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
Asymptotically Optimal Scheduling for Energy Harvesting Wireless Sensor Networks
Date
2017-10-13
Author
Gül, Ömer Melih
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
187
views
0
downloads
Cite This
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 objective is to find a simple policy whereby maximum total throughput is achieved in this data back-logged system. A node can transmit data whenever being scheduled, provided it has sufficient energy for transmission. A simple policy, Uniforming Random Ordered Policy (UROP), is proposed for the problem. UROP is proved to be asymptotically optimal over infinite time horizon for general EH processes. Numerical results indicate that even with finite-capacity batteries, UROP achieves near-optimal throughput. We believe that UROP is applicable to a wider area than EH wireless sensor networks.
Subject Keywords
Energy harvesting
,
Mobile computing
,
Resource allocation
,
Scheduling policy
,
Wireless sensor networks
URI
https://hdl.handle.net/11511/55871
Conference Name
28th Annual IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Average Throughput Performance of Myopic Policy in Energy Harvesting Wireless Sensor Networks
Gül, Ömer Melih; Demirekler, Mübeccel (MDPI AG, 2017-9-26)
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 ...
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...
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...
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...
Exploiting energy-aware spatial correlation in wireless sensor networks
Shah, Ghalib A.; Bozyigit, Muslim (2007-01-12)
Wireless sensor networks (WSNs) promise fine-grain monitoring in a wide variety of applications, which require dense sensor nodes deployment. Due to high density of nodes, spatially redundant or correlated data is generated. Redundancy increases the reliability level of information delivery but increases the energy consumption of the nodes too. Since energy conservation is a key issue for WSNs, therefore, spatial correlation can be exploited to deactivate some of the nodes generating redundant information. ...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
Ö. M. Gül, “Asymptotically Optimal Scheduling for Energy Harvesting Wireless Sensor Networks,” presented at the 28th Annual IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Montreal, CANADA, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55871.