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Incentive-based resource allocation and control for large-scale computing services

Posted on:2010-05-31Degree:Ph.DType:Dissertation
University:Stanford UniversityCandidate:Yolken, Benjamin HenryFull Text:PDF
GTID:1448390002977437Subject:Operations Research
Abstract/Summary:
Computing services, loosely defined as the allocation and management of computer resources by providers for their clients, have received much recent attention in the IT world. This framework potentially allows participants to increase revenues and reduce costs, but at the same time introduces the need for novel approaches to resource allocation and control. First, the systems supporting these services are large, distributed, and heterogeneous, often to an extent well beyond that of traditional IT infrastructure. Second, participants can be expected to behave strategically; any controls must consider user incentives and, if possible, align these with the optimality of the system as a whole.;In this dissertation, we discuss four distinct models which address the issues above in service computing environments. Each focuses on an allocation or control problem within a specific layer of the latter: (1) high-level investment decisions among competing service providers, (2) pricing resources and allocating them among clients, (3) low-level, power aware hardware scheduling, and (4) transmission power control for wireless devices. Although the specific assumptions and functional forms in each differ, the controls in each case are determined by the actions of selfish, heterogeneous users. In all but the third model, these users anticipate the effect of their decisions on the system outcome, a framework ideal for game theoretic analysis. By leveraging the theory of the latter, we are able to characterize the properties of the expected equilibria, as well as prove existence, uniqueness, convergence, and other types of results. The third model does not use game theory directly but instead maps the latter strategies into low-level hardware schedules, thereby implementing the policies determined in other layers. Overall, we thus develop incentive-aligned controls for resources in service computing environments, procedures which have many desirable properties but, at the same time, require little centralized knowledge or authority.
Keywords/Search Tags:Computing, Service, Allocation
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