A Framework for Optimizing the Process of Energy Harvesting from Ambient RF Sources

Energy harvesting has been an active research topic in the past half a decade with respect to wireless networks. We reviewed some of the recent techniques towards improving energy harvesting performance to find that there is a large scope of improvement in terms of optimization and addressing problems pertaining to low-powered communicating mobile nodes. Therefore, we present a framework for identifying available RF sources of energy and constructing a robust link between the energy source and the mobile device. We apply linear optimization approach to enhance the performance of energy harvesting. Probabilility theory is used for identification of event loss in the presence of different number of nodes as well as node distances. The objective of the proposed system is to offer better availability of RF signals as well as better probability of energy harvesting for mobile devices. The proposed technique is also found to be computationally cost effective

A new task scheduling approach for energy conservation in Internet of Things

Internet of Things (IoT) and mobile edge computing (MEC) architectures are common in real-time application scenarios for improving the reliability of service responses. Energy conservation (EC) and energy harvesting (EH) are significant concerns in such architectures due to the self-sustainable devices and resource-constraint edge nodes. The density of the users and service requirements are further reasons for energy conservation and the need for energy harvesting in these scenarios. This article proposes decisive task scheduling for energy conservation (DTS-EC). The proposed energy conservation method relies on conditional decision-making through classification disseminations and energy slots for data handling. By classifying the energy requirements and the states of the mobile edge nodes, the allocation and queuing of data are determined, preventing overloaded nodes and dissemination. This process is recurrent for varying time slots, edge nodes, and tasks. The proposed method is found to achieve a high data dissemination rate (8.16%), less energy utilization (10.65%), and reduced latency (11.44%) at different time slots

Improving Maximum Data Collection Based On Pre-Specified Path Using a Mobile Sink for WSN

Data aggregation is one of the challenging issues which are faced in the wireless sensor network by using Energy Harvesting Sensors. Data collection in a fixed pre-defined path with time varying characteristic forms a major problem in Energy Harvesting Sensor Networks. In the proposed work the Adjustment based allocation method is used to allocate fixed time slots to each sensor nodes in which the network throughput can be increased with less energy consumption. The mobile sink transmits the polling message to all the nodes within the transmission range and makes decision based on the profits gained by the sensor nodes in each timeslot. The NP-Hard problem is defined with the form of reducing the complexity of the sensor nodes where larger number of data can be collected from the environment. The data collection throughput is maximized with the use of optimized path for the mobile sink in the network. This record was migrated from the OpenDepot repository service in June, 2017 before shutting down

Piezoelectric Energy Harvesting: Enhancing Power Output by Device Optimisation and Circuit Techniques

Energy harvesting; that is, harvesting small amounts of energy from environmental sources such as solar, air flow or vibrations using small-scale (≈1cm 3 ) devices, offers the prospect of powering portable electronic devices such as GPS receivers and mobile phones, and sensing devices used in remote applications: wireless sensor nodes, without the use of batteries. Numerous studies have shown that power densities of energy harvesting devices can be hundreds of µW; however the literature also reveals that power requirements of many electronic devices are in the mW range. Therefore, a key challenge for the successful deployment of energy harvesting technology remains, in many cases, the provision of adequate power. This thesis aims to address this challenge by investigating two methods of enhancing the power output of a piezoelectric-based vibration energy harvesting device. Cont/d

Energy harvesting over Rician fading channel: A performance analysis for half-duplex bidirectional sensor networks under hardware impairments

In this paper, a rigorous analysis of the performance of time-switching energy harvesting strategy that is applied for a half-duplex bidirectional wireless sensor network with intermediate relay over a Rician fading channel is presented to provide the exact-form expressions of the outage probability, achievable throughput and the symbol-error-rate (SER) of the system under the hardware impairment condition. Using the proposed probabilistic models for wireless channels between mobile nodes as well as for the hardware noises, we derive the outage probability of the system, and then the throughput and SER can be obtained as a result. Both exact analysis and asymptotic analysis at high signal-power-to-noise-ratio regime are provided. Monte Carlo simulation is also conducted to verify the analysis. This work confirms the effectiveness of energy harvesting applied in wireless sensor networks over a Rician fading channel, and can provide an insightful understanding about the effect of various parameters on the system performance.Web of Science186art. no. 1781

Ultra low-power photovoltaic MPPT technique for indoor and outdoor wireless sensor nodes

Photovoltaic (PV) energy harvesting is commonly used to power wireless sensor nodes. To optimise harvesting efficiency, maximum power point tracking (MPPT) techniques are often used. Recently-reported techniques focus solely on outdoor applications, being too power-hungry for use under indoor lighting. Additionally, some techniques have required light sensors (or pilot cells) to control their operating point. This paper describes an ultra low-power MPPT technique which is based on a novel system design and sample-and-hold arrangement, which enables MPPT across the range of light intensities found indoors and outdoors and is capable of cold-starting. The proposed sample-and-hold based technique has been validated through a prototype system. Its performance compares favourably against state-of-the-art systems, and does not require an additional pilot cell or photodiode. This represents an important contribution, in particular for sensors which may be exposed to different types of lighting (such as body-worn or mobile sensors)

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

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

Power Switching Protocol for Two-way Relaying Network under Hardware Impairments

In this paper, we analyze the impact of hardware impairments at relay node and source node (i.e. imperfect nodes) on network performance by evaluating outage probability based on the effective signal to noise and distortion ratio (SNDR). Especially, we propose energy harvesting protocol at the relay and source nodes, namely, power switching imperfect relay (PSIR) and power switching imperfect source (PSIS). Aiming to determine the performance of energy constrained network, we first derive closed-form expressions of the outage probability and then the throughput can be maximized in delay-limited transmission mode. The simulation results provide practical insights into the impacts of hardware impairments and power switching factors of the energy harvesting protocol on the performance of energy harvesting enabled two-way relaying network