Developing parallel technique for the internet of things devices by using local map reduce at the sink node

العناوين الأخرى

تطوير تقنيات موازية لأجهزة إنترنت الأشياء باستخدام متعقب الوظيفة المحلي في عقدة التجميع

مقدم أطروحة جامعية

Uways, Muna George

مشرف أطروحة جامعية

al-Hammuz, Sadiq

أعضاء اللجنة

Ahmad, Mamun
Abu Arqub, Abd al-Rahman
al-Ababinah, Muhammad Fandi

الجامعة

جامعة الشرق الأوسط

الكلية

كلية تكنولوجيا المعلومات

القسم الأكاديمي

قسم علم الحاسوب

دولة الجامعة

الأردن

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2016

الملخص الإنجليزي

Due to the accelerating demand on the Internet of things (IoT) objects in which the Wireless Sensor Network (WSN) is the main source of Big Data, the huge scaled data is gathered excessively, causing network traffic problems and consuming huge amounts of power and an enormous size of memory which, in turn, would affect the network’s performance.

In order to address the issues of network performance related to Big Data, several research studies were conducted in an attempt to provide both convenient and effective solutions for such issues.

This thesis aimed at providing parallel, localized technique for IoT devices utilizing MapReduce at the sink node rather than employing this technique to agents’ wireless or storage devices.

In this study, the dataset was generated using a Java code, and MATLAB software programming tools (Math Works, R2015a) were used.

MapReduce was used twice in order to manage big data; the first time for producing key value pairs, and the second time for reading pairs on the sensor to produce all distinct reading.

The results showed that the MapReduce approach utilized in this work resulted in less power consumption, less network traffic, and more efficient memory usage.

MapReduce outperformed the traditional protocols by (Paik, Nam, Kim, & Won, 2014).

The data reduction by utilizing the MapReduce approach was found to reach 79% in comparison to the 63% reported by others in the literature.

We also found 43% enhancement of throughput and 27% less energy consumption with MapReduce compared to traditional protocols in WSNs.

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

عدد الصفحات

66

قائمة المحتويات

Table of contents.

Abstract.

Abstract in Arabic.

Chapter One : Introduction.

Chapter Two : Theoretical framework and literature review.

Chapter Three : Methodology.

Chapter Four : Results and discussion.

Chapter Five : Conclusions and future works.

References.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Uways, Muna George. (2016). Developing parallel technique for the internet of things devices by using local map reduce at the sink node. (Master's theses Theses and Dissertations Master). Middle East University, Jordan
https://search.emarefa.net/detail/BIM-721110

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Uways, Muna George. Developing parallel technique for the internet of things devices by using local map reduce at the sink node. (Master's theses Theses and Dissertations Master). Middle East University. (2016).
https://search.emarefa.net/detail/BIM-721110

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Uways, Muna George. (2016). Developing parallel technique for the internet of things devices by using local map reduce at the sink node. (Master's theses Theses and Dissertations Master). Middle East University, Jordan
https://search.emarefa.net/detail/BIM-721110

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-721110