MongoDB Database Management System

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Table of Content

• INTRODUCTION OF THE NOSQL DATABASE MANAGEMENT SYSTEM
• What is NoSQL?
• Types of NoSQL Databases
• Why NoSQL?
• The Growth of Big Data
• Continuous Data Availability
• Real Location Independence
• Modern Transactional Capabilities
• Flexible Data Models
• Better Architecture
• Analytics and Business Intelligence
• NoSQL vs Relational DBMS
• Advantages
• Disadvantages
• DATA MODELLING CONCEPTS (WITH EXAMPLES)
• HOW MONGODB STORE AND MANAGE DATA
• FEATURES AND CAPABILITIES OF MONGODB IN ENSURING DATABASE SECURITY INTEGRITY AND PERFORMANCE
• Integrity
• Atomicity in MongoDB
• Write Durability
• Security
• Authentication
• Authorization
• Encryption
• Auditing
• Governance
• Performance
• Indexing
• Query Optimization
• Working Sets
• Dynamic Data Balancing
• STRENGTHS AND WEAKNESSES OF MONGODB
• Strengths
• Easy to scale out
• Flexible document data model
• Replication and high availability
• Better performance when used correctly
• Rich query capabilities
• Weaknesses
• Not recommended for relational data
• No internal transaction support
• MONGODB REAL WORLD APPLICATIONS
• SPECIFICATION REQUIREMENTS OF MONGODB
• Conclusion
• References

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Introduction

A NoSQL database environment is, simply put, a non-relational and largely distributed database system that enables rapid, ad-hoc organization and analysis of extremely high-volume, disparate data types. NoSQL databases are sometimes referred to as cloud databases, non-relational databases, Big Databases and a myriad of other terms and were developed in response to the sheer volume of data being generated, stored and analyzed by modern users (user-generated data) and their applications (machine-generated data). In general, NoSQL databases have become the first alternative to relational databases, with scalability, availability, and fault tolerance being key deciding factors. They go well beyond the more widely understood legacy, relational databases (such as Oracle, SQL Server and DB2 databases) in satisfying the needs of today’s modern business applications. A very flexible and schema-less data model, horizontal scalability, distributed architectures, and the use of languages and interfaces that are “not only” SQL typically characterize this technology. From a business standpoint, considering a NoSQL or ‘Big Data’ environment has been shown to provide a clear competitive advantage in numerous industries. In the ‘age of data’, this is compelling information as a great saying about the importance of data is summed up with the following “if your data isn’t growing then neither is your business”.

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TinyOS An Operating System For Sensor Networks

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Table of Content

• Introduction
• Background
• Overview of TinyOS
• Purporse of TinyOS
• Small Form Factor & Low Energy Usage
• Concurrency Intensive Operation
• Limited Physical Parallelism & Controller Hierarchy
• Flexibility
• Application of TinyOS
• Habitat Monitoring
• Object Tracking
• TinyDB
• Review & Discussion
• Uniqueness
• Comparison
• Key Distribution
• Decryption
• Conclusion
• References

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Introduction

Advances in technology in the fields of networking and integration have contributed to the emergence of nodes that are flexible, inexpensive, and have tiny form factors. The nodes are equipped with sensors, actuators, and communication capabilities that allow them to have interaction with their surrounding environment. Systems that only utilize a single chip are now emerging where low-power CPU and memory, radio or optical communication are all integrated [1]. Sensor networks are a very active research space, with ongoing work on networking [2, 3, 4], application support [5, 6, 7], radio management [8, 9], and security [10, 11, 12, 13], as a partial list. A primary goal of TinyOS is to enable and accelerate this innovation.

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Multi Server Queue Simulation Using C# Source Code

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Program Interface

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Application of Discrete Mathematics RSA Algorithm Report

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Table of Content

• Introduction
• Mathematical Prerequisites
• Euler's Totient Function
• Coprime Integers
• Modular Multiplicative Inverse
• Euler's Theorem
• Modulo Congruence
• Operation
• Generating Public & Private Keys
• Encryption
• Key Distribution
• Decryption
• Working Example
• Alternative Solution
• Caesar Cipher
• RSA Reliability & Advantages
• Prime Generation & Integer Factorization
• Modular Exponetiation and Roots
• Advantages of RSA over Caesar Cipher
• Conclusion

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Introduction

Number theory may be one of the “purest” branches of mathematics, but it has turned out to be one of the most useful when it comes to computer security. For instance, number theory helps to protect sensitive data such as credit card numbers when you shop online. This is the result of some remarkable mathematic research from the 1970s that is now being applied worldwide.

Sensitive data exchanged between a user and a Web site needs to be encrypted to prevent it from being disclosed to or modified by unauthorized parties. The encryption must be done in such a way that decryption is only possible with the knowledge of a secret decryption key. The decryption key should be known by authorized parties.

