Semantic-Based Dynamic Service Adaptation in Context-Aware Mobile Cloud Learning

Abstract Self-adaptable system concerns on service adaptation whenever errors persist within the system. Changes in contextual information such as networks or sensors will affect system’s effectiveness because process is not comprehensively handled those contexts. Besides, correctness to get most equivalence services be substituted limitedly being addressed from previous works. A dynamic framework introduced monitor and run a reasoning control solve these issues. Hence, this paper presents case study proof that leverages semantic-based approach context-aware environment. The evaluation of resulted significant difference for at 95% confidence level, which can interpreted confirm promising used operating pervasive