department of computer science, hkbu, hk international wic institute, bjut, china
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Examining Dynamic Trust Relationships in Autonomy-Oriented Partner Finding. Student ： Hongjun Qiu Supervisor ： Prof. Jiming Liu Aug. 31, 2009. Department of Computer Science, HKBU, HK International WIC Institute, BJUT, China. Partner Finding. - PowerPoint PPT PresentationTRANSCRIPT
Examining Dynamic Trust Relationships in
Autonomy-Oriented Partner Finding
Department of Computer Science, HKBU, HKInternational WIC Institute, BJUT, China
Student ： Hongjun Qiu
Supervisor ： Prof. Jiming Liu
Aug. 31, 2009
• Finding partners: to identify which can provide services as needed
– the limited abilities of entities.
• Partner finding in cloud computing
– The cloud: the Internet
– The servers need response to hundreds or thousands of requests of data storage, program running and so on per second.
– Each user can ask more than one servers to immediately do their tasks.
Partner Finding
The International WIC Institute, BJUT, China
References:[1] http://www.sciencemag.org/sciext/125th/[2] B. Hayes, cloud computing, Communication of the ACM, 51(7): 9-11, 2008.
[3] M. Greeger, CTO roundtable: Cloud computing, Communications of the ACM, 52(8): 50-56, 2009.
The Internet
The Internet
The Internet
Server
End user
Server
End user
• A solution of partner finding: dynamically measuring and changing trust relationships.
– Trust relationships: the beliefs that others will accomplish a request of assigned services at hand.
– Computing methods: based on recalling their past experiences
– Advantages: quickly identify partners for new requests.
Trust Relationships
The International WIC Institute, BJUT, China
References:[1] Jennifer. Golbeck, Weaving a web of trust, Science, 321(5896): 1640-1641, 2008.
[2] S. D. Kamvar, M. T. Schlosser and H. Garcia-Molina. The Eigentrust Algorithm for Reputation Management in P2P Networks. In: Proceedings of the 12th International Conference on World Wide Web (WWW’03). 2003, 640 – 651.
[3] eBay. http://www.eBay.com. 2003
Questions
The International WIC Institute, BJUT, China
• Goal: to determine whether the change of trust relationships will really make entities efficiently find partners
• Questions to be answered:
How do entities update their trust relationships?
What are the mechanisms for entities find partners?
What is the change of trust relationships in a distributed multi-entity network?
Will the efficiency of finding partners really get enhanced along with the change of trust relationships?
− Will entities find partners in a fewer time?
− Will found partners successfully provide services?
• Basic phenomena:– Entities prefer to interact with their trustees rather than
strangers.– Successful interactions strengthen trust relationships and vice
versa.
• Assumptions: – A dynamic trust network:
• Nodes: entities– fixed and limited abilities– Friendly and honestly
• Links: trust relationships
– Entities can find a partner to finish or transfer the whole request, which cannot be finished by themselves.
The Scenario We Study
The International WIC Institute, BJUT, China
• To model a dynamic trust network – Define the mechanisms for finding partners– Define the mechanisms for updating trust relationships
• To characterize the change of trust relationships – the structural characteristics of this network at different
moments
• To measure whether the efficiency of this network in finding partners changes along with the dynamics of trust relationships
Questions
The International WIC Institute, BJUT, China
A Dynamic Trust Network
Hongjun Qiu The International WIC Institute, BJUT, China
Entity Trust relationship
The Steps of Finding Partners
Hongjun Qiu The International WIC Institute, BJUT, China
a request
Matching: determine whether it can finish this request
1
Search and selection: find a partner to finish the whole request
2
Updating: the asker updates its trust relationships
3 feedbac
k
propagation
Entity
Trust relationship
Two ideas from AOC
Hongjun Qiu The International WIC Institute, BJUT, China
a request
Matching: determine whether it can finish this request
Search and selection: find a partner to finish the whole request
Updating: the asker updates its trust relationships
autonomy
Self-organizati
on
Autonomy-Oriented
Computing (AOC)
References:[1] Jiming Liu, Xiaolong Jin, Kwok Ching Tsui. Autonomy-Oriented Computing (AOC): Formulating Computational Systems With Autonomous Components ,
IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, Vol. 35, No. 6 (2005) 879-902
[2] Jiming Liu, Xiaolong Jin, Kwok Ching Tsui. Autonomy Oriented Computing–From Problem Solving to Complex Systems Modeling, Springer Series on Multiagent Systems, Artificial Societies, and Simulated Organizations Vol. 12,(2005)
• Basic idea: entities activate different behaviors in a probabilistic manner based on measuring their abilities, requests and trust relationships
• Search behaviors
– Neighbor-based search
– Recommendation-based search
– Random search: for new comers to this network
• Selection behaviors
– Trust-based select
– Random select
The Local Autonomy of Entities
Hongjun Qiu
)(. mi rsimREe
)(.1 mi rsimREe
)(. mi rsimREe
)(.1 mi rsimREe
1) The probability of activating each behavior is adaptive;
2) Entities mainly find partners from their trustees for the requests which are near to their abilities.
