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Top1. Introduction
For the past two decades, many meta-heuristic optimization algorithms are proposed to solve problems in different fields. Nowadays, these algorithms are quite popular methods because of their excellent computation power and easy conversion to the real problem. Meta-heuristic methods are very general, which can be adapted easily to any type of problem with a single objective or multi-objective (Kalita, K., Dey, P., Haldar, S., & Gao, X. Z., 2019).
A recent study indicates that plants also exhibit intelligent behaviors, which can be modeled mathematically for the system model and objective function. For example, foraging behavior of Venus flytrap, a carnivorous plant can be modeled as an optimal search algorithm for identifying the optimal solution under specified constraints.
Swarm Intelligence based Search algorithms inspired by social insects, fish, bird flocking, honey bees, etc., mimic direct or indirect communication among individuals, especially information regarding promising search space for their foraging. But, many species search for food independently and autonomously rather than cooperatively. Such species also have food search stratagems to maintain the species, which is known as Non-Swarm Intelligence.
The Discrete Venus Fly-Trap Search Algorithm (DVFS) is modeled based on the foraging behavior of Venus Fly-Trap plant. The botanical name of Venus flytrap is Dionaea Muscipula is shown in the following figure 1. The great scientist Darwin quoted this plant as “one of the most wonderful in the world.” This algorithm devised on the rapid closure action of its traps (also called as leaves). This trap closure is due to the stimulation of the trigger hairs that present in the two lobes of the leaf by the movements of prey (small insects, small animals, raindrop, fast blowing wind, etc.). The traps in this plant search for their food independently and autonomously without any information exchange among them (Sivabalan S, Gowri R, Rathipriya R, 2015).
Energy Resource Optimization (ERO) is a technique that can find an optimal energy resource selection for a home appliance through wireless power transfer to calculate the overall network energy consumption. In this paper, the Discrete Venus Fly-Trap Search Algorithm (DVFS) is the new optimal search algorithm devised the first time for selecting energy sources (Gowri R, Sivabalan S, Rathipriya R, 2015). The remaining part of the paper organized as follows. Section 2 presents the state-of-the-art of energy-efficient sensor network models using optimization algorithms. Section 3 describes the methods and materials needed for the proposed work. The detail description of the proposed work is in section 4. The summary and possible future enhancement are in Section 5.
Figure 1. Different Stages of Venus Fly-Trap
Top2. Review Of Literature
Table 1 describes the detailed assessment of the state-of-the-art in energy-efficient model techniques for sensor network and the issues in the present research work related to node energy saving.