Balanced Distribution of Load on Grid Resources using Cellular Automata

Load balancing is a technique for equal and fair distribution of load on resources and maximizing their performance as well as reducing the overall execution time. However, meeting all of these goals in a single algorithm is not possible due to their inherent conflict, so some of the features must be given priority based on requirements and objectives of the system and the desired algorithm smust be designed with their orientation. In this article, a decentralized load balancing algorithm based on cellular automata and fuzzy logic has been presented which has capabilities needed for fair distribution of resources in Grid level. Each computing node in this algorithm has been modeled as a Cellular Automata’s cell and has been provided with the help of fuzzy logic in which each node can be an expert system and have a decisive role which is the best choice for tasking in dynamic environment and uncertain data. Each node is mapped to one of the VL, L, VN, and H, VH conditions based on information exchange on certain time periods with its neighboring nodes and based on fuzzy logic and tries to estimate the status of the other nodes in subsequent periods to reduce communication overhead with the help of Fuzzy Logic and the decision making to send or receive task loads is done based on the status of each node. So an appropriate structure for the system can greatly improve the efficiency of the algorithm. Fuzzy control does not use search and optimization and makes decisions based on inputs which are effective parameters of the system and are mostly based on incomplete and nonspecific information.

@article{Sadeghi2016,
  title     = {Balanced Distribution of Load on Grid Resources using Cellular Automata},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {7},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Amir Akbarian Sadeghi and Ahmad Khademzadeh and Mohammad Reza Salehnamadi},
  doi       = {10.14569/IJACSA.2016.070783},
  url       = {https://doi.org/10.14569/IJACSA.2016.070783}
}