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Top1. Introduction
In Wireless Sensors Network (WSNs), Sensor Nodes (SNs)link the physical world with the digital world by capturing and revealing real-world phenomena. SNs are small in size, and design cost is very low. It can apply in many fields in IoT-based applications such as smart cities (Adam, Anisi, & Ali, 2020), smart environments, smart grid (Faheem & Gungor, 2018), smart monitoring of the air quality index (AQI) (Patil, Thanuja, & Melinamath, 2019), water and gas distribution networks etc. In any WSN, replacement of dead/ nonfunctional SNs are challenging and expensive task. Smart use of energy resources of the SNs to archive an improved network lifetime is a research issue. Many articles have been proposed for saving the energy resource of SNs in WSNs, such as clustering, wake-up scheduling, sensing data aggregation and compression, etc. Among these approaches, wake-up scheduling of SNs is most popular and efficient in terms of energy saving and improving the network lifetime.
In node scheduling, an optimal number of SNs are in an active state, and the remaining SNs are in a sleep state for a short period of time. In a small time frame, the active sensor will monitor target nodes and perform data sensing and gathering tasks. This concept will enhance the network lifetime of the WSNs. Most of the existing schemes are designed by considering either coverage or connectivity restraints for generating the optimal schedule. Only few research articles have considered both constraints to perform node scheduling. Generally, these existing methods do not guarantee for optimal solution set and sometimes struck in local minima to find an optimal solution. Thus, this paper proposes a hybrid metaheuristic-based wake-up scheduling scheme, named as Memtic-Tabu-based-WS in which best feature of memtic algorithm and Tabu Search algorithm is combined to find an optimal wake-up schedule of SNs to fullfill the coverage and connectivity constraints.
There are two types of approaches exist in literature to find solution of optimal wake-up schedule, known as deterministic algorithm-based approach and approximate algorithm-based approach (Mansouri & Pathan, 2019; Brezinski & Guevarra, 2020; Aliyu & Murali, 2020). Find an optimal set of an active SNs can be classified as an NP-hard problem. Thus, the proposed hybrid metaheuristic-based wake-up scheduling scheme, named as Memtic-Tabu-based-WS is used to find a set of active SNs among deployed SNs by considering coverage and connectivity constraints. So, after applying this proposed method selected optimal solution set will satisfy k-coverage and m-connectivity constraints. The main contribution of the proposed research work are as follows
- a.
A hybid metaheuristic using best feature of Memetic and Tabu Search algorithm is devised to find the optimal solution set where Tabu search concept has been included in mutation and local phases that provide efficient and fast coverage of the proposed hybrid method.
- b.
A novel fitness function has been derived by condering four basic parameters: coverage cost, connectivity cost, number of active SNs, and remaining energy of nodes.
- c.
Result analysis of the proposed scheme have been done in two network scenario and its performance is compared with three well known existing sleep scheduling schemes.