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مسیریابی آگاه از انرژی برای اینترنت اشیا با استفاده از الگوریتم بهینه سازی ملخ بهبود یافته | ||
پدافند الکترونیکی و سایبری | ||
دوره 11، شماره 1 - شماره پیاپی 41، خرداد 1402، صفحه 15-29 اصل مقاله (1.48 M) | ||
نوع مقاله: مقاله پژوهشی | ||
نویسندگان | ||
معصومه میر1؛ مهدی یعقوبی* 2؛ مریم خیرآبادی3 | ||
1دانشجوی دکترا، گروه مهندسی کامپیوتر، واحد نیشابور، دانشگاه آزاد اسلامی، نیشابور، ایران | ||
2دانشیار، گروه مهندسی کامپیوتر، واحد نیشابور، دانشگاه آزاد اسلامی، نیشابور، ایران | ||
3استادیار، گروه مهندسی کامپیوتر، واحد نیشابور، دانشگاه آزاد اسلامی، نیشابور، ایران | ||
تاریخ دریافت: 21 آذر 1400، تاریخ بازنگری: 11 اردیبهشت 1401، تاریخ پذیرش: 03 دی 1401 | ||
چکیده | ||
مصرف انرژی در فرآیند مسیریابی یکی از چالش های مهم در اینترنت اشیا است؛ چراکه گرههای شبکه از نظر منبع انرژی با محدودیت مواجه هستند. لذا ارائه الگوریتم های مسیریابی انرژی آگاه همواره مورد توجه بوده است. یکی از روش هایی که در این حوزه عملکرد قابل قبولی از خود نشان داده است؛ طرح مساله در قالب مسائل بهینه سازی است. در این مقاله یک رویکرد انرژی آگاه برای مسیریابی در اینترنت اشیا پیشنهاد گردیده که در آن از الگوریتم بهینه سازی ملخ بهبودیافته با تئوری آشوب برای زمانبندی خواب و بیدار گره ها استفاده شده است. برای بررسی کارایی روش پیشنهادی از سه معیار ارزیابی انرژی باقیمانده، طول عمر شبکه و نرخ پوشش استفاده شد. بررسی یافته ها در دو سناریو مختلف (کارایی در طول زمان و کارایی به ازای تعداد گره های مختلف) نشان داد که روش پیشنهادی همواره در تمامی سناریو ها و به ازای همه معیارهای ارزیابی کارایی بهتری نسبت به طرح های پایه دارد. | ||
کلیدواژهها | ||
مسیریابی؛ اینترنت اشیا؛ مصرف انرژی؛ تئوری آشوب؛ الگوریتم بهینه سازی ملخ | ||
عنوان مقاله [English] | ||
Energy Aware Routing in the Internet of Things using improved Grasshopper Metaheuristic Algorithm | ||
نویسندگان [English] | ||
Masoomeh Mir1؛ Mahdi Yaghoobi2؛ Maryam kheirabadi3 | ||
1PhD student, Department of Computer Engineering, Neyshabur Branch, Islamic Azad University, Neyshabur, Iran | ||
2Associate Professor, Department of Computer Engineering, Neyshabor Branch, Islamic Azad University, Neyshabor, Iran | ||
3Assistant Professor, Department of Computer Engineering, Neyshabor Branch, Islamic Azad University, Neyshabor, Iran | ||
چکیده [English] | ||
In most Internet of Things (IoT) applications, network nodes are limited in terms of energy source. Therefore, the need for innovative methods to eliminate energy loss which shortens the life of networks is fully felt in such networks. One of the optimization techniques of energy consumption on the Internet of things is efficient energy routing that the required energy can be reduced by choosing an optimal path. In this paper, an informed or efficient energy approach is proposed for routing on the Internet of Things in which focus is on the sleep-wake schedule of nodes; therefore, a new optimization algorithm called chaos fuzzy grasshopper optimization algorithm was used. In chaos fuzzy grasshopper algorithm, the initial population of grasshoppers is generated by Lorenz chaos theory and the input and output parameters of the algorithm are adjusted by fuzzy approach. To evaluate the efficiency of the proposed method, three criteria of evaluation of remaining energy, network life and coverage rate were used. Investigating the findings in two different scenarios (efficiency over time and efficiency per number of different nodes) showed that the proposed method always is better than the base methods in all scenarios and for all performance evaluation criteria. So that in the study of the death of 30% of nodes which indicates the life of the network, results showed that the proposed method of the paper (FLGOA) has 9% better efficiency than FGOA, 12% better than GOA and 16% better than GSO. Also, the findings about the remaining energy of the network showed that the proposed method has 16% better efficiency than FGOA method, 21% better than GOA and 22% better than GSO. Finally, studies in the coverage rate evaluation criterion showed that the proposed method has 12% coverage rate better than FGOA method, 15% better than GOA and 16% better than GSO. | ||
کلیدواژهها [English] | ||
Routing, Internet of Things, Chaos Theory, Fuzzy Logic, Grasshopper Optimization Algorithm | ||
مراجع | ||
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آمار تعداد مشاهده مقاله: 360 تعداد دریافت فایل اصل مقاله: 356 |