ntvНаучно-технический вестник информационных технологий, механики и оптикиScientific and Technical Journal of Information Technologies, Mechanics and Optics2226-14942500-0373Университет ИТМО10.17586/2226-1494-2024-24-1-81-89ntv-134Research ArticleКОМПЬЮТЕРНЫЕ СИСТЕМЫ И ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИCOMPUTER SCIENCEНовый стратегический траекторно-базированный протокол для повышения эффективности беспроводных сенсорных сетейA novel strategic trajectory-based protocol for enhancing efficiency in wireless sensor networkshttps://orcid.org/0000-0003-2456-265XГопалакришнанР.GopalakrishnanR.

Гопалакришнан Рангарадж — PhD, исследователь

 Салем, 636011 

Rangaraj Gopalakrishnan — PhD, Research Scholar

 Salem, 636011

gopaldharun1978@gmail.comhttps://orcid.org/0000-0001-5131-7428Сентил КумарА.Senthil KumarA.

Сентил Кумар Ангамуту — PhD, доцент

 Расипурам, 637401

sc 57674299700

Angamuthu Senthil Kumar — PhD, Assistant Professor

 Rasipuram, 637401

sc 57674299700

senthilkumarmca76@gmail.comУниверситет ПериярИндияPeriyar UniversityIndiaГосударственный колледж искусств ТируваллувараИндияThiruvalluvar Government Arts CollegeIndia2024131220242418189Copyright © Гопалакришнан Р., Сентил Кумар А., 20242024Гопалакришнан Р., Сентил Кумар А.Gopalakrishnan R., Senthil Kumar A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://ntv.elpub.ru/jour/article/view/134

Исследован комплексный подход к повышению эффективности и производительности беспроводных сенсорных сетей путем решения критических проблем, таких как условия гонки, проблемы резервирования и избыточные данные. Для решения этих проблем предложен новый протокол, сочетающий в себе самоадаптирующуюся кластеризацию с устранением избыточности и управление полосой пропускания распределенной нагрузки. Используется разумный способ для извлечения функции передачи сообщений с «перескоком» через узлы (их пропуском) и передачи сообщений любому из ближайших узлов. Для этого используется информация о разнесенном трафике, получаемая на основе файлов трассировки, исключая узлы с избыточными данными. Количество кластеров динамически регулируется в зависимости от плотности узлов, используя метод распространения сходства. Балансировка нагрузки достигается посредством перераспределения доступной полосы пропускания и повторной сегментации полосы пропускания. В исследовании представлена предлагаемая сетевая инфраструктура и координация каналов. Архитектура включает в себя совместную кластеризацию узлов, выбор точки доступа, сжатие данных и миграцию каналов. Эффективность сети значительно повышается за счет взаимодействия между узлами внутри кластеров, разумного выбора точек доступа и использования эффективных методов сжатия данных. Стратегия миграции каналов еще больше повышает гибкость и оперативность сети. Интеграция способности обнаружения канала обогащает подход за счет сбора информации о состоянии канала и дополнения пространственной и временной информации об узлах. Эта дополнительная информация позволяет сети принимать более обоснованные решения относительно распределения и координации каналов, способствуя снижению помех и оптимизации передачи данных. Предложенная методология позволила получить средний коэффициент доставки пакетов (PDR) равный 99,1 % и среднее снижение потерь пакетов на 4,3 % по сравнению с существующими исследованиями. Новый протокол продемонстрировал повышение средней пропускной способности на 4,7 % и снижение средней задержки сети до 52 мс, что подчеркивает его значительный вклад в увеличение производительности WSN.

This research presents a comprehensive approach to enhance the efficiency and performance of Wireless Sensor Networks (WSNs) by addressing critical challenges, such as race conditions, reservation problems, and redundant data. A novel protocol combining Self-Adaptive Redundancy Elimination Clustering and Distributed Load Bandwidth Management is proposed to mitigate these challenges. The work intelligently extracts transmission hops and any-cast transmission features from diversity traffic information obtained through trace files, to eliminate nodes harboring redundant data. To optimize network organization, the number of clusters is dynamically adjusted according to the node density using the affinity propagation technique. Furthermore, load balancing is achieved by reallocating available bandwidth through bandwidth re-segmentation. The research also delves into the Proposed Network Infrastructure and Channel Coordination. The architecture encompasses cooperative clustering of nodes, strategic access point selection, data compression, and channel migration. By fostering collaboration among nodes within clusters, selecting access points judiciously, and employing efficient data compression techniques, the network overall efficiency is significantly improved. Channel migration strategies further bolster the network agility and responsiveness. The integration of Channel Sensing enriches the approach by collecting channel state information, enriched with spatial and temporal node information. This added insight empowers the network to make more informed decisions regarding channel allocation and coordination contributing to reduced interference and optimized data transmission. As a result of the work, the proposed methodology achieves remarkable results, including an average Packet Delivery Ratio of 99.1 % and an average reduction of packet loss by 4.3 % compared to existing studies. Additionally, the proposed protocol exhibits an average throughput improvement of 4.7 % and reduces average network delay to 52 milliseconds highlighting its significant contributions to the enhancement of WSN performance.

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The authors declare that there are no conflicts of interest present.