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Data replication in geographically dispersed servers is an essential technique for reducing the user perceived access time in large -scale distributed computing systems . A majority of the conventional replica placement techniques lack scalability and solution quality . To counteract such issues , this thesis proposes a game theoretical replica placement framework , in which autonomous agents compete for the allocation or reallocation of replicas onto their representative servers in a self -managed fashion . Naturally , each agent's goal is to maximize its own benefit . However , the framework is designed to suppress individualism and to ensure system -wide optimization . Using this framework as an environment , several cooperative and non -cooperative low -complexity , flexible , and scalable game theoretical replica placement techniques are proposed , analytically investigated , and experimentally evaluated . Each of these techniques supports different game theoretical (pareto -optimality , catering to agents' interests , deliberate discrimination of allocation , budget balanced , pure Nash equilibrium , and Nash equilibrium ) and system (link distance , congestion control , minimization of communication cost , and memory optimization ) related properties . Using a detailed test -bed involving eighty various network topologies and two real -world access logs , each game theoretical technique is also extensively compared with conventional replica placement techniques , such as , greedy heuristics , branch -and -bound techniques and genetic algorithms . The experimental study confirms that in each case the proposed techniques outperform other conventional methods . The results can be summarized in four ways : 1 ) The number of replicas in a system self -adjusts to reflect the ratio of the number of reads versus writes access ; 2 ) Performance is improved by replicating objects to the servers based on the locality of reference ; 3 ) Replica allocations are made in a fast algorithmic turn -around time ; 4 ) The complexity of the data replication problem is decreased by multifold . |
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