A Framework to Design the Computational Load Distribution of Wireless Sensor Networks in Power Consumption Constrained Environments

Abstract

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.

Highly Sensitive and Compact Quad-Band Ambient RF Energy Harvester

“…T HE INTERNET of Things (IoTs) is spawning the use of sensors, which are both pervasive and ubiquitous in every aspect of our lives. Whilst recent advances in modern sensors and IoT devices appear to be unlimited, the dependence of their operation on batteries remains a significant weakness which has imposed restrictions on the range, lifetime, environmental pollution, and are often challenging to replace them [1]- [3]. This creates an inspiration to develop an alternative method to feed sensors.…”

Design of Wireless Sensors for IoT with Energy Storage and Communication Channel Heterogeneity

“…A wide range of WSN standards for communication for short, medium, and long range exist, implemented on a variety of communication protocols and various frequencies, using a wide range of power sources, as summarized in Table 1 [1,2,3,4,5,6,7]. However, not all of them can be applied to real-world applications, where factors such as: environmental conditions (temperature, humidity, etc.…”

“…Only possible by adding a long range antenna (gain: 20-30 dB) 2. Based on range and throughput loss measurements and estimations[79,81,84].…”

“…The T2: [t1,t2] interval can be replaced with the T4: [t3,t4] interval due to reduced energy and period 2. The spike interval is considered as part of the T1: [0,t1] interval since it is not outside the transmission period.…”

Design of a Novel Load Balanced Multi-Sink Based Hierarchical Data Gathering Protocol for Wireless Sensor Networks

“…Sensed data's are converted to digital signal for multiple purposes like reading, displaying or can used for further processing. The sensors are the mostly resource constraint in nature i.e., low computational capacity, limited data transmission and equipped with constraint power [2]. These sensors have been connected in Ad-hoc mode to form a wireless sensor Network (WSN) are used to gather data from the sensing field then process the collected data and forwards the processed data to the sink node (SN) by strategies for radio signs [3].…”