1. Context Caching using Neighbor Graphs for Fast Handoffs in a Wireless Network Arunesh Mishra Min-ho Shin William A. Arbaugh Computer Science Department University of Maryland
Publication：INFOCOM
Date ：March 2004
On page ：351 ~ 361
Reference ：19
by Xinchang
2007/1/12

2. Outline Introduction Related Work Context Transfer protocol IAPP
Handoff Concepts
Neighbor Graph
Proactive Caching Algorithm
Performance Analysis
Experiment
Simulation
Conclusion
Roam 即為 paper 所說的 discrete mobility

3. Introduction Wireless Network mobility：
discrete mobility (like roam)
continuous mobility (like seamless handoff)
Voice and Multimedia are usual in continuous mobility
Total latency(L2 + L3) of handoff must be fast (< 50 ms)
Unfortunately ,the most Wi-Fi network Not achieve this Goal !!
How to reduce handoff latency ??
proactive context caching mechanism base on NG
Only Layer 2 latency approximately to 90% of all, exceeds 100ms
Latency of Handovers
the time between :
the last moment where the MN can receive and send packets through the old AR
the first moment where MN can receive and send packets through the new AR.
This Paper want to improve reassociation latency

4. Relate Work Context Transfer Topology algorithm
R. Koodli and C.E. Perkins,
“Fast Handover and Context Relocation in Mobile Networks”
M. Nakhjiri, C. Perkins, and R. Koodli,
“Context Transfer Protocol,”
Topology algorithm
Sangheon Pack and Yanghee Choi.
“Fast Inter-AP Handoff using Predictive-Authentication Scheme in a Public Wireless LAN,”
“Pre-Authenticated Fast Handoff in a Public Wireless LAN based on IEEE 802.1x Model,”
S. Capkun, Levente Buttyan, and Jean-Pierre Hubaux,
“Self-Organized Public-Key Management for MANET”
Radia Perlman, “An algorithm for distributed computation of a spanningtreein an extended lan,”

5. Context Transfer protocol
Context Transfer protocol (CXTP)
enable authorized context transfer
Why need to perform Context transfer between APs ??
support Node mobility can operate with minimal disruption
provide an interoperable solution to support L2 radio access
Context Transfer takes place when an event Trigger
pAR transfer the context
nAR request the context
MN send a message to AR to transfer context
What informations of Context ??
MN’s IP address
QoS , security , header compression,AAA information
Minimal disruption 即想要做到 seamless mobility
支援 IPv4 和 IPv6
在reassociation 時，the APs involved exchange station context message using IAPP
between APs
between AP and the RAUDIO server

6. IAPP increase overall handoff latency of their reactive fashion
IAPP play a significant role during handoff
Single Association Invariant
Secure transfer of state and context information between APs
Two types of interaction for Complete Context transfer
between APs
between AP and the RADIUS server
Two message will trigger IAPP
Association
Reassociation
IAPP increase overall handoff latency of their reactive fashion

7. Handoff Concepts Handoff Types Handoff Scenarios Horizontal Handoff
The handoff in homogeneous networks
Intrasystem Handoff
Vertical Handoff
The handoff between heterogeneous networks
Intersystem Handoff
Handoff Scenarios
L2 handoff
MN’s movement between APs belong to a common IP’subset
L3 handoff
MN’s movement between APs belong to a different domain

8. Handoff Scenarios

9. Handoff Procedure Handoff Procedure 1.discovery phase
2.reauthentication phase or
1.scan phase
2.authentication phase
3.reassociation phase
[Note]
講一下此圖為何為 reactive fashion??
說明 neighbor graph => proactive fashion

10. Neighbor Graph Definition Reassociation Relation
Two APs, said APi and APj ,
are said to have reassociation relationship
if it is possible for an STA to perform an reassociation through some path of motion between locationsof APi and APj
Association Pattern
Γ(c) for a client c is association pattern
as {(ap1, t1), (ap2, t2), , (apn, tn)}
where api is the AP which the client reassociates at time ti
AP Neighbor Graph
Define a undirected graph G = (V , E)
where V = {ap1, ap2, , apn} is the set of all APs
E = { e / e =(api, apj) if between api, apj have reassociation relation }

