Effect of Battery Dynamics and the Associated Technologies on the Life Time of Wireless Sensor Networks (original) (raw)
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Efficient Battery Management in Wireless Sensor Node: Review Paper
Wireless sensor network is an emerging field in wireless networking. Wireless Sensor Node (WSN) is the key component of wireless sensor networks for data communication inn large networks. WSN is powered with battery as its source of energy. It is usually deployed in hostile. Alkaline batteries are dominantly used in WSN. We need to maximize utilization of battery used in WSN. In this paper we have reviewed various models of the alkaline battery for maximizing its utilization and its lifetime. A brief experiment on relaxation model has been carried out which is most suitable battery model for predicting lifetime of battery in WSN.
Journal of Sensor and Actuator Networks
The operation of Wireless Sensor Networks (WSNs) is subject to multiple constraints, among which one of the most critical is available energy. Sensor nodes are typically powered by electrochemical batteries. The stored energy in battery devices is easily influenced by the operating temperature and the discharge current values. Therefore, it becomes difficult to estimate their voltage/charge behavior over time, which are relevant variables for the implementation of energy-aware policies. Nowadays, there are hardware and/or software approaches that can provide information about the battery operating conditions. However, this type of hardware-based approach increases the battery production cost, which may impair its use for sensor node implementations. The objective of this work is to propose a software-based approach to estimate both the state of charge and the voltage of batteries in WSN nodes based on the use of a temperature-dependent analytical battery model. The achieved results demonstrate the feasibility of using embedded analytical battery models to estimate the lifetime of batteries, without affecting the tasks performed by the WSN nodes.
mTOSSIM: A simulator that estimates battery lifetime in wireless sensor networks
Simulation Modelling Practice and Theory, 2013
Knowledge of the battery lifetime of the wireless sensor network is important for many situations, such as in evaluation of the location of nodes or the estimation of the connectivity, along time, between devices. However, experimental evaluation is a very time-consuming task. It depends on many factors, such as the use of the radio transceiver or the distance between nodes. Simulations reduce considerably this time. They allow the evaluation of the network behavior before its deployment. This article presents a simulation tool which helps developers to obtain information about battery state. This simulator extends the well-known TOSSIM simulator. Therefore it is possible to evaluate TinyOS applications using an accurate model of the battery consumption and its relation to the radio power transmission. Although an specific indoor scenario is used in testing of simulation, the simulator is not limited to this environment. It is possible to work in outdoor scenarios too. Experimental results validate the proposed model.
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… and Applications Workshops, 2007, 7
It is challenging to design a sensor network if sensors are battery powered. Efficient scheduling and budgeting battery power in sensor networks has become a critical issue in network design. We investigate how energy ratio and the battery ratio, the ratio of initial battery capacities for sensors and cluster heads, affects sensor network lifetime. These results allow the network designer to specify required battery capacities which optimizing energy usage, and therefore leads to reduced total costs for the network which is extremely important in wireless sensor networks.
Experimental Analysis of Wireless Sensor Nodes Current Consumption
2008 Second International Conference on Sensor Technologies and Applications (sensorcomm 2008), 2008
Wireless Sensor Node (WSN) lifetime is correlated with the battery current usage profile. State of the art in wireless sensor nodes current consumption shows that available models have not been extensively tested and experimentally validated. This work aims to seek answers to the following questions: is it accurate the node lifetime prediction obtained with available models? Moreover, is the radio transceiver always responsible for depleting the battery? In order to perform experimental evaluations, we implemented a prototype board that enables to visualize charge extracted from batteries and battery current consumption waveforms of wireless sensor nodes. We selected benchmarks that represent usual tasks in WSN applications and we made experimental evaluations of battery current consumption. Finally, a battery fulldepletion time measurement has been performed. Overall results are presented and discussed.
