The rapid expansion of the Internet of Things ecosystem has created an urgent need for efficient data processing and analysis technologies. This review aims to systematically examine and compare edge computing, cloud computing, and hybrid architectures, focusing on their applications within IoT environments. The methodology involved a comprehensive search and analysis of peer-reviewed journals, conference proceedings, and industry reports, highlighting recent advancements in computing technologies for IoT. Key findings reveal that edge computing excels in reducing latency and enhancing data privacy through localized processing, while cloud computing offers superior scalability and flexibility. Hybrid approaches, such as fog and mist computing, present a promising solution by combining the strengths of both edge and cloud systems. These hybrid models optimize bandwidth use and support low-latency, privacy-sensitive applications in IoT ecosystems. Hybrid architectures are identified as particularly effective for scenarios requiring efficient bandwidth management and low-latency processing. These models represent a significant step forward in addressing the limitations of both edge and cloud computing for IoT, offering a balanced approach to data analysis and resource management.

More and more resources are becoming available on the Web, and there is a growing need for infrastructures that, based on advertised descriptions, can match demands with supplies in an electronic marketplace. Several matchmakers rely on simple keyword matching, but significant matching results can only be obtained by exploiting the semantics inherent in structured descriptions. To this end, a novel knowledge representation approach is proposed, based on description logics, that is superior to both keyword- and basic subsumption-based matchmaking. The properties a matchmaker should have are formalized, and a matchmaking facilitator, compliant with the desired properties, is presented. The system embeds a NeoClassic reasoner whose structural subsumption algorithm has been modified to allow match categorization into potential and partial, and ranking of matches within categories. Experiments show good correspondence between users and system rankings.

Development of Web Applications (WA) needs new methods, techniques and tools to support an engineered project during all the phases of its life cycle. To ensure the reliability of WA it is important they be validated and verified at early design phase. We use Model Checking techniques to perform automated verification of the UML design of a WA.We propose a mathematical model of a WA partitioning the usual Kripke structure into windows, links, pages and actions. Then we specify properties to be checked in a temporal logic, Computation Tree Logic (CTL). Verification is performed adapting the SMV model checker to our formalism. An implemented system that embeds the SMV verifier automatically parses the XMI output of UML tool and builds the SMV model to be verified with respect to specifications. Results of verification proved the benefits of the method