Fault-Tolerant Distributed Stream Processing System

2006 ◽  
Author(s):  
M. Gorawski ◽  
P. Marks
Keyword(s):  
Fault Tolerant ◽  
Stream Processing ◽  
Processing System ◽  
Distributed Stream Processing

scholarly journals Fault-tolerance in the borealis distributed stream processing system

2008 ◽  
Vol 33 (1) ◽  
pp. 1-44 ◽  
Author(s):  
Magdalena Balazinska ◽  
Hari Balakrishnan ◽  
Samuel R. Madden ◽  
Michael Stonebraker
Keyword(s):  
Fault Tolerance ◽  
Stream Processing ◽  
Processing System ◽  
Distributed Stream Processing

scholarly journals High availability of data using Automatic Selection Algorithm (ASA) in distributed stream processing systems

2019 ◽  
Vol 8 (2) ◽  
pp. 690-698
Author(s):  
Sultan Alshamrani ◽  
Hesham Alhumyani ◽  
Quadri Waseem ◽  
Isbudeen Noor Mohamed
Keyword(s):  
Stream Processing ◽  
Processing System ◽  
High Availability ◽  
Selection Algorithm ◽  
Advantages And Disadvantages ◽  
Automatic Selection ◽  
Recovery Techniques ◽  
Recovery Technique ◽  
System Requirements ◽  
Distributed Stream Processing

High Availability of data is one of the most critical requirements of a distributed stream processing systems (DSPS). We can achieve high availability using available recovering techniques, which include (active backup, passive backup and upstream backup). Each recovery technique has its own advantages and disadvantages. They are used for different type of failures based on the type and the nature of the failures. This paper presents an Automatic Selection Algorithm (ASA) which will help in selecting the best recovery techniques based on the type of failures. We intend to use together all different recovery approaches available (i.e., active standby, passive standby, and upstream standby) at nodes in a distributed stream-processing system (DSPS) based upon the system requirements and a failure type). By doing this, we will achieve all benefits of fastest recovery, precise recovery and a lower runtime overhead in a single solution. We evaluate our automatic selection algorithm (ASA) approach as an algorithm selector during the runtime of stream processing. Moreover, we also evaluated its efficiency in comparison with the time factor. The experimental results show that our approach is 95% efficient and fast than other conventional manual failure recovery approaches and is hence totally automatic in nature.

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