Computational intelligent techniques for resource management schemes in wireless sensor networks

Kori, Gururaj S.; Kakkasageri, Mahabaleshwar S.; Manvi, Sunilkumar S.

doi:10.1016/b978-0-12-822844-9.00023-2

Cited by 6 publications

(6 citation statements)

References 79 publications

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“…Product improvement requires innovation in order to gain a competitive advantage in the market (business success; He L. et al, 2020 ; Wang et al, 2021 ). Not all small and medium-sized businesses, however, can afford the high cost of innovation ( Kori et al, 2021 ; Zheng et al, 2021 ). Therefore, the industrial design service platform based on collaborative innovation between industry and university research frequently plays an important role in small and medium-sized business innovation ( Lawson, 2005 ; Shao X.-F. et al, 2021 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Investigate the Influencing Factors of Industrial Design Platform Demand: From the Perspective of Emotional Interaction

Zhang¹,

Yang²,

Tong³

et al. 2022

Front. Psychol.

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With the deep integration of industries brought about by big data technology, users’ design needs are diversifying and individuating. Thanks to big data technology, users’ diverse design needs can be precisely met. Meanwhile, big data can be used to realize emotional interaction for personalized design needs of users, resulting in a better user experience. Using grounded theory to mine user demand text data, this paper investigates the influencing factors of emotional interaction and dynamic resource allocation in the digital design supply chain. The results show that government-driven factors have a direct impact on the demand for industrial design in user emotional interactions. Market factors are the most fundamental in the development of an industrial design service platform, and universities play an important role in this. Furthermore, a lack of market sensitivity stems from a lack of emotional interaction with users, resulting in a schism between industry, university, and research, which has become a major impediment to the development of China’s industrial design industry. This study not only lays the theoretical groundwork for understanding the mechanisms of user emotional interaction on IDSPs, but it also points the way forward for future industrial design service platform development.

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Section: Literature Reviewmentioning

confidence: 99%

Investigate the Influencing Factors of Industrial Design Platform Demand: From the Perspective of Emotional Interaction

Zhang¹,

Yang²,

Tong³

et al. 2022

Front. Psychol.

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“…Wireless networks have revolutionized communication, and wireless sensor networks (WSNs) have brought about significant advancements in ubiquitous computing, smart systems, and the Internet of Things [1]. WSNs comprise several tiny sensor nodes that are densely deployed inside or near the phenomenon to be sensed.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, WSNs use cooperative effort, as each sensor node is fitted with an onboard processor that carries out simple computations and transmits only required and partially processed data rather than sending raw data to nodes responsible for fusion [2]. WSNs are highly distributed and self-aware networks that face resource problems, such as power consumption, processing speed, communication range, and available bandwidth [1]. A genenaral form of aWSN architecture is shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Parameters of LEACH Protocol for Efficient Routing in Wireless Sensor Networks

Verma¹

2023

JCMM

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The increasing popularity of wireless sensor networks can be attributed to their unique characteristics, which include high density, low power consumption, software programmability, and long-term accuracy. This paper presents a thorough analysis of key parameters for sensor network applications, including network lifetime, packet delivery ratio, energy-efficient transmission, and dead node ratio. This paper examines the effectiveness of clustering in wireless sensor networks for achieving efficiency. The research focuses on the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol and proposes an enhanced algorithm that improves network lifetime, throughput, and the number of living nodes. This paper evaluates the performance of the improved LEACH protocol and compares it to other protocols currently in use. The results indicate that the proposed method significantly improves the performance of the protocol, making it a promising method for efficient routing in wireless sensor networks. This study is an important contribution to the field of wireless sensor networks and can aid in the creation of more efficient and effective protocols for various sensor network applications.

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“…Nodes with no energy create voids in the network which increases the re-transmission rate and packet drops which consume more energy (1) . The performance of WSN depends on resource https://www.indjst.org/ management which addresses scalability, reliability, stability and efficiency of the network (2) . Extending the network lifetime and management of resources is established through efficient network topology where the transmission and communication power of the sensors are kept at the maximum (3) .…”

Section: Introductionmentioning

confidence: 99%

A Novel Energy Efficient Cluster Based Routing in Wireless Sensor Network

Subhash¹,

Kumuthini²

2023

IJST

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Objective: Network lifetime of WSN can be extended through assigning nodes with higher energy levels as cluster heads. Cluster heads selection improves the packet transmission rate and conserves energy by reducing re-transmission. The proposed algorithm assigns nodes with high energy as clusters heads and finds optimal path which improves network coverage by avoiding dead nodes. Methods: To improve network lifetime and conserve node energy, a novel approach which involves optimum cluster head selection using Firefly algorithm (FF) and Glow Swarm Optimization (GSO) algorithm for routing in WSN (FFGSO) was developed. The cluster head selection is designed to be multi-objective function which meant for not only minimizing the energy consumption but also to minimize the distance and to improve coverage. Findings: The proposed model reduces energy consumption to about 16.21% which avoids dead nodes effectively and finds the shortest path to reach sink which eventually improves network coverage and improves the throughput by 9.52%. Novelty: To overcome the limitations of dead nodes and to improve the network lifetime, the proposed method introduces cluster head selection as a multi-objective function. To improve energy consumption, network lifetime and network coverage and to overcome the limitations of PSO-GSO, Leach and FF-PSO cluster head selection is designed as multi-objective function. The proposed method improves network stability and network lifetime through reducing energy consumption and finding the shortest path.

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Computational intelligent techniques for resource management schemes in wireless sensor networks

Cited by 6 publications

References 79 publications

Investigate the Influencing Factors of Industrial Design Platform Demand: From the Perspective of Emotional Interaction

Investigate the Influencing Factors of Industrial Design Platform Demand: From the Perspective of Emotional Interaction

Enhancing Parameters of LEACH Protocol for Efficient Routing in Wireless Sensor Networks

A Novel Energy Efficient Cluster Based Routing in Wireless Sensor Network

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