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Admission control and resource provisioning in fog-integrated cloud using modified fuzzy inference system

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Abstract

Fog-integrated cloud (FiC) contains a fair amount of heterogeneity, leading to uncertainty in the resource provisioning. An admission control manager (ACM) is proposed, using a modified fuzzy inference system (FiS), to place a request based on the request’s parameters, e.g., CPU, memory, storage, and few categorical parameters, e.g., job priority and time sensitivity. The ACM considers the extended three-layer architecture of FiC. FiC nodes are classified into three computing nodes: fog node, aggregated fog node, and cloud node using modified FiS model. For performance study, extensive simulation experiments have been carried out on real Google trace. Different batches on the number of relevant rules are created and compared on metrics of job execution time, memory overhead, accuracy, and hit ratio with the modified rules. The proposed work has also been compared with the state of the art. The results have been encouraging and exhibit the benefits of the proposed model apart from being it lightweight with reduced number of rules, especially suited for the FiC.

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Abbreviations

NDS:

Non-delay sensitive

DS:

Delay sensitive

SC:

Scheduling class

RS:

Rule strength

Pr:

Priority of job

Th:

Threshold

Agg fog:

Aggregated fog node

Nom:

Number of membership

CPUfuzz :

Fuzzy membership value for CPU

Memoryfuzz :

Fuzzy membership value for memory

Storagefuzz :

Fuzzy membership value for storage

Priorityfuzz :

Fuzzy membership value for priority

Schedulingfuzz :

Fuzzy membership value for scheduling class

Thr :

Threshold values for rth parameter

M_fxn:

Compute membership functions

Cg:

Compute centroid

NoM:

Number of membership

Agg fog:

Aggregated fog node

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Acknowledgements

This work was supported by the School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi. The authors are also grateful to University Grant Commission (UGC) for funding one of the author with Maulana Azad National fellowship (MANF). The role of the authors, in this work, are as follows. Eht E Sham: Idea of the model, Experimental execution, Analysis, First draft of the manuscript. D P Vidyarthi: Idea of the model, Analysis & Conclusion, Manuscript refinement, proofreading. All data and materials as well as a software application or custom code support comply with field standards.

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  1. School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, 110067, India

    Eht E Sham & Deo Prakash Vidyarthi

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  1. Eht E Sham
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Correspondence to Deo Prakash Vidyarthi.

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Sham, E.E., Vidyarthi, D.P. Admission control and resource provisioning in fog-integrated cloud using modified fuzzy inference system. J Supercomput 78, 15463–15503 (2022). https://doi.org/10.1007/s11227-022-04483-7

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