SGPS A Hybrid of Topology and Location Based Protocol for Ad hoc Networks Jingyi Yu Computer Graphics Group.

Slides:



Advertisements
Similar presentations
Geographic Routing Without Location Information AP, Sylvia, Ion, Scott and Christos.
Advertisements

ECE /24/2005 A Survey on Position-Based Routing in Mobile Ad-Hoc Networks Alok Sabherwal.
Mobile and Wireless Computing Institute for Computer Science, University of Freiburg Western Australian Interactive Virtual Environments Centre (IVEC)
Proposed ad hoc Routing Approaches Conventional wired-type schemes (global routing, proactive): –Distance Vector; Link State Proactive ad hoc routing:
Network Layer Routing Issues (I). Infrastructure vs. multi-hop Infrastructure networks: Infrastructure networks: ◦ One or several Access-Points (AP) connected.
Geographic Routing Without Location Information A. Rao, S. Ratnasamy, C. Papadimitriou, S. Shenker, I. Stoica Paper and Slides by Presented by Ryan Carr.
Ranveer Chandra , Kenneth P. Birman Department of Computer Science
MANETs Routing Dr. Raad S. Al-Qassas Department of Computer Science PSUT
Mobile and Wireless Computing Institute for Computer Science, University of Freiburg Western Australian Interactive Virtual Environments Centre (IVEC)
Mobile and Wireless Computing Institute for Computer Science, University of Freiburg Western Australian Interactive Virtual Environments Centre (IVEC)
A Performance Comparison of Multi-Hop Wireless Ad Hoc Network Routing Protocols By Josh Broch, David A. Maltz, David B. Johnson, Yih- Chun Hu, Jorjeta.
An Analysis of the Optimum Node Density for Ad hoc Mobile Networks Elizabeth M. Royer, P. Michael Melliar-Smith and Louise E. Moser Presented by Aki Happonen.
1 Spring Semester 2007, Dept. of Computer Science, Technion Internet Networking recitation #4 Mobile Ad-Hoc Networks AODV Routing.
1 A Performance Comparison of Multi-Hop Wireless Ad Hoc Network Routing Protocols Josh Broch David A. Maltz David B. Johnson Yih-Chun Hu Jorjeta Jetcheva.
Mobile and Wireless Computing Institute for Computer Science, University of Freiburg Western Australian Interactive Virtual Environments Centre (IVEC)
Wireless Ad Hoc Network Routing Protocols CSE Maya Rodrig.
ITIS 6010/8010 Wireless Network Security Dr. Weichao Wang.
A Performance Comparison of Multi-Hop Wireless Ad Hoc Network Routing Protocols Josh Broch David A. Maltz David B. Johnson Yih-Chun Hu Jorjeta Jetcheva.
Routing Security in Ad Hoc Networks
Mobile and Wireless Computing Institute for Computer Science, University of Freiburg Western Australian Interactive Virtual Environments Centre (IVEC)
CS 268: Ad Hoc Routing Kevin Lai Feb 20, Ad Hoc Motivation  Internet goal: decentralized control -someone still has to deploy.
CS 672 Paper Presentation Presented By Saif Iqbal “CarNet: A Scalable Ad Hoc Wireless Network System” Robert Morris, John Jannotti, Frans Kaashoek, Jinyang.
Di Wu 03/03/2011 Geographic Routing in Clustered Multi-layer Vehicular Ad Hoc Networks for Load Balancing Purposes.
Ad-hoc On-Demand Distance Vector Routing (AODV) Sirisha R. Medidi.
1 Spring Semester 2007, Dept. of Computer Science, Technion Internet Networking recitation #5 Mobile Ad-Hoc Networks TBRPF.
Ad Hoc Wireless Routing COS 461: Computer Networks
