Hierarchical Grid Location Management for Large Wireless Ad hoc Networks

1. Hierarchical Grid Location Management for Large WirelessAd hoc Networks Sumesh J. Philip Chunming Qiao Dept. of Computer Science and Engineering State University of New York at Buffalo Amherst NY 14260 {sumeshjp, qiao}@cse.buffalo.edu

2. LOCATION MANAGEMENT PROBLEM • Nodes are location aware using GPS or localization techniques • Geographic forwarding (MFR, GPSR) for routing packets • The problem • How can the destination’s current location be obtained ? • How to efficiently store node location information in a distributed way ? • Current Solutions • Grid Location Service [Jinyang Li, et. al, ’00] • Scalable Update Based Routing [Woo & Singh, ’01] • Scalable Location Management [Xu, et. al, ’01] • SLALoM [Cheng, et. al, ’02]

3. MOTIVATIONS & CONTRIBUTIONS • Motivations • Current solutions do not scale well or not robust with node mobility • Do not consider localized mobility or local communication needs • Although there are grid based solutions, they use a single layer for location management, and hence can be improved • Contributions • Proposed a multi-layer Grid scheme which uses hierarchical location management, suitable for large networks • Analyzed cost for location management overhead • Show that the proposed scheme performs better in large, dense systems

4. HIERARCHICAL GRID ORDERING • Topography tiled into unit (Level 0) grids • Grid hierarchy built from unit grids recursively • At each level, one of the four lower level leaders selected as the leader for the current level • Top level leaders defined by the four grids that form the center • Figure shows a three level hierarchy • Grid ordering arbitrary; other orderings possible Level II Level I Level 0

5. Mobile Node Movement LOCATION REGISTRATION • Nodes in unit grid aware of each other by periodic broadcast • Nodes located in a region act as location servers • Hierarchy of a server decided by its position as well as the locale of the region • Nodes update servers as they cross grid boundaries • Number of updates, and distance traversed by the updates depends upon boundary hierarchy • Localized movement results in few updates that traverse short distances Update msg

6. Movement LOCATION MAINTENANCE A (A_loc) B (B_loc) … Location database to store ? • On entry into a grid, a node announces its presence • If the unit grid is a server region, a node already present in the region replies with location information that the newly arrived node has to store • Use of timers to avoid a broadcast storm Mobile Node

7. LOCATION DISCOVERY& DATA TRANSFER • If source, destination located in the same unit grid, they can talk directly • If not, source initiates a query message to discover the location of the destination • Query visits leaders until the approximate location of the destination is known • Data forwarded to the approximate location • Data continues to be forwarded to leaders that have more accurate information of the destination or until it reaches the destination Query msg Response msg Data

8. PERFORMANCE ANALYSIS:Location Management Overhead • Observations • Cost of location management consists of registration, maintenance and discovery • The number of transmissions required per message proportional to distance traversed by the message • An update that resulted from an ith boundary crossing visits at most (i +1) leader grids for (0  i  k ) • A query visits at most i leader grids, if source and destination located in the same ithgrid • Notations:

9. LOCATION REGISTRATION COST • Pr[ ith server is updated] = • Average distance traversed by update = • Average number of broadcasts = • Average location update cost =

10. LOCATION MAINTENANCE COST • When a node enters a new grid, it broadcasts its presence • A server node will respond with location information to store • In the worst case, all the nodes in the grid will broadcast back the location maintenance message • Pr[node enters a server grid] = • Average location maintenance cost =

11. LOCATION DISCOVERY COST • Location query visits at most k leaders • Average distance for query in the kthgrid = • Assuming worst case distance in the ith grid, • Average location discovery cost =

12. PERFORMANCE ANALYSIS:Simulations (GloMoSim) • Compared against SLURP, a well known protocol in literature • Parameter values • Topography size varied from 1000x1000m – 4000x4000m • Node density 80 nodes/km2 (unit grid side 250 m) • Transmission range 350 m, speed 2Mbps • IEEE 802.11 MAC • Random Waypoint mobility (Maximum speed 25 m/s, Minimum speed 0 m/s, Pause Time 0s) • Random, Constant Bit Rate traffic • 1024 bit payload • Performance Metrics • Registration overhead, registration delay, data delivery ratio, data delay • Results shown for increasing number of nodes

13. Registration Delay Registration Overhead Data Delay Data Delivery Ratio RESULTS

14. CONCLUSIONS • Cost of location management is important in geographic forwarding based protocols • Designed a multi-level grid ordering scheme for hierarchical location management • Average location registration cost increases only logarithmically in number of nodes for our scheme; hence scales well for large ad hoc networks • Simulations show that our scheme outperforms SLURP • For dense networks, simulations indicate that the protocol is robust with node mobility • For localized movements and local communication needs, hierarchical grid location management should perform even better

15. SELECTED REFRENCES • C. Cheng, S. Philip, H. Lemberg, E. van den Berg, T. Zhang, SLALoM: A Scalable Location Management Scheme for Large Mobile Ad-hoc Networks, Proceedings of IEEE Wireless Communications and Networking Conference, March, 2002. • Y. B. Ko, N. H. Vaidya, Location Aided Routing in Ad-Hoc networks, Proceedings of ACM/IEEE Mobicom’98, Dallas, TX, Oct. 1998. • Yuan Xue, Baochun Li, Klara Nahrstedt. A Scalable Location Management scheme in Mobile Ad hoc networks, in Proceedings of the 26th IEEE Annual Conference on Local Computer Networks (LCN 2001), pp. 102-111, Tampa, Florida, November 15-16, 2001. • Jinyang Li, John Janotti, Douglas S. J. De Couto, David R. Karger, and Robert Morris, A Scalable Location Service for Geographic Ad Hoc Routing, The Sixth Annual International Conference on Mobile Computing and Networking, pages 120-130, August 2000. • Seung-Chul M. Woo and Suresh Singh, Scalable Routing in Ad-Hoc Networks, Wireless Networks, volume 7, January 2001, pages 513-520. • S. Basagni, I. Chlamtac, Violet R. Syrotiuk, and B. A. Woodward, A Distance Routing Effect Algorithm for Mobility (DREAM), Proceedings of the Fourth Annual ACM/IEEE International conference on Mobile Computing and Networking, MobiCom'98, pp. 76-84, Dallas, TX, October 25-30, 998. • F. Kamoun and L. Kleinrock, Stochastic Performance Evaluation of Hierarchical Routing for Large Networks, Computer Networks, volume 3, November 1979, pages 337-353. • Xiang Zeng, Rajive Bagrodia and Mario Gerla, GloMoSim: A Library for Parallel Simulation of Large-scale Wireless Networks, Proceedings of the 12th Workshop on Parallel and Distributed Simulations (PADS '98), May 1998. • B. Karp and H. T. Kung, GPSR : Greedy perimeter stateless routing for wireless networks, Proceedings ACM/IEEE MobiCom,August 2000