research-article

Pocket cloudlets

Authors:

Emmanouil Koukoumidis,

Dimitrios Lymberopoulos,

Doug BurgerAuthors Info & Claims

ASPLOS XVI: Proceedings of the sixteenth international conference on Architectural support for programming languages and operating systems

Pages 171 - 184

https://doi.org/10.1145/1950365.1950387

Published: 05 March 2011 Publication History

Abstract

Cloud services accessed through mobile devices suffer from high network access latencies and are constrained by energy budgets dictated by the devices' batteries. Radio and battery technologies will improve over time, but are still expected to be the bottlenecks in future systems. Non-volatile memories (NVM), however, may continue experiencing significant and steady improvements in density for at least ten more years. In this paper, we propose to leverage the abundance in memory capacity of mobile devices to mitigate latency and energy issues when accessing cloud services.

We first analyze NVM technology scaling trends, and then propose a cloud service cache architecture that resides on the mobile device's NVM (pocket cloudlet). This architecture utilizes both individual user and community access models to maximize its hit rate, and subsequently reduce overall service latency and energy consumption.

As a showcase we present the design, implementation and evaluation of PocketSearch, a search and advertisement pocket cloudlet. We perform mobile search characterization to guide the design of PocketSearch and evaluate it with 200 million mobile queries from the search logs of m.bing.com. We show that PocketSearch can serve, on average, 66% of the web search queries submitted by an individual user without having to use the slow 3G link, leading to 16x service access speedup. Finally, based on experience with PocketSearch we provide additional insight and guidelines on how future pocket cloudlets should be organized, from both an architectural and an operating system perspective.

References

[1]

E. Benson, A. Marcus, D. Karger, and S. Madden. Sync kit: a persistent client-side database caching toolkit for data intensive websites. In Proceedings of the 19th international conference on World wide web, WWW '10, pages 121--130, New York, NY, USA, 2010. ACM.

Digital Library

[2]

P. J. Braam. The coda distributed file system. Linux J., 1998, June 1998.

Digital Library

[3]

K. Church, B. Smyth, K. Bradley, and P. Cotter. A large scale study of european mobile search behaviour. In MobileHCI, 2008.

Digital Library

[4]

K. Church, B. Smyth, P. Cotter, and K. Bradley. Mobile information access: A study of emerging search behavior on the mobile internet. ACM Trans. Web, 1(1):4, 2007.

Digital Library

[5]

S. R. et al. Phase-change random access memory: A scalable technology. IBM Journal of Reseach and Development, 52(4/5), Jul/Sep 2008.

Digital Library

[6]

D. K. et all. A stackable cross point phase change memory. In 2009 International Electron Device Meeting, Dec 2009.

[7]

T. Fagni, R. Perego, F. Silvestri, S. Orlando, U. Ca, and F. Venezia. Boosting the performance of web search engines: Caching and prefetching query results by exploiting historical usage data. ACM Trans. Inf. Syst, 24, 2006.

Digital Library

[8]

H. Falaki, R. Mahajan, S. Kandula, D. Lymberopoulos, G. Ramesh, and D. Estrin. Diversity in smartphone usage. In MobiSys, 2010.

Digital Library

[9]

I. T. R. for Semiconductors Working Group. International technology roadmap for semiconductors 2009 report. Technical report, International Technology Roadmap for Semiconductors, 2009.

[10]

M. J. Franklin, M. J. Carey, and M. Livny. Local disk caching for client-server database systems. In Proceedings of the 19th International Conference on Very Large Data Bases, VLDB '93, pages 641--655, San Francisco, CA, USA, 1993. Morgan Kaufmann Publishers Inc.

Digital Library

[11]

S. Guha, A. Reznichenko, K. Tang, H. Haddadi, and P. Francis. Serving ads from localhost for performance, privacy, and profit. In Hotnets, 2009.

[12]

Y. Huai. Spin-transfer torque mram (stt-mram): challenges and prospects. AAPPS Bulletin, 18(6):33--40, Dec 2008.

[13]

S. Isaacman and M. Martonosi. The c-link system for collaborative web usage: A real-world deployment in rural nicaragua. In NSDR '09, pages location =, doi =, publisher = address =, 2009.

[14]

R. C. Johnson. Memristors ready for prime time. http://www.eetimes.com/electronics-news/4077811/Memristors-ready-for-prime-time, Jul 2008.

[15]

M. Kamvar and S. Baluja. A large scale study of wireless search behavior: Google mobile search. In CHI, 2006.

Digital Library

[16]

M. Kamvar and S. Baluja. Deciphering trends in mobile search. Computer, 40(8):58--62, 2007.

Digital Library

[17]

M. Kamvar and S. Baluja. The role of context in query input: using contextual signals to complete queries on mobile devices. In MobileHCI, 2007.

Digital Library

[18]

M. Kamvar and S. Baluja. Query suggestions for mobile search: understanding usage patterns. In CHI, 2008.

Digital Library

[19]

M. Kamvar, M. Kellar, R. Patel, and Y. Xu. Computers and iphones and mobile phones, oh my! In WWW, April 2009.

Digital Library

[20]

E. Markatos. On caching search engine query results. In Computer Communications, 2000.

[21]

E. P. Markatos and C. E. Chronaki. A top-10 approach to prefetching on the web. In Proceedings of INET, 1998.

[22]

Mobile Search Trends Report, http://www.marketingcharts.com/interactive/mobile-local-search-ad-reven%ues-to-reach-13b-by-2013-8092/.

[23]

A. Nanopoulos, D. Katsaros, and Y. Manolopoulos. A data mining algorithm for generalized web prefetching. IEEE Trans. on Knoweledge and Data Engineering, 2003.

