Storing and Indexing Spatial Data in P2P Systems


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Abstract

Our goal is to create from scratch a technique that is inherently distributed and also maintains the multidimensionality of data. Our focus is on structured P2P systems that share spatial information. We present SPATIALP2P, a totally decentralized indexing and searching framework that is suitable for spatial data. SPATIALP2P supports P2P applications in which spatial information of various sizes can be dynamically inserted or deleted, and peers can join or leave. The proposed technique preserves well locality and directionality of space.

Existing System:

Existing works first, order multidimensional data using a space-filling curve and, then, define a distance according to this ordering. The main challenge of these approaches is to preserve the important properties of multidimensional space (i.e., locality and directionality). Unfortunately, space-filling curves do not always preserve locality and directionality. For instance, two multidimensional regions that are close in the original space are not necessarily close in the z-ordering curve. The searching strategy of the P2P network inherits these locality problems of the 1D ordering.

Proposed System:

We propose SPATIALP2P, a totally decentralized framework for spatial (i.e., 2D) data that confirms to the autonomy principle of P2P networks. SPATIALP2P provides storing, indexing, and searching services for spatial data in a P2P network. SPATIALP2P exploits existing experience in the field of DHTs and can be built on top of any 1D DHT. Thus, SPATIALP2P distributes the spatial information to peers and guarantees the retrieval of any spatial area that exists in the system with low space and time complexity. Additionally, SPATIALP2P efficiently handles changes in the spatial information and in the network structure caused by joining or leaving peers without the need of load balancing or restructuring. Finally, contrary to existing DHT-based approaches, SPATIALP2P captures the locality and directionality of the 2D space.

Conclusions

In this work, we have focused on spatial data. We have presented the SPATIALP2P framework for handling spatial data in a P2P network. SPATIALP2P provides efficient storing, indexing, and searching services by preserving locality and directionality. As a result, SPATIALP2P performs exceptionally well for point and range query operations. SPATIALP2P supports dynamic insertion and deletion of spatial information of various sizes and dynamic joining and leaving of peers. In the future, we intend to adjust and test the SPATIALP2P framework for data of higher dimensions.