Social Governance Structure Construction and Resource Allocation Methods under the Management Mode of the Internet of Things

Aiming at the problems in the social governance structure level under the management mode of the Internet of Things, this paper designs a network agent based on the idea of service grid construction that has the functions of service resource configuration discovery, load balancing, and protocol conversion. Using it as a service governance infrastructure reduces the coupling between business services and service governance, and the network agent will intercept the service call traffic within the platform to achieve cross-protocol and cross-frame service communication. Through the proposed global query decomposition strategy and algorithm, a global query mapping is realized, which solves the problem of global query decomposition based on the global data model. We designed the unified management mechanism of two commonly used IoT databases based on XML. This process involves the realization of heterogeneous Internet of Things database resource configuration, data mode conversion, and global query mapping. Among them, in the process of data schema conversion, the conflict of the data in the schema mapping is resolved, the XML Schema is generated, the schema mapping metadata is established, and the XML document of the data is generated. We build a framework for optimal allocation of cloud computing resources based on load forecasting and propose an adaptive elastic control system for resource allocation based on resource status monitoring and demand forecasting. In view of the low resource utilization problem caused by the resource management mode of single virtual machine serving single user adopted by Internet of Things service providers, this paper constructs a new public cloud architecture with a five-layer structure. On the basis of this architecture, an adaptive configuration mode of virtualized resources based on a single virtual machine serving multiple users is proposed. This mode can automatically search for optimal virtualization resources for application resource requests made by different users and run different applications on the same virtual machine without affecting the quality of service, so that IoT providers can guarantee services. At the same time, it improves the utilization efficiency of IoT resources and reduces energy consumption.

Continuous Join Query Processing over Structured Overlay Networks

P2P network is more suitable for distributed data flow processing. This paper concentrates on how to answer continuous join query in structured p2p overlay networks. In the algorithm proposed, the data that cannot contribute the queries’ results will not be distributed in the network based on global query indices. Experiment shows that the algorithm ensures the availability of join query and network traffic is reduced.

Enhanced Information Retrieval Evaluation between Pseudo Relevance Feedback and Query Similarity Relevant Documents Methology Applied on Arabic Text

Information retrieval systems utilize user feedback for generating optimal queries with respect to a particular information need. However, the methods that have been developed in IR for generating these queries do not memorize information gathered from previous search processes, and hence cannot use such information in new search processes. Thus, a new search process cannot profit from the results of the previous processes. Web Information Retrieval systems should be able to maintain results from previous search processes, thus learning from previous queries and improving overall retrieval quality. In this chapter, we are using the similarity of a new query to previously learned queries. We then expand the new query by extracting terms from documents, which have been judged as relevant to these previously learned queries. Thus, the new method uses global feedback information for query expansion in contrast to local feedback information, which has been widely used in previous work in query expansion methods. Experimentally, we compared a new query expansion method with two conventional information retrieval methods in local and global query expansion to enhance the traditional information system. From the results gathered it can be concluded that although the traditional IR system performance is high, but we notice that PRF method increases the average recall and decreases the fallout measure.