Optimal energy management policies for energy harvesting sensor nodes

By V. Sharma, U. Mukherji, V. Joseph, Shrey Gupta. IEEE Transactions on Wireless Communications, 2008

655 citations recorded by the source corpus.

We study a sensor node with an energy harvesting source. The generated energy can be stored in a buffer. The sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time. We obtain energy management policies that are throughput optimal, i.e., the data queue stays stable for the largest possible data rate. Next we obtain energy management policies which minimize the mean delay in the queue. We also compare performance of several easily implementable sub-optimal energy management policies. A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/2d2a9a9d3a7b989151b6052423bcd51e3c8a2a78

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Joint mobile energy replenishment and data gathering in wireless rechargeable sensor networks (2011, background): “In this section, we briefly review some related work in the literature, which includes the work on energy replenishment in wireless networks, and the work on mobile data gathering in wireless sensor networks.”
Energy-Harvesting Wireless Sensor Networks (EH-WSNs) (2018, methodology): “This variability in the available energy for EH-WSNs has led to the idea of designing either the individual node or the larger network to operate at an energy equilibrium, also called energy-neutral operation (ENO) (Sharma et al. 2010b).”
Optimal Energy Allocation for Wireless Communications With Energy Harvesting Constraints (2011, background): “In [3], the discounted throughput is maximized over an infinite horizon, where queuing for data is also considered.”
Robust Beamforming for Wireless Information and Power Transmission (2012, background): “ENERGY harvesting for wireless communication is able to extend the flying power of handheld devices and advocacy for green communication [1]- [3].”
Advances in Energy Harvesting Communications: Past, Present, and Future Challenges (2016, methodology): “design considerations [75], [83]–[85], [88], [94].”
Throughput Maximization for the Gaussian Relay Channel with Energy Harvesting Constraints (2011, methodology): “For the point-to-point communication powered by EH sources, the power management problem was studied in [3]–[5] with the deterministic EH model, and in [4], [6], [7] with the random EH model.”
Broadcasting with an Energy Harvesting Rechargeable Transmitter (2010, methodology): “References [12], [13] address single-user energy harvesting rechargeable systems as well, with a slotted time system model.”
Optimum Transmission Policies for Battery Limited Energy Harvesting Nodes (2010, background): “The performance that such systems can deliver is tied closely to efficient utilization of energy that is currently available, as well as that is to be harvested.”
Joint Energy Harvesting and Communication Analysis for Perpetual Wireless Nanosensor Networks in the Terahertz Band (2012, critical): “Even in several recent models for energy harvesting networks [16], [18], [21], [30], the correlation between the energy harvesting and the energy consumption processes are not fully captured.”
The role of communication systems in smart grids: Architectures, technical solutions and research challenges (2013, background): “Therefore, new power management schemes, transmission techniques, data aggregation and link scheduling algorithms, and routing protocols are needed to exploit the sporadic availability of energy [191] [192] [193] .”