Understanding performance modeling for modular mobile-cloud applications

Giurgiu, Ioana

doi:10.1145/2188286.2188333

Cited by 4 publications

(2 citation statements)

References 10 publications

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“…Giurgiu [14] has presented an approach for estimating the performance of mobile‐cloud applications. The approach tried to identify the factors that impact interaction response times, such as the application distribution schemes, workload sizes and intensities, or the resource variations of the mobile‐cloud application setup.…”

Section: Related Workmentioning

confidence: 99%

Towards the optimization of a parallel streaming engine for telco applications

Theeten¹,

Bedini²,

Cogan³

et al. 2014

Bell Labs Tech. J.

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Parallel and distributed computing is becoming essential to process in real time the increasingly massive volume of data collected by telecommunications companies. Existing computational paradigms such as MapReduce (and its popular open-source implementation Hadoop) provide a scalable, fault tolerant mechanism for large scale batch computations. However, many applications in the telco ecosystem require a real time, incremental streaming approach to process data in real time and enable proactive care. Storm is a scalable, fault tolerant framework for the analysis of real time streaming data. In this paper we provide a motivation for the use of real time streaming analytics in the telco ecosystem. We perform an experimental investigation into the performance of Storm, focusing in particular on the impact of parameter configuration. This investigation reveals that optimal parameter choice is highly non-trivial and we use this as motivation to create a parameter configuration engine. As first steps towards the creation of this engine we provide a deep analysis of the inner workings of Storm and provide a set of models describing data flow cost, central processing unit (CPU) cost, and system management cost. ©2014 Alcatel-Lucent

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Section: Related Workmentioning

confidence: 99%

Towards the optimization of a parallel streaming engine for telco applications

Theeten¹,

Bedini²,

Cogan³

et al. 2014

Bell Labs Tech. J.

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“…Giurgiu [14] has presented an approach for estimation of performance for mobile-cloud applications. The approach tried to identify the factors which impact interaction response times, such as the application distribution schemes, workload sizes and intensities, or the resource variations of the mobile-cloud application setup.…”

Section: Related Workmentioning

confidence: 99%

Modeling performance of a parallel streaming engine

Bedini¹,

Sakr²,

Theeten³

et al. 2013

Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering

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While data are growing at a speed never seen before, parallel computing is becoming more and more essential to process this massive volume of data in a timely manner. Therefore, recently, concurrent computations have been receiving increasing attention due to the widespread adoption of multi-core processors and the emerging advancements of cloud computing technology. The ubiquity of mobile devices, location services, and sensor pervasiveness are examples of new scenarios that have created the crucial need for building scalable computing platforms and parallel architectures to process vast amounts of generated streaming data. In practice, efficiently operating these systems is hard due to the intrinsic complexity of these architectures and the lack of a formal and in-depth knowledge of the performance models and the consequent system costs. The Actor Model theory has been presented as a mathematical model of concurrent computation that had enormous success in practice and inspired a number of contemporary work in this area. Recently, the Storm system has been presented as a realization of the principles of the Actor Model theory in the context of the large scale processing of streaming data. In this paper, we present, to the best of our knowledge, the first set of models that formalize the performance characteristics of a practical distributed, parallel and fault-tolerant stream processing system that follows the Actor Model theory. In particular, we model the characteristics of the data flow, the data processing and the system management costs at a fine granularity within the different steps of executing a distributed stream processing job. Finally, we present an experimental validation of the described performance models using the Storm system.

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Architectural Designs from Mobile Cloud Computing to Ubiquitous Cloud Computing - Survey

Lomotey

Deters

2014

2014 IEEE World Congress on Services

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Understanding performance modeling for modular mobile-cloud applications

Cited by 4 publications

References 10 publications

Towards the optimization of a parallel streaming engine for telco applications

Towards the optimization of a parallel streaming engine for telco applications

Modeling performance of a parallel streaming engine

Architectural Designs from Mobile Cloud Computing to Ubiquitous Cloud Computing - Survey

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