Scalable Location Management for Large Mobile Ad hoc Networks Sumesh J. Philip

Contents Wireless Ad hoc networks Issue of Scalability Geographic Routing Scalable Location Update based Routing SLALoM - Scalable Location Management Grid Location Service Hierarchical Grid Location Management Simulations and Results Conclusion

Wireless Ad hoc networks Infrastructure-less networks that can be easily deployed Each wireless host acts as an independent router for relaying packets Network topology changes frequently and unpredictably How to route packets? Quite a lot of protocols proposed in literature (table driven/reactive/hybrid) Dynamic source Routing (DSR) works well for small networks

Issue of Scalability Increasing density increases average node degree, decreases network diameter Routing cost less Any reasonable scheme might work! To test scalability, area (playground size) must increase with nodes Average node degree constant Will present a mobility model that consolidates the above relationship

Traditional Protocols Table driven incur large overheads due to routing table maintenance Delayed control as good as no control On-demand flood the entire network with discovery packets long latency for discovery Path maintenance means additional state No separation between data and control Ultimately, data suffers!!

Any contenders ? Not many invariants to play with (IP address, local connectivity) Nodes physically located closer likely to be connected by a small number of radio hops Possible to obtain node location via a GPS receiver Geographic forwarding Packet header contains the destination’s location Most forward with fixed radius

Geographic Forwarding A B C D F C’s radio range E G A addresses a packet to G’s latitude, longitude C only needs to know its immediate neighbors to forward packets towards G. Geographic forwarding needs location management!

Desirable Properties of Location Management Spread load evenly over all nodes Degrade gracefully as nodes fail Queries for nearby nodes stay local Per-node storage and communication costs grow slowly as the network size grows

Scalable Location based Routing Protocol (SLURP) Hybrid Protocol that has a deterministic manner of discovering the destination Topography divided into square grids Each node (ID) selects a home region using f(ID), and periodically registers with the HR Nodes that wish to communicate with a node query its HR using f --1 (ID) Use geographic forwarding to send data, once location is known (e.g. MFR)

Example [12] [10] - Home region - Update/Query - Location Database - Data f(ID)- ID Mod(R T ) ID = 22; R T = 12; HR=22%12 = 10; DST = 22; R T = 12; HR=22%12 = 10;

Cost of Location Management Location Registration Periodic Triggered Location Maintenance Operations for database consistency Location Discovery Query/response Data Transfer

Mobility Model Each node moves independently and randomly Direction, Velocity [ v-c, v+c ] at t New direction and velocity at destination Node degree = To keep degree constant, A must grow linearly with N

Location update Overhead

Home Region Maintenance On region crossing Inform previous region of departure Inform new region of arrival Update from any node in new region

Total Overhead Cost of Locating Send a Location query to Home region Total Overhead = Sum of all overheads for all nodes

ScaLAble Location Management (SLALoM) Define a hierarchy of regions : Order(3), Order(2), Order(1) Each Order(2) region consists of K 2 Order(1) regions Each node assigned a HR in an Order(2) region To reduce location update overhead, define far and near HRs; near regions updated frequently Nodes that wish to communicate with another node query its HR in current Order(2) grid Queries from far HRs find way to near ones for exact location of destination

Protocol Operation - Order 3 - Update/Query - Location Database - Data K = 3 - Order 2 - Home region

Control Overhead Maintenance Overhead Location Update Cost of Locating Total Overhead

Grid Location Service (GLS) n s s s s s s s s s s is n’s successor in that square. (Successor is the node with “least ID greater than” n ) sibling level-0 squares sibling level-1 squares sibling level-2 squares

... 1 GLS Updates 9 23, 2 11, location table content location update 2 Invariant (for all levels): For node n in a square, n’s successor in each sibling square “knows” about n.

, 2 11, location table content query from 23 for 1 GLS Query

HIEARCHICAL GRID LOCATION MGMT 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

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 Mobile Node Movement Update msg

LOCATION MAINTENANCE 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 Movement Location database to store ? A (A_loc) B (B_loc) …

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 Response msg Query msg Data

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 i th 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 i th grid Notations:

LOCATION REGISTRATION COST Pr[ i th server is updated] = Average distance traversed by update = Average number of broadcasts = Average location update cost =

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 =

LOCATION DISCOVERY COST Location query visits at most k leaders Average distance for query in the k th grid = Assuming worst case distance in the i th grid, Average location discovery cost =

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/km 2 (unit grid side 250 m) Transmission range 350 m, speed 2Mbps IEEE 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

RESULTS Registration Overhead Registration Delay Data Delivery Ratio Data Delay

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

References C. Cheng, S. Philip, H. Lemberg, E. van den Berg, T. Zhang, SLALoM: A Scalable Location Management Scheme for Large Mobile Ad-hoc Networks, to appear in Proceedings of 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 Josh Broch, David A. Maltz, David B. Johnson, Yih-Chun Hu, and Jorjeta Jetcheva. A Performance comparison of multi-hop wireless Ad-Hoc network routing protocols. In Proceedings ACM/IEEE MobiCom, pages 85-97, October 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 Netwroking, pages , August 2000 Seung-Chul M. Woo and Suresh Singh, Scalable Routing in Ad-Hoc Networks, Technical Report, TR00.001, March 2000 Basagni SBasagni S. and Chlamtac, I. and Syrotiuk, V. R. and Woodward, B. A. 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 , Dallas, TX, October 25-30, 998 K. Fall and K. Varadhan, NS notes and documentation, technical report, UC Berkeley, LBL, USC/ISI and Xerox Parc,