BIG Cache Abstraction for Cache Networks

Eman Ramadan; Arvind Narayanan; Zhi-Li Zhang; Runhui Li; Gong Zhang

doi:10.1109/ICDCS.2017.306

BIG Cache Abstraction for Cache Networks

Eman Ramadan, Arvind Narayanan, Zhi-Li Zhang, Runhui Li, Gong Zhang

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

9 Scopus citations

Abstract

In this paper, we advocate the notion of 'BIG' cache as an innovative abstraction for effectively utilizing the distributed storage and processing capacities of all servers in a cache network. The 'BIG' cache abstraction is proposed to partly address the problem of (cascade) thrashing in a hierarchical network of cache servers, where it has been known that cache resources at intermediate servers are poorly utilized, especially under classical cache replacement policies such as LRU. We lay out the advantages of 'BIG' cache abstraction and make a strong case both from a theoretical standpoint as well as through simulation analysis. We also develop the dCLIMB cache algorithm to minimize the overheads of moving objects across distributed cache boundaries and present a simple yet effective heuristic for addressing the cache allotment problem in the design of 'BIG' cache abstraction.

Original language	English (US)
Title of host publication	Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017
Editors	Kisung Lee, Ling Liu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	742-752
Number of pages	11
ISBN (Electronic)	9781538617915
DOIs	https://doi.org/10.1109/ICDCS.2017.306
State	Published - Jul 13 2017
Event	37th IEEE International Conference on Distributed Computing Systems, ICDCS 2017 - Atlanta, United States Duration: Jun 5 2017 → Jun 8 2017

Publication series

Name	Proceedings - International Conference on Distributed Computing Systems

Other

Other	37th IEEE International Conference on Distributed Computing Systems, ICDCS 2017
Country/Territory	United States
City	Atlanta
Period	6/5/17 → 6/8/17

Bibliographical note

Funding Information:
This research was supported in part by NSF grants CNS-1411636, CNS 1618339 and CNS 1617729 and a Huawei gift.

Keywords

BIG Cache
Cache Replacement Policies
Caching
Content Network Distribution
DCLIMB
Hierarchical Caching

Publisher link

10.1109/ICDCS.2017.306

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Ramadan, E., Narayanan, A., Zhang, Z-L., Li, R., & Zhang, G. (2017). BIG Cache Abstraction for Cache Networks. In K. Lee, & L. Liu (Eds.), Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017 (pp. 742-752). [7980017] (Proceedings - International Conference on Distributed Computing Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDCS.2017.306

BIG Cache Abstraction for Cache Networks. / Ramadan, Eman; Narayanan, Arvind; Zhang, Zhi-Li et al.
Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017. ed. / Kisung Lee; Ling Liu. Institute of Electrical and Electronics Engineers Inc., 2017. p. 742-752 7980017 (Proceedings - International Conference on Distributed Computing Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ramadan, E, Narayanan, A, Zhang, Z-L, Li, R & Zhang, G 2017, BIG Cache Abstraction for Cache Networks. in K Lee & L Liu (eds), Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017., 7980017, Proceedings - International Conference on Distributed Computing Systems, Institute of Electrical and Electronics Engineers Inc., pp. 742-752, 37th IEEE International Conference on Distributed Computing Systems, ICDCS 2017, Atlanta, United States, 6/5/17. https://doi.org/10.1109/ICDCS.2017.306

Ramadan E, Narayanan A, Zhang Z-L, Li R, Zhang G. BIG Cache Abstraction for Cache Networks. In Lee K, Liu L, editors, Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 742-752. 7980017. (Proceedings - International Conference on Distributed Computing Systems). doi: 10.1109/ICDCS.2017.306

Ramadan, Eman ; Narayanan, Arvind ; Zhang, Zhi-Li et al. / BIG Cache Abstraction for Cache Networks. Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017. editor / Kisung Lee ; Ling Liu. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 742-752 (Proceedings - International Conference on Distributed Computing Systems).

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abstract = "In this paper, we advocate the notion of 'BIG' cache as an innovative abstraction for effectively utilizing the distributed storage and processing capacities of all servers in a cache network. The 'BIG' cache abstraction is proposed to partly address the problem of (cascade) thrashing in a hierarchical network of cache servers, where it has been known that cache resources at intermediate servers are poorly utilized, especially under classical cache replacement policies such as LRU. We lay out the advantages of 'BIG' cache abstraction and make a strong case both from a theoretical standpoint as well as through simulation analysis. We also develop the dCLIMB cache algorithm to minimize the overheads of moving objects across distributed cache boundaries and present a simple yet effective heuristic for addressing the cache allotment problem in the design of 'BIG' cache abstraction.",

keywords = "BIG Cache, Cache Replacement Policies, Caching, Content Network Distribution, DCLIMB, Hierarchical Caching",

author = "Eman Ramadan and Arvind Narayanan and Zhi-Li Zhang and Runhui Li and Gong Zhang",

note = "Funding Information: This research was supported in part by NSF grants CNS-1411636, CNS 1618339 and CNS 1617729 and a Huawei gift.; 37th IEEE International Conference on Distributed Computing Systems, ICDCS 2017 ; Conference date: 05-06-2017 Through 08-06-2017",

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N2 - In this paper, we advocate the notion of 'BIG' cache as an innovative abstraction for effectively utilizing the distributed storage and processing capacities of all servers in a cache network. The 'BIG' cache abstraction is proposed to partly address the problem of (cascade) thrashing in a hierarchical network of cache servers, where it has been known that cache resources at intermediate servers are poorly utilized, especially under classical cache replacement policies such as LRU. We lay out the advantages of 'BIG' cache abstraction and make a strong case both from a theoretical standpoint as well as through simulation analysis. We also develop the dCLIMB cache algorithm to minimize the overheads of moving objects across distributed cache boundaries and present a simple yet effective heuristic for addressing the cache allotment problem in the design of 'BIG' cache abstraction.

AB - In this paper, we advocate the notion of 'BIG' cache as an innovative abstraction for effectively utilizing the distributed storage and processing capacities of all servers in a cache network. The 'BIG' cache abstraction is proposed to partly address the problem of (cascade) thrashing in a hierarchical network of cache servers, where it has been known that cache resources at intermediate servers are poorly utilized, especially under classical cache replacement policies such as LRU. We lay out the advantages of 'BIG' cache abstraction and make a strong case both from a theoretical standpoint as well as through simulation analysis. We also develop the dCLIMB cache algorithm to minimize the overheads of moving objects across distributed cache boundaries and present a simple yet effective heuristic for addressing the cache allotment problem in the design of 'BIG' cache abstraction.

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BIG Cache Abstraction for Cache Networks

Abstract

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Keywords

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