Evaluation of dynamic adaptivity through metrics: an achievable target?

Raibulet, Claudia; Masciadri, Laura

doi:10.1109/wicsa.2009.5290667

Cited by 27 publications

(15 citation statements)

References 10 publications

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“…Specifically, the tests focus on a set of metrics that are meaningful for the analysis of the performance of the system and for the effects on the service discovery process when agents incorporate self-organization mechanisms [21] [35]. These metrics are:…”

Section: Resultsmentioning

confidence: 99%

Combination of self-organization mechanisms to enhance service discovery in open systems

Val

Rebollo

Botti

2014

Information Sciences

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Decentralized systems have emerged as an alternative to centralized approaches for dealing with dynamic requirements in new business models. These systems should provide mechanisms that contribute to flexibility and facilitate adaptation to changes in the environment. In this paper, we present two self-organization mechanisms for a decentralized service discovery system in order to improve its performance. These mechanisms are based on local actions of agents that only consider local information about queries they forward during the discovery process. The self-organization actions are chosen by each agent individually when the agent considers them to be appropriate. The actions are: remaining in the system, leaving the system, cloning, and changing structural relations with other agents. We have evaluated each self-organization mechanism separately but also the combination of the two as the environmental conditions in the service demand change. The results show that the proposed self-organization mechanisms considerably improve the performance of the service discovery system.

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Section: Resultsmentioning

confidence: 99%

Combination of self-organization mechanisms to enhance service discovery in open systems

Val

Rebollo

Botti

2014

Information Sciences

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“…Numerous measures for the evaluation of adaptivity in adaptive systems have been proposed [9] which aim to measure the scientific performance of components and perform user-based evaluation of the adaptivity offered by the system. The approaches can be broadly divided into three categories: (i) Adaptivity Metrics; (ii) User-Interaction Metrics; and (iii) Performance Metrics.…”

Section: Multilingual Results Re-ranking Based On Query-document Featuresmentioning

confidence: 99%

Multilingual Adaptive Search for Digital Libraries

Ghorab

Leveling

Lawless

et al. 2011

Research and Advanced Technology for Digital Libraries

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Abstract. This paper describes a framework for Adaptive Multilingual Information Retrieval (AMIR) which allows multilingual resource discovery and delivery using on-the-fly machine translation of documents and queries. Result documents are presented to the user in a contextualised manner. Challenges and affordances of both Adaptive and Multilingual IR, with a particular focus on Digital Libraries, are detailed. The framework components are motivated by a series of results from experiments on query logs and documents from The European Library. We conclude that factoring adaptivity and multilinguality aspects into the search process can enhance the user's experience with online Digital Libraries.

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“…Claudia Raibulet and Laura Masciadri proposed a set of architectural metrics to evaluate the adaptivity of a software system. 17 Although these metrics are not specific for energy-driven self-adaptation, they can be adopted as a reference for developers who want to introduce self-adaptive mechanisms into their applications. For example, their MaAC (Minimum architectural Adaptive Cost) metric expresses the fixed cost of adaptivity at the architecture level.…”

Section: Self-adaptation: Green Software By Designmentioning

confidence: 99%

Understanding Green Software Development: A Conceptual Framework

et al. 2015

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Developers who aim to write energy-efficient software require both a new mindset and models and tools that can measure and reduce the software effect on hardware energy consumption. The authors' conceptual framework provides a unifying view of strategies, models, and tools. IT energy consumption is an increasingly relevant concern. Traditionally, only hardware designers dealt with energy consumption. However, as hardware became more powerful, the influence of software behavior on energy consumption grew significantly.During the last few years, we have explored several facets of IT energy consumption from a software engineering perspective. What was once purely anecdotal evidence about the pivotal role of software on energy consumption is now supported by sound empirical data we collected through a series of experiments on different hardware platforms: servers, desktop PCs, and mobile phones. We analyzed the power consumption of three servers performing different tasks, and we observed that power consumption can increase up to 40 percent depending on the usage scenario. 1 We analyzed desktop computers from different technological generations in distinct software usage scenarios and found out that, depending on the software applications used, power consumption can increase up to 20 percent. 2 Finally, we profiled the power consumption of mobile devices, comparing two generations of Android OS-based smartphones. Our results show how different execution profiles of the same application can significantly affect the power consumption of a mobile device. 3 Although the actual figures vary depending on the specific hardware platform, the impact of software on energy consumption is definitely relevant. This implies a change of mindset for the software engineering community. First,

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Evaluation of dynamic adaptivity through metrics: an achievable target?

Cited by 27 publications

References 10 publications

Combination of self-organization mechanisms to enhance service discovery in open systems

Combination of self-organization mechanisms to enhance service discovery in open systems

Multilingual Adaptive Search for Digital Libraries

Understanding Green Software Development: A Conceptual Framework

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