Non-Intrusive Cloud Application Transaction Pattern Discovery

2019 ◽  
Author(s):  
Shay Horovitz ◽  
Yair Arian ◽  
Maxim Vaisbrot ◽  
Noam Peretz
Keyword(s):  
Pattern Discovery ◽  
Cloud Application ◽  
Transaction Pattern

A Perspective Study on Pattern Discovery of Web Usage Mining

2019 ◽  
Vol 7 (4) ◽  
pp. 1076-1081
Author(s):  
G. Ragupathy ◽  
M.K. Prakash
Keyword(s):  
Pattern Discovery ◽  
Web Usage Mining ◽  
Web Usage

scholarly journals COM-PACE: Compliance-Aware Cloud Application Engineering Using Blockchain

2020 ◽  
Vol 24 (5) ◽  
pp. 45-53
Author(s):  
Gagangeet Singh Aujla ◽  
Masoud Barati ◽  
Omer Rana ◽  
Schahram Dustdar ◽  
Ayman Noor ◽  
...  
Keyword(s):  
Cloud Application ◽  
Application Engineering

Incremental pattern discovery on streams, graphs and tensors

2008 ◽  
Vol 10 (2) ◽  
pp. 28-29
Author(s):  
Jimeng Sun
Keyword(s):  
Pattern Discovery

scholarly journals Swarm-Like Distributed Algorithm for Scheduling a Microservice-Based Application to the Cloud Servers

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1553
Author(s):  
Marian Rusek ◽  
Grzegorz Dwornicki
Keyword(s):  
Distributed Applications ◽  
Practical Implementation ◽  
Live Migration ◽  
Cloud Infrastructure ◽  
Application Development ◽  
Cloud Management ◽  
Cloud Application ◽  
Cloud Servers ◽  
Distributed Cloud ◽  
Better Than

Introduction of virtualization containers and container orchestrators fundamentally changed the landscape of cloud application development. Containers provide an ideal way for practical implementation of microservice-based architecture, which allows for repeatable, generic patterns that make the development of reliable, distributed applications more approachable and efficient. Orchestrators allow for shifting the accidental complexity from inside of an application into the automated cloud infrastructure. Existing container orchestrators are centralized systems that schedule containers to the cloud servers only at their startup. In this paper, we propose a swarm-like distributed cloud management system that uses live migration of containers to dynamically reassign application components to the different servers. It is based on the idea of “pheromone” robots. An additional mobile agent process is placed inside each application container to control the migration process. The number of parallel container migrations needed to reach an optimal state of the cloud is obtained using models, experiments, and simulations. We show that in the most common scenarios the proposed swarm-like algorithm performs better than existing systems, and due to its architecture it is also more scalable and resilient to container death. It also adapts to the influx of containers and addition of new servers to the cloud automatically.

scholarly journals Water quality monitoring via cloud application: Brief review

2021 ◽  
Vol 1078 (1) ◽  
pp. 012001
Author(s):  
A N Abdul Muta’ali ◽  
N Sazali ◽  
S A C Ghani ◽  
J Walter
Keyword(s):  
Water Quality ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Cloud Application
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