Load Balancing Using Hybrid ACO - Random Walk Approach

Author(s):  
Neha Bhatia ◽  
Rohan Kundra ◽  
Anurag Chaurasia ◽  
Satish Chandra
Keyword(s):  
Author(s):  
Sudha S. Senthilkumar ◽  
Brindha K. ◽  
Nitesh Kumar Agrawal ◽  
Akshat Vaidya

With the ever-increasing size of the systems, there is a greater need for load balancing. Various algorithms are used for balancing the overall load of the cloud and a few of them are the honeybee foraging algorithm, a biased random sampling on a random walk procedure and active clustering. Here, the authors focus on the honeybee foraging algorithm. There is a type of bees called the forager bees who continually search for food sources and upon finding the same they return to the hive and advertise their discovery by a dance called a waggle. In case of load balancing in the web servers, whenever the demand sees a spike there is a dynamic allocation of services to regulate the changing demands of the user. The servers are grouped under Virtual servers (VS), each virtual server is assigned a specific queue for itself. Each server while processing a request calculates the reward and this is analogous to the quality of the find. The dance floor in case of the bees can be analogous to the advert board here which advertises the reward to the entire colony.


Author(s):  
Joseph Rudnick ◽  
George Gaspari
Keyword(s):  

1990 ◽  
Vol 51 (C1) ◽  
pp. C1-67-C1-69
Author(s):  
P. ARGYRAKIS ◽  
E. G. DONI ◽  
TH. SARIKOUDIS ◽  
A. HAIRIE ◽  
G. L. BLERIS
Keyword(s):  

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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