TY - GEN
T1 - Caching with time windows
AU - Gupta, Anupam
AU - Kumar, Amit
AU - Panigrahi, Debmalya
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/6/8
Y1 - 2020/6/8
N2 - We consider the (weighted) Paging with Time Windows problem, which is identical to the classical weighted paging problem but where each page request only needs to be served by a given deadline. This problem arises in many practical applications of online caching, such as the deadline I/O scheduler in the Linux kernel and video-on-demand streaming. From a theoretical perspective, this generalizes the caching problem to allow delayed service, a line of work that has recently gained traction in online algorithms (e.g., Emek et al. STOC '16, Azar et al. STOC '17, Azar and Touitou FOCS '19, etc.). Our main result is an O(log k log n)-competitive algorithm for the Paging with Time Windows problem on n pages with a cache of size k. This significantly improves on the previous best bound of O(k) (Azar et al. (STOC '17). We also consider the offline version of this problem, for which we give an O(1) approximation algorithm and prove APX-hardness. These are the first results for the offline problem; even NP-hardness was not known before our work. At the heart of our algorithms is a novel hitting-set LP relaxation of this problem that overcomes the Omega(k) integrality gap of the natural LP for the problem. To the best of our knowledge, this is the first example of an LP-based algorithm for an online algorithm with delays/deadlines.
AB - We consider the (weighted) Paging with Time Windows problem, which is identical to the classical weighted paging problem but where each page request only needs to be served by a given deadline. This problem arises in many practical applications of online caching, such as the deadline I/O scheduler in the Linux kernel and video-on-demand streaming. From a theoretical perspective, this generalizes the caching problem to allow delayed service, a line of work that has recently gained traction in online algorithms (e.g., Emek et al. STOC '16, Azar et al. STOC '17, Azar and Touitou FOCS '19, etc.). Our main result is an O(log k log n)-competitive algorithm for the Paging with Time Windows problem on n pages with a cache of size k. This significantly improves on the previous best bound of O(k) (Azar et al. (STOC '17). We also consider the offline version of this problem, for which we give an O(1) approximation algorithm and prove APX-hardness. These are the first results for the offline problem; even NP-hardness was not known before our work. At the heart of our algorithms is a novel hitting-set LP relaxation of this problem that overcomes the Omega(k) integrality gap of the natural LP for the problem. To the best of our knowledge, this is the first example of an LP-based algorithm for an online algorithm with delays/deadlines.
KW - Approximation algorithms
KW - Online caching
UR - http://www.scopus.com/inward/record.url?scp=85086758893&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85086758893&partnerID=8YFLogxK
U2 - 10.1145/3357713.3384277
DO - 10.1145/3357713.3384277
M3 - Conference contribution
AN - SCOPUS:85086758893
T3 - Proceedings of the Annual ACM Symposium on Theory of Computing
SP - 1125
EP - 1138
BT - STOC 2020 - Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing
A2 - Makarychev, Konstantin
A2 - Makarychev, Yury
A2 - Tulsiani, Madhur
A2 - Kamath, Gautam
A2 - Chuzhoy, Julia
PB - Association for Computing Machinery
T2 - 52nd Annual ACM SIGACT Symposium on Theory of Computing, STOC 2020
Y2 - 22 June 2020 through 26 June 2020
ER -