Routing Two papers: Location-Aided Routing (LAR) in mobile ad hoc networks (2000) Ad-hoc On-Demand Distance Vector Routing (1999)
A Scalable Location Service for Geographic Ad Hoc Routing Jinyang Li, John Jannotti, Douglas S. J. De Couto, David R. Karger, Robert Morris MIT Laboratory.
ENHANCING AND EVALUATION OF AD-HOC ROUTING PROTOCOLS IN VANET.
Itrat Rasool Quadri ST ID COE-543 Wireless and Mobile Networks
1 Spring Semester 2009, Dept. of Computer Science, Technion Internet Networking recitation #3 Mobile Ad-Hoc Networks AODV Routing.
Mobile Routing protocols MANET
Scalable Routing Protocols for Mobile Ad Hoc Networks Xiaoyan Hong, Kaixin Xu, and Mario Gerla at UCLA.
Mobile Adhoc Network: Routing Protocol:AODV
Ad hoc On-demand Distance Vector (AODV) Routing Protocol ECE 695 Spring 2006.
Ad-hoc On-Demand Distance Vector Routing (AODV) and simulation in network simulator.
ROUTING ALGORITHMS IN AD HOC NETWORKS
Routing Protocols of On- Demand Dynamic Source Routing (DSR) Ad-Hoc On-Demand Distance Vector (AODV)
The Destination Sequenced Distance Vector (DSDV) protocol
1 Ad Hoc On-Demand Distance Vector Routing (AODV) Dr. R. B. Patel.
Connectivity-Aware Routing (CAR) in Vehicular Ad Hoc Networks Valery Naumov & Thomas R. Gross ETH Zurich, Switzerland IEEE INFOCOM 2007.
AODV: Introduction Reference: C. E. Perkins, E. M. Royer, and S. R. Das, “Ad hoc On-Demand Distance Vector (AODV) Routing,” Internet Draft, draft-ietf-manet-aodv-08.txt,
SRL: A Bidirectional Abstraction for Unidirectional Ad Hoc Networks. Venugopalan Ramasubramanian Ranveer Chandra Daniel Mosse.
Dual-Region Location Management for Mobile Ad Hoc Networks Yinan Li, Ing-ray Chen, Ding-chau Wang Presented by Youyou Cao.
Traditional Routing A routing protocol sets up a routing table in routers A node makes a local choice depending on global topology.
CarNet/Grid: Scalable Ad-Hoc Geographic Routing Robert Morris MIT / LCS
Ad-hoc On Demand Distance Vector Protocol Hassan Gobjuka.
Ad Hoc On-Demand Distance Vector Routing (AODV) ietf
Fundamentals of Computer Networks ECE 478/578
Performance Comparison of Ad Hoc Network Routing Protocols Presented by Venkata Suresh Tamminiedi Computer Science Department Georgia State University.
Ad Hoc Wireless Routing Different from routing in the “wired” world Desirable properties of a wireless routing protocol –Distributed operation –Loop freedom.
Spatial Aware Geographic Forwarding for Mobile Ad Hoc Networks Jing Tian, Illya Stepanov, Kurt Rothermel {tian, stepanov,
Mobile Ad Hoc Networks. What is a MANET (Mobile Ad Hoc Networks)? Formed by wireless hosts which may be mobile No pre-existing infrastructure Routes between.
Ad Hoc Wireless Routing
A Cluster-based Routing Protocol for Mobile Ad hoc Networks
GeoTORA: A Protocol for Geocasting in Mobile Ad Hoc Networks
DSDV Highly Dynamic Destination-Sequenced Distance-Vector Routing
Internet Networking recitation #4
A comparison of Ad-Hoc Routing Protocols
Routing Protocols in MANETs
Sensor Network Routing
任課教授:陳朝鈞 教授 學生:王志嘉、馬敏修
Ad Hoc Wireless Routing
Temporally-Ordered Routing Algorithm (TORA)
Mobile and Wireless Networking
by Saltanat Mashirova & Afshin Mahini
Proactive vs. Reactive Routing
Routing.
Vinay Singh Graduate school of Software Dongseo University
DSDV Destination-Sequenced Distance-Vector Routing Protocol
Presentation transcript:

