Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Average Throughput Performance of Myopic Policy in Energy Harvesting Wireless Sensor Networks
Download
10.3390s17102206.pdf
Date
2017-9-26
Author
Gül, Ömer Melih
Demirekler, Mübeccel
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
207
views
134
downloads
Cite This
This paper considers a single-hop wireless sensor network where a fusion center collects data from M energy harvesting wireless sensors. The harvested energy is stored losslessly in an infinite-capacity battery at each sensor. In each time slot, the fusion center schedules K sensors for data transmission over K orthogonal channels. The fusion center does not have direct knowledge on the battery states of sensors, or the statistics of their energy harvesting processes. The fusion center only has information of the outcomes of previous transmission attempts. It is assumed that the sensors are data backlogged, there is no battery leakage and the communication is error-free. An energy harvesting sensor can transmit data to the fusion center whenever being scheduled only if it has enough energy for data transmission. We investigate average throughput of Round-Robin type myopic policy both analytically and numerically under an average reward (throughput) criterion. We show that Round-Robin type myopic policy achieves optimality for some class of energy harvesting processes although it is suboptimal for a broad class of energy harvesting processes.
Subject Keywords
Energy harvesting
,
Decision making
,
Resource allocation
,
Scheduling policy
,
Wireless sensor network
URI
https://hdl.handle.net/11511/51464
Journal
Sensors
DOI
https://doi.org/10.3390/s17102206
Collections
Department of Electrical and Electronics Engineering, Article
Suggestions
OpenMETU
Core
Asymptotically Optimal Scheduling for Energy Harvesting Wireless Sensor Networks
Gül, Ömer Melih (2017-10-13)
This paper considers a single-hop wireless sensor network where a fusion center (FC) collects data from M energy harvesting (EH) wireless sensor nodes. The harvested energy is stored losslessly in an infinite-capacity battery at each node. In each time slot, K nodes can be scheduled by the FC to send data over K orthogonal channels. The FC has no direct knowledge on the battery states of nodes, or the statistics of EH processes; it only has information of the outcomes of previous transmission attempts. The ...
Asymptotically Throughput Optimal Scheduling for Energy Harvesting Wireless Sensor Networks
Gul, Omer Melih; Demirekler, Mubeccel (Institute of Electrical and Electronics Engineers (IEEE), 2018)
In this paper, we investigate a single-hop wireless sensor network in which a fusion center (FC) collects data packets from M energy harvesting (EH) sensor nodes. Energy harvested by each node is stored without battery overflow and leakage at that node. The FC schedules K nodes over its mutually orthogonal channels to receive data from them in each time slot. The FC knows neither the statistics of EH processes nor the battery states of nodes. The FC solely has information on consequences of previous transmi...
Energy scavenging from low-frequency vibrations by using frequency up-conversion for wireless sensor applications
Külah, Haluk (2008-03-01)
This paper presents an electromagnetic (EM) vibration-to-electrical power generator for wireless sensors, which can scavenge energy from low-frequency external vibrations. For most wireless applications, the ambient vibration is generally at very low frequencies (1-100 Hz), and traditional scavenging techniques cannot generate enough energy for proper operation. The reported generator up-converts low-frequency environmental vibrations to a higher frequency through a mechanical frequency up-converter using a...
Analysis and modeling of routing and security problems in wireless sensor networks with mathematical programming
İncebacak, Davut; Baykal, Nazife; Bıçakcı, Kemal; Department of Information Systems (2013)
Wireless Sensor Networks (WSNs) are composed of battery powered small sensor nodes with limited processing, memory and energy resources. Self organization property together with infrastructureless characteristics of WSNs make them favorable solutions for many applications. Algorithms and protocols developed for WSNs must consider the characteristics and constraints of WSNs but since battery replenishment is not possible or highly challenging for sensor nodes, one of the major concerns in designing network p...
Wearable battery-less wireless sensor network with electromagnetic energy harvesting system
Chamanian, Salar; Ulusan, Hasan; Zorlu, Ozge; Baghaee, Sajjad; Uysal, Elif; Külah, Haluk (2016-10-01)
This paper presents a battery-less wireless sensor network (WSN) equipped with electromagnetic (EM) energy harvesters and sensor nodes with adjustable time-interval based on stored the energy. A wearable EM energy harvesting system is developed and optimized to power-up a typical wireless sensor mote from body motion. This is realized through characterization of the body motion and design of a compact EM energy harvester according to vibration frequencies generated during human running and walking. The harv...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
Ö. M. Gül and M. Demirekler, “Average Throughput Performance of Myopic Policy in Energy Harvesting Wireless Sensor Networks,”
Sensors
, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/51464.