Connectivity Estimation Approaches for Internet of Things-Enabled Wireless Sensor Networks

Dagdeviren, Zuleyha Akusta; Akram, Vahid Khalilpour

doi:10.4018/978-1-7998-4186-9.ch006

Cited by 7 publications

(5 citation statements)

References 37 publications

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“…In [36], the authors address fault tolerance and connectivity challenges in wireless sensor networks (WSNs). They specifically focus on connection restoration and propose a simple and efficient algorithm for motion-based k-connectivity reconstruction.…”

Section: Related Workmentioning

confidence: 99%

Efficient fog node placement using nature-inspired metaheuristic for IoT applications

Naouri,

Nouri,

Khelloufi

et al. 2024

Cluster Comput

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Managing the explosion of data from the edge to the cloud requires intelligent supervision, such as fog node deployments, which is an essential task to assess network operability. To ensure network operability, the deployment process must be carried out effectively regarding two main factors: connectivity and coverage. The network connectivity is based on fog node deployment, which determines the network’s physical topology, while the coverage determines the network accessibility. Both have a significant impact on network performance and guarantee the network quality of service. Determining an optimum fog node deployment method that minimizes cost, reduces computation and communication overhead, and provides a high degree of network connection coverage is extremely hard. Therefore, maximizing coverage and preserving network connectivity is a non-trivial problem. In this paper, we propose a fog deployment algorithm that can effectively connect the fog nodes and cover all edge devices. Firstly, we formulate fog deployment as an instance of multi-objective optimization problems with a large search space. Then, we leverage Marine Predator Algorithm (MPA) to tackle the deployment problem and prove that MPA is well-suited for fog node deployment due to its rapid convergence and low computational complexity, compared to other population-based algorithms. Finally, we evaluate the proposed algorithm on a different benchmark of generated instances with various fog scenario configurations. Our algorithm outperforms state-of-the-art methods, providing promising results for optimal fog node deployment. It demonstrates a 50% performance improvement compared to other algorithms, aligning with the No Free Lunch Theorem (NFL Theorem) Theorem’s assertion that no algorithm has a universal advantage across all problem domains. This underscores the significance of selecting tailored algorithms based on specific problem characteristics.

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Section: Related Workmentioning

confidence: 99%

Efficient fog node placement using nature-inspired metaheuristic for IoT applications

Naouri,

Nouri,

Khelloufi

et al. 2024

Cluster Comput

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“…Companies require improving their service offerings and strengthening their relationships with customers (Tolstoy, Hånell, & Özbek, 2022). The internet and cloud computing allow companies for true interactivity and connectivity, customer-specific and situational personalization, and realtime adjustments of the firm's offerings (Dagdeviren & Akram, 2022). However, companies should be aware about various privacy and security issues related to the data and information collected by them from customers (Żywiołek, Trigo, Rosak-Szyrocka, & Khan, 2022).…”

Section: Increasing Roles Of Technologymentioning

confidence: 99%

The New Service Realities

Mandal

2024

Journal of Business Ecosystems

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Companies require superior services to succeed in the competition. They realize and understand the new service realities in the 21st century. The objective of the study is to analyze the various aspects of the reality. The methodology adopted is a conceptual analysis of the realities and the strategies and initiatives adopted by companies. The new service realities relate to increasing roles of technology, customer empowerment, customer co-production, and the need to satisfy both customers and employees. Enlightened companies adopt several strategies and initiatives to deal with the realities. Academicians should analyze the realities and suggest effective ways of dealing with the realities. Practicing managers focus on adopting strategies and initiatives which are effective in dealing with the new realities, developing effective customer relationships, and in achieving business excellence in the long run.

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“…Later, authors in [24] tackle fault tolerance and connectivity problems in WSNs. They focused their work on the restoration of connectivity and proposed a simple and efficient algorithm to accomplish movement-based k-connectivity restoration that divides the nodes into the critical, which are the nodes whose failure reduces k, and non-critical groups.…”

Section: Related Workmentioning

confidence: 99%

Area Coverage Maximization under Connectivity Constraint in Wireless Sensor Networks

Tossa

Ansari

Ezin

et al. 2022

Sensors

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Wireless sensor networks (WSNs) have several important applications, both in research and domestic use. Generally, their main role is to collect and transmit data from an ROI (region of interest) to a base station for processing and analysis. Therefore, it is vital to ensure maximum coverage of the chosen area and communication between the nodes forming the network. A major problem in network design is the deployment of sensors with the aim to ensure both maximum coverage and connectivity between sensor node. The maximum coverage problem addressed here focuses on calculating the area covered by the deployed sensor nodes. Thus, we seek to cover any type of area (regular or irregular shape) with a predefined number of homogeneous sensors using a genetic algorithm to find the best placement to ensure maximum network coverage under the constraint of connectivity between the sensors. Therefore, this paper tackles the dual problem of maximum coverage and connectivity between sensor nodes. We define the maximum coverage and connectivity problems and then propose a mathematical model and a complex objective function. The results show that the algorithm, called GAFACM (Genetic Algorithm For Area Coverage Maximization), covers all forms of the area for a given number of sensors and finds the best positions to maximize coverage within the area of interest while guaranteeing the connectivity between the sensors.

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Connectivity Estimation Approaches for Internet of Things-Enabled Wireless Sensor Networks

Cited by 7 publications

References 37 publications

Efficient fog node placement using nature-inspired metaheuristic for IoT applications

Efficient fog node placement using nature-inspired metaheuristic for IoT applications

The New Service Realities

Area Coverage Maximization under Connectivity Constraint in Wireless Sensor Networks

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