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Non‐inferior Nash strategies for routing control in parallel‐link communication networks
Author(s) -
Liu Yong,
Simaan Marwan A.
Publication year - 2005
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.708
Subject(s) - computer science , nash equilibrium , routing (electronic design automation) , node (physics) , context (archaeology) , game theory , control (management) , operations research , computer network , distributed computing , mathematical optimization , artificial intelligence , microeconomics , paleontology , mathematics , structural engineering , engineering , economics , biology
We consider a routing control problem of two‐node parallel‐link communication network shared by competitive teams of users. Each team has various types of entities (traffics or jobs) to be routed on the network. The users in each team cooperate for the benefit of their team so as to achieve optimal routing over network links. The teams, on the other hand, compete among themselves for the network resources and each has an objective function that relates to the overall performance of the network. For each team, there is a centralized decision‐maker, called the team leader or manager, who coordinates the routing strategies among all entities in his team. A game theoretic approach to deal with both cooperation within each team and competition among the teams, called the Non‐inferior Nash strategy, is introduced. Considering the roles of a group manager in this context, the concept of a Non‐inferior Nash strategy with a team leader is introduced. This multi‐team solution provides a new framework for analysing hierarchically controlled systems so as to address complicated coordination problems among the various users. This strategy is applied to derive the optimal routing policies for all users in the network. It is shown that Non‐inferior Nash strategies with a team leader is effective in improving the overall network performance. Various types of other strategies such as team optimization and Nash strategies are also discussed for the purpose of comparison. Copyright © 2005 John Wiley & Sons, Ltd.