مشخصات مقاله | |
ترجمه عنوان مقاله | حداکثرسازی طول عمر شبکه حسگر بی سیم متحرک با استفاده از روش های محاسباتی تکاملی |
عنوان انگلیسی مقاله | Mobile wireless sensor network lifetime maximization by using evolutionary computing methods |
انتشار | مقاله سال 2020 |
تعداد صفحات مقاله انگلیسی | 13 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) |
4.301 در سال 2019 |
شاخص H_index | 79 در سال 2020 |
شاخص SJR | 0.648 در سال 2019 |
شناسه ISSN | 1570-8705 |
شاخص Quartile (چارک) | Q1 در سال 2019 |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | مهندسی فناوری اطلاعات، مهندسی کامپیوتر |
گرایش های مرتبط | شبکه های کامپیوتری، مهندسی الگوریتم و محاسبات |
نوع ارائه مقاله |
ژورنال |
مجله | شبکه های ادهاک – Ad Hoc Networks |
دانشگاه | Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin 300387, China |
کلمات کلیدی | شبکه حسگر بی سیم، حداکثرسازی طول عمر، محاسبات تکاملی، انرژی کارآمد، بهینه سازی |
کلمات کلیدی انگلیسی | wireless sensor network، lifetime maximization، evolutionary computing، energy efficient، optimization |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.adhoc.2020.102094 |
کد محصول | E14644 |
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 1. Introduction 2. Lifetime model of the mobile wireless sensor network 3. Evolutionary computing algorithms 4. Simulation experiment 5. Conclusion Declaration of Competing Interest Acknowledgments Appendix. Supplementary materials Research Data References |
بخشی از متن مقاله: |
Abstract
Due to the continuous development and progress of wireless communication technology and sensor network technology, wireless sensor networks (WSNs) have gradually become an attractive technology that facilitates people’s lives. Due to the extensive use of WSNs, maximizing the lifetime of WSNs to obtain real-time and effective information has become a critical concern. This paper studies the life of mobile wireless sensor networks (MWSNs). MWSNs are a special type of WSN in that the sensor nodes are movable within a certain area. A system model is developed to prolong the network lifetime of MWSNs. This paper uses five evolutionary computing (EC) algorithms to develop the MWSN lifetime optimization model. Numerical simulations are performed to study the advantages and disadvantages of the five algorithms for solving the model. The comparison and discussion can provide advice for using EC algorithms to solve MWSN lifetime maximization problems. Introduction Due to the continuous development and progress of wireless communication technology, network technology, microprocessor technology and sensor network technology, WSNs have gradually become an attractive technology that facilitates people’s lives [1]-[5]. Moreover, WSNs are a new way to acquire information through real-time monitoring of the environment. Because of their unique way of obtaining information, WSNs are widely used in various fields, such as military defense, biological medicine, smart home technology, industry and agriculture [2], [3]. As the capacity of battery of nodes is limited, the operational longevity of nodes is critical. The longevity of a WSN directly affects the overall performance of the network [4]. MWSNs are a special distributed network of many deployed sensor nodes that are movable within a monitoring area. MWSNs form a selforganizing network through wireless communication technology [5]. Unlike in static WSNs, the mobility of sensors or sink nodes in MWSNs causes network topology to change dynamically. Thus, compared to when designing static WSNs, more issues have to be addressed when designing mobile networks [4]. Recently, there have been studies on the lifetime of MWSNs. [6] studied maximizing the lifetime of MWSNs that contained mobile sink nodes. In [7], the exploration and exploitation trade-off was studied, and different methods were compared. |