| مشخصات مقاله | |
| ترجمه عنوان مقاله | روش مسیریابی بهینه برای شبکه های حسگر بی سیم ناهمگن نرم افزار محور فعال شده با اینترنت اشیا با استفاده از PSO مبنی بر جهش ژنتیکی |
| عنوان انگلیسی مقاله | Optimized routing technique for IoT enabled software-defined heterogeneous WSNs using genetic mutation based PSO |
| انتشار | مقاله سال 2022 |
| تعداد صفحات مقاله انگلیسی | 15 صفحه |
| هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
| پایگاه داده | نشریه الزویر |
| نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
| مقاله بیس | این مقاله بیس نمیباشد |
| نمایه (index) | Scopus – Master Journals List – JCR |
| نوع مقاله | ISI |
| فرمت مقاله انگلیسی | |
| ایمپکت فاکتور(IF) |
2.487 در سال 2020 |
| شاخص H_index | 63 در سال 2020 |
| شاخص SJR | 0.556 در سال 2020 |
| شناسه ISSN | 0920-5489 |
| شاخص Quartile (چارک) | Q2 در سال 2020 |
| فرضیه | ندارد |
| مدل مفهومی | ندارد |
| پرسشنامه | ندارد |
| متغیر | ندارد |
| رفرنس | دارد |
| رشته های مرتبط | مهندسی کامپیوتر |
| گرایش های مرتبط | معماری سیستم های کامپیوتری، نرم افزار |
| نوع ارائه مقاله |
ژورنال |
| مجله | استانداردهای کامپیوتر و رابط ها – Computer Standards & Interfaces |
| کلمات کلیدی | اینترنت اشیا، شبکه حسگر بی سیم نرم افزار محور، توازن بار، بهره وری انرژی، روش مسیریابی |
| کلمات کلیدی انگلیسی | Internet of Things, Software-defined WSN, Load balancing, Energy efficiency, Routing technique |
| شناسه دیجیتال – doi |
https://doi.org/10.1016/j.csi.2021.103548 |
| کد محصول | E15573 |
| وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
| دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
| سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
| فهرست مطالب مقاله: |
| Abstract Keywords Introduction Literature review Conventional PSO System and energy dissipation model Proposed method: genetic mutation based particle swarm optimization (GMPSO) Performance analysis of the proposed method Conclusion Author statement Declaration of Competing Interest References |
| بخشی از متن مقاله: |
| ABSTRACT Now a days, emerging trends in the field of wireless sensor networks (WSNs) tend to work on more complex scenarios and flexible network models as the conventional WSN systems that are based on a classical arrangement of sensors. Generally, these networks have different limitations such as control node election, data aggregation, load balancing during data collection etc. The load balancing depends on the effective routing techniques which provide an optimum path to transmit the data such that the minimum amount of energy should be consumed. The control nodes are responsible for assigning the task and data transmission in the cluster-based routing techniques and the selection of the control node is an NP-hard problem. To resolve this problem, an adaptive particle swarm optimization (PSO) ensemble with genetic mutation-based routing is proposed to select control nodes for IoT based software-defined WSN. The proposed algorithm plays a significant role in selecting the control nodes by considering energy and distance parameters. The proposed work is implemented for the heterogeneous networks having different computing power accompanied by single and multiple sinks. The experiment was carried out on the scale of the performance matrix such as fitness value, stability period, average residual energy, etc. The simulation result of the proposed algorithm outperforms over other algorithms under the different arrangements of the network. Introduction A wireless network typically consists of several individual entities and is considered as the backbone of sensing in a remote and harsh environmental location where human intervention is not possible. The sensing task is independent of location and the sensors may have to operate in a harsh environment where the wired network can be frequently damaged and can’t be repaired. The wireless sensor network (WSN) consists of a chip-based electronic module called a sensor node to monitor and cooperatively share the collected data to the control station or server. |