An Efficient Diffusion Load Balancing Algorithm in Distributed System
Rafiqul Zaman Khan,Farrah Ali +1 more
TL;DR: The number of communication overheads depends on the number of overloaded nodes present in the domain of an under loaded nodes and vice-versa and that communication overhead for load balancing is always fairly less than KN but in worst case the algorithm's complexity becomes equal to KN.
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Abstract: In distributed computing system some nodes are very fast and some are slow and during the computation many fast nodes become idle or under loaded while the slow nodes become over loaded due to the uneven distribution of load in the system. In distributed system, the most common important factor is the information collection about loads on different nodes. The success of load balancing algorithm depends on how quickly the information about the load in the system is collected by a node willing to transfer or accept load. In this paper we have shown that the number of communication overheads depends on the number of overloaded nodes present in the domain of an under loaded nodes and vice-versa. We have also shown that communication overhead for load balancing is always fairly less than KN but in worst case our algorithm's complexity becomes equal to KN.
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Citations
•Proceedings Article
Load Balancing
R. McConnell
- 25 Jan 1995
TL;DR: In EFI XF 3.0, load balancing is not an officially supported feature and can only be achieved by manual ticket editing as mentioned in this paper, which is only recommended for experienced users.
110
Load Balancing in Cloud Computing: A State of the Art Survey
TL;DR: This paper study the necessary requirements and considerations for designing and implementing a suitable load balancer for cloud environments, and a complete survey of current proposed cloud load balancing solutions which can be classified into three categories: General Algorithm-based, Architectural-based and Artificial Intelligence-based load balancing mechanisms.
Improving Fault-Tolerant Load Balancing Algorithms in Computational Grids
TL;DR: An Adaptive Scheduling Algorithm namely ASA is presented that allocates any number of jobs to a million nodes with relatively low overhead and high flexibility and Experimental results show that the performance of ASA is better than those of its counterparts.
•Proceedings Article
An Improved Dynamic Load Balancing Routing Protocol Based on Mesh Network
Lu Yan,Ding Xiong +1 more
- 22 Mar 2019
TL;DR: An improved dynamic load balancing routing protocol based on mesh networks with real-time monitoring and adjustment is proposed, and the network fairness problem is solved when the multi-path task and the single- path task compete for the link.
Meta-heuristics based load balancing algorithms in grid and clouds-a review
Gurveer Kaur Brar,Amit Chhabra +1 more
- 01 Mar 2016
TL;DR: This paper presents an extensive review of different meta-heuristic techniques that are applicable in grid and cloud systems to generate optimal load balancing solution.
4
References
A trace-driven simulation study of dynamic load balancing
TL;DR: A trace-driven simulation study of dynamic load balancing in homogeneous distributed systems supporting broadcasting finds that source initiative algorithms were found to perform better than server initiative algorithms and the performances of all hosts, even those originally with light loads, are generally improved by load balancing.
The Gradient Model Load Balancing Method
F.C.H. Lin,Robert M. Keller +1 more
TL;DR: A dynamic load balancing method is proposed for a class of large-diameter multiprocessor systems based on the "gradient model," which entails transferring backlogged tasks to nearby idle processors according to a pressure gradient indirectly established by requests from idle processors.
A comparison of receiver-initiated and sender-initiated adaptive load sharing
TL;DR: It is shown that sender-initiated strategies outperform receiver-in Initiated strategies at light to moderate system loads, and that receiver-Initiated Strategies are preferable at high system loads only if the costs of task transfer under the two strategies are comparable.
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A trace-driven simulation study of dynamic load balancing
TL;DR: In this paper, a trace-driven simulation study of dynamic load balancing in homogeneous distributed systems supporting broadcasting is presented, where information about job CPU and input/output (I/O) demands collected from production systems is used as input to a simulation model that includes a representative CPU scheduling policy and considers the message exchange and job transfer cost explicitly.
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