1. Rendezvous Regions: A Scalable Architecture for Service Location and Data-Centric Storage in Large-Scale Wireless Sensor Networks
Karim Seada, Ahmed Helmy
Electrical engineering Department, University of Southern California
IEEE IPDPS 2004
Speaker: Hao-Chun Sun

2. Outline Introduction Related Work Rendezvous Regions (RR) Architecture
Performance Evaluation
Conclusion

3. Introduction Challenges of sensor networks Sensor network
Limited resources
Extremely large number of nodes
Sensor network
Application-specific
The tasks is sent to nodes.
The data is recorded by nodes about the environment.

4. Introduction
Typical approaches for resources discovery and data storage
Local storage
Flooding
External storage
High energy cost
Data-centric storage
No flooding
sink
Access path

5. Related Work
GHT: A Geographic Hash Table for Data-Centric Storage (ACM WSNA 2002)
Sensor nodes is randomly deployment over a well-defined area.
Every node is aware of its location and its one-hop neighbor location information.
All nodes have the same capability.
Nodes are reasonably stationary and stable.

6. Related Work Distributed hash-table
Put (key, value)
This stores value according to the key.
key: event type
Get (key)
This retrieves the value of the key.
Distributed hash-table (DHT) over GPSR
GPSR
Strongly geographic routing algorithm

7. Related Work Conceptions— Geographic Hash Table (GHT) (key)
Distributed Hash Table
(DHT)
Location
Event
peer-to-peer lookup algorithm
Temperature>50℃
GPSR
Home node for this event

8. Related Work Distributed hash-table (DHT) over GPSR Put (type, valuec)
Key: type c
Get (type) e b
Valuec
sink

9. Related Work Disadvantages of GHT Motivation of this paper
Rendezvous point
Requirement for location accuracy
Not enough robust to the topology changes caused by mobility.
Motivation of this paper
High mobility environment
More robust to the topology changes caused by mobility.

10. Rendezvous Regions (RR) Architecture
Data model
Resource discovery
Lookup operation
Data storage
Insertion operation
Ratio between lookups and insertions
Large LIR (Lookup-to-Insertion)
Application
Users and object tracking
Database querying in sensor networks

11. Rendezvous Regions (RR) Architecture
Rendezvous Regions Basic conception
Using a rendezvous region instead of a rendezvous point.
Robustness for mobility.
Relaxing the requirements for exact geographic information.
A set of events
A set of events
Rendezvous point
Rendezvous region

12. Rendezvous Regions (RR) Architecture
Assumptions
The network space is divided into rectangular equal-size regions, where the size of the region is set based on the radio range and how many hops we want the region to cover.
Each node has a localization mechanism to detect its approximate geographic location and accordingly its region.
The network is connected and each region has nodes in it.

13. Rendezvous Regions (RR) Architecture
Design overview
KSeti  RRi
RR1
RR2
RR3
RR6
RR5
RR4
RR7
RR8
RR9
Events
(keys)
Distributed Hash Table
(DHT)
Server election
Problem
Region
(RRi)

14. Rendezvous Regions (RR) Architecture
Design overview
Inter-region routing scheme
The RR scheme can built on top of any routing protocol that can route packets toward geographic regions.
The only requirement of the routing protocol is to maintain approximate geographic information.
RRi
RRj

15. Rendezvous Regions (RR) Architecture
Design overview
Intra-region routing scheme
Geocast—Send packets to all nodes in the region.
Anycast—Reach any node of a set of servers.
Unicast—Update data between servers
RRj

16. Rendezvous Regions (RR) Architecture
Design overview
Server election
Number of servers and storage overhead are tradeoff.
Servers are elected on-demand during insertions.
Geocast
RRj
ACK
insertion
Probability P
RRi
flooder

17. Rendezvous Regions (RR) Architecture
Design overview—Insertion/Lookup
Geocast
RR1
RR2
RR3
RR6
RR5
RR4
RR7
RR8
RR9
Anycast
flooder R
sink
RR1 KSet1
RR2 KSet2
……………
RRn KSetn
KSeti  RRi
flooder
insertion S

18. Rendezvous Regions (RR) Architecture
Design overview
Replication
Several servers inside the region store the key and data.
Robustness to server node failure.
RRj

19. Rendezvous Regions (RR) Architecture
Design overview
Mobility
Rendezvous region
Local movements of nodes and servers have negligible effect.
Robustness to mobility
RRj
Server election
Check its region periodically

20. Rendezvous Regions (RR) Architecture
Design overview
Failures
Server node failure
Server node mobility
Server election procedure
Insertion operation
Mobility
It is unlikely that independent reasonable failures will cause all servers to vanish.

21. Performance Evaluation
Simulator: NS-2
Number of Nodes: 100 ~ 400
Routing protocol: modified GPSR to route to regions instead of specific destinations.
Radio range: 60m ~ 120m
The rate of lookups is 2/s.
The number of retransmissions for both insertion and lookup is 3.
The periodic check interval: 20s

22. Performance Evaluation
Mobility update overhead—

23. Performance Evaluation
Lookups success rate—

24. Performance Evaluation
Lookups overhead—

25. Performance Evaluation
Success rate at low inaccuracy range—

26. Performance Evaluation
Success rate at high inaccuracy range—

27. Performance Evaluation
Total message overhead (LIR=10)—

28. Performance Evaluation
Hotspot message overhead (LIR=10)—

29. Conclusion
This paper presents the design and evaluation of RR, a scalable rendezvous-based architecture for wireless networks.
The simulation results show that RR is scalable to large number of nodes and is highly efficient, especially in applications with high lookup-to-insertion ratios.
In mobile networks, RR has a significant advantage over GHT with higher success rate and much lower overhead.
RR is more robust to location inaccuracy than GHT.