Research On The Decentralized Management And Composition Techniques Of Geospatial Services

With large-scale applications of Internet technology and Web technology, Geographical information system network has become an inevitable trend of development. Various kinds of geospatial information system have gradually become important fundamental infrastructures. More and more geospatial data resources, geospatial computing resources and geospatial applications relying on the Internet have become public accessible network resources. All these have promoted the traditional sense of released geospatial information to shift to the open Internet-based distributed computing infrastructure gradually. In recent years, with the maturation of Web services technology and their promotion, service-oriented architecture for geospatial information sharing has become a mainstream paradigm. Geospatial services have been concerned by many domestic and international research groups. From the creation of geospatial services to the use of geospatial services, we have accumulated a lot of mature experience, technology, standards and norms. As technology continues to be studied in depth, we need to further consolidate and promote geospatial service technology by enhancing the efficient use of geospatial service.Hosts of geospatial services can not collaborate actively with each other if we deploy these services directly on the Internet. Such direct deployment also makes geospatial service management (such as geospatial service deployment, publish, discovery and selection) less scalability and depresses the ability of composition system to improve performance. With more and more geospatial services deployed, such questions will be faced with more challenge. In this dissertation, we present a different idea which uses a decentralized geo-p2p overlap network to manage and compose geospatial services. In our methods, we first bring forward a decentralized network infrastructure based on p2p technologies, and then focus on the management and composition for geospatial services with this infrastructure. During our studies, we investigate the technologies of the geo-p2p network topology, geospatial service query model and its implementation on the geo-p2p, modeling and execution of geospatial service composition. Our main contributions are:1. We have presented a decentralized framework for management and composition of geospatial services. In our framework, we bring forward a geo-p2p network based on the traditional p2p technology. We also design geo-peers to construct such decentralized network. All these geo-peers can act as geospatial service consumers, providers, discoverers and composers synchronously. With these active geo-peers, we can enhance the scalability and composition performance of geo-p2p networks. We study different levels of geo-p2p networks from system architecture, geospatial service management model and geospatial service composition model to support further research.2. We have studied geo-p2p network topology and present a hybrid network topology based on the multi-layer sparse topology as well as its dynamic maintenance algorithm. We first establish a geospatial service query cost model by modeling the service discovery process, and then compute an optimal ratio between super geo-peers and basic geo-peers from a general sense of geospatial service discovery. Finally, we give a dynamic maintenance algorithm for the geo-p2p network topology. Experimental results support well with our theoretical conclusions.3. We have probed into query models for geospatial services on geo-p2p networks and present a new query model based on information retrieval technology. In the query model, we propose a non-spatial similarity function and a spatial similarity function to evaluate the degree similarity between a query and a geospatial service partially. In the non-spatial similarity function, both a geospatial service and a query are represented as vectors as those in information retrieval. The vector model proposed can evaluate the degree of similarity of a service and a query as the correlation between those two vectors non-spatially. In the spatial similarity function, both a geospatial service and a query are represented as rectangles. The topology measure, distance measure and direction measure between those two rectangles can be used to evaluate the degree of similarity between the service and the query spatially. Therefore, we can use the two weighted functions ultimately to compute the degree of similarity between each geospatial services stored in the geo-p2p networks and the user query.4. We have implemented two kinds of geospatial service query on geo-p2p networks. The first implementation is to cluster geo-peers into different geospatial semantic groups according to the correlation between geo-peers. This idea is coming from an optimization mechanism called contents aggregation for shared-resources discovery over traditional p2p networks. The query can walk between those groups biasedly, so it can get a better performance in those heuristic groups. The other implementation is to maintain a distributed index called CAN-QTree for geospatial service query over geo-p2p networks. In such method, all geo-peers to be queried interrelate with each other using a structured topological network called CAN, and the metadata of their geospatial services are indexed by a Quadtree data structure. With a deliberate mapping between the zones of the CAN and the underlying space of the Quadtree, we can maintain a distributed index call CAN-QTree on geo-p2p networks to provide a O(n1/2) search performance. All those two methods are verified by our experiments in this dissertation.5. We have explored modeling decentralized geospatial service composition and present global process model, local process model and sub-process model to represent overall geospatial service composition, corresponding geospatial service composition of each geo-peer on geo-p2p network and their relationship. In the global process model, we use activities, control-flows and data-flows to model steps of geospatial service composition, sequences between all activities and messages. We also evaluate quantitatively those global process models through a critical path concept. In local process model, we add collaborative activities to model the control-flows or data-flows which span different local processes.6. We have investigated decentralized executions for geospatial service composition on geo-p2p networks. We present an indirect algorithm for decomposing a global process into different local processes based on best process concept. In the algorithm, we first turn a global process into a best process without losing any functions, and then decompose the best process into several local processes on the principle of minimizing messages transmission between those local processes after decomposition. Our simulations show that the algorithm is better than the traditional direct decomposition algorithm and it is also superior to the implementations of centralized execution for geospatial service composition in the circumstances with large messages or limited network bandwidth.7. We finally design and implement an experimental prototype system according to the research presented above. In our system, we design different interfaces for geo-peers to act as geospatial service consumers, geospatial service providers, geospatial service discoverers and geospatial service composers synchronously. Our experimental prototype system shows that our achievements are effective and practical.