• Publications
  • Influence
Workload adaptation in autonomic DBMSs
Workload adaptation is a performance management process in which an autonomic database management system (DBMS) efficiently makes use of its resources by filtering or controlling the workloadExpand
  • 44
  • 3
  • PDF
Towards Autonomic Workload Management in DBMSs
Workload management is the discipline of effectively managing, controlling, and monitoring work flow across computing systems. It is an increasingly important requirement of database managementExpand
  • 31
  • 1
  • PDF
Workload Adaptation in Autonomic Database Management Systems
Workload adaptation is a performance management process in which an autonomic database management system (DBMS) efficiently makes use of its resources by filtering or controlling the workloadExpand
  • 3
  • 1
  • PDF
Poster Session: Adapting Mixed Workloads to Meet SLOs in Autonomic DBMSs
Workload adaptation allows an autonomic database management system (DBMS) to efficiently make use of its resources and meet its service level objectives (SLOs) by filtering or controlling theExpand
  • 16
  • PDF
An Efficient Cascaded Filtering Retrieval Method for Big Audio Data
Fast audio retrieval is crucial for many important applications and yet demanding due to the high dimension nature and increasingly larger volume of audios on the Internet. Although audioExpand
  • 8
A clustering-based sampling method for building query response time models
  • 3
Audio Identification by Sampling Sub-fingerprints and Counting Matches
It is challenging to retrieve audio clips from large audio datasets not only due to the high dimensionality of audio but also due to the large number of audios. Fingerprinting methods primarily focusExpand
  • 4
An Efficient Cascaded Filtering Retrieval Method for Big Audio Data
Fast audio retrieval is crucial for many important applications and yet demanding due to the high dimension nature and increasingly larger volume of audios in the internet. Although audioExpand
  • 3
A Sampling and Counting Method for Big Audio Retrieval
This paper proposes a sampling and counting method, which remarkably improves retrieval speed yet maintaining high recall rate and precision for short audio clips retrieval. A new inverted indexExpand
  • 2
Enhancing Sampling and Counting Method for Audio Retrieval with Time-Stretch Resistance
An ideal audio retrieval method should be not only highly efficient in identifying an audio track from a massive audio dataset, but also robust to any distortion. Unfortunately, none of the audioExpand
  • 1