Currently, advanced technological hardware can offer mobile devices which fits in the hand with a capacity to consult documents at anytime and anywhere. Multiple user context constraints as well as mobile device capabilities may involve the adaptation of multimedia content. In this article, the authors propose a new graph-based method for adapting multimedia documents in complex situations. Each contextual situation could correspond to a physical handicap and therefore triggers an adaptation action using ontological reasoning. Consequently, when several contextual situations are identified, this leads to multiple disabilities and may give rise to inconsistency between triggered actions. Their method allows modeling relations between adaptation-actions to select the compatible triggerable ones. In order to evaluate the feasibility and the performance of their proposal, an experimental study has been made on some real scenarios. When tested and compared with some existing approaches, their proposal showed improvements according to various criteria.

Nowadays, multimedia documents are omnipresent at any time from and to any devices. However, mobile devices heterogeneity and the various contexts of the user require their adaptation. In this context, the existing systems transform contents to comply with the target constraints. Nevertheless, the current solutions do not exploit the profile semantic benefits to reason upon the context for assisting the adaptation. Furthermore, there is no work that care of adapting HTML pages containing CSS and changing in time, where time specification is declarative (e.g. by means of timesheets). This paper provides an adaptation approach called “Handicap-based Multimedia Adaptation” (HaMA), in which each context constraint corresponds to handicap types in order to discover adaptation services. Thus, a generic ontology is introduced to reason upon the context and then deduces the corresponding handicap in order to infer the suitable adaptation guideline. Also, we propose a method for selecting appropriate services with respect to quality criteria. To validate HaMA, scenarios were implemented.

Pervasive systems help access to multimedia documents at any time, from anywhere and through several devices (smart TV, laptop, tablet, etc.). Nevertheless, due to changes in users’ contexts (e.g. noisy environment, preferred language, public place, etc.), restrictions on correct access to these documents may be imposed. One possible solution is to adapt their contents using adaptation services so that they comply, as far as possible, with the current constraints. In this respect, several adaptation approaches have been proposed. However, when it comes to selecting the required adaptation services, they often carry out this task according to predefined configurations or deterministic algorithms. Actually, the efficient selection of adaptation services is one of the key-elements involved in improving the quality of service in adaptation processes. To deal with this issue (i.e. the efficient selection of adaptation services), we first provide an enriched problem formulation as well as methods that we use in problem-solving. Then, we involve standard and compact evolutionary algorithms to find efficient adaptation plans. The standard version is usually adopted in systems that are not subject to specific constraints. The compact one is used in systems for which constraints on computational resources and execution time are considered. The proposal is validated through simulation, experiments and comparisons according to performance, execution time and energy consumption. The obtained results are satisfactory and encouraging.

No abstract

No abstract