مشخصات مقاله | |
ترجمه عنوان مقاله | مقایسه و تحلیل روش های ادغام اطلاعات مبتنی بر هوش مصنوعی در شبکه های حسگر بی سیم |
عنوان انگلیسی مقاله | Comparison and Analysis on Artificial Intelligence Based Data Aggregation Techniques in Wireless Sensor Networks |
انتشار | مقاله سال 2018 |
تعداد صفحات مقاله انگلیسی | 9 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research article) |
مقاله بیس | این مقاله بیس نمیباشد |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
رشته های مرتبط | مهندسی کامپیوتر، فناوری اطلاعات |
گرایش های مرتبط | هوش مصنوعی، شبکه های کامپیوتری |
نوع ارائه مقاله |
ژورنال |
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 |
کلمات کلیدی انگلیسی | Data Aggregation،Particle Swarm Optimization (PSO)،Wireless Sensor Networks (WSN)،Ant Colony Optimization (ACO)،Network Lifetime |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.procs.2018.05.002 |
کد محصول | E10510 |
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- Literature Survey 3- Proposed Algorithm 4- Results Analysis 5- Conclusions and Future Work References |
بخشی از متن مقاله: |
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. Introduction Artificial intelligence (AI) includes number of techniques like Particle Swarm Optimization (PSO), Neural Networks (NN), Genetics Algorithms (GA)Ant Colony Optimization (ACO) etc. Artificial intelligence based techniques help in improvement of network lifetime & throughput. ACO may be used for the better routing to wireless sensor networks and PSOis good solution for clustering to select the best cluster head in the network. These approaches may be used in wireless sensor networks at different stages. Basically there are four energy dissipation ways in wireless sensor networks; First one is retransmitting the data, second one is overhearing means “when a particular node catch unwanted data”, third one is idle listening and fourth one is overhead of the data [14]. When data aggregation operation performed in WSN, data conflicting arises in the networks.To overcome thisissue of data conflicting in WSN environment, secure data aggregation may be considered as one of the solution. There are number of data aggregation approaches in WSNssuch as;(i) Centralized approach, (ii) In network aggregation, (iii) Cluster based approach and (iv) Tree based approach [3]. Some researcher used particle swarm optimization technique for cluster head selection. Number of cluster head in wireless sensor networks, iscalculating by equation |