Conference Paper

Wireless Sensor Networks Powered by Ambient Energy Harvesting (WSN-HEAP) - Survey and Challenges

Networking Protocols Dept., Inst. for Infocomm Res., Singapore, Singapore
DOI: 10.1109/WIRELESSVITAE.2009.5172411 Conference: Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology, 2009. Wireless VITAE 2009. 1st International Conference on
Source: IEEE Xplore


Wireless sensor networks (WSNs) research has pre-dominantly assumed the use of a portable and limited energy source, viz. batteries, to power sensors. Without energy, a sensor is essentially useless and cannot contribute to the utility of the network as a whole. Consequently, substantial research efforts have been spent on designing energy-efficient networking protocols to maximize the lifetime of WSNs. However, there are emerging WSN applications where sensors are required to operate for much longer durations (like years or even decades) after they are deployed. Examples include in-situ environmental/habitat monitoring and structural health monitoring of critical infrastructures and buildings, where batteries are hard (or impossible) to replace/recharge. Lately, an alternative to powering WSNs is being actively studied, which is to convert the ambient energy from the environment into electricity to power the sensor nodes. While renewable energy technology is not new (e.g., solar and wind) the systems in use are far too large for WSNs. Those small enough for use in wireless sensors are most likely able to provide only enough energy to power sensors sporadically and not continuously. Sensor nodes need to exploit the sporadic availability of energy to quickly sense and transmit the data. This paper surveys related research and discusses the challenges of designing networking protocols for such WSNs powered by ambient energy harvesting.

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Available from: Winston K. G. Seah
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    • "Such systems are also motivated by the cost or difficulty of access, and also by the potential environmental damage when one discards batteries, and by the need to save energy in ICT [4], [5]. Thus energy harvesting from solar, thermal, vibrationial, or ambient electromagnetic radiation including light, are of particular interest [6], [7], especially in remote sensing and security applications [8], [9], [10], and recent research has addressed such technologies for communications [11]. However much work still needs to be done to understand the performance of such systems which need to operate autonomously for very long periods of time. "
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    ABSTRACT: While complex autonomic self-organising systems have received much attention, simple autonomous systems are also needed for remote sensing applications, as well as for the Internet of Things. Such autonomous stand-alone unattended devices may not have access to reliable sources of mains power, and will have to harvest energy locally from ambient sources such as vibrations, heat or light. However energy leakage will also be a problem. This paper proposes a mathematical model to analyse the performance of such systems in the presence of a random source of energy, as well as a random source of data. The equilibrium between random energy, random data and random leakage results in an interesting performance analysis of these small but ubiquitous systems as a whole. A discussion is also provided about the effect of transmission errors.
    Full-text · Article · Jan 2016
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    • "The emergence of wireless sensor networks (WSNs) can be traced back to an initiative by the National Research Council [1] and development has been motivated by military applications, like battlefield surveillance, where sensors are typically powered by batteries. Since then, new WSN applications, such as environmental monitoring and structural health monitoring (SHM) have emerged where deployment is expected to last much longer periods, and alternative energy sources like energy harvesting [2] are increasingly sought. Whether the sensor node is powered by batteries or energy harvesting, power constraint remains a key design issue. "
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    ABSTRACT: Wireless sensor networks (WSNs) are designed for sensing phenomenon and acquiring data. In structural health monitoring (SHM) of critical infrastructure, increasingly large number of sensor nodes are deployed to acquire data at the spatial density needed for structural integrity assessment. After rare catastrophic events (like earthquakes) a large volume of data related to the event can be produced in an instant, and need to be sent (to remote locations) for analysis. When many nodes are trying to transmit their data simultaneously, the contention for the wireless channel increases the probability of packet collisions resulting in packet drops, multiple retransmission attempts and consequently delays; it is also not uncommon to find certain nodes (e.g. closer to the sink) having better chances of successful transmission leading to biased data delivery. While clustering has been extensively used to reduce contention in wireless networks, the performance criteria for the network is still very node-focused. This paper presents a new perspective on cluster-based WSNs and proposes a cluster centric design that aims to tackle medium access control (MAC) layer congestion associated with burst packet generation in an unbiased manner, making it suitable for applications like SHM.
    Full-text · Conference Paper · May 2015
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    • "IGHT-HARVESTING wireless sensors that can sense and communicate using energy harvested from ambient light have been proposed for monitoring applications related to environment, buildings, and remote equipment [1]–[3] as well as for low-rate control applications in building and lighting systems [4]–[6]. "
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    ABSTRACT: We consider networked control of luminaires to adapt illumination in an indoor environment to occupancy and daylight based on distributed light-harvesting wireless sensing modules. Each light-harvesting wireless sensing module consists of an occupancy sensor, a light sensor, a wireless radio, a microcontroller unit, and a photovoltaic cell. The occupancy sensor and light sensor, respectively, determine presence and illumination level within their fields-of-view. This local sensor information, along with control information from neighboring sensing modules, is used by a local controller to determine the dimming level of its luminaire so as to achieve its reference setpoint. To realize this system, we propose a low-power wireless sensing protocol and a neighbor-aided illumination control method considering the harvesting constraints of the sensors. The proposed methods are implemented in an indoor lighting system testbed and the performance is shown to meet desired illumination conditions.
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