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Cooperation in
heterogeneous networks
Ryoichi Shinkuma
Graduate School of Informatics
Kyoto University, Japan
April 2019
1
Drones (Micro UAVs)
Trend: diversification of connected `things'
2
Reserved by Ryoichi Shinkuma
Connected things
Before 2000, only
servers and PCs are
connected
After 2005, many kinds
of smart devices are
connected
In coming years,
everything will be
connected
My research
started in 2003
2000 Feature
phones
Servers PCs
2010 IoT
2005
2015
2020
My research started
Diversified
Smartphones
Wearable
devices
Connected cars
Benefits of heterogeneous networks
Reserved by Ryoichi Shinkuma
3
Diversity of environment Diversity of connection
Diversity of resources Diversity of data
Many nodes for
cooperation,
congested
network
Few nodes for
cooperation,
no congestion
Powerful
computing
resource
High-speed
communication
resource
Wide-range but
low-speed
connection
High-speed but
short-range
connection
Collect and
provide bird's-
eye view and
wide-range data
Collect and
provide fine-
grained data in
dedicated area
Cooperation in homogenous network
One entity can control all
nodes
How to optimize?
e.g. Maximum flow problem
s t
b
a
e
g
f
c
d
4
Reserved by Ryoichi Shinkuma
Maximize flow from s to t
Definition of `heterogeneous'
More than just variety of
parameters:
• Two or more kinds of
nodes
• Each node owned and
controlled by different
entities
5
Reserved by Ryoichi Shinkuma
Much more difficult
to optimize
than homogeneous
networks
Research questions
Communications
Engineering
Mathematical
Informatics
Economics
Reserved by Ryoichi Shinkuma
6
How to...
 define cooperative actions
 model cost caused by
cooperation
 model utility brought about
by cooperation
 model individual decision-
making and behavior
 design mechanism for
incentivizing nodes
 create means of giving
incentive rewards
How to solve the problem of cooperation in
heterogeneous networks
Conventional approach: simplify and introduce game theory [Han'12]
My approach: understand and create a new model [Shinkuma'12]
Incentive reward
allocated to
contribution, Ri
Utility brought
about by
cooperation, Ui
Cost caused by
cooperation, Ci
Ui + Ri > Ci ?
Yes
No
No motivation
Incentive
mechanism S Ui
S Ri
(< S Ui – Profit)
7
Reserved by Ryoichi Shinkuma
[(Invitied) R. Shinkuma and K. Yamori, ``A Dynamic Traffic Control Technique in Communication Networks Using Incentive Engineering,''
IEICE Technical report, CQ2012-69, Nov. 2012 (in Japanese)
Actions for cooperation in heterogeneous
networks
Sharing
• Communication resources (bandwidth) and energy resources to
forward other's data
• Computing resources and energy resources to process other's task
Delaying
requests from peak time to off-peak time
Moving
to location where more efficient resource is available
8
Reserved by Ryoichi Shinkuma
[H. Kubo, R. Shinkuma, and T. Takahashi, IEICE Trans. Inf. & Syst., vol. E93-D, no. 12, pp. 3260-3268, Dec. 2010]
[M. Yoshino, R. Shinkuma, and T. Takahashi, Proc. IEEE GLOBECOM 2008, vol. 12, pp. 5042-5046, Dec. 2008]
Modeling of cost caused by cooperative
forwarding
Modeling of cost
• Forwarding data for others causes
battery cost
• Psychological factor related to
social relationship?
