TY - JOUR
T1 - Toward Rendering-Latency Reduction for Composable Web Services via Priority-Based Object Caching
AU - Hu, Han
AU - Li, Yuanlong
AU - Wen, Yonggang
N1 - Publisher Copyright:
© 1999-2012 IEEE.
PY - 2018/7
Y1 - 2018/7
N2 - Web services serve as the cornerstone of the Internet for rendering webpages. The initial rendering latency of webpages, which depends on a subset of critical objects required by the webpage, is a key metric for web services. In this work, we propose to identify this set of critical objects systematically with the goal of caching them at a higher priority to reduce the initial rendering time. We first conduct a measurement study on a mainstream content delivery network provider, the results of which suggest that not all currently cached objects are critical and that only a small portion of the critical objects are cached. Thus, we model the critical-object aware caching scheme as a constrained optimization problem. Using the stochastic optimization framework, we decompose the problem into a set of one-shot optimization problems, which are proved to be NP-hard. We then develop two greedy algorithms with different computational complexity but the same performance bound. Finally, we integrate the resulting approximation algorithms into an online algorithm. Through trace-based simulations, we verify that our proposed algorithm can reduce service latency and network traffic by ensuring a higher cache hit ratio.
AB - Web services serve as the cornerstone of the Internet for rendering webpages. The initial rendering latency of webpages, which depends on a subset of critical objects required by the webpage, is a key metric for web services. In this work, we propose to identify this set of critical objects systematically with the goal of caching them at a higher priority to reduce the initial rendering time. We first conduct a measurement study on a mainstream content delivery network provider, the results of which suggest that not all currently cached objects are critical and that only a small portion of the critical objects are cached. Thus, we model the critical-object aware caching scheme as a constrained optimization problem. Using the stochastic optimization framework, we decompose the problem into a set of one-shot optimization problems, which are proved to be NP-hard. We then develop two greedy algorithms with different computational complexity but the same performance bound. Finally, we integrate the resulting approximation algorithms into an online algorithm. Through trace-based simulations, we verify that our proposed algorithm can reduce service latency and network traffic by ensuring a higher cache hit ratio.
KW - Webpage caching
KW - submodular function maximization
UR - http://www.scopus.com/inward/record.url?scp=85036582204&partnerID=8YFLogxK
U2 - 10.1109/TMM.2017.2779041
DO - 10.1109/TMM.2017.2779041
M3 - Article
AN - SCOPUS:85036582204
SN - 1520-9210
VL - 20
SP - 1864
EP - 1875
JO - IEEE Transactions on Multimedia
JF - IEEE Transactions on Multimedia
IS - 7
ER -