SGPS A Hybrid of Topology and Location Based Protocol for Ad hoc Networks Jingyi Yu Computer Graphics Group

Existing Routing Protocols for MANET Topology-Oriented –Distance Vector DSDV AODV TORA DSR –Hierarchical HSR Landmark Location Oriented –Flooding LAR DREAM –Hierarchical GLS SGPS

Analysis of Topology Based Protocol DSDV (Destination-Sequenced DV) Modified Distance Vector Use sequence numbers to differentiate freshness(even and odd) Loop free Fail to converge as node mobility increases AODV (Ad hoc On-demand DV) Combination of DSDV and DSR Route Discovery from DSR Sequence number from DSDV Reverse Route and Forward Route (avoid source routing) DSR (Dynamic Source Routing) Aggressive caching Reduce routing overhead when flooding Packets are forwarded according to “source route” TORA (Temporally-order Routing Algorithm) Link reversal(Query/Update) Flow of traffic, network tube Need routing update delivered by “temporal order”

Performance Analysis of Topology Oriented Protocols DSDV –Converge slowly TORA – Implemented on IMEP AODV – High delivery rate DSR – High delivery rate This simulation is done for 50 nodes, 1500m x 300m Each node remains stationary for pause time seconds before sending packets.

Performance Analysis of Topology Oriented Protocols (cont.) DSDV –Almost constant overhead TORA – Huge routing overhead – Why? Reliable IMEP AODV – Large routing overhead DSR – Low routing overhead

Location Oriented Routing Flooding Based –LAR Route discovery by flooding Request zone, cache previous position/speed –DREAM Periodical flood location update The further, the less frequent update Hierarchical –GLS Geographical hierarchy Geographical forwarding Location servers Forward pointer –SGPS Handle problems when GPS fails How to choose more location servers

GLS Routing Pipeline Why location servers? –If every node knows any other node’s position, it can just send packets through geographic forwarding. Problem: Too much location update flooding through the network Solution: Hierarchical approach, keep a limited amount of location servers –If we have stationary leaders, those “unfortunate” will be the bottleneck and die out faster Solution: Each node is some other nodes’ location server Establish a space hierarchy Recruiting location servers Route discovery: Location query Location response Get Dest’s location Route packets to Dest using Geographic forwarding

Geographical Hierarchy Global Partitioning 4 order-n squares form an order-(n+1) square Each node easily maps its ID to HID Can extend to module M space partition ID Space Each node has a unique ID (IP to ID, etc) Positive integer “Closer” relation

Recruiting Location Servers (Location Update) “Closer” Relation A node Y is closer to X than a node Z to X if and only if one of the following is satisfied: 1.Y id < Z id < X id 2.Y id > X id and Z id < X id 3.Z id > Y id >X id Recruiting Location Servers –For each level of grid, a node chooses three nodes closest to its ID as its location servers. –Keep a table of location servers’ HID –How to choose? Implicit recruiting, i.e., sending location update to each level

Recruiting Location Servers An Example

Packets Routing between Two Nodes Location Query –A sends a request to the least node greater than or equal to B for which A has location information and so on until the request reaches B –B responds to A using geographic forwarding –At most N steps if A and B share some order-N square Bootstrapping –How does A recruit its location servers? A sends its location updates to an order-n square The first node L picks up the update and begins a location query for A Assumption: before a location update reaches an order-n square, all nodes have recruited their location servers of order-(n-1) square –Geographical forwarding A simple two hop distance vector protocol Each node periodically broadcasts a list of all neighbors it can reach in one hop Each entry of neighbor expires in a fixed time and is no longer broadcasted as neighbors, but can still be used. Why? (think of ) HELLO messages are not unusual to get lost Unicast is acknowledged, i.e., invalid entry will be removed due a forwarding packet failure

