Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Josep Lluis Berral"'
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Universitat Politècnica de Catalunya (UPC)
Autoscaling methods are used for cloud-hosted applications to dynamically scale the allocated resources for guaranteeing Quality-of-Service (QoS). The public-facing application serves dynamic workloads, which contain bursts and pose challenges for au
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b1df532320bd81633bbc6af8d9df6ed3
https://hdl.handle.net/2117/373291
https://hdl.handle.net/2117/373291
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Future Generation Computer Systems
Universitat Politècnica de Catalunya (UPC)
Future Generation Computer Systems
Accurate prediction of data center resource utilization is required for capacity planning, job scheduling, energy saving, workload placement, and load balancing to utilize the resources efficiently. However, accurately predicting those resources is c
Publikováno v:
CLOUD
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Detection of behavior patterns on resource usage in containerized Cloud applications is necessary for proper resource provisioning. Applications can use CPU/Memory with repetitive patterns, following a trend over time independently. By identifying su
Autor:
Luisa Delgado-Serrano, David Carrera, Josep Lluis Berral, David Torrents, Gonzalo Gómez-Sánchez
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Universitat Politècnica de Catalunya (UPC)
Background: For many years, a major question in the field of cancer genomics has been the identification of those variations that can have a functional role in cancer, and distinguish from the majority of genomic changes that have no functional con
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Universitat Politècnica de Catalunya (UPC)
Tuning configurations of Spark jobs is not a trivial task. State-of-the-art auto-tuning systems are based on iteratively running workloads with different configurations. During the optimization process, the relevant features are explored to find good
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8b6a59f62513f88213118b717b28a8d
https://hdl.handle.net/2117/340271
https://hdl.handle.net/2117/340271
Autor:
David Carrera, Clemens Szyperski, Raghu Ramakrishnan, Nicolas Poggi, Thomas Fenech, Alejandro Montero, José A. Blakeley, Donald Kossmann, Josep Lluis Berral, Umar Farooq Minhas, Víctor Cuevas-Vicenttín, Gonzalo Gómez, Davide Brini
Publikováno v:
Performance Evaluation and Benchmarking for the Era of Cloud(s) ISBN: 9783030550233
TPCTC
TPCTC
We introduce an extension for TPC benchmarks addressing the requirements of big data processing in cloud environments. We characterize it as the Elasticity Test and evaluate under TPCx-BB (BigBench). First, the Elasticity Test incorporates an approac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::01a9513de161773f820ae6f89f02f5c4
https://doi.org/10.1007/978-3-030-55024-0_1
https://doi.org/10.1007/978-3-030-55024-0_1
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
CLOUD
Universitat Politècnica de Catalunya (UPC)
CLOUD
Understanding the resource usage behaviors of the ever-increasing machine learning workloads are critical to cloud providers offering Machine Learning (ML) services. Capable of auto-scaling resources for customer workloads can significantly improve r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cd6a39fa72bc1474b76566f0590b31d9
http://hdl.handle.net/2117/340053
http://hdl.handle.net/2117/340053
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
IEEE Transactions on Parallel and Distributed Systems
Recercat. Dipósit de la Recerca de Catalunya
instname
Universitat Politècnica de Catalunya (UPC)
IEEE Transactions on Parallel and Distributed Systems
Recercat. Dipósit de la Recerca de Catalunya
instname
The fast evolution of data analytics platforms has resulted in an increasing demand for real-time data stream processing. From Internet of Things applications to the monitoring of telemetry generated in large data centers, a common demand for current
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::014f2fa94e2311f3a3f3803aaa17b019
https://hdl.handle.net/2117/121867
https://hdl.handle.net/2117/121867
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
IEEE Transactions on Network and Service Management
Universitat Politècnica de Catalunya (UPC)
IEEE Transactions on Network and Service Management
Accurate estimation of data center resource utilization is a challenging task due to multi-tenant co-hosted applications having dynamic and time-varying workloads. Accurate estimation of future resources utilization helps in better job scheduling, wo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a6064be3f14c3980bd804ad98edcd35
https://hdl.handle.net/10576/13649
https://hdl.handle.net/10576/13649
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
IEEE Systems Journal
Universitat Politècnica de Catalunya (UPC)
IEEE Systems Journal
Large-scale data centers are composed of thousands of servers organized in interconnected racks to offer services to users. These data centers continuously generate large amounts of telemetry data streams (e.g., hardware utilization metrics) used for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ac15176c7aadeaa64680089d9c7c0f2