Dynamic Request Allocation and Scheduling for Context Aware Applications Subject to a Percentile Response Time SLA in a Distributed Cloud

2010 ◽  
Author(s):  
Keerthana Boloor ◽  
Rada Chirkova ◽  
Yannis Viniotis ◽  
Tiia Salo
Keyword(s):  
Response Time ◽  
Context Aware ◽  
Distributed Cloud

scholarly journals Multi-Objective Service Placement Scheme Based on Fuzzy-AHP System for Distributed Cloud Computing

2019 ◽  
Vol 9 (17) ◽  
pp. 3550 ◽  
Author(s):  
A-Young Son ◽  
Eui-Nam Huh
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Response Time ◽  
Data Centers ◽  
Cloud Data ◽  
Multi Objective ◽  
Service Placement ◽  
Service Response Time ◽  
Cloud Data Centers ◽  
Distributed Cloud

With the rapid increase in the development of the cloud data centers, it is expected that massive data will be generated, which will decrease service response time for the cloud data centers. To improve the service response time, distributed cloud computing has been designed and researched for placement and migration from mobile devices close to edge servers that have secure resource computing. However, most of the related studies did not provide sufficient service efficiency for multi-objective factors such as energy efficiency, resource efficiency, and performance improvement. In addition, most of the existing approaches did not consider various metrics. Thus, to maximize energy efficiency, maximize performance, and reduce costs, we consider multi-metric factors by combining decision methods, according to user requirements. In order to satisfy the user’s requirements based on service, we propose an efficient service placement system named fuzzy- analytical hierarchical process and then analyze the metric that enables the decision and selection of a machine in the distributed cloud environment. Lastly, using different placement schemes, we demonstrate the performance of the proposed scheme.

scholarly journals Context-aware distributed cloud computing using CloudScheduler

2017 ◽  
Vol 898 ◽  
pp. 052039
Author(s):  
R Seuster ◽  
CR Leavett-Brown ◽  
K Casteels ◽  
C Driemel ◽  
M Paterson ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Context Aware ◽  
Distributed Cloud

Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time

2016 ◽  
Vol 63 (6) ◽  
pp. 333-342
Author(s):  
Roberto Limongi ◽  
Angélica M. Silva
Keyword(s):  
Response Time ◽  
Short Term Memory ◽  
Estimation Error ◽  
Predictive Coding ◽  
Time Estimation ◽  
Prediction Errors ◽  
Memory Scanning ◽  
Short Term ◽  
Term Memory ◽  
Temporal Prediction

Abstract. The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production – where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

A Response-Time Investigation of Vehicle Stereotypes

2000 ◽  
Author(s):  
Michael Anthony ◽  
Robert W. Fuhrman
Keyword(s):  
Response Time

A Response Time Model on the Role of Spectral and Duration Cues in Vowel Perception

2014 ◽  
Author(s):  
Gabriel Tillman ◽  
Don van Ravenzwaaij ◽  
Scott Brown ◽  
Titia Benders
Keyword(s):  
Response Time ◽  
Time Model ◽  
Vowel Perception ◽  
Response Time Model
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