Real Time Path Predicting for Autonomous Underwater Vehicle Using Support Vector Regression Machines

2008 ◽  
Author(s):  
Rubo Zhang ◽  
Guanqun Liu ◽  
Xueyao Li
Keyword(s):  
Support Vector Regression ◽  
Real Time ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Support Vector ◽  
Time Path

Real-time path planning and obstacle avoidance for RAIS: an autonomous underwater vehicle

2001 ◽  
Vol 26 (2) ◽  
pp. 216-227 ◽  
Author(s):  
G. Antonelli ◽  
S. Chiaverini ◽  
R. Finotello ◽  
R. Schiavon
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Time Path

scholarly journals Stream Data Load Prediction for Resource Scaling Using Online Support Vector Regression

Algorithms ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 37 ◽  
Author(s):  
Zhigang Hu ◽  
Hui Kang ◽  
Meiguang Zheng
Keyword(s):  
Support Vector Regression ◽  
Real Time ◽  
Virtual Machines ◽  
Time Window ◽  
Performance Model ◽  
Streaming Data ◽  
Support Vector ◽  
Load Prediction ◽  
Stream Data ◽  
Online Support Vector Regression

A distributed data stream processing system handles real-time, changeable and sudden streaming data load. Its elastic resource allocation has become a fundamental and challenging problem with a fixed strategy that will result in waste of resources or a reduction in QoS (quality of service). Spark Streaming as an emerging system has been developed to process real time stream data analytics by using micro-batch approach. In this paper, first, we propose an improved SVR (support vector regression) based stream data load prediction scheme. Then, we design a spark-based maximum sustainable throughput of time window (MSTW) performance model to find the optimized number of virtual machines. Finally, we present a resource scaling algorithm TWRES (time window resource elasticity scaling algorithm) with MSTW constraint and streaming data load prediction. The evaluation results show that TWRES could improve resource utilization and mitigate SLA (service level agreement) violation.

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