The cosine-based similarity degree
between the ability of this entity and this request
• Basic rules:
– change trust relationships based on the feedback from the latest partner of an entity.
– Strengthen trust relationships if the partner is more suitable for the latest request
• Operations
– Creating trust relationships if the partner is newly-found.
– Updating existing trust relationships if the partner is one of the past partners of this entity.
– Eliminating the trust relationships to its other past partners if their strength are less than a threshold.
Self-organizing Trust Relationships
• Introduced: a dynamic trust network
• Experiments:– To characterize the change of trust relationships by means of
observing the dynamic links of this network • Network structural characteristics
– To determine whether the efficiency of this network in finding partners gets enhanced by means of comparing the efficiency at different moments
• Without trust relationships,• With newly-generated trust relationships• With frequently-changed trust relationships
Experimental Objectives
• Given: – A trust network of 1000 entities, without links– Requests
• 100 fixed requests
• Basic process
1. For( cycle=0; cycle<1500; cycle++)2. For( i=0;i<100; i++)3. Stochastically submit the ith request to the network4. Find partners within given times to finish this request5. End for6. Stochastically submit one random request to the network7. Update trust relationships while finding partners for this request8. End for
Experimental Settings
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• To measure structural characteristics at different cycles– Network indegree/outdegree– Harmonic mean of average path length– Clustering coefficient
• To measure the efficiency of entities in finishing the same 100 requests at different cycles
– The accomplishment ratio– The average propagation step: the times entities find partners – The standard deviation of propagation step
Experimental Measurements
The International WIC Institute, BJUT, China
The Dynamics of the Network
Hongjun Qiu The International WIC Institute, BJUT, China
Cycle=0 Cycle=1500
The Dynamics of the Structure
Hongjun Qiu
0 500 1000 1500
0.0
0.5
1.0
1.5
2.0
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3.0
ne
two
rk in
de
gre
e/o
utd
eg
ree
cycle0 500 1000 1500
0.00
0.05
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HM
AP
L
cycle
0 500 1000 1500
0.000
0.005
0.010
0.015
clu
ste
rin
g c
oe
ffici
en
t
cycle
Results and discussions:
1. The values of network indegree (outdegree), harmonic mean of average path length, clustering coefficient increase rapidly at first and later change slightly.
2. Entities greatly change their trust relationships at first and then maintain parts of those relationships.
The Structural Emergence
Hongjun Qiu
Results and discussions:
1. Entities’ indegree (outdegree) approximately follow a power-law distribution since about the 16th cycle.
2. The process of self-organization makes the network quickly converge to be scale-free.
100 101 102
100
101
102
103
cycle=1 cycle=100 cycle=500 cycle=1000 cycle=1500
entit
y nu
mbe
r
outdegree
100 101 102
100
101
102
103
cycle=1 cycle=100 cycle=500 cycle=1000 cycle=1500
entit
y nu
mbe
r
indegree
The Change of the Efficiency
0 50 100 150
0.94
0.95
0.96
0.97
acc
om
plis
he
me
nt r
atio
10*cycles0 500 1000 1500
0.90
0.92
0.94
0.96
0.98
1.00
acco
mpl
ishm
ent r
atio
cycle
The accomplishment ratio in each cycle and each 10 cycles
0 500 1000 1500
30
40
50
60
ave
rag
e p
ropa
ga
tion
ste
p
cycle0 50 100 150
35
40
45
50
55
ave
rag
e pr
op
ag
atio
n s
tep
s
10*cycles
The average propagation step in each cycle and each 10 cycles
0 500 1000 1500
30
40
50
60
70
stan
dard
dev
iatio
n of
pro
paga
tion
step
cycles0 50 100 150
40
45
50
55
60
65
sta
nd
ard
de
via
tion
of p
rop
ag
atio
n s
tep
10*cycles
The standard deviation of propagation step in each cycle and each 10 cycles
Results and discussions:
1. The accomplishment ratio gradually increases.
2. The average value and standard deviation of propagation step gradually decrease.
3. In the later cycles, entities can more quickly find partners to provide services with a higher probability.
4. In the later cycles, entities have found their relatively partners and they are coupled together.
• Experimental results– The network quickly converges to be scale-free, no matter what
distribution the abilities follow;– Trust relationships are frequently changed at first and remain
stable later;– The efficiency is enhanced along with dynamic trust
relationships.
• Conclusions– Trust relationships are changed toward a certain state, in
which entities quickly find partners to successfully provide services.
– The ideas from AOC speed up the change of trust relationships.
Concluding Remarks
Thank You! Thank You!