Scheduling Algorithms for Optimizing Age of Information in Wireless Networks With Throughput Constraints

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-...

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Vydané v:	IEEE/ACM transactions on networking Ročník 27; číslo 4; s. 1359 - 1372
Hlavní autori:	Kadota, Igor, Sinha, Abhishek, Modiano, Eytan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.08.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Age of information Algorithms Computer simulation Drift Freshness Information age Monitoring Nodes Optimization Policies quality of service Radio equipment Scheduling Sensors Throughput Weight Wireless communication Wireless networks Wireless sensor networks
ISSN:	1063-6692, 1558-2566
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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 four 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, a Drift-Plus-Penalty policy, and a Whittle's Index policy, and show that they are guaranteed to be within a factor of two, four, two, and eight, respectively, away from the minimum AoI possible. The simulation results show that Max-Weight and Drift-Plus-Penalty outperform the other policies, both in terms of AoI and throughput, in every network configuration simulated, and achieve near-optimal performance.
AbstractList	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 four 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, a Drift-Plus-Penalty policy, and a Whittle’s Index policy, and show that they are guaranteed to be within a factor of two, four, two, and eight, respectively, away from the minimum AoI possible. The simulation results show that Max-Weight and Drift-Plus-Penalty outperform the other policies, both in terms of AoI and throughput, in every network configuration simulated, and achieve near-optimal performance.
Author	Kadota, Igor Modiano, Eytan Sinha, Abhishek
Author_xml	– sequence: 1 givenname: Igor orcidid: 0000-0002-9075-3377 surname: Kadota fullname: Kadota, Igor email: kadota@mit.edu organization: Laboratory for Information & Decision Systems (LIDS), Massachusetts Institute of Technology, Cambridge, MA, USA – sequence: 2 givenname: Abhishek orcidid: 0000-0001-7220-0691 surname: Sinha fullname: Sinha, Abhishek email: abhishek.sinha@ee.iitm.ac.in organization: IIT Madras, Chennai, India – sequence: 3 givenname: Eytan surname: Modiano fullname: Modiano, Eytan email: modiano@mit.edu organization: Laboratory for Information & Decision Systems (LIDS), Massachusetts Institute of Technology, Cambridge, MA, USA
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SubjectTerms	Age of information Algorithms Computer simulation Drift Freshness Information age Monitoring Nodes Optimization Policies quality of service Radio equipment Scheduling Sensors Throughput Weight Wireless communication Wireless networks Wireless sensor networks
Title	Scheduling Algorithms for Optimizing Age of Information in Wireless Networks With Throughput Constraints
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