Parallel load balancing for dynamic execution environments

Author(s):  
T. Minyard ◽  
Y. Kallinderis ◽  
K. Schulz
2021 ◽  
Vol 12 (4) ◽  
pp. 1-26
Author(s):  
Chun Ouyang ◽  
Michael Adams ◽  
Arthur H. M. Ter Hofstede ◽  
Yang Yu

Business Process Management Systems ( BPMSs ) provide automated support for the execution of business processes in modern organisations. With the emergence of cloud computing, BPMS deployment considerations are shifting from traditional on-premise models to the Software-as-a-Service ( SaaS ) paradigm, aiming at delivering Business Process Automation as a Service. However, scaling up a traditional BPMS to cope with simultaneous demand from multiple organisations in the cloud is challenging, since its underlying system architecture has been designed to serve a single organisation with a single process engine. Moreover, the complexity in addressing both the dynamic execution environment and the elasticity requirements of users impose further challenges to deploying a traditional BPMS in the cloud. A typical SaaS often deploys multiple instances of its core applications and distributes workload to these application instances via load balancing. But, for stateful and often long-running process instances, standard stateless load balancing strategies are inadequate. In this article, we propose a conceptual design of BPMS capable of addressing dynamically varying demands of end users in the cloud, and present a prototypical implementation using an open source traditional BPMS platform. Both the design and system realisation offer focused strategies on achieving scalability and demonstrates the system capabilities for supporting both upscaling, to address large volumes of user demand or workload, and downscaling, to release underutilised computing resources, in a cloud environment.


Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.


2003 ◽  
Vol 123 (10) ◽  
pp. 1847-1857
Author(s):  
Takahiro Tsukishima ◽  
Masahiro Sato ◽  
Hisashi Onari
Keyword(s):  

2014 ◽  
Vol 134 (8) ◽  
pp. 1104-1113
Author(s):  
Shinji Kitagami ◽  
Yosuke Kaneko ◽  
Hidetoshi Kambe ◽  
Shigeki Nankaku ◽  
Takuo Suganuma
Keyword(s):  

2013 ◽  
Vol 133 (4) ◽  
pp. 891-898
Author(s):  
Takeo Sakairi ◽  
Masashi Watanabe ◽  
Katsuyuki Kamei ◽  
Takashi Tamada ◽  
Yukio Goto ◽  
...  

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