دانلود رایگان مقاله انگلیسی روش های ادغام اطلاعات مبتنی بر هوش مصنوعی در شبکه های حسگر بی سیم - الزویر 2018

عنوان فارسی
مقایسه و تحلیل روش های ادغام اطلاعات مبتنی بر هوش مصنوعی در شبکه های حسگر بی سیم
عنوان انگلیسی
Comparison and Analysis on Artificial Intelligence Based Data Aggregation Techniques in Wireless Sensor Networks
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
9
سال انتشار
2018
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
نوع نگارش
مقالات پژوهشی (تحقیقاتی)
رفرنس
دارد
کد محصول
E10510
رشته های مرتبط با این مقاله
مهندسی کامپیوتر، فناوری اطلاعات
گرایش های مرتبط با این مقاله
هوش مصنوعیشبکه های کامپیوتری
مجله
مجله علوم کامپیوتر پروسیدیا - Procedia Computer Science
دانشگاه
Department of Computer Science & Engineering Jaypee University of Information Technology - Waknaghat - Solan
کلمات کلیدی
جمع آوری داده ها، بهینه سازی گروه ذرات (PSO)، شبکه های سنسور بی سیم (WSN)، بهینه سازی کلونی مورچه (ACO)، طول عمر شبکه
doi یا شناسه دیجیتال
https://doi.org/10.1016/j.procs.2018.05.002
چکیده

Abstract


In modern era WSN, data aggregation technique is the challenging area for researchers from long time. Numbers of researchers have proposed neural network (NN) and fuzzy logic based data aggregation methods in Wireless Environment. The main objective of this paper is to analyse the existing work on artificial intelligence (AI) based data aggregation techniques in WSNs. An attempt has been made to identify the strength and weakness of AI based techniques.In addition to this, a modified protocol is designed and developed.And its implementation also compared with other existing approaches ACO and PSO. Proposed approach is better in terms of network lifetime and throughput of the networks. In future an attempt can be made to overcome the existing challenges during data aggregation in WSN using different AI and Meta heuristic based techniques.

نتیجه گیری

Conclusions and Future Work


In this paper, projected work is compared with existing approaches PSO and ACO. Proposed approach is better in terms of first node dead, packets reached to the base station and all nodes dead in the network as compare to the PSO and ACO. Energy consumption is one of the most prominent research areas in WSNs. If network has less energy consumption then network lives longer. Artificial intelligence based techniques may further help in improving the network lifetime and throughput. Ant colony optimization may used for the better routing in WSNs and PSO isgood solution for clustering based data aggregation to select the cluster head in network. Fuzzy logic based approaches may be used for calculating the fitness function in the network. In future, combination of these approaches may be tried to check the suitability of these approaches for WSNs.


بدون دیدگاه