Adapting Distributed Real-Time and Embedded Pub/Sub Middleware for Cloud Computing Environments

Hoffert, Joe; Schmidt, Douglas C.; Gokhale, Aniruddha

doi:10.1007/978-3-642-16955-7_2

Cited by 20 publications

(16 citation statements)

References 17 publications

(24 reference statements)

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“…Some exclusive frameworks for cloud platforms have also been proposed recently such as Twister [22], framework by Bonakdarpour et al [23], and Publish/Subscribe (Pub/Sub) middlewares [24], [25], but every such framework has a particular set of complexities that discourage users from using these frameworks. To our knowledge, there is no similar system over Azure.…”

Section: Background and Literaturementioning

confidence: 99%

Towards an MPI-Like Framework for the Azure Cloud Platform

Agarwal

Karamati

Puri

et al. 2014

2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing

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Message Passing Interface (MPI) has been the predominant standardized system for writing parallel and distributed applications. However, while MPI has been the software system of choice for traditional parallel and distributed computing platforms such as large compute clusters and Grid, MPI is not the system of choice for cloud platforms. The primary reasons for this is the lack of low latency high bandwidth network capabilities of the cloud platforms and the inherent architectural differences from traditional compute clusters. Prior studies suggest that the message latency of cloud platforms could be as much as 35x slower than that of an infiniband-connected cluster [1] for popular MPI implementations. MPI-like environment on cloud platforms is desirable for a large class of applications that run for long time spans with varying computing needs, such as the modeling and analysis to predict swath of a hurricane. Such applications could benefit from cloud's resiliency and on-demand access for a robust and green solution. Interestingly, most of the cloud vendors provide APIs to access cloud resources in an efficient manner different than how an MPI implementation would avail of those resources. We have done extensive research to identify the pain-points for designing and implementing an MPIlike framework for cloud platforms. Our research has provided us with vital guidelines that we are sharing in this paper. We present the details of the key components required for such a framework along with our experience while implementing a preliminary MPI-like framework over Azure dubbed cloudMPI and evaluate its pros and cons. A large GIS application has been ported over cloudMPI to study its effectiveness and limitations. 1

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Section: Background and Literaturementioning

confidence: 99%

Towards an MPI-Like Framework for the Azure Cloud Platform

Agarwal

Karamati

Puri

et al. 2014

2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing

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“…(i) Like typical publish-subscribe system, a cloud-based publish-subscribe system [33] needs to state how the subscriber expresses their interest (e.g., topicbased, content-based, type-based, and parametrized) and how matching is performed by the notification system. (ii) It is important to determine how information is disseminated or propagated from publishers to subscribers.…”

Section: Notification and Sharingmentioning

confidence: 99%

Framework for a Cloud-Based Multimedia Surveillance System

Hossain

2014

International Journal of Distributed Sensor Networks

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The new generation of multimedia surveillance systems integrates a large number of heterogeneous sensors to collect, process, and analyze multimedia data for identifying events of potential security threats. Some of the major concerns facing these systems are scalability, ubiquitous access to sensory data, event processing overhead, and massive storage requirements-all of which demand novel scalable approach. Cloud computing can provide a powerful and scalable infrastructure for large-scale storage, processing, and dissemination of sensor data. Furthermore, the integration of sensor technology and cloud computing offers new possibilities for efficient development and deployment of sensor-based systems. This paper proposes a framework for a cloud-based multimedia surveillance system and highlights several research and technical issues. A prototype surveillance system is also designed and analyzed in the context of the proposed surveillance framework. The paper finally reports that cloud-based multimedia surveillance system can effectively support the processing overload, storage requirements, ubiquitous access, security, and privacy in large-scale surveillance settings.

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“…The ADAMANT project [19] is a pub/sub middleware that uses supervised machine learning to autonomously configure available resources among distributed clouds. It aims at designing a cloud middleware for supporting on-demand requests of cloud resources as a part of a disaster management system.…”

Section: Related Workmentioning

confidence: 99%

Time-critical event dissemination in geographically distributed clouds

Chen

2011

2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

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Abstract-Cloud computing has rapidly become a new infrastructure for organizations to reduce their capital cost in IT investment and to develop planetary-scale distributed applications. One of the fundamental challenges in geographically distributed clouds is to provide efficient algorithms for supporting intercloud data management and dissemination. In this paper, we present Plume, a generic distributed intercloud overlay for time-critical event dissemination services. Plume aims at improving the interoperability of interclouds in time-critical event dissemination services, such as computing policy updating, message sharing, event notifications and so forth. Plume organizes these distributed clouds into a novel quorum ring overlay to support a constant event dissemination latency. Our numerical results show that the proposed Plume greatly improves the efficiency as compared to a DHT-based overlay approach and provides better scalability than the fully-meshed approach.

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Adapting Distributed Real-Time and Embedded Pub/Sub Middleware for Cloud Computing Environments

Cited by 20 publications

References 17 publications

Towards an MPI-Like Framework for the Azure Cloud Platform

Towards an MPI-Like Framework for the Azure Cloud Platform

Framework for a Cloud-Based Multimedia Surveillance System

Time-critical event dissemination in geographically distributed clouds

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