Experimental evaluation
• Emulator developed by our lab
• 58 subjects
• Results of qR :
• Friends: 41.2%
• Friends of friends: 55.4%
• Strangers: 60.8%
9
Reserved by Ryoichi Shinkuma
Relay network
Social network
Differentiate social relationships (1)
• Prior work: only friends,
friends of friends, and
strangers
• My work: more
differentiated social
relationship metrics for
cooperative forwarding
Reserved by Ryoichi Shinkuma
10
[Y. Inagaki and R. Shinkuma, "Shared-Resource Management Using Online Social-Relationship Metric for Altruistic Device Sharing,''
IEEE Access, vol. 6, pp. 23191-23201, April 2018]
Adamic-Adar Index
Katz Index
( kz: no. of degree of z )
( Al
xy: number of paths of length l between x and y )
Extract from structure
of social networks,
validated by experiment
using Stanford
Brightkite dataset
Differentiate social relationship (2)
• Prior work: only pre-
determined social
relationships
• My work: more dynamically
changed social
relationships
Reserved by Ryoichi Shinkuma
11
[R. Shinkuma, Y. Sugimoto, and Y. Inagaki, "Weighted network graph for interpersonal communication with temporal regularity,''
Springer Soft Computing, Nov. 2017]
Convert time
domain
to frequency
domain
per 1 day
per 10 minExtract from intercontact
logs like message
exchanges, Bluetooth
connections, validated by
experiment using MIT
Friends-and-Family dataset
Incentive mechanism for cooperative forwarding
Bandwidth Exchange (BE) in
wireless relay network:
Giving a portion of radio frequency
band when asking for forwarding
Nash Bargaining Solution (NBS)
based incentive mechanism
• Maximize product of utilities
• Ensure efficiency and fairness
Problem formulation
• ui: utility of node i
• Pij: relay-request probability from i to j
• lx: probability of choosing strategy x
• Pc
ij: cooperation probability of i for j
12
Reserved by Ryoichi Shinkuma
Incentive mechanism for cooperative forwarding (2)
Geometricmeanofthroughput:
13
Reserved by Ryoichi Shinkuma
 Decision-making model
• NBS: long-term profit
• Myopic: short-term profit
• Altruistic: always cooperate
 Numerical evaluation
• Rayleigh fading channel
• Orthogonal frequency division multiplexing
(OFDM) system
• Results: NBS achieves best fair throughput
NBS saves 4 times transmission
power
Means of giving incentive reward for cooperative
forwarding
• Monetary payment
• Payment by quality of service (QoS)
• Radio frequency band in physical layer [Zhang, 2010]
• TXOP in data link layer [Nishio, 2012]
• Packet queuing in network layer [Liu, 2015]
• Flow rate in transport layer [Nishio, 2011]
• Content delivery in application layer [Maki, 2012]
Physical
Data link
Network
Transport
Session
Presentation
Application
[D. Zhang, R. Shinkuma, and N. Mandayam, IEEE Trans. Wireless Communications, vol. 9, no. 6, pp. 2055-2065, Jun. 2010]
[T. Nishio, R. Shinkuma, T. Takahashi, and N. Mandayam, IEICE Trans. Commun., vol. E95-B, no. 6, pp. 1944-1952, Jun. 2012]
[W. Liu, R. Hu, R. Shinkuma, and T. Takahashi, IEICE Trans. Commun., vol. E98.B, no. 11, pp. 2141-2150, Nov. 2015]
[T. Nishio, R. Shinkuma, T. Takahashi, and G. Hasegawa, EURASIP Journal on Wireless Communications and Networking, vol. 2011,
no. 1, Aug. 2011]
[N. Maki, T. Nishio, R. Shinkuma, T. Mori, N. Kamiyama, R. Kawahara, and T. Takahashi, IEICE Trans. Inf. & Syst., vol. E95-D, no. 12,
pp. 2860-2869, Dec. 2012] 14
Reserved by Ryoichi Shinkuma
Modeling of utility brought about by cooperative
computing-resource sharing
 Sharing computing resources via
networks
• Utility
• Problem formulation
Is it different from forwarding?
