ON BIG DATA MANAGEMENT IN INTERNET OF THINGS

For more Computer Science projects click here


ABSTRACT




The Internet of Things (IoT) has generated a large amount of research interest across a wide variety of technical areas. These include the physical devices themselves, communications among them, and relationships between them. One of the effects of ubiquitous sensors networked together into large ecosystems has been an enormous flow of data supporting a wide variety of applications. In this work, we propose a new “IntelliFog-Cloud” approach to IoT Big Data Management by leveraging mined historical intelligence from a Big Data platform and combining it with real-time actionable events from IoT devices at the Fog layer to reduce action latency in IoT applications. This approach is demonstrated through an advertisement service simulation with VoltDB technology where advertisements are being served on mobile phones based on geo-location and highest bids, and displayed from user interests determined by data analytics of activities on the web. Results from the demonstration show very low latency overhead of processing large hundreds of thousands of transactions. This approach improves both action latency and accuracy of real-time decisions in IoT applications.


TABLE OF CONTENTS

ABSTRACT
LIST OF FIGURES

CHAPTER ONE
INTRODUCTION
1.0       Introduction
1.1       Research Question
1.2       Objective of the Research
1.3       Implication of Research
1.4       Scope of work
1.5       Organization

CHAPTER TWO
LITERATURE REVIEW
2.0       Internet of Things (IoT)
2.0.1    Why Internet of Things?
2.0.2    Applications of IoT
2.0.3    Challenges of IoT
2.1       Big Data
2.1.1    Big Data Management
2.1.2    Big Data and Internet of Things
2.2       Data Streams
2.2.1    Data Stream Processing
2.2.2    Stream Processing Models
2.3       Real-Time Data Stream Processing
2.3.1 Requirements of Real-time Data Stream Processing
2.4       Stream Processing Applications
2.4.1    Aurora
2.4.2    Borealis
2.4.3    Apache Storm
2.4.4    Apache S4
2.4.5    Apache Samza
2.4.6    VoltDb
2.5       Related Work
2.5.1    Towards Cloud-Based Big Data Analytics for Smart Future Cities
2.5.2    A Data-Centric Framework for Development and Deployment of Internet of Things Applications in Clouds
2.5.3    A CIM-Based Framework for Utility Big Data Analytics
2.5.4    Data  Management for the Internet of Things: Design Primitives and Solution
2.5.5    An Architecture to Support the Collection of Big Data in the Internet of Things
2.5.6    Lambda Architecture
2.6       Chapter Summary

CHAPTER THREE
ANALYSIS
3.0       Latency
3.0.1    Types of Latency
3.1       Fog Computing
3.2       Multi-Tier Fog-Cloud Architecture
3.3       Analysis of the Existing/Traditional Approach
3.3.1    From Devices to Cloud
3.3.2    Existing Fog Approach
3.4       The Proposed Latency-Reducing Intelli-Fog Approach
3.4.1    The intelli-Fog Layer
3.4.2    The Cloud Layer
3.5 Chapter Summary

CHAPTER FOUR
USE CASES AND IMPLEMENTATION
4.0       Introduction
4.1       Use Case Scenarios
4.1.1    Intelligent Patient Monitoring System
4.1.2    Smart Cities (Intelligent Traffic Light)
4.1.3    Geo-Location and User Interest Based Mobile Advertisement display
4.2       Use Case Implementation (Intelli-Fog Advertisement Display Based on Location and User Interest)
4. 2.1   Technology and Tools
4.2.2    The Developed Advertisement Display Simulation
4.4       Chapter Summary

CHAPTER FIVE
SUMMARY, CONCLUSION AND RECOMMENDATION
5.0       Summary
5.1       Conclusion
5.2       Recommendations
References
Appendix


CHAPTER ONE


INTRODUCTION

1.0         Introduction

Advances in sensor technology, communication capabilities and data analytics have resulted in a new world of novel opportunities. With improved technology such as nanotechnology, manufacturers can now make sensors which are not only small enough to fit into anything and everything but also more intelligent. These sensors can now pass their sensing data effectively and in real time due to improvements in communication protocols among devices. There are now, also, emerging tools for processing these data. These phenomena combined have made the Internet of Things (IoT) a topic of interest among researchers in recent years. Simply put, the IoT is the ability of people’s “things” to conn ect with anything, anywhere and at any time using any communication medium. “Things” here means connected devices of any form. It is estimated that by 2020 there will be 50 to 100 billion devices connected to the internet [2]. These devices will generate an incredible amount of massively heterogeneous data. These data, due to their size, rate at which they are generated and their heterogeneity are referred to as “Big Data”. Big Data can be defined with the famous thre e characteristics known as the 3Vs: volume, variety, and velocity or sometimes 5Vs, including Value and Veracity [3], [12]. These data, if well managed, can give us invaluable insights into the behaviour of people and “things”; an insight that can have a wide range of applications.



The potentials of incorporating insights from IoT data into aspects of our daily lives are becoming a reality at a very fast rate. The acceptability and trust level is also growing as people have expressed willingness to apply IoT data analytics results in situations even as delicate as stock market trading [1]. These developments inform the need for efficient approaches to manage and make use these huge and fast-moving data streams. Distributed processing frameworks such as Hadoop have been developed to manage large data but not data streams. One major limitation of distributed settings such as Hadoop is latency. They are still based on the traditional Store-Process-and-Forward approach which makes them unsuitable for real-time processing, a contrast with the real-time demands of the current and emerging application areas

Store and forward also will not be able to satisfy the latency requirements of IoT data because of the velocity and the unstructured nature of the data. Stream processing frameworks like Apache Storm and Samza are then introduced to solve this problem. In stream processing, data from data sources are continuously processed as they arrive and do not need to be stored first. This improves latency, especially in stateless stream processing..... 

For more Computer Science projects click here
___________________________________________________________________________
This is a Postgraduate Thesis and the complete research material plus questionnaire and references can be obtained at an affordable price of N3,000 within Nigeria or its equivalent in other currencies.


INSTRUCTION ON HOW TO GET THE COMPLETE PROJECT MATERIAL

Kindly pay/transfer a total sum of N3,000 into any of our Bank Accounts listed below:
·         Diamond Bank Account:
A/C Name:      Haastrup Francis
A/C No.:         0096144450

·         GTBank Account:
A/C Name:      Haastrup Francis
A/C No.:         0029938679

After payment, send your desired Project Topic, Depositor’s Name, and your Active E-Mail Address to which the material would be sent for downloading (you can request for a downloading link if you don’t have an active email address) to +2348074521866 or +2348066484965. You can as well give us a direct phone call if you wish to. Projects materials are sent in Microsoft format to your mail within 30 Minutes once payment is confirmed. 

--------------------------------------------------------
N/B:    By ordering for our material means you have read and accepted our Terms and Conditions


Terms of Use: This is an academic paper. Students should NOT copy our materials word to word, as we DO NOT encourage Plagiarism. Only use as guide in developing your original research work.

Delivery Assurance
We are trustworthy and can never SCAM you. Our success story is based on the love and fear for God plus constant referrals from our clients who have benefited from our site. We deliver project materials to your Email address within 15-30 Minutes depending on how fast your payment is acknowledged by us.

Quality Assurance
All research projects, Research Term Papers and Essays on this site are well researched, supervised and approved by lecturers who are intellectuals in their various fields of study.
Share:

No comments:

Post a Comment

Note: Only a member of this blog may post a comment.

Search for your topic here

To view a full list of Project Topics under your Department

Featured Post

Article: How to Write a Research Proposal

Most students and beginning researchers do not fully understand what a research proposal means, nor do they understand ...

Popular Posts