11. Neighbor Graph
Neighbor(api) = {apik : apik ∈ V, (api, apik ) ∈ E}

12. Neighbor Graph Generation of NG
automatically generate
by individual APs over times
two ways that APs can learn the edges in NG
AP receive reassociate request from STA
AP receive Move-Notify from another AP via IAPP
Each AP maintains edges locally (use LRU)
eliminate the outlier
[Situation]
client that goes into power saving mode, and wake up
in a different location to reassociation to any other AP
Timestamp base LRU would guarantee freshness of NG over time

13. Proactive Caching Algorithm
Proactive Caching & Locality of Mobility
Proactive Caching Algorithm
Function/Notation
Context(c)
Cach(apk)
Propagate_Context(api, c , apj)
Obtain_Context(apfrom, c , apto)
Remove_Context(apold, c , apnghbr)
Insert_Cache(apj , Context(c))
Who will perform this Algorithm ??
Cache replacement mechanism
LRU

14. Proactive Caching Algorithm

15. Performance Analysis Upper bound on the cache size
Clientlist(api) = the set of clients associated to api
Napi = | Neighbor(api) | = degree(api)
M = maximum number of clients associated to any AP

16. Performance Analysis Characterizing the Cache Misses
we expect 100% cache hit ratio for reassociation (before)
if following is hold：
NG has been learned edge
Cache size is unlimited
Two kinds of cache miss possible during a reassociation
Reassociation between non-neighbor APs
Context evicted by LRU replacement
This mean Cache at each AP is large enough according to eq (1)
A faster client spent less time at AP, have higher probablity of cache hit

17. Performance Analysis IAPP and Proactive Caching Cache-Notify
Cache-Response
Cache-Invalidate

18. Experiment Measure 114 reassociations in the Testbed
resulting average reassociations latency
Wireless Testbed
five AP at 3rd floor
four AP at 2nd floor
IAPP, neighbor graph, caching algorithm implement in driver
實驗: 實作 IAPP with Neighbor Graph

19. Experiment Experiment process Experiment Result Mobile unit
Two experiments
Experiment A
Experiment B
Experiment Result
cache-miss without an outlier：15.37ms
cache-miss with the outlier：23.58ms
cache-hit：1.7ms

20. Experiment
Experiment A

21. Simulation Simulation Objective Simulation Model and Assumptions
To observe the effect of cache size, the number of clients, the mobility of clients on the cache hit ratio
To observe the performance of caching with various NGs
Simulation Model and Assumptions
AP Neighbor Graph does not change during the simulation
Correctness and completeness of the Neighbor Graphs
Initial User-AP distribution
Roaming Model
User Mobility
roaming model => (a) (b) (c)
user mobility => mobility index

22. Simulation Simulation Environment Simulation Result
random and connected NG
with 10, 20, 50 and 100 vertices
Duration of the Simulation
The simulation runs for one million reassociation events
Simulation Result
Mobility Improves Proactive Caching Performance
Effect of Cache Size and Client Mobility on Hit Ratio
Effect of Cache Size and Number of Users on Hit Ratio
15 % 的 cache size 就可以讓 hit ratio 達到 98%

23. Simulation

24. Simulation

25. Simulation
In Fig. 11, We find 15% Cache Size is sufficient for a hit ratio of 98%

26. Conclusion
Introduce a novel, efficient and dynamic data structure, Neighbor Graph(NG)
NG, which capture the topology of a wireless network by automously monitoring Network
NG can also used to eliminate the expensive scanning operation for faster MAC handoff
Implement the proactive caching algorithm base on NG for faster wireless handoff
In Simulation, find that cache size plays an important role in the performance of algorithm