 Modeling of utility
• Service consists of multiple tasks;
task-oriented cooperation might
cause inefficient cooperation
=> Service-oriented cooperation is
proposed
15
Reserved by Ryoichi Shinkuma
Computing-resource sharing network
Modeling of utility brought about by cooperative
computing-resource sharing (2)
Results
• Proposed (service-oriented)
cooperation reduced latency
up to upper-bound level
• Proposed model achieved best
fairness
16
Reserved by Ryoichi Shinkuma
Problem formulation
• ti: service start time with cooperation
• t'i: service start time w/o cooperation
• Tl
i: processing time for task l of node i
• Ei: energy consumption with
cooperation
• E'i: energy consumption w/o
cooperation
(Reduced service latency)
Delaying as cooperative action
Delaying requests from peak time
to off-peak time
Delaying should not cause another
peak traffic
[R. Shinkuma, Y. Tanaka, Y. Yamada, E. Takahashi, and T. Onishi, Elsevier Computer Networks, vol. 137, pp. 17-26, Jun. 2018]
[Y. Yamada, R. Shinkuma, T. Iwai, T. Onishi, T. Nobukiyo, and K. Satoda, vol. 146, pp. 115-124, Dec. 2018] 17
Reserved by Ryoichi Shinkuma
(Current traffic) (Predicted traffic
after delaying)
Delaying as cooperative action (2)
Modeling of decision making
and behavior
• Random utility model: statistic
model for making binary
decisions (delay or not)
Results
• Reproduced traffic, estimated from
signal quality measured in
Kawasaki-city, Kanagawa, Japan
• Off-peak is reduced by cooperation
instead of forcing nodes to delay
18
Reserved by Ryoichi Shinkuma
(Expected utility by choosing `Yes')
(Expected utility by choosing `No')
(Probability of choosing `Yes')
TA: sensitivity
of nodes to
delay
Moving as cooperative action
Moving to location where more efficient resource is available:
[T. Kangawa, M. Yoshino, R. Shinkuna, and T. Takahashi, IEICE Trans. Communications, vol. J90-B, no. 12, pp. 1263-1273, Dec. 2007 (in Japanese)]
[M. Yoshino, K. Sato, R. Shinkuma, and T. Takahashi, IEICE Trans. Commun., vol. E91-B, no. 10, pp. 3132-3140, Oct. 2008]
[T. Kakehi, R. Shinkuma, T. Murase, G. Motoyoshi, K. Yamori, and T. Takahashi, IEICE Trans. Commun., vol. E95-B, no. 6, pp. 1965-1973, Jun. 2012] 19
Reserved by Ryoichi Shinkuma
Conclusion
Recommended design of cooperation mechanism in heterogeneous
networks
1. Cooperative actions:
Sharing resources, delaying, moving
2. Cost model:
Psychological factor related to social relationships
3. Utility model:
Service-oriented
4. Incentive mechanism:
NBS-based
5. Decision-making:
stochastic models like random utility theory are ready-to-use but not
enough to reflect individual characteristics
=> further research is needed
Reserved by Ryoichi Shinkuma
20

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Research summary of R. Shinkuma, Kyoto University, Japan

  • 1. Cooperation in heterogeneous networks Ryoichi Shinkuma Graduate School of Informatics Kyoto University, Japan April 2019 1
  • 2. Drones (Micro UAVs) Trend: diversification of connected `things' 2 Reserved by Ryoichi Shinkuma Connected things Before 2000, only servers and PCs are connected After 2005, many kinds of smart devices are connected In coming years, everything will be connected My research started in 2003 2000 Feature phones Servers PCs 2010 IoT 2005 2015 2020 My research started Diversified Smartphones Wearable devices Connected cars
  • 3. Benefits of heterogeneous networks Reserved by Ryoichi Shinkuma 3 Diversity of environment Diversity of connection Diversity of resources Diversity of data Many nodes for cooperation, congested network Few nodes for cooperation, no congestion Powerful computing resource High-speed communication resource Wide-range but low-speed connection High-speed but short-range connection Collect and provide bird's- eye view and wide-range data Collect and provide fine- grained data in dedicated area
  • 4. Cooperation in homogenous network One entity can control all nodes How to optimize? e.g. Maximum flow problem s t b a e g f c d 4 Reserved by Ryoichi Shinkuma Maximize flow from s to t
  • 5. Definition of `heterogeneous' More than just variety of parameters: • Two or more kinds of nodes • Each node owned and controlled by different entities 5 Reserved by Ryoichi Shinkuma Much more difficult to optimize than homogeneous networks
