Search for dissertations about: "Performance anomalies"

Showing result 1 - 5 of 39 swedish dissertations containing the words Performance anomalies.

  1. 1. Performance problem diagnosis in cloud infrastructures

    Author : Olumuyiwa Ibidunmoye; Erik Elmroth; Guilliano Casale; Viktoria Fodor; Henrik Björklund; Umeå universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Systems Performance; Performance anomalies; Performance bottlenecks; Cloud infrastructures; Cloud Computing; Cloud Services; Cloud Computing Performance; Performance problems; Performance anomaly detection; Performance bottleneck identification; Performance Root-cause Analysis; Computer Systems; datorteknik; Computer Science; datalogi;

    Abstract : Cloud datacenters comprise hundreds or thousands of disparate application services, each having stringent performance and availability requirements, sharing a finite set of heterogeneous hardware and software resources. The implication of such complex environment is that the occurrence of performance problems, such as slow application response and unplanned downtimes, has become a norm rather than exception resulting in decreased revenue, damaged reputation, and huge human-effort in diagnosis. READ MORE

  2. 2. Performance anomaly detection and resolution for autonomous clouds

    Author : Olumuyiwa Ibidunmoye; Erik Elmroth; Ewnetu Bayuh Lakew; Rolf Stadler; Umeå universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Cloud Computing; Distributed Systems; Performance Management; Anomaly Detection; Quality of Service; Performance Analytics; Machine Learning; Computer Systems; datorteknik; business data processing; administrativ databehandling; Computer Science; datalogi;

    Abstract : Fundamental properties of cloud computing such as resource sharing and on-demand self-servicing is driving a growing adoption of the cloud for hosting both legacy and new application services. A consequence of this growth is that the increasing scale and complexity of the underlying cloud infrastructure as well as the fluctuating service workloads is inducing performance incidents at a higher frequency than ever before with far-reaching impact on revenue, reliability, and reputation. READ MORE

  3. 3. Essays on financial market anomalies and Investment strategies

    Author : Mahdi Heidari; Handelshögskolan i Stockholm; []
    Keywords : SAMHÄLLSVETENSKAP; SOCIAL SCIENCES;

    Abstract : This dissertation consists of three papers on momentum strategy and the comovement of stock returns.Momentum Crash Management studies the fat-tailed distribution of momentum strategy’s return and the predictability of momentum crashes. Momentum strategy has both high average returns, and Sharpe ratios. READ MORE

  4. 4. Machine learning for anomaly detection in edge clouds

    Author : Javad Forough; Erik Elmroth; Monowar H. Bhuyan; Shahid Raza; Umeå universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Edge Clouds; Anomaly Detection; Machine Learning;

    Abstract : Edge clouds have emerged as an essential architecture, revolutionizing data processing and analysis by bringing computational capabilities closer to data sources and end-users at the edge of the network. Anomaly detection is crucial in these settings to maintain the reliability and security of edge-based systems and applications despite limited computational resources. READ MORE

  5. 5. Ett dynamiskt perspektiv på individuella skillnader av heuristisk kompetens, intelligens, mentala modeller, mål och konfidens i kontroll av mikrovärlden Moro

    Author : Fredrik Elg; Linköpings universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; complexed dynamic systems; Ravens matrices; Computer science; Datavetenskap;

    Abstract : Theories predicting performance of human control of complex dynamic systems must assess how decision makers capture and utilise knowledge for achieving and maintaining control. Traditional problem solving theories and corresponding measures such as Ravens matrices have been applied to predict performance in complex dynamic systems. READ MORE