Open Access Open Access  Restricted Access Subscription Access

A Novel Air Index for Range Queries in Road Networks


Affiliations
1 Dept. of Computer Sci. and Engg., Pondicherry Engg. College, Pondicherry, India
 

   Subscribe/Renew Journal


Objective of the present work is to improve range query performance using Hybrid Spatial Air Index (HSAI). HSAI has been designed with combination of both cache management and network coding for processing range queries in road networks. HSAI has been utilized the advantage of both cache management and network coding and reduce client search space. The experiments have been conducted for evaluating performance, the experimental results show that HSAI outperform.

Keywords

Hybrid Spatial Air Index, Cache Management, Network Coding, Range Queries, Road Networks.
User
Subscription Login to verify subscription
Notifications
Font Size

  • D. Zhang, C.Y. Chow, Q. Li, X. Zhang and Y. Xu. 2012. SMashQ: Spatial mashup framework for k-NN queries in time-dependent road networks, Distributed Parallel Data bases, 31, 259-287. https://doi.org/10.1007/s10619-012-7110-6.
  • Y. Li, and M.L. Yiu. 2015. Route-saver: Leveraging route APIs for accurate and efficient query processing at location-based services, IEEE Trans. Knowledge and Data Engg., 27, 235-249. https://doi.org/10.1109/TKDE.2014.2324597.
  • H. Samet, J. Sankaranarayanan and H. Alborzi. 2008. Scalable network distance browsing in spatial databases, Proc. ACM SIGMOD Int. Conf. on Mgmt Data, 43-54. https://doi.org/10.1145/1376616.1376623.
  • H. Kriegel, P. Kroger, P. Kunath, M. Renz and T. Schmidt. 2007. Proximity queries in large traffic networks, Proc. 15th Annual ACM Int. Symp. Adv. Geographic Info. Systems, 21-28. https://doi.org/10.1145/1341012.1341040.
  • M.F. Mokbel, C.Y. Chow and W.G. Aref. 2006. The new casper: Query processing for location services without compromising privacy, Proc. 32nd Int. Conf. Very Large Data Bases, 763-774.
  • T. Imielinski, S. Viswanathan and B.R. Badrinath. 1997. Data on air: Organization and access, IEEE Trans. Knowledge and Data Engg., 9, 353-372. https://doi.org/10.1109/69.599926.
  • G. Li, Q. Zhou and J. Li. 2015. A novel scheduling algorithm for supporting periodic queries in broadcast environments, IEEE Trans. Mobile Computing, 14, 419-432. https://doi.org/10.1109/TMC.2015.2398417.
  • W. Sun, Y. Qin, j. Wu, B. Zheng, Z. Zhang, P. Yu and J. Zhang. 2014. Air indexing for on-demand XML data broadcast, IEEE Trans. Parallel and Distributed Systems, 25, 1371-1381. https://doi.org/10.1109/TPDS.2013.87.
  • K. Mouratidis, S. Bakiras and D. Papadias. 2009. Continuous monitoring of spatial queries in wireless broadcast environments, IEEE Trans. Mobile Computing, 8, 1297-1311. https://doi.org/10.1109/TMC.2009.14.
  • B. Zheng, W.C. Lee and D.L. Lee. 2007. On searching continuous k-nearest neighbors in wireless data broadcast systems, IEEE Trans. Mobile Computing, 6, 748-761. https://doi.org/10.1109/TMC .2007.1004.
  • U.L. Hou, H.J. Zhao, M.L. Yiu, Y. Li and Z. Gong. 2014. Towards online shortest path computation, IEEE Trans. Knowledge and Data Engg., 26, 1012-1025. https://doi.org/10.1109/TKDE.2013.176.
  • W. Sun, C. Chen, B. Zheng, C. Chen and P. Liu. 2015. An air index for spatial query processing in road networks, IEEE Trans. Knowledge and Data Engg., 27, 382-395. https://doi.org/10.1109/TKDE.2014.2330836.
  • S. Kim and S.H. Kang. 2010. Scheduling data broadcast: An efficient cut-off point between periodic and on-demand data, IEEE Communications Letters, 14, 1176-1178. https://doi.org/10.1109/LCOMM.2010.101210.101228.
  • P.T. Joy and K.P Jacob. 2012. A comparative study of cache replacement policies in wireless mobile networks, Proc. Int. Symp. Adv. in Computing and Info. Tech., 609-619. https://doi.org/10.1007/978-3-642-31513-8_62.
  • W.C. Peng and M.S. Chen. 2005. Design and performance studies of an adaptive cache retrieval scheme in a Mobile computing environment, IEEE Trans. Mobile Computing, 4, 29-40. https://doi.org/10.1109/TMC.2005.9.
  • W.C. Peng and M.S. Chen. 2005. Shared data allocation in a mobile computing system: Exploring local and global optimization, IEEE Trans. Parallel and Distributed Systems, 16, 374-384. https://doi.org/10.1109/TPDS.2005.50.
  • L. Yin and G. Cao. 2006. Supporting cooperative caching in adhoc networks, IEEE Trans. Mobile Computing, 5, 77-89. https://doi.org/10.1109/TMC.2006.15.
  • Q. Zhu, D.L. Lee and W.C. Lee. 2011. Collaborative caching for spatial queries in mobile P2P networks, IEEE Int. Conf. Data Engg., 279-290.
  • R. Ahlswede, N. Cai, S.Y. Li and R.W. Yeung .2000. Network information flow, IEEE Trans. Info. Theory, 46, 1204-1216. https://doi.org/10.1109/18.850663.
  • Y. Sagduyu and A. Ephremides. 2008. Cross-layer optimization of MAC and network coding in wireless queuing tandem networks, IEEE Trans. Info. Theory, 54, 554-571. https://doi.org/10.1109/TIT.2007.913423.
  • Y. Birk and T. Kol. 2006. Coding on demand by an informed source (ISCOD) for efficient broadcast of different supplemental data to caching clients, IEEE Trans. Info. Theory, 52, 2825-2830. https://doi.org/10.1109/TIT.2006.874540.
  • C. Zhan, C. Victor, S. Lee, J. Wang and Y. Xu. 2011. Coding-based data broadcast scheduling in on-demand broadcast, IEEE Trans. Wireless Comms., 10, 3774-3783. https://doi.org/10.1109/TWC.2011.092011.101652.
  • F. Li, D. Cheng, M. Hadjieleftheriou, G. Kollios and S. Teng. 2005. On trip planning queries in spatial databases, Proc. 9th Int. Conf. on Adv. Spatial Temporal Databases, 923-923. https://doi.org/10.1007/11535331_16.

Abstract Views: 495

PDF Views: 183




  • A Novel Air Index for Range Queries in Road Networks

Abstract Views: 495  |  PDF Views: 183

Authors

M. Veeresha
Dept. of Computer Sci. and Engg., Pondicherry Engg. College, Pondicherry, India
M. Sugumaran
Dept. of Computer Sci. and Engg., Pondicherry Engg. College, Pondicherry, India

Abstract


Objective of the present work is to improve range query performance using Hybrid Spatial Air Index (HSAI). HSAI has been designed with combination of both cache management and network coding for processing range queries in road networks. HSAI has been utilized the advantage of both cache management and network coding and reduce client search space. The experiments have been conducted for evaluating performance, the experimental results show that HSAI outperform.

Keywords


Hybrid Spatial Air Index, Cache Management, Network Coding, Range Queries, Road Networks.

References





DOI: https://doi.org/10.4273/ijvss.9.2.04