A framework to design the computational load distribution of wireless sensor networks in power consumption constrained environments

En este documento, presentamos un trabajo basado en la distribución de la carga computacional entre los nodos homogéneos y el Hub/Sink de las Redes de Sensores Inalámbricos (WSN). La principal contribución del trabajo es un marco de apoyo a las decisiones tempranas que ayuda a los diseñadores de WSN a tomar decisiones sobre la distribución de la carga computacional para aquellas WSN en las que el consumo de energía es una cuestión clave (cuando nos referimos a "marco" en este trabajo, lo consideramos como una herramienta de apoyo para tomar decisiones en las que el juicio ejecutivo puede ser incluido junto con el conjunto de herramientas matemáticas del diseñador de WSN; este trabajo muestra la necesidad de incluir la distribución de la carga como un componente integral del sistema de WSN para tomar decisiones tempranas en relación con el consumo de energía). El marco aprovecha la idea de que equilibrar los nodos sensores y la carga computacional del Hub/Sink puede conducir a un mejor consumo de energía para la totalidad o al menos los nodos alimentados por batería de la WSN. El enfoque no es trivial y tiene en cuenta cuestiones conexas como la distribución de los datos necesarios, los nodos y la conectividad y disponibilidad del Hub/Sink debido a sus características de conectividad y su ciclo de trabajo. Para una demostración práctica, el marco propuesto se aplica a un estudio de caso de agricultura, un sector muy relevante en nuestra región. En este tipo de contexto rural, las distancias, los bajos costos debido a los precios de venta de las verduras y la falta de suministro continuo de energía pueden dar lugar a soluciones de detección viables o inviables para los agricultores. El marco propuesto sistematiza y facilita a los diseñadores de las WSN los complejos cálculos necesarios teniendo en cuenta las variables más relevantes en cuanto al consumo de energía, evitando implementaciones completas/parciales/prototipos, y mediciones de diferentes soluciones potenciales de distribución de la carga computacional para una WSN específica.In this paper, we present a work based on the computational load distribution among the homogeneous nodes and the Hub/Sink of Wireless Sensor Networks (WSNs). The main contribution of the paper is an early decision support framework helping WSN designers to take decisions about computational load distribution for those WSNs where power consumption is a key issue (when we refer to “framework” in this work, we are considering it as a support tool to make decisions where the executive judgment can be included along with the set of mathematical tools of the WSN designer; this work shows the need to include the load distribution as an integral component of the WSN system for making early decisions regarding energy consumption). The framework takes advantage of the idea that balancing sensors nodes and Hub/Sink computational load can lead to improved energy consumption for the whole or at least the battery-powered nodes of the WSN. The approach is not trivial and it takes into account related issues such as the required data distribution, nodes, and Hub/Sink connectivity and availability due to their connectivity features and duty-cycle. For a practical demonstration, the proposed framework is applied to an agriculture case study, a sector very relevant in our region. In this kind of rural context, distances, low costs due to vegetable selling prices and the lack of continuous power supplies may lead to viable or inviable sensing solutions for the farmers. The proposed framework systematize and facilitates WSN designers the required complex calculations taking into account the most relevant variables regarding power consumption, avoiding full/partial/prototype implementations, and measurements of different computational load distribution potential solutions for a specific WSN.• Ministerio de Economía y Competitividad y Fondos FEDER. Proyecto TIN2015-69957-R (I+D+i) • Project International Institute of Investigation and Innovation of Aging. Ref. 0445_4IE_4_P • European Regional Development Fund (ERDF) through the Interreg V-A Spain Portugal Program (POCTEP) 2014-2020peerReviewe

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Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

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