Title:
System Support for End-to-End Performance Management

dc.contributor.advisor Schwan, Karsten
dc.contributor.author Agarwala, Sandip en_US
dc.contributor.committeeMember Bolter, Jay D.
dc.contributor.committeeMember Grinter, Rebecca
dc.contributor.committeeMember Edwards, W. Keith
dc.contributor.committeeMember Kellogg, Wendy A.
dc.contributor.department Computing en_US
dc.date.accessioned 2007-08-16T17:42:35Z
dc.date.available 2007-08-16T17:42:35Z
dc.date.issued 2007-07-09 en_US
dc.description.abstract This dissertation introduces, implements, and evaluates the novel concept of "Service Paths", which are system-level abstractions that capture and describe the dynamic dependencies between the different components of a distributed enterprise application. Service paths are dynamic because they capture the natural interactions between application services dynamically composed to offer some desired end user functionality. Service paths are distributed because such sets of services run on networked machines in distributed enterprise data centers. Service paths cross multiple levels of abstraction because they link end user application components like web browsers with system services like http providing communications with embedded services like hardware-supported data encryption. Service paths are system-level abstractions that are created without end user, application, or middleware input, but despite these facts, they are able to capture application-relevant performance metrics, including end-to-end latencies for client requests and the contributions to these latencies from application-level processes and from software/hardware resources like protocol stacks or network devices. Beyond conceiving of service paths and demonstrating their utility, this thesis makes three concrete technical contributions. First, we propose a set of signal analysis techniques called ``E2Eprof' that identify the service paths taken by different request classes across a distributed IT infrastructure and the time spent in each such path. It uses a novel algorithm called ``pathmap' that computes the correlation between the message arrival and departure timestamps at each participating node and detect dependencies among them. A second contribution is a system-level monitoring toolkit called ``SysProf', which captures monitoring information at different levels of granularity, ranging from tracking the system-level activities triggered by a single system call, to capturing the client-server interactions associated with a service paths, to characterizing the server resources consumed by sets of clients or client behaviors. The third contribution of the thesis is a publish-subscribe based monitoring data delivery framework called ``QMON'. QMON offers high levels of predictability for service delivery and supports utility-aware monitoring while also able to differentiate between different levels of service for monitoring, corresponding to the different classes of SLAs maintained for applications. en_US
dc.description.degree Ph.D. en_US
dc.identifier.uri http://hdl.handle.net/1853/16171
dc.publisher Georgia Institute of Technology en_US
dc.subject End-to-end performance diagnosis and management en_US
dc.subject Enterprise systems en_US
dc.subject Autonomic computing en_US
dc.subject Pathmap en_US
dc.subject E2EProf en_US
dc.subject SysProf en_US
dc.subject QMON en_US
dc.subject Operating systems en_US
dc.subject Distributed systems en_US
dc.subject.lcsh Network performance (Telecommunication) en_US
dc.subject.lcsh End-user computing en_US
dc.subject.lcsh Information resources management en_US
dc.subject.lcsh Management information systems en_US
dc.title System Support for End-to-End Performance Management en_US
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Schwan, Karsten
local.contributor.corporatename College of Computing
relation.isAdvisorOfPublication a89a7e85-7f70-4eee-a49a-5090d7e88ce6
relation.isOrgUnitOfPublication c8892b3c-8db6-4b7b-a33a-1b67f7db2021
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