Adaptive Load Balancing Dashboard in Dynamic Distributed Systems
Author(s) -
Seyedeh Leili Mirtaheri,
Seyed Arman Fatemi,
Lucio Grandinetti
Publication year - 2017
Publication title -
supercomputing frontiers and innovations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 16
eISSN - 2409-6008
pISSN - 2313-8734
DOI - 10.14529/jsfi170403
Subject(s) - load balancing (electrical power) , computer science , distributed computing , merge (version control) , response time , load management , network load balancing services , process (computing) , real time computing , server , computer network , engineering , parallel computing , geometry , mathematics , computer graphics (images) , electrical engineering , grid , operating system
Considering the dynamic nature of new generation scientific problems, load balancing is a necessity to manage the load in an efficient manner. Load balancing systems are use to optimize the resource consumption, maximize the throughput, minimize response time, and to prevent overload in resources. In current research, we consider operational distributed systems with dynamic variables caused by different nature of the applications and heterogeneity of the various levels in the system. Conducted studies indicate that many different factors should be considered to select the load balancing algorithm, including the processing power, load transfer and communication delay of nodes. In this work, We aim to design a dashboard that is capable to merge the load balancing algorithms in different environments. We design an adaptive system infrastructure with the ability to adjust various factors in the run time of a load balancing algorithm. We propose a task and a resource allocation mechanism and further introduce a mathematical model of load balancing process in the system. We calculate a normalized hardware score that determines the maturity of system according to the environmental conditions of the load balancing process. Evaluation results confirm that the proposed method performs well and reduces the probability of system failure.
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