Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. Optimizing Age of Information in Wireless Networks with Throughput Constraints

Optimizing Age of Information in Wireless Networks with Throughput Constraints

Thumbnail Image
Download
Name

2018INFOCOM.pdf

Description
Accepted version
Size

545.61 KB

Format

Adobe PDF

Checksum (MD5)

086ef5eac05b71666c7fd744815def19

sword-2019-10-30T15:37:05.original.xml (130 B)
Original SWORD entry document
Author(s)
Kadota, Igor
•
Sinha, Abhishek
•
Modiano, Eytan H
Date Issued
April 2018
Journal
IEEE INFOCOM 2018 - IEEE Conference on Computer Communications
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Kadota, Igor, Sinha, Abhishek, and Modiano, Eytan. "Optimizing Age of Information in Wireless Networks with Throughput Constraints," IEEE INFOCOM 2018 - IEEE Conference on Computer Communications, April 2018, Honolulu, HI, 2018 Institute of Electrical and Electronics Engineers.
Version
Author's final manuscript
Abstract
Age of Information (AoI) is a performance metric that captures the freshness of the information from the perspective of the destination. The AoI measures the time that elapsed since the generation of the packet that was most recently delivered to the destination. In this paper, we consider a single-hop wireless network with a number of nodes transmitting time-sensitive information to a Base Station and address the problem of minimizing the Expected Weighted Sum AoI of the network while simultaneously satisfying timely-throughput constraints from the nodes. We develop three low-complexity transmission scheduling policies that attempt to minimize AoI subject to minimum throughput requirements and evaluate their performance against the optimal policy. In particular, we develop a randomized policy, a Max-Weight policy and a Whittle's Index policy, and show that they are guaranteed to be within a factor of two, four and eight, respectively, away from the minimum AoI possible. In contrast, simulation results show that Max-Weight outperforms the other policies, both in terms of AoI and throughput, in every network configuration simulated, and achieves near optimal performance.
MIT Department
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
http://creativecommons.org/licenses/by-nc-sa/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/124684
DOI of Published Version
https://doi.org/10.1109/infocom.2018.8486307
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.