Development of a Smart Technique for Mobile Web Services Discovery

Web service(WS)presents a good solution to the interoperability of different types of systems that aims to reduce the overhead of high processing in a resource-limited environment.With the increasing demand for mobile WS(MWS),the WS discovery process has become a significant challenging point in the WS lifecycle that aims to identify the relevant MWSs that best match the service requests.This discovery process is a resource-consuming task that cannot be performed efficiently in a mobile computing environment due to the limitations of mobile devices.Meanwhile,a cloud computing can provide rich computing resources for mobile environments given its unlimited and easily scalable resources.This paper proposes a semantic WS discovery and invocation framework in mobile environments based on cloud and a relationship-aware matchmaking algorithm.The discovery algorithm enriches MWS and user requests semantically with the functional and non-functional properties of Ontology Web Language for Services,such as Quality of Web Service,device context,and user preferences.The WS repository is filtered based on logical reasoning and a parameter-based matching algorithm to minimize the matching space and improve runtime performance.The cosine similarity between the user request and services repository is then assessed to generate the most relevant WS.The relationships among concepts in the ontology are considered to improve the recall and precision ratio.After the WS discovery process,users can invoke and test these services in a mobile environment through a dynamic user interface.The interface of the invocation process is changed according to the WS description document.An application prototype is also developed to evaluate the framework based on a Cordova cross-mobile development framework.

A Sensor Network Web Platform Based on WoT Technology

This study proposes a Web platform,the Web of Things(WoT),whose Internet of Things(IoT)architecture is used to develop the technology behind a new standard Web platform.When a remote sensor passes data to a microcontroller for processing,the protocol is often not known.This study proposes a WoT platform that enables the use of a browser in a mobile device to control a remote hardware device.An optimized code is written using an artificial intelligencebased algorithm in a microcontroller.Digital data convergence technology is adopted to process the packets of different protocols and place them on the Web platform for access by other mobile devices.The platform has high efficiency and cross-platform advantages,with no limitation on the operating system.Message queueing telemetry transport(MQTT)technology is used to simplify the original HTTP protocol.Assume that the mobile device is a subscriber,i.e.,the controller,and a microcontroller that connects the sensing device is the publisher.The publishers and subscribers of MQTT need not know each other if they share a message broker.The intermediate agent role is much like a router.Publishers and subscribers do not need to interact,and publishers do not have to wait for subscriber confirmation to cause interactive permission be locked.Nor must publishers and subscribers be online at the same time,and they are free to choose when to get messages.The proposed WoT method is compared with the traditional IoT method regarding data transfer.The results show that the proposed method can save time in processing large amounts of data,as the traditional IoT method wastes time,especially in data format transfer.

RFES: a real-time fire evacuation system for Mobile Web3D

There are many bottlenecks that limit the computing power of the Mobile Web3 D and they need to be solved before implementing a public fire evacuation system on this platform.In this study,we focus on three key problems:(1)The scene data for large-scale building information modeling(BIM)are huge,so it is difficult to transmit the data via the Internet and visualize them on the Web;(2)The raw fire dynamic simulator(FDS)smoke diffusion data are also very large,so it is extremely difficult to transmit the data via the Internet and visualize them on the Web;(3)A smart artificial intelligence fire evacuation app for the public should be accurate and real-time.To address these problems,the following solutions are proposed:(1)The large-scale scene model is made lightweight;(2)The amount of dynamic smoke is also made lightweight;(3)The dynamic obstacle maps established from the scene model and smoke data are used for optimal path planning using a heuristic method.We propose a real-time fire evacuation system based on the ant colony optimization(RFES-ACO)algorithm with reused dynamic pheromones.Simulation results show that the public could use Mobile Web3 D devices to experience fire evacuation drills in real time smoothly.The real-time fire evacuation system(RFES)is efficient and the evacuation rate is better than those of the other two algorithms,i.e.,the leader-follower fire evacuation algorithm and the random fire evacuation algorithm.