TY - GEN
T1 - Age-based scheduling
T2 - 19th ACM International Symposium on Mobile Ad-Hoc Networking and Computing, MobiHoc 2018
AU - Lu, Ning
AU - Ji, Bo
AU - Li, Bin
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/6/26
Y1 - 2018/6/26
N2 - We consider the problem of scheduling real-time traffic with hard deadlines in a wireless ad hoc network. In contrast to existing real-time scheduling policies that merely ensure a minimal timely throughput, our design goal is to provide guarantees on both the timely throughput and data freshness in terms of age-of-information (AoI), which is a newly proposed metric that captures the "age" of the most recently received information at the destination of a link. The main idea is to introduce the AoI as one of the driving factors in making scheduling decisions. We first prove that the proposed scheduling policy is feasibility-optimal, i.e., satisfying the per-traffic timely throughput requirement. Then, we derive an upper bound on a considered data freshness metric in terms of AoI, demonstrating that the network-wide data freshness is guaranteed and can be tuned under the proposed scheduling policy. Interestingly, we reveal that the improvement of network data freshness is at the cost of slowing down the convergence of the timely throughput. Extensive simulations are performed to validate our analytical results. Both analytical and simulation results confirm the capability of the proposed scheduling policy to improve the data freshness without sacrificing the feasibility optimality.
AB - We consider the problem of scheduling real-time traffic with hard deadlines in a wireless ad hoc network. In contrast to existing real-time scheduling policies that merely ensure a minimal timely throughput, our design goal is to provide guarantees on both the timely throughput and data freshness in terms of age-of-information (AoI), which is a newly proposed metric that captures the "age" of the most recently received information at the destination of a link. The main idea is to introduce the AoI as one of the driving factors in making scheduling decisions. We first prove that the proposed scheduling policy is feasibility-optimal, i.e., satisfying the per-traffic timely throughput requirement. Then, we derive an upper bound on a considered data freshness metric in terms of AoI, demonstrating that the network-wide data freshness is guaranteed and can be tuned under the proposed scheduling policy. Interestingly, we reveal that the improvement of network data freshness is at the cost of slowing down the convergence of the timely throughput. Extensive simulations are performed to validate our analytical results. Both analytical and simulation results confirm the capability of the proposed scheduling policy to improve the data freshness without sacrificing the feasibility optimality.
UR - http://www.scopus.com/inward/record.url?scp=85049838886&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85049838886&partnerID=8YFLogxK
U2 - 10.1145/3209582.3209602
DO - 10.1145/3209582.3209602
M3 - Conference contribution
AN - SCOPUS:85049838886
T3 - Proceedings of the International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc)
SP - 191
EP - 200
BT - Mobihoc 2018 - Proceedings of the 2018 19th International Symposium on Mobile Ad Hoc Networking and Computing
PB - Association for Computing Machinery
Y2 - 26 June 2018 through 29 June 2018
ER -