A Novel Mechanism for Flooding Based Route Discovery in Ad Hoc Networks Jian Li and Prasant Mohapatra GlobeCom’03 Speaker ︰ CHUN-WEI
Outline Introduction PANDA Design PANDA-LO PANDA-LV PANDA-TP Simulation Conclusion
Introduction Flooding based route discovery AODV,DSR…etc Broadcast storm problem In [11]”A Performance Comparison of Multi- hop Wireless Ad-hoc Networking Routing Protocol“ use Random Rebroadcast Delay (RRD) approach to solve the problem
Introduction RRD approach is not the most suitable one in term of search for a better route RRD approach may choice the worst next - hop candidate S I J K L M D
Introduction We propose to use location and velocity information in determining the rebroadcast delay time Positional Attribute based Next-hop Determination Approach (PANDA)
PANDA Design Basic idea Discriminate neighboring node as good or bad candidate for the next hop Good candidate Shorter rebroadcast delay Bad candidate Longer rebroadcast delay Algorithm PANDA-LO (Location Only) PANDA-LV (Location & Velocity) PANDA-TP (Transmission Power)
PANDA Design Assume Each mobile node is equipped GPS Location and velocity information
PANDA Design – PANDA-LO The farther away node form the upstream node, the shorter rebroadcast delay
PANDA Design – PANDA-LO Random value between 0 to t 1
PANDA Design – PANDA-LO PANDA-LO may lead to fragile path Not consider the link lifetime
PANDA Design – PANDA-LV Use both location and velocity information Estimating the link lifetime Choosing stable links as the next hop
PANDA Design – PANDA-LV Θ
PANDA Design – PANDA-TP In wireless sensor network, power conservation is more important than reduction of end-to-end delay Break a big single hop into several small hops Demonstrated the following example Small hops power consumption is smaller than a big single hop
PANDA Design – PANDA-TP Assume ︰ P RXmin is the minimal receive power L is propagation loss
PANDA Design – PANDA-TP (α is between 2 and 4)
PANDA Design – PANDA-TP
Simulation PANDA-LO and PANDA-LV Use the codebase of DSR in ns-2 simulator Simulation area is 1500×300 square meter 100 nodes uniformly deployed A node’s speed is uniformly distributed in the range of (0, 20) meter per second Transmission range is 250 meter
Simulation
PANDA-TP Simulation program by ourselves Simulation area is 1500×300 square meter Nodes can dynamically control their transmission range In the route discovery phase, the nodes used a fixed transmission range of 250 meter
Simulation
Conclusion PANDA approach can improving the performance, quality, and energy conservation of routing algorithm