Abstract
In this new age, with the maturation of Internet of things (IoT), a multitude of advanced and innovative services are foreseen. Cloud, an accustomed computing technology, being circumscribed by the huge traffic cannot assuage the real-time services demanded by the cross-vertical IoT applications. Over and above this, though the fog computing paradigm, a hopeful alternative providing real-time services, was introduced, still, fog and cloud collaboratively may not be able to bear the tremendous amount of requests that arises from the numerous vertical IoT applications, because of the resource-bounded nature of fog. An indecent resource management and load balancing strategy in the fog infrastructure may further lead to a deterioration in the quality of service (QoS) and failure in providing services in real time. Without disregarding the unignorable issues and challenges in fog, this paper A Resource-Aware Load Balancing Strategy for Real-Time, Cross-vertical IoT Applications has been envisioned. The designed architecture and the proposed model are presented comprehensively with an emphasis on elucidating the resource-aware load balancing strategy. The equations and algorithms for resource management mechanism and load balancing are presented meticulously. Following the end, the efficacy of the proposed methodology is validated using CloudSim and the performance is evaluated in terms of load balance, resource utilization, and power consumption based on employed fog nodes.
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Behera, R.K., Patro, A., Roy, D.S. (2022). A Resource-Aware Load Balancing Strategy for Real-Time, Cross-vertical IoT Applications. In: Dehuri, S., Prasad Mishra, B.S., Mallick, P.K., Cho, SB. (eds) Biologically Inspired Techniques in Many Criteria Decision Making. Smart Innovation, Systems and Technologies, vol 271. Springer, Singapore. https://doi.org/10.1007/978-981-16-8739-6_2
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DOI: https://doi.org/10.1007/978-981-16-8739-6_2
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