An adaptive context-aware optimization framework for multimedia adaptation service selection

Laboudi, Zakaria; Moudjari, Abdelkader; Saighi, Asma; Draa, Amer; Hadjadj, Selma

doi:10.1007/s00521-021-06644-w

Cited by 6 publications

(2 citation statements)

References 25 publications

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“…Vehicle routing problem with time window [292] cSCA Public transit vehicles dispatch [294] McSCA Node localisation in 3D actual terrain [293] pcCSA Optimal bibliographic ontology matching [211] UcGA Optimal thrust allocation (in cybership III) [289] cHHO (v) Adaptation and learning: Lightweight algorithms with increased intelligence will be needed, that is, algorithms that can self-adapt their parameters to the problem at hand. Another possibility would be to put multiple lightweight algorithms together, using, for instance, a scheme similar to that introduced in [327]: in this scheme, 6 algorithms are arranged into three bags, each with two algorithms, depending on the number of solutions used in the optimisers. Once a bag is selected, its optimisers are run according to a reinforcement learning process based on its performance.…”

Section: Future Research Directionsmentioning

confidence: 99%

Metaheuristics in the Balance: A Survey on Memory-Saving Approaches for Platforms with Seriously Limited Resources

Khalfi,

Caraffini,

Iacca

2023

International Journal of Intelligent Systems

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In the last three decades, the field of computational intelligence has seen a profusion of population-based metaheuristics applied to a variety of problems, where they achieved state-of-the-art results. This remarkable growth has been fuelled and, to some extent, exacerbated by various sources of inspiration and working philosophies, which have been thoroughly reviewed in several recent survey papers. However, the present survey addresses an important gap in the literature. Here, we reflect on a systematic categorisation of what we call “lightweight” metaheuristics, i.e., optimisation algorithms characterised by purposely limited memory and computational requirements. We focus mainly on two classes of lightweight algorithms: single-solution metaheuristics and “compact” optimisation algorithms. Our analysis is mostly focused on single-objective continuous optimisation. We provide an updated and unified view of the most important achievements in the field of lightweight metaheuristics, background concepts, and most important applications. We then discuss the implications of these algorithms and the main open questions and suggest future research directions.

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Section: Future Research Directionsmentioning

confidence: 99%

Metaheuristics in the Balance: A Survey on Memory-Saving Approaches for Platforms with Seriously Limited Resources

Khalfi,

Caraffini,

Iacca

2023

International Journal of Intelligent Systems

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“…Table 1 gives some typical context values, conflicts, and adaptation actions related to the MDA process used. [23]. The adoption of a particular category depends on many factors such as devices computing features, the communication bandwidth, and the available resources.…”

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confidence: 99%

On the use of historical data in context-aware multimedia documents adaptation processes

Smaala,

Laboudi,

Saighi

et al. 2024

Bulletin EEI

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Playing multimedia documents in ubiquitous systems may require content adaptation based on gathered context information and accumulated historical data. Several approaches have already been proposed, in which adaptation actions are performed to provide adapted documents. Nevertheless, these approaches focus mainly on efficient use of context information without involving historical users data to improve the adaptation process. Thus, this paper allows for consideration of historical users data during the execution of the adaptation process. To do so, the context elements and the adaptation actions are first modeled using the oriented-object approach and then converted into relational and NoSQL databases schemes. Finally, algorithms for storing, retrieving and analysing data are designed. The proposal is validated by implementing scenarios through a real prototype. At a first step, the performances are measured to estimate the cost of data processing. The experiments show that NoSQL databases excel in data storage and ease of implementation, while relational databases perform well in data retrieve. At a second step, the proposal usefulness is highlighted by showing how historical data contribute to adaptation rules personalization using datadriven rule learning mechanisms rather than defining them explicitly. The analysis algorithm could retain personalized adaptation rules with confidence degree greater than 90%. Overall, the results are satisfactory.

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Multimedia Adaptation in Ubiquitous Systems: Literature Review, Critical Analysis and Future Trends

Ayadi

Saighi

Laboudi

2023

Lecture Notes in Networks and Systems

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An adaptive context-aware optimization framework for multimedia adaptation service selection

Cited by 6 publications

References 25 publications

Metaheuristics in the Balance: A Survey on Memory-Saving Approaches for Platforms with Seriously Limited Resources

Metaheuristics in the Balance: A Survey on Memory-Saving Approaches for Platforms with Seriously Limited Resources

On the use of historical data in context-aware multimedia documents adaptation processes

Multimedia Adaptation in Ubiquitous Systems: Literature Review, Critical Analysis and Future Trends

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