Online estimation of battery lifetime for wireless sensors network
2012
Battery is a major hardware component of wireless sensor networks. Most of them have no power supply and are generally deployed for a long time. Researches have been done on battery physical model and their adaptation for sensors. We present an implementation on a real sensor operating system and how architectural constraints have been assumed. Experiments have been made in order to test the impact of some parameter, as the application throughput, on the battery lifetime.
Schemes for Extending the Network Lifetime of Wireless Rechargeable Sensor Networks
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Most Wireless Rechargeable Sensor Networks (WRSN) allow simultaneous energy replenishment with data gathering. These schemes suffer from high energy consumption of mobile chargers and could require new sensor design for their integration. Thus, we propose Distributed Energy Replenishment and Data Gathering (DERDG) to reduce the energy consumption of the chargers and Spatio-Temporal Non-Concurrent Data gathering and Energy replenishment (ST-NCDR) that are easily be integratable on the sensor nodes. In these schemes, sensor nodes are divided into clusters and requests from energy-hungry nodes are arranged based on their temporal properties in DERDG, but using their spatial and temporal properties in ST-NCDR. In ST-NCDR scheme, two mobile chargers replenish the energy of energyhungry nodes when they are not performing sensing and transmission of data, but irrespective of their operational states in DERDG scheme. Simulation results indicate the superiority of the schemes over state-of-the-art schemes in terms of energy consumption of mobile chargers and average residual energy of the nodes. Both DERDG and ST-NCDR reduced the energy consumption of the chargers, without reduction in the network lifetime, by an average of 29.45% and 73.70%, respectively, when compared to the work of Han et al. (2018), and by 71.40% and 93.80% in comparison to the work of Mikail et al. (2020). DERDG reduces data delivery delay by 95.50% in comparison to the work of Han et. al, (2018). The findings imply that ST-NCDR can be easily integrated into sensor nodes and yields a reduction in the energy of mobiles chargers use in charging the sensor nodes that translate to lower cost of network operation, in addition to improving the residual energy of nodes in WRSN. This part should state the context of the research being reported. Aim: the objective of the research should be clearly stated here Method: the research approach used in the study, justifying its suitability for the study should be stated here. Results: the findings and their implication(s) should be clearly enumerated and briefly discussed here.
Journal of Computer Networks and Communications, 2012
Despite the well-known advantages of communication solutions based on energy harvesting, there are scenarios where the absence of batteries (supercapacitor only) or the use of rechargeable batteries is not a realistic option. Therefore, the alternative is to extend as much as possible the lifetime of primary cells (nonrechargeable batteries). By assuming low duty-cycle applications, three powermanagement techniques are combined in a novel way to provide an efficient energy solution for wireless sensor networks nodes or similar communication devices powered by primary cells. Accordingly, a customized node is designed and long-term experiments in laboratory and outdoors are realized. Simulated and empirical results show that the battery lifetime can be drastically enhanced. However, two trade-offs are identified: a significant increase of both data latency and hardware/software complexity. Unattended nodes deployed in outdoors under extreme temperatures, buried sensors (underground communication), and nodes embedded in the structure of buildings, bridges, and roads are some of the target scenarios for this work. Part of the provided guidelines can be used to extend the battery lifetime of communication devices in general.
Extending the Lifetime and Balancing Energy Consumption in Wireless Sensor Networks
Network lifetime is a crucial performance metric to evaluate data-gathering wireless sensor networks (WSNs) where battery-powered sensor nodes periodically sense the environment and forward collected samples to a sink node. In this project, we propose an analytic model to estimate the entire network lifetime from network initialization until it is completely disabled, and determine the boundary of energy hole in a data-gathering WSN. Specifically, we theoretically estimate the traffic load, energy consumption, and lifetime of sensor nodes during the entire network lifetime. Furthermore, we investigate the temporal and spatial evolution of energy hole, and apply our analytical results to WSN routing in order to balance the energy consumption and improve the network lifetime. Extensive simulation results are provided to demonstrate the validity of the proposed analytic model in estimating the network lifetime and energy hole evolution process.