Proof of Correctness and Efficiency (by induction) Claim: In n or fewer location query steps, a query reaches the node with the lowest ID closest to the destination in the order-n square containing the source. Suppose the destination is ID 0 and the query starts at X and the node with lowest ID (closest to 0) in order-n square is Y. Base case:order-1 square. If X = Y, then with 0 step, query reaches Y1. If X != Y, then Y is the lowest node X can route. Otherwise if X can route some other node Y1 lower than Y outside its order-1 square, Y1 would have chosen Y rather than X as its location server. Inductive step: order-(n+1) square. We want to show if the query is at node X with the lowest ID in its order-n square, then X will route the query to the node Y with the lowest ID in its order-(n+1) square in zero or one step. If X has the lowest node ID in order-(n+1) square, then the claim is trivially true. If X has not, then X will know Y’s location and will not know any node whose ID is lower than Y. i) X will know Y’s location, since X has the lowest node ID in order-n square, Y must have selected X as its location server at X’s order-n square. ii) X will not know the location of any node lower than Y outside of its order-(n+1) square since any such node would have chosen Y as its location server in X’s order-(n+1) square. Thus the lowest node X can location is Y and the query can be forwarded there in one location query step.

Routing Using Location Servers

Problems with GLS Flooding vs. Location Servers –Flooding: Efficient routing Too much routing overhead –Location Server: Fixed amount of location updates Scale well when nodes are uniformed distributed Not adaptive to node density –Solution: Balancing between flooding and location update Adaptive sub-division Recruit more than one location servers in each sibling grid Correct? What if location query fails –Forwarding pointer –On leaving an order-1 grid, each node leaves a forwarding pointer in it indicating that it has moved to another grid What if GPS fails –A node can no longer know its position and hence cannot send location update. Solution: Tunneling through its neighbors

Dynamic Hierarchy for GLS Problems of naïve solution to recruit more location servers –Increase routing overhead –Will not improve performance, since each query will still pick the smallest ID node Dynamic Hierarchy –Dynamic space partition –Difficulty: hard to synchronize the network An example of a 3x3 grid

An Example of Dynamic Hierarchy Each node estimates the number of nodes in its order-1 square If one detects the square is overwhelmed, it broadcasts to its neighbors SUB_DIVIDE The next location update will use the new sub-division level to recruit location servers It also indicates the subdivision level to all its location servers to keep the location servers updated. HID should be sub-division compatible Bottleneck Sub_div Loc_update

SGPS and Tunneling A B 1. GPS_FAIL Broadcast to all neighbors 2. ACK_OK 4. Forward new location and ID 3. Grant Tunneling Three-way handshaking protocol On detecting its GPS failure, each node broadcasts “recruiting tunnel server” Those 1 ring neighbors who have GPS then reply ACK_OK The GPS-failure node then chooses one of them as its tunnel server It then update its location as the tunnel server location to its location servers

Simulation Results Simulation Scenario radio bandwidth 2Mbps Distance threshold 200M No node is a source in more than one connection No node is a destination in more than 3 connections Each connection sends 4 128byte packets per second for 20 seconds Moving speed 10m/s Location Query Failure Broken links Congestion

Path Length Analysis 300 nodes with speed 10m/s Query travels about 6 hops more than the geographic forwarding A tradeoff between routing efficiency and routing overhead

Routing Overhead Analysis DSR route request route reply cached reply GLS HELLO Location Update Location Query Location Response Congestion Not much increase, since almost half of the protocol packets are HELLO

Conclusion and Future work Compare Topology-oriented and Location-oriented MANET routing –DSR is the best of non-hierarchical topology routing –Unfair hierarchical routing is not desirable –Flooding based GPS routing incurs large routing overhead –Location server based routing maintains the fairness and avoid location flooding. But GLS does not support adaptive hierarchy and does not know how to handle GPS failure SUB_DIVISION scheme to solve adaptive hierarchy –Implementation of GLS with 2x2 and 3x3 partition shows promising result –Need a consistent hierarchy ID for fine and coarse grid –Need aggregation-behavior scenario TUNNELING to solve GPS failure Acknowledgement: Special thanks to Jingyang, Robert and Hari.