A survey on energy efficient routing techniques in WSNs focusing IoT applications and enhancing fog computing paradigm

Kaur, Loveleen; Kaur, Rajbir

doi:10.1016/j.gltp.2021.08.001

Cited by 30 publications

(13 citation statements)

References 42 publications

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“…A concise survey of energy‐efficient routing protocols for IoT applications that use WSNs has been provided by Kaur and Kaur, 90 in which the key points, architectures, and frameworks of various energy‐efficient sensor routing techniques have been presented. They have highlighted the role of fog computing in several energy‐efficient strategies.…”

Section: Related Survey Studiesmentioning

confidence: 99%

The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

Dong‐liang

Bei

Wang

2023

Int J Communication

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Summary Over the last decade, the Internet of Things (IoT) has become ever more popular, as is evident from its role in changing the human lifestyle and conferring remarkable privileges for them. It has a significant presence in various crucial areas, including smart cities, smart factories, manufacturing, transportation, and healthcare. Massive amounts of data generated by IoT devices have the potential to endanger the lifetime of nodes in IoT‐based networks due to increased communication power consumption. It has become crucial to propose solutions for network‐based issues, such as quality of service, security, network heterogeneity, congestion avoidance, reliable routing, and energy conservation. To address the mentioned problems, routing protocols play a critical role in data transmission among heterogeneous items. In such environments, routing refers to constructing routes between mobile nodes. Since identifying optimal routes among IoT nodes and establishing an effective routing protocol in an IoT network are an NP‐hard issue, employing metaheuristic algorithms may be a viable solution to overcome this problem. Various IoT routing protocols based on metaheuristic algorithms have been presented in recent years, but there is still a lack of systematic study for reviewing the existing works. The current study emphasizes the impact of metaheuristic algorithms in the IoT routing problem, discusses the optimization models, presents a comprehensive comparison of protocols based on critical parameters, and eventually suggests some hints for future studies.

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Section: Related Survey Studiesmentioning

confidence: 99%

The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

Dong‐liang

Bei

Wang

2023

Int J Communication

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“…The method finds the best route with low power ingesting and prolongs the life of the network. Kaur et al 33 have examined the latest steering protocols in sensor networks and develops exploit strategies for different approaches. The design of routing protocols is one of the most promising of these systems, showing the best features needed to send information.…”

Section: Related Workmentioning

confidence: 99%

Coverage hole aware optimal cluster based routing for wireless sensor network assisted IoT using hybrid deep recurrent neural network

Srivastava¹,

Paulus²

2022

Concurrency and Computation

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Nowadays, the wireless sensor network (WSN) with IoT is intended to monitor real-world physical or environmental phenomena in a number of applications, including foreign areas such as health and habitat monitoring. The WSN-IoT network generates huge volume of data, which has to be processed and accessed by the remote users. Due to this large volume of data generation and resource constraint ability make achieving optimal cluster based routing in WSN-IoT. The location of the sensor nodes significantly affects the accuracy of the information collected, which determines the quality of service provided by the application system. WSN can have multiple conflicts, which can create different coverage holes. These holes will break the existing overlap or connection and affect the required operation of the networks. Therefore, it is essential to find and repair the coverage holes to ensure the full functioning of the WSN as a motivation of this study. In this paper, we suggest a novel Coverage Hole aware Optimal Cluster based Routing (CHOCR) scheme for WSN-IoT. First, we propose Modified Lichtenberg optimization (MLO) algorithm for balanced clustering which improve the performance of coverage hole. Second, we develop a linear equilibrium optimization based decision making (LEO-DM) technique to subtract trust value of each IoT node using multiple restraints in cluster and consider the highest trusted node is act as cluster head (CH). After that, a hybrid deep recurrent neural network (HD-RNN) is developed for intermediate node selection to frame the routing between two nodes.Finally, we simulate our proposed CHOCR scheme on the NS3.26 simulator. According to energy consumption, network longevity, number of nodes that are still alive and packet delivery ratio, packet loss ratio and throughput, end-to-end latency and delay of our proposed CHOCR routing system, we compare it to other current routing schemes.

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“…Over the years, various researchers have solved the optimal routing or path-finding problem. Most of these works in the field of wireless sensor networks (WSNs), fog, and IoT systems focus on optimal routing protocols and data forwarding techniques, which in most cases have a single objective, e.g., optimize energy usage [ 5 , 6 , 7 ]. As concluded in [ 5 ], one of the drawbacks of existing routing techniques is fixed static routing and the reliability of decision-making nodes.…”

Section: Introductionmentioning

confidence: 99%

“…Most of these works in the field of wireless sensor networks (WSNs), fog, and IoT systems focus on optimal routing protocols and data forwarding techniques, which in most cases have a single objective, e.g., optimize energy usage [ 5 , 6 , 7 ]. As concluded in [ 5 ], one of the drawbacks of existing routing techniques is fixed static routing and the reliability of decision-making nodes. The survey dedicated solely to nature-inspired algorithms for WSNs [ 8 ] concluded that these algorithms are well-suited for solving multi-objective real-world optimization problems, while traditional algorithms fail to provide satisfactory results because the problem is complex.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Path Optimization in Fog Architectures Using the Particle Swarm Optimization Approach

Morkevičius

Liutkevičius

Venčkauskas

2023

Sensors

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IoT systems can successfully employ wireless sensor networks (WSNs) for data gathering and fog/edge computing for processing collected data and providing services. The proximity of edge devices to sensors improves latency, whereas cloud assets provide higher computational power when needed. Fog networks include various heterogeneous fog nodes and end-devices, some of which are mobile, such as vehicles, smartwatches, and cell phones, while others are static, such as traffic cameras. Therefore, some nodes in the fog network can be randomly organized, forming a self-organizing ad hoc structure. Moreover, fog nodes can have different resource constraints, such as energy, security, computational power, and latency. Therefore, two major problems arise in fog networks: ensuring optimal service (application) placement and determining the optimal path between the user end-device and the fog node that provides the services. Both problems require a simple and lightweight method that can rapidly identify a good solution using the constrained resources available in the fog nodes. In this paper, a novel two-stage multi-objective path optimization method is proposed that optimizes the data routing path between the end-device and fog node(s). A particle swarm optimization (PSO) method is used to determine the Pareto Frontier of alternative data paths, and then the analytical hierarchy process (AHP) is used to choose the best path alternative according to the application-specific preference matrix. The results show that the proposed method works with a wide range of objective functions that can be easily expanded. Moreover, the proposed method provides a whole set of alternative solutions and evaluates each of them, allowing us to choose the second- or third-best alternative if the first one is not suitable for some reason.

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A survey on energy efficient routing techniques in WSNs focusing IoT applications and enhancing fog computing paradigm

Cited by 30 publications

References 42 publications

The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

Coverage hole aware optimal cluster based routing for wireless sensor network assisted IoT using hybrid deep recurrent neural network

Multi-Objective Path Optimization in Fog Architectures Using the Particle Swarm Optimization Approach

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