  • 6. Research questions Communications Engineering Mathematical Informatics Economics Reserved by Ryoichi Shinkuma 6 How to...  define cooperative actions  model cost caused by cooperation  model utility brought about by cooperation  model individual decision- making and behavior  design mechanism for incentivizing nodes  create means of giving incentive rewards
  • 7. How to solve the problem of cooperation in heterogeneous networks Conventional approach: simplify and introduce game theory [Han'12] My approach: understand and create a new model [Shinkuma'12] Incentive reward allocated to contribution, Ri Utility brought about by cooperation, Ui Cost caused by cooperation, Ci Ui + Ri > Ci ? Yes No No motivation Incentive mechanism S Ui S Ri (< S Ui – Profit) 7 Reserved by Ryoichi Shinkuma [(Invitied) R. Shinkuma and K. Yamori, ``A Dynamic Traffic Control Technique in Communication Networks Using Incentive Engineering,'' IEICE Technical report, CQ2012-69, Nov. 2012 (in Japanese)
  • 8. Actions for cooperation in heterogeneous networks Sharing • Communication resources (bandwidth) and energy resources to forward other's data • Computing resources and energy resources to process other's task Delaying requests from peak time to off-peak time Moving to location where more efficient resource is available 8 Reserved by Ryoichi Shinkuma
  • 9. [H. Kubo, R. Shinkuma, and T. Takahashi, IEICE Trans. Inf. & Syst., vol. E93-D, no. 12, pp. 3260-3268, Dec. 2010] [M. Yoshino, R. Shinkuma, and T. Takahashi, Proc. IEEE GLOBECOM 2008, vol. 12, pp. 5042-5046, Dec. 2008] Modeling of cost caused by cooperative forwarding Modeling of cost • Forwarding data for others causes battery cost • Psychological factor related to social relationship? Experimental evaluation • Emulator developed by our lab • 58 subjects • Results of qR : • Friends: 41.2% • Friends of friends: 55.4% • Strangers: 60.8% 9 Reserved by Ryoichi Shinkuma Relay network Social network
  • 10. Differentiate social relationships (1) • Prior work: only friends, friends of friends, and strangers • My work: more differentiated social relationship metrics for cooperative forwarding Reserved by Ryoichi Shinkuma 10 [Y. Inagaki and R. Shinkuma, "Shared-Resource Management Using Online Social-Relationship Metric for Altruistic Device Sharing,'' IEEE Access, vol. 6, pp. 23191-23201, April 2018] Adamic-Adar Index Katz Index ( kz: no. of degree of z ) ( Al xy: number of paths of length l between x and y ) Extract from structure of social networks, validated by experiment using Stanford Brightkite dataset
  • 11. Differentiate social relationship (2) • Prior work: only pre- determined social relationships • My work: more dynamically changed social relationships Reserved by Ryoichi Shinkuma 11 [R. Shinkuma, Y. Sugimoto, and Y. Inagaki, "Weighted network graph for interpersonal communication with temporal regularity,'' Springer Soft Computing, Nov. 2017] Convert time domain to frequency domain per 1 day per 10 minExtract from intercontact logs like message exchanges, Bluetooth connections, validated by experiment using MIT Friends-and-Family dataset
  • 12. Incentive mechanism for cooperative forwarding Bandwidth Exchange (BE) in wireless relay network: Giving a portion of radio frequency band when asking for forwarding Nash Bargaining Solution (NBS) based incentive mechanism • Maximize product of utilities • Ensure efficiency and fairness Problem formulation • ui: utility of node i • Pij: relay-request probability from i to j • lx: probability of choosing strategy x • Pc ij: cooperation probability of i for j 12 Reserved by Ryoichi Shinkuma
  • 13. Incentive mechanism for cooperative forwarding (2) Geometricmeanofthroughput: 13 Reserved by Ryoichi Shinkuma  Decision-making model • NBS: long-term profit • Myopic: short-term profit • Altruistic: always cooperate  Numerical evaluation • Rayleigh fading channel • Orthogonal frequency division multiplexing (OFDM) system • Results: NBS achieves best fair throughput NBS saves 4 times transmission power