This is the concept of public-key cryptography. The distinguishing technique used in public-key cryptography is the use of asymmetric key algorithms, where a key used by one party to perform either encryption or decryption is not the same as the key used by another in the counterpart decryption. RSA is one of the asymmetric algorithms.

RSA is one of the first practical public-key cryptosystems and is widely used for secure data transmission. In RSA, this asymmetry is based on the practical difficulty of factoring the two products of two large prime numbers, the factoring problem. RSA is made of the initial letters of the surnames of Ron Rivest, Adi Shamir, and Leonard Adleman, who first publicly described the algorithm in 1977.

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Smart Parking System Based On Wireless Sensor Network Report

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Table of Content

• Abstract
• Introduction
• Existing Approach
• Issue/Problems
• Absence of Parking Guidance
• Undetermined Parking Availability
• Absence of Parking Pricing & Regulations Information
• Poor Law Enforcement
• Inconvenient Payment Solution
• Absence of Parking Analytic Data
• Solution
• Mobile Application Solution
• Wireless Sensor Network
• Guided Parking Enforcement
• Mobile Payment Solution
• Concept Art
• Network Architecture & Protocol Stack
• Introduction
• Sensor Node Structure
• Architecture
• Protocol Stack
• Application Layer
• Transport Layer
• Network Layer
• Data Link Layer
• Physical Layer
• Literature Review
• Parking Guidance & Information Systems (PGIS)
• Transit-Based Smart Parking System
• Smart Payment Solution
• E-Parking
• Other WSN based Systems
• Potential Flaws & Ways To Overcome
• Summary
• Citation
• Works Cited

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Introduction

Parking, the most agonizing experience any urban driver can have. The thoughts that come to mind are often quite negative. When it comes to finding a parking space, drivers either rely on their good eyesight where they make move as soon as they lock-on a target or they just simply bet on their instincts where each turn they make hopefully will lead to a jackpot. People can spend up to hours just to find one parking space. Not only does this make the drivers go nuts, it also contributes to traffic congestion and even environmental pollution. However, it isn’t always about the driver. Shops and local businesses are also heavily affected by the parking availability near them. On the other hand, from time to time some portion of the people just doesn’t feel like abiding the rules. This is where parking violations comes in that ruins the parking enforcement laws. As we look at ways to apply technology to tackle some of the most pressing issues facing our cities today, parking is sure ripe for some innovation. Below are some interesting facts provided by Cisco that tells us a little bit more about parking.

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Wireshark Lab ARP Solution

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1.  Write down the contents of your computer’s ARP cache (see above procedure: Step 1).  What is the meaning of each column value?

Answer: The Internet Address column represents the IP address of the computer at the network layer, the Physical Address column contains the MAC address to physically communicate with the hardware that is located at that IP address, and the Type column indicates whether it is changing (dynamic) or not (static).

2.  Where in the ARP request does the “question” appear – the Ethernet address of the machine whose corresponding IP address is being queried? (see Wireshark).

Answer: The “question” appears in the ‘Target MAC address’.

3.  Why is the ARP request message sent as broadcast (i.e. to all other devices), whereas the ARP reply is sent as a unicast directly to the sender device only? Explain.

Answer: ARP requests are sent as broadcast because the destination or the target device is yet unknown. Broadcasting will be faster and more efficient to look for the device that matches the address of the request. ARP replies are sent as unicast because a connection has been established between two devices, therefore direct communication can be formed.

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Wireshark Lab IP Solution

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1.  Within the IP packet header, what is the value in the protocol field? What does this value mean?

Answer: The value in the protocol field is ICMP (1). It means the protocol field has only 1 byte.

2.  How many bytes are in the IP header? How many bytes are in the payload of the IP datagram?  Explain how you determined the number of payload bytes.

Answer: There are 20 bytes in the IP header, and 92 bytes total length, this gives 72 bytes in the payload of the IP datagram.

3.  Which fields in the IP datagram always change from one datagram to the next within this series of ICMP messages sent by your computer? Explain why they change.

Answer: Identification, Time to live and Header checksum always change. The identification is a unique value. Different IP packets must have different IDs to identify themselves. TTL always changes because traceroute increments each subsequent packet. Header checksum changes because since header change, checksum must also change.

4.  What is the value in the Identification field and the TTL field?

Answer: 

The value in the identification field is 46463.

The value in the TTL field is 255.

5.  Do these values (referring to question 4) remain unchanged for all of the ICMP TTL-exceeded replies sent to your computer by the nearest (first hop) router?  Why?

Answer: The identification field changes for all the ICMP TTL-exceeded replies because the identification field is a unique value. When two or more IP datagrams have the same identification value, then it means that these IP datagrams are fragments of a single large IP datagram.

The TTL field remains unchanged because the TTL for the first hop router is always the same.

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