Encyclopedia of Wireless Networks

Living Edition
| Editors: Xuemin (Sherman) Shen, Xiaodong Lin, Kuan Zhang

Efficiency and Pareto Optimality

  • Xiaowen Gong
  • Lei Yang
  • Xu Chen
  • Junshan Zhang
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-32903-1_23-1

Synonyms

Definitions

An economic system is efficient if the resource production and allocation maximizes the total payoff of all agents in the system. More generally, a system is efficient if the system state maximizes a desired performance metric (such as the total utility of all entities in the system) given the inputs to the system.

An economic system is Pareto-optimal if there does not exist alternative resource production and allocation that improves at least one agent’s payoff without reducing any agent’s payoff. More generally, a system is Pareto-optimal if there does not exist an alternative system state that makes at least one preference metric (such as some entity’s utility) better off without making any preference metric worse off.

Historical Background

The concept of Pareto efficiency is named after Vilfredo Pareto who was an Italian engineer and economist. He used the concept in his studies of economic efficiency and...

This is a preview of subscription content, log in to check access.

References

  1. Beresford A, Stajano F (2003) Location privacy in pervasive computing. In: IEEE pervasive computing 2003CrossRefGoogle Scholar
  2. Boyd S, Vandenberghe L (2004) Convex optimization. Cambridge University PressGoogle Scholar
  3. Chen X, Huang J (2013) Database-assisted distributed spectrum sharing. IEEE J Sel Areas Commun 31(11):2349–2361CrossRefGoogle Scholar
  4. Chen M, Liew S, Shao Z, Kai C (2010) Markov approximation for combinatorial network optimization. In: INFOCOM, 2010 proceedings IEEE. IEEE, pp 1–9Google Scholar
  5. Chen X, Gong X, Yang L, Zhang J (2016) Exploiting social tie structure for cooperative wireless networking: a social group utility maximization framework. IEEE/ACM Trans Netw 24(6):3593–3606CrossRefGoogle Scholar
  6. FCC (September 23, 2010) Second memorandum opinion and orderGoogle Scholar
  7. Freudiger J, Manshaei MH, Hubaux JP, Parkes DC (2009) On non-cooperative location privacy: a game-theoretic analysis. In: ACM CCS 2009Google Scholar
  8. Gong X, Chen X, Xing K, Shin DH, Zhang M, Zhang J (2017) From social group utility maximization to personalized location privacy in mobile networks. IEEE/ACM Trans Netw 25(3):1703–1716CrossRefGoogle Scholar
  9. Hindriks J, Myles GD (2013) Intermediate public economics. MIT Press, CambridgeGoogle Scholar
  10. Kauffmann B, Baccelli F, Chaintreau A, Mhatre V, Papagiannaki K, Diot C (2007) Measurement-based self organization of interfering 802.11 wireless access networks. In: 26th IEEE international conference on computer communications (INFOCOM 2007). IEEE, pp 1451–1459Google Scholar
  11. Mas-Colell A, Whinston MD, Green JR et al (1995) Microeconomic theory, vol 1. Oxford University Press, New YorkzbMATHGoogle Scholar
  12. Osborne M, Rubinstein A (1994) A course in game theory. MIT Press, LondonzbMATHGoogle Scholar
  13. Yang L, Kim H, Zhang J, Chiang M, Tan CW (2013) Pricing-based decentralized spectrum access control in cognitive radio networks. IEEE/ACM Trans Netw (TON) 21(2):522–535CrossRefGoogle Scholar
  14. Young H (2001) Individual strategy and social structure: an evolutionary theory of institutions. Princeton University Press, PrincetonGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Xiaowen Gong
    • 1
  • Lei Yang
    • 2
  • Xu Chen
    • 3
  • Junshan Zhang
    • 4
  1. 1.Auburn UniversityAuburnUSA
  2. 2.University of Nevada RenoRenoUSA
  3. 3.Sun Yat-sen UniversityGuangzhouChina
  4. 4.Arizona State UniversityTempeUSA

Section editors and affiliations

  • Jianwei Huang
    • 1
  • Yuan Luo
  1. 1.Department of Information EngineeringThe Chinese University of Hong Kong, StainHong KongChina