Load Balancing Method Using Connection Pool in RFID Middleware

Author(s):  
Sung-Mee Park ◽  
Jeong-Hwan Song ◽  
Chae-Soo Kim ◽  
Jung-Ja Kim
2011 ◽  
Vol 187 ◽  
pp. 282-286 ◽  
Author(s):  
Xiao Zou

RFID middleware plays an important role in extracting information from RFID reader and sending them to the terminal server. Although the traditional middleware technique solution of RFID can ensure the continuous operation of the system, the cost is too much CPU working load and serious waste of physical resources. The Agent that has played a central role in many application fields can also provide non-centralized and adaptive solutions for load balancing. The paper presented a RFID middleware load balancing method based on Agent according to characteristics of RFID middleware and designed adaptive load allocation algorithm. Two kinds of agents were design, namely information collection Agent and load balancing Agent, to collaborate to complete corresponding strategies of load balancing.


Author(s):  
Jiann-Liang Chen ◽  
Nong-Kun Chen ◽  
Yi-Wei Ma ◽  
Han-Chieh Chao ◽  
Cheng-Yen Wu

Author(s):  
Young-Sik Noh ◽  
Yung-Cheol Byun ◽  
Dong-Cheol Lee

2011 ◽  
Vol 34 (3) ◽  
pp. 811-820 ◽  
Author(s):  
Yi-Wei Ma ◽  
Han-Chieh Chao ◽  
Jiann-Liang Chen ◽  
Cheng-Yen Wu

2010 ◽  
Vol 40 (6) ◽  
pp. 485-506 ◽  
Author(s):  
Heung Seok Chae ◽  
Jae Geol Park ◽  
Jian Feng Cui ◽  
Joon Sang Lee

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.


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