Open Access Open Access  Restricted Access Subscription or Fee Access

Distance based Query Processing in Mobile Applications

K.S. Kannan, A. Manjula


A digital ecosystem which have been motivated by natural systems aspire to deliver the complication of digital world which is likely to have the properties to self- organize , is scalable and is achievable . Distributed wireless mobile network is the main technology in a digital ecosystem. It provides information exchange and information services that are to be delieverd , which satisfies the requirement for digital ecosystems. Many drivers utilize Global Positioning System (GPS) to replace traditional printed map with ongoing development of the motor industry and mobile communication technology. Given a group of candidate interest objects, a question purpose, and therefore the variety of objects k, dkNN finds the shortest path that goes through all k interest objects with the minimum shortest distance among all attainable methods. By following this path, the user can visit all k interest objects one by one .This path has the shortest distance among all other possible paths. The algorithm functions well if the density is high and the number of interest objects is smaller than seven. This method works on both small and large number of nodes. And also increases the result accuracy for small and large number of nodes.


Digital EcoSystem , Query Processing,

Full Text:



Geng Zhao, Kefeng Xuan, and David Taniar ,”Path kNN Query Processing in Mobile Systems”, IEEE Transactions On Industrial Electronics, Vol. 60, No. 3, March 2013

G. Zhao, K. Xuan, W. Rahayu, D. Taniar, M. Safar, M. Gavrilova, and B. Srinivasan, “Voronoi-based continuousknearest neighbor search in mobile navigation,”IEEE Trans. Ind. Electron., vol. 58, no. 6, pp. 2247–2257, Jun. 2011.

Y. Gao, B. Zheng, G. Chen, W.-C. Lee, K. C. K. Lee, and Q. Li, “Visible reverse k-nearest neighbor query processing in spatial databases,”IEEE Trans. Knowl. Data Eng., vol. 21, no. 9, pp. 1314–1327, Sep. 2009.

K. Mouratidis and D. Papadias, “Continuous nearest neighbor queries over sliding windows,”IEEE Trans. Knowl. Data Eng., vol. 19, no. 6, pp. 789–803, Jun. 2007.

D. Papadias, J. Zhang, N. Mamoulis, and Y. Tao, “Query processing in spatial network databases,” in Proc. 29th VLDB, Berlin, Germany, 2003,pp. 802–813.

J. Jayaputera and D. Taniar, “Data retrieval for location dependent queries in a multi-cell wireless environment,” Mobile Inf. Syst., vol. 1, no. 2,pp. 91–108, Apr. 2005.

N. Roussopoulos, S. Kelley, and F. Vincent, “Nearest neighbor queries,”in Proc. ACM SIGMOD, San Jose, CA, 1995, pp. 71–79.

M. Safar, “K nearest neighbor search in navigation systems,” Mobile Inf.Syst., vol. 1, no. 3, pp. 207–224, Aug. 2005.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.