  • 14. Means of giving incentive reward for cooperative forwarding • Monetary payment • Payment by quality of service (QoS) • Radio frequency band in physical layer [Zhang, 2010] • TXOP in data link layer [Nishio, 2012] • Packet queuing in network layer [Liu, 2015] • Flow rate in transport layer [Nishio, 2011] • Content delivery in application layer [Maki, 2012] Physical Data link Network Transport Session Presentation Application [D. Zhang, R. Shinkuma, and N. Mandayam, IEEE Trans. Wireless Communications, vol. 9, no. 6, pp. 2055-2065, Jun. 2010] [T. Nishio, R. Shinkuma, T. Takahashi, and N. Mandayam, IEICE Trans. Commun., vol. E95-B, no. 6, pp. 1944-1952, Jun. 2012] [W. Liu, R. Hu, R. Shinkuma, and T. Takahashi, IEICE Trans. Commun., vol. E98.B, no. 11, pp. 2141-2150, Nov. 2015] [T. Nishio, R. Shinkuma, T. Takahashi, and G. Hasegawa, EURASIP Journal on Wireless Communications and Networking, vol. 2011, no. 1, Aug. 2011] [N. Maki, T. Nishio, R. Shinkuma, T. Mori, N. Kamiyama, R. Kawahara, and T. Takahashi, IEICE Trans. Inf. & Syst., vol. E95-D, no. 12, pp. 2860-2869, Dec. 2012] 14 Reserved by Ryoichi Shinkuma
  • 15. Modeling of utility brought about by cooperative computing-resource sharing  Sharing computing resources via networks • Utility • Problem formulation Is it different from forwarding?  Modeling of utility • Service consists of multiple tasks; task-oriented cooperation might cause inefficient cooperation => Service-oriented cooperation is proposed 15 Reserved by Ryoichi Shinkuma Computing-resource sharing network
  • 16. Modeling of utility brought about by cooperative computing-resource sharing (2) Results • Proposed (service-oriented) cooperation reduced latency up to upper-bound level • Proposed model achieved best fairness 16 Reserved by Ryoichi Shinkuma Problem formulation • ti: service start time with cooperation • t'i: service start time w/o cooperation • Tl i: processing time for task l of node i • Ei: energy consumption with cooperation • E'i: energy consumption w/o cooperation (Reduced service latency)
  • 17. Delaying as cooperative action Delaying requests from peak time to off-peak time Delaying should not cause another peak traffic [R. Shinkuma, Y. Tanaka, Y. Yamada, E. Takahashi, and T. Onishi, Elsevier Computer Networks, vol. 137, pp. 17-26, Jun. 2018] [Y. Yamada, R. Shinkuma, T. Iwai, T. Onishi, T. Nobukiyo, and K. Satoda, vol. 146, pp. 115-124, Dec. 2018] 17 Reserved by Ryoichi Shinkuma (Current traffic) (Predicted traffic after delaying)
  • 18. Delaying as cooperative action (2) Modeling of decision making and behavior • Random utility model: statistic model for making binary decisions (delay or not) Results • Reproduced traffic, estimated from signal quality measured in Kawasaki-city, Kanagawa, Japan • Off-peak is reduced by cooperation instead of forcing nodes to delay 18 Reserved by Ryoichi Shinkuma (Expected utility by choosing `Yes') (Expected utility by choosing `No') (Probability of choosing `Yes') TA: sensitivity of nodes to delay
  • 19. Moving as cooperative action Moving to location where more efficient resource is available: [T. Kangawa, M. Yoshino, R. Shinkuna, and T. Takahashi, IEICE Trans. Communications, vol. J90-B, no. 12, pp. 1263-1273, Dec. 2007 (in Japanese)] [M. Yoshino, K. Sato, R. Shinkuma, and T. Takahashi, IEICE Trans. Commun., vol. E91-B, no. 10, pp. 3132-3140, Oct. 2008] [T. Kakehi, R. Shinkuma, T. Murase, G. Motoyoshi, K. Yamori, and T. Takahashi, IEICE Trans. Commun., vol. E95-B, no. 6, pp. 1965-1973, Jun. 2012] 19 Reserved by Ryoichi Shinkuma
  • 20. Conclusion Recommended design of cooperation mechanism in heterogeneous networks 1. Cooperative actions: Sharing resources, delaying, moving 2. Cost model: Psychological factor related to social relationships 3. Utility model: Service-oriented 4. Incentive mechanism: NBS-based 5. Decision-making: stochastic models like random utility theory are ready-to-use but not enough to reflect individual characteristics => further research is needed Reserved by Ryoichi Shinkuma 20

Editor's Notes

  1. Z. Han, D. Niyato, W. Saad, T. Başar, and A. Hjørungnes, ``Game theory in wireless and communication networks: theory, models, and applications,'' Cambridge university press, 2012
  2. Lambda 1, 2, 3, 4 corresponding to <n,c><c,c><c,n><n,n>