TY - GEN
T1 - Average-Case Competitive Ratio of Scheduling Algorithms of Multi-user Cache
AU - Berend, Daniel
AU - Dolev, Shlomi
AU - Hassidim, Avinatan
AU - Kogan-Sadetsky, Marina
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - The goal of this paper is to present an efficient realistic metric for evaluating cache scheduling algorithms in multi-user multi-cache environments. In a previous work, the requests sequence was set deliberately by an opponent (offline optimal) algorithm in an extremely unrealistic way, leading to an unlimited competitive ratio and to extremely unreasonable and unrealistic cache management strategies. In this paper, we propose to analyze the performance of cache management in a typical scenario, i.e., we consider all possibilities with their (realistic) distribution. In other words, we analyze the average case and not the worst case of scheduling scenarios. In addition, we present an efficient, according to our novel average case analysis, online heuristic algorithm for cache scheduling. The algorithm is based on machine-learning concepts, it is flexible and easy to implement.
AB - The goal of this paper is to present an efficient realistic metric for evaluating cache scheduling algorithms in multi-user multi-cache environments. In a previous work, the requests sequence was set deliberately by an opponent (offline optimal) algorithm in an extremely unrealistic way, leading to an unlimited competitive ratio and to extremely unreasonable and unrealistic cache management strategies. In this paper, we propose to analyze the performance of cache management in a typical scenario, i.e., we consider all possibilities with their (realistic) distribution. In other words, we analyze the average case and not the worst case of scheduling scenarios. In addition, we present an efficient, according to our novel average case analysis, online heuristic algorithm for cache scheduling. The algorithm is based on machine-learning concepts, it is flexible and easy to implement.
KW - Competitive ratio
KW - Concurrent cache
KW - Scheduling algorithm
UR - http://www.scopus.com/inward/record.url?scp=85087793204&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-49785-9_15
DO - 10.1007/978-3-030-49785-9_15
M3 - Conference contribution
AN - SCOPUS:85087793204
SN - 9783030497842
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 237
EP - 244
BT - Cyber Security Cryptography and Machine Learning - 4th International Symposium, CSCML 2020, Proceedings
A2 - Dolev, Shlomi
A2 - Weiss, Gera
A2 - Kolesnikov, Vladimir
A2 - Lodha, Sachin
PB - Springer
T2 - 4th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2020
Y2 - 2 July 2020 through 3 July 2020
ER -