Healthcare: A priority-based energy harvesting scheme for managing sensor nodes in WBANs

Gherairi, Salsabil

doi:10.1016/j.adhoc.2022.102876

Cited by 14 publications

(4 citation statements)

References 38 publications

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“…The average waiting time was calculated as the difference between the turnaround time and the burst time. These calculations are presented in (18) to (20). The average waiting time was found to be 6.57143 while the average turnaround time was 10.1429 as calculated from Table 4.…”

Section: Definition (Priority Scheduling Nonpreemptive Algorithm)mentioning

confidence: 95%

“…However, in the proposed scheme, the coordinator receives small-sized data packets in very short intervals; furthermore, the coordinator forwards the information to the decision-maker for critical rescue operations. The following points highlight the significant contributions made by this work: [5], lowrate wireless personal area networks (LR-WPAN) [20], and priority-based adaptive schemes [5,20].…”

Section: Application Of Resource Allocation Methods In Wbanmentioning

confidence: 99%

“…Tavg represents the average transmission delay which is the total time required to transmit data packets in a minimal interval from the sensor node to the coordinator. It can be evaluated in [20] as follows:…”

Section: Transmission Timementioning

confidence: 99%

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Priority-Based Resource Allocation and Energy Harvesting for WBAN Smart Health

Selvaprabhu

Chinnadurai

Tamilarasan

et al. 2022

Wireless Communications and Mobile Computing

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With the emergence of new viral infections and the rapid spread of chronic diseases in recent years, the demand for integrated short-range wireless technologies is becoming a major bottleneck. Implementation of advanced medical telemonitoring and telecare systems for on-body sensors needs frequent recharging or battery replacement. This paper discusses a priority-based resource allocation scheme and smart channel assignment in a wireless body area network capable of energy harvesting. We investigate our transmission scheme in regular communication, where the access point transmits energy and command while the sensor simultaneously sends the information to the access point. A priority scheduling nonpreemptive algorithm to keep the process running for all the users to achieve the maximum reliability of access by the decision-maker or hub during critical situations of users has been proposed. During an emergency or critical situation, the process does not stop until the decision-maker or the hub takes a final decision. The objective of the proposed scheme is to get all the user processes executed with minimum average waiting time and no starvation. By allocating a higher priority to emergency and on data traffic signals such as critical and high-level signals, the proposed transmission scheme avoids inconsistent collisions. The results demonstrate that the proposed scheme significantly improves the quality of the network service in terms of data transmission for higher priority users.

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Section: Definition (Priority Scheduling Nonpreemptive Algorithm)mentioning

confidence: 95%

Section: Application Of Resource Allocation Methods In Wbanmentioning

confidence: 99%

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Priority-Based Resource Allocation and Energy Harvesting for WBAN Smart Health

Selvaprabhu

Chinnadurai

Tamilarasan

et al. 2022

Wireless Communications and Mobile Computing

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“…The work identifies the major sources of energy depletion and follows up with a 2-hop routing model that can be energy efficient and also can effectively handle issues occurring due to posture changes. Other similar routing models for energy awareness include the grey wolf optimization-based model [21] and the energy harvesting-based model [22]. A comparative analysis of the discussed literature works has been tabulated and provided in Table 1.…”

Section: Introductionmentioning

confidence: 99%

Metaheuristic based routing incorporated with energy harvesting for enhanced network lifetime in WBAN

Sathya

Evanjaline

2023

Bulletin EEI

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Wireless body area networks (WBAN) have improved healthcare industries to a large extent by providing contactless measurements and remote data analysis. However, the challenges encountered are mostly in the form of energy depletion scenarios, which results in the reduction of network lifetime to a large extent. This work presents an effective model to provide energy-efficient routing and enhanced energy harvesting mechanisms to improve network lifetime. The ant colony optimization (ACO) method has been extended to include a fitness function that takes into account several factors, and this is the basis for the routing model. These processes ensure effective routing, which conserves energy and, in turn, results in enhanced network lifetime. Performance of the proposed model has been compared with the existing state-of-the-art models in the domain. Comparison with the metaheuristic-based model, cooperative energy efficient and priority based reliable routing protocol with network coding (CEPRAN), indicates the efficiency of the energy harvesting mechanism used in the proposed work. When compared with models using energy harvesting mechanisms, results exhibit higher network lifetime, depicting the efficiency of the proposed routing mechanism.

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