Tối ưu hóa viễn thông và thích nghi Kỹ thuật Heuristic P16

Today an ever increasing number of social and financial services can be provided over data networks. Individuals and businesses alike initiate and complete a large number of commercial transactions over the Internet or other specially constructed networks. Home banking, home shopping, video on demand, buying and selling of stocks and other financial securities can now be undertaken from almost any part of the world where an access to a local network can be achieved.
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Tối ưu hóa viễn thông và thích nghi Kỹ thuật Heuristic P16 Telecommunications Optimization: Heuristic and Adaptive Techniques. Edited by David W. Corne, Martin J. Oates, George D. Smith Copyright © 2000 John Wiley & Sons Ltd ISBNs: 0-471-98855-3 (Hardback); 0-470-84163X (Electronic)16Evolutionary Game TheoryApplied to Service Selection andNetwork EcologiesSverrir Olafsson16.1 IntroductionToday an ever increasing number of social and financial services can be provided over datanetworks. Individuals and businesses alike initiate and complete a large number ofcommercial transactions over the Internet or other specially constructed networks. Homebanking, home shopping, video on demand, buying and selling of stocks and other financialsecurities can now be undertaken from almost any part of the world where an access to alocal network can be achieved. New services are being offered all the time, and whensuccessful face an immediate competition from a large number of companies andindividuals with sufficient knowledge base, financial resources and access to the Internet. The increasing competition in service provision on the Internet provides individuals withan increasing choice, lower prices and previously unknown opportunities. But this alsocreates greater difficulties in making the right choices at the right time. The problem is notonly that of making the right choice, but also to acquire the necessary information so thateducated decisions can be made. Clearly, all network users or agents browsing the networkcan in principle acquire a complete information on all competing network services.However, acquiring complete information can be excessively expensive, relative to the onlymarginal improvements it may provide the holder of that information. The problemtherefore is to strike the balance between sacrificing information and the penalties one hasto pay for making decisions when equipped with only limited information.Telecommunications Optimization: Heuristic and Adaptive Techniques, edited by D. Corne, M.J. Oates and G.D. Smith© 2000 John Wiley & Sons, Ltd284 Telecommunications Optimization: Heuristic and Adaptive Techniques Also, the increasing speed with which services are introduced requires an increasingcomplexity of networks as well as the need for efficient distributed control mechanism. Thesupply of a multitude of continuously changing and interacting services requires thesimultaneous or sequential use of many network resources, possibly distributed overlocations large geographical distances apart. That requires reliable algorithms, whichidentify the required sources and support their efficient utilization. It is in principle possibleto burden every network and network user with the communication overheads, which makeknowledge of all network resources available. Such an overhead, on the other hand, wouldseverely limit the processing capacity of the network and be very time consuming for theuser. In principle, the most appropriate resource can be found for the execution of everytask, but the computational expense and the time required for achieving that might wellexceed the benefits from using that resource as compared with another, slightly lesseffective one. This problem is of a very general nature and relates to a number ofoptimization problems, as well as many management issues where performance has alwaysto be compared with the cost of achieving it. As a result of these problems soft, biologically based, approaches to resourcemanagement have become increasingly popular in recent years (Huberman, 1988).Predominantly these approaches have been based on a neural network approach and variousimplementations of genetic algorithms. For example, neural networks have been developedfor resource allocation (Bousono and Manning, 1995) and for the switching of networktraffic (Amin et al., 1994). Genetic algorithms have been applied to resource allocation(Oates and Corne, 1998b), routing or file management in distributed systems (Bilchev andOlafsson, 1998a), just to mention a few. In this paper we take a different approach, based onevolutionary game theory. Game theoretic approach to network utilisation has beenconsidered by a number of authors in recent years (Olafsson, 1995). Common to most ofthese approaches is the notion of an agent utility, which dictates the dynamics of theallocation of service requirements to network resources. The system performance resultingfrom this dynamic therefore depends strongly on the selected agent utility function, i.e. withwhat rationality criteria the agents have been programmed. A potential problem with agent based approaches is the fact that agents sometimesconsider only their own demand for processing requirements. Where each agent is guidedonly by its own interests, the performance of the whole system can still be very low. In viewof this, it seems essential to design systems whose agents are concerned, not only for theirown service requirements, but also those of the whole community of agents. This mayrequires some co-operation between agents, which is aimed at improving the meanefficiency of the whole system. Occasionally, this can be detrimental to the interests of afew agents, but the whole community of agents is likely to benefit from the co-operation. Infact, this problem is very similar to that of the prisoners dilemma (Axelrod, 1984) or thetragedy of the commons (Hardin, 1984), which are representative for many competitivesituations in areas as diverse as, politics, commerce, marketing and real biological systems. The approach taken here is based on evolutionary game theory (Maynard Sm ...