research-article

Cloud-TM: harnessing the cloud with distributed transactional memories

Authors:

Luis Rodrigues,

Joäo CachopoAuthors Info & Claims

ACM SIGOPS Operating Systems Review, Volume 44, Issue 2

Pages 1 - 6

https://doi.org/10.1145/1773912.1773914

Published: 14 April 2010 Publication History

Abstract

One of the main challenges to harness the potential of Cloud computing is the design of programming models that simplify the development of large-scale parallel applications and that allow ordinary programmers to take full advantage of the computing power and the storage provided by the Cloud, both of which made available, on demand, in a pay-only-forwhat-you-use pricing model.

In this paper, we discuss the use of the Transactional Memory programming model in the context of the cloud computing paradigm, which we refer to as Cloud-TM. We identify where existing Distributed Transactional Memory platforms still fail to meet the requirements of the cloud and of its users, and we point several open research problems whose solution we deem as essential to materialize the Cloud-TM vision.

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Cited By

Zhang GLiu LGuo H(2021)Investigating the Impact of Cloud Computing Vendor on the Adoption of Cloud ComputingMobile Information Systems10.1155/2021/65579372021Online publication date: 26-Dec-2021
https://dl.acm.org/doi/10.1155/2021/6557937
Principe MTocci TSanzo PQuaglia FPellegrini A(2020)A Distributed Shared Memory Middleware for Speculative Parallel Discrete Event SimulationACM Transactions on Modeling and Computer Simulation10.1145/337333530:2(1-26)Online publication date: 20-Mar-2020
https://dl.acm.org/doi/10.1145/3373335
Busch CHerlihy MPopovic MSharma G(2018)Time-communication impossibility results for distributed transactional memoryDistributed Computing10.1007/s00446-017-0318-y31:6(471-487)Online publication date: 1-Nov-2018
https://dl.acm.org/doi/10.1007/s00446-017-0318-y
Show More Cited By

Index Terms

Cloud-TM: harnessing the cloud with distributed transactional memories
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
2. Software and its engineering
  1. Software organization and properties
    1. Contextual software domains
      1. Operating systems
        Memory management
        Distributed memory
    2. Software system structures
      1. Distributed systems organizing principles

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Information & Contributors

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Published In

cover image ACM SIGOPS Operating Systems Review

ACM SIGOPS Operating Systems Review Volume 44, Issue 2

April 2010

92 pages

ISSN:0163-5980

DOI:10.1145/1773912

Issue’s Table of Contents

Copyright © 2010 Authors.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 April 2010

Published in SIGOPS Volume 44, Issue 2

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Cited By

Zhang GLiu LGuo H(2021)Investigating the Impact of Cloud Computing Vendor on the Adoption of Cloud ComputingMobile Information Systems10.1155/2021/65579372021Online publication date: 26-Dec-2021
https://dl.acm.org/doi/10.1155/2021/6557937
Principe MTocci TSanzo PQuaglia FPellegrini A(2020)A Distributed Shared Memory Middleware for Speculative Parallel Discrete Event SimulationACM Transactions on Modeling and Computer Simulation10.1145/337333530:2(1-26)Online publication date: 20-Mar-2020
https://dl.acm.org/doi/10.1145/3373335
Busch CHerlihy MPopovic MSharma G(2018)Time-communication impossibility results for distributed transactional memoryDistributed Computing10.1007/s00446-017-0318-y31:6(471-487)Online publication date: 1-Nov-2018
https://dl.acm.org/doi/10.1007/s00446-017-0318-y
Gramoli VGuerraoui RTrigonakis V(2018)$$\hbox {TM}^{2}$$TM2CDistributed Computing10.1007/s00446-017-0310-631:5(367-388)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1007/s00446-017-0310-6
Popovic MKordic BBasicevic I(2017)Transaction scheduling for Software Transactional Memory2017 IEEE 2nd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)10.1109/ICCCBDA.2017.7951909(191-195)Online publication date: Apr-2017
https://doi.org/10.1109/ICCCBDA.2017.7951909
(2017)Partial Rollback-based Scheduling on In-memory Transactional Data GridsBig Data Research10.1016/j.bdr.2017.06.0049:C(47-56)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1016/j.bdr.2017.06.004
Leite AAlves VRodrigues GTadonki CEisenbeis CMelo A(2017)DohkoCluster Computing10.1007/s10586-017-0897-120:3(1951-1976)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1007/s10586-017-0897-1
Sang BPetri GArdekani MRavi SEugster P(2016)Programming Scalable Cloud Services with AEONProceedings of the 17th International Middleware Conference10.1145/2988336.2988352(1-14)Online publication date: 28-Nov-2016
https://dl.acm.org/doi/10.1145/2988336.2988352
Leite AAlves VRodrigues GTadonki CEisenbeis CMelo A(2016)Autonomic Provisioning, Configuration, and Management of Inter-cloud Environments Based on a Software Product Line Engineering Method2016 International Conference on Cloud and Autonomic Computing (ICCAC)10.1109/ICCAC.2016.13(72-83)Online publication date: Sep-2016
https://doi.org/10.1109/ICCAC.2016.13
Busch CHerlihy MPopovic MSharma GGeorgiou CSpirakis P(2015)Impossibility Results for Distributed Transactional MemoryProceedings of the 2015 ACM Symposium on Principles of Distributed Computing10.1145/2767386.2767433(207-215)Online publication date: 21-Jul-2015
https://dl.acm.org/doi/10.1145/2767386.2767433
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