Digital Library

[24]

V. N. Padmanabhan and J. C. Mogul. Using predictive prefetching to improve world wide web latency. SIGCOMM Comput. Commun. Rev., 26(3):22--36, 1996.

Digital Library

[25]

J. Pitkow and P. Pirolli. Mining longest repeating subsequences to predict world wide web surfing. In USENIX, pages 139--150, 1999.

Digital Library

[26]

C. Silverstein, H. Marais, M. Henzinger, and M. Moricz. Analysis of a very large web search engine query log. SIGIR Forum, 33(1), 1999.

Digital Library

[27]

Sony Ericsson Xperia X1a Mobile Phone, http://www.sonyericsson.com/x1/.

[28]

J. Teevan, E. Adar, R. Jones, and M. A. S. Potts. Information re-retrieval: repeat queries in yahoo's logs. In SIGIR, 2007.

Digital Library

[29]

J. Teevan, S. T. Dumais, and E. Horvitz. Personalizing search via automated analysis of interests and activities. In SIGIR, 2005.

Digital Library

[30]

Y. Xie and D. O'Hallaron. Locality in search engine queries and its implications for caching. In Infocom, 2002.

[31]

J. Yi, F. Maghoul, and J. Pedersen. Deciphering mobile search patterns: a study of yahoo! mobile search queries. In WWW, 2008.

Digital Library

Cited By

Denby BLucia BLarus JCeze LStrauss K(2020)Orbital Edge ComputingProceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems10.1145/3373376.3378473(939-954)Online publication date: 9-Mar-2020
https://dl.acm.org/doi/10.1145/3373376.3378473
Xiao XHou XWang CLi YHui PChen S(2019)Jamcloud: Turning Traffic Jams Into Computation Opportunities–Whose Time Has ComeIEEE Access10.1109/ACCESS.2019.29273437(115797-115815)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2927343
Raza AUl Haq IShaukat U(2018)Cloudlet-based Augmentation of Mobile Devices2018 14th International Conference on Emerging Technologies (ICET)10.1109/ICET.2018.8603627(1-6)Online publication date: Nov-2018
https://doi.org/10.1109/ICET.2018.8603627
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Index Terms

Pocket cloudlets
1. Information systems

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cover image ACM Conferences

ASPLOS XVI: Proceedings of the sixteenth international conference on Architectural support for programming languages and operating systems

March 2011

432 pages

ISBN:9781450302661

DOI:10.1145/1950365

General Chair:
Rajiv Gupta
University of California, Riverside
,
Program Chair:
Todd C. Mowry
Carnegie Mellon University

ACM SIGPLAN Notices Volume 46, Issue 3
ASPLOS '11
March 2011
407 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/1961296
Issue’s Table of Contents
ACM SIGARCH Computer Architecture News Volume 39, Issue 1
ASPLOS '11
March 2011
407 pages
ISSN:0163-5964
DOI:10.1145/1961295
Issue’s Table of Contents

Copyright © 2011 ACM.

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Published: 05 March 2011

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ASPLOS'11: Sixteenth International Conference on Architectural Support for Programming Languages and Operating Systems

March 5 - 11, 2011

California, Newport Beach, USA

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Cited By

Denby BLucia BLarus JCeze LStrauss K(2020)Orbital Edge ComputingProceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems10.1145/3373376.3378473(939-954)Online publication date: 9-Mar-2020
https://dl.acm.org/doi/10.1145/3373376.3378473
Xiao XHou XWang CLi YHui PChen S(2019)Jamcloud: Turning Traffic Jams Into Computation Opportunities–Whose Time Has ComeIEEE Access10.1109/ACCESS.2019.29273437(115797-115815)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2927343
Raza AUl Haq IShaukat U(2018)Cloudlet-based Augmentation of Mobile Devices2018 14th International Conference on Emerging Technologies (ICET)10.1109/ICET.2018.8603627(1-6)Online publication date: Nov-2018
https://doi.org/10.1109/ICET.2018.8603627
Liu XMa YLin F(2018)Rethinking Resource Management in Mobile Web: Measurement, Deployment, and Runtime2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS.2018.00135(1347-1356)Online publication date: Jul-2018
https://doi.org/10.1109/ICDCS.2018.00135
Taherkordi AZahid FVerginadis YHorn G(2018)Future Cloud Systems Design: Challenges and Research DirectionsIEEE Access10.1109/ACCESS.2018.28831496(74120-74150)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2018.2883149
Zulkafli ABasri SAhmad RImam A(2018)Image synchronization gateway for NoSQL document database and server-side SQL database in mobile environment10.1063/1.5055559(020157)Online publication date: 2018
https://doi.org/10.1063/1.5055559
Shahzadi SIqbal MDagiuklas TQayyum Z(2017)Multi-access edge computingJournal of Cloud Computing: Advances, Systems and Applications10.1186/s13677-017-0097-96:1(1-13)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1186/s13677-017-0097-9
Dutta KVandermeer D(2017)Caching to Reduce Mobile App Energy ConsumptionACM Transactions on the Web10.1145/312577812:1(1-30)Online publication date: 9-Sep-2017
https://dl.acm.org/doi/10.1145/3125778
Liu XMa YWang XLiu YXie THuang G(2017)SWAROVsky: Optimizing Resource Loading for Mobile Web BrowsingIEEE Transactions on Mobile Computing10.1109/TMC.2016.264556316:10(2941-2954)Online publication date: 1-Oct-2017
https://doi.org/10.1109/TMC.2016.2645563
Burago ILevorato MChowdhery A(2017)Bandwidth-Aware Data Filtering in Edge-Assisted Wireless Sensor Systems2017 14th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)10.1109/SAHCN.2017.7964938(1-9)Online publication date: Jun-2017
https://doi.org/10.1109/SAHCN.2017.7964938
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