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SEES: a scalable and energy-efficient scheme for green IoT-based heterogeneous wireless nodes

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Abstract

Realizing energy-efficient communication in the IoT-based large-scale systems has become a key challenge in the past few years. The need is to minimize the global energy usage of battery-operated objects so as to reduce data transmission cost and extend the network lifetime. In this paper, we propose SEES, a scalable and energy-efficient scheme for green IoT-based heterogeneous wireless nodes. We study the impact of energy-harvesting techniques by utilizing ambient energy-harvesting relay nodes in such a way that enables a higher energy conservation and guarantees a long-lived network. SEES includes: (1) a zone-based hybrid-placement scheme, (2) a Multi-Stage Weighted Election heuristic (MSWE), and (3) a Minimum Cost Cross-layer Transmission model (MCCT). Our aim is to ensure an even-random deployment of heterogeneous nodes, a scalable pre-deterministic placement of energy-harvesting nodes, a fair energy-load balancing among all the zones, and a minimum energy-cost for data transmission from the bottom layer to the topmost layer. SEES is a general scheme that supports up to n levels of heterogeneity, as well as m different election parameters (static and dynamic, associated with m generated weights), and can be used for any type of IoT-based deployment. Experimental results of extensive simulations indicate the superiority of SEES over the other traditional protocols proposed in literature. It can save up to \(62\%\) of the total energy, and, at least, it increases the network lifetime by 58, 68, 70, \(42\%\); the stability period by 192, 108, 424, \(150\%\); and the network throughput by 107, 111, 100, \(114\%\); over LEACH, SEP, ZSEP, and hetDEEC protocols respectively, for all the cases and scenarios tested.

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Correspondence to Antar Shaddad H. Abdul-Qawy.

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Abdul-Qawy, A.S.H., Srinivasulu, T. SEES: a scalable and energy-efficient scheme for green IoT-based heterogeneous wireless nodes. J Ambient Intell Human Comput 10, 1571–1596 (2019). https://doi.org/10.1007/s12652-018-0758-7

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