While the batteries are recharged by solar energy, the Depth of Discharge (DoD) they reach during eclipse significantly affects their lifetime – and by extension, the service life of the satellites themselves. For batteries of the type that power Iridium and Iridium-NEXT satellites, a 15% increase to the DoD can practically cut their service lives in half. We first focus on routing and propose two new routing metrics – LASER and SLIM – that try to strike a balance between performance and battery DoD in LEO satellite constellations. Our basic approach is to leverage the deterministic movement of satellites for favoring routing traffic over satellites exposed to the sun as opposed to the eclipsed satellites, thereby decreasing the average battery DoD– all without taking a significant penalty in performance. Then, we deal with resource consolidation – a new paradigm for the reduction of the power consumption. It consists in having a carefully selected subset of network links entering a sleep state, and use the rest to transport the required amount of traffic. This possible without causing major disruptions to network activities. Since communication networks are designed over the peak traffic periods, and with redundancy and over-provisioned in mind. As a remedy to these issues, we propose two different methods to perform resource consolidation in LEO networks. First, we propose trafficaware metric for quantifiying the quality of a frugal topology, the Maximum Link Utilization (MLU). With the problem being NP-hard subject to a given MLU threshold, we introduce two heuristics, BASIC and SNAP, which represent different tradeoffs in terms of performance and simplicity. Second, we propose a new lightweight traffic-agnostic metric for quantifiying the quality of a frugal topology, the Adequacy Index (ADI). After showing that the problem of minimizing the power consumption of a LEO network subject to a given ADI threshold is NP-hard, we propose a heuristc named AvOId to solve it. We evaluate both forms of resource consolidation using realistic LEO topologies and traffic requests. The results show that the simple schemes we develop are almost double the satellite batteries lifetime. Following the green networking in LEO systems, the second part of this thesis focuses on extending the resource consolidation schemes to current wired networks. Indeed, the energy consumption of wired networks has been traditionally overlooked. Several studies exhibit that the traffic load of the routers only has a small influence on their energy consumption. Hence, the power consumption in networks is strongly related to the number of active network elements. In this context, we extend the traffic-agnostic metric, ADI, to the wired networks. We model the problem subject to ADI threshold as NP-hard. Then, we propose two polynomial time heuristics – ABStAIn and CuTBAck. Although ABStAIn and CuTBAck are traffic unaware, we assess their behavior under real traffic loads from 3 networks, demonstrating that their performance are comparable to the more complex traffic-aware solutions proposed in the literature