Computer Science UGC Net

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Topology in Computer Networks

Network Topology The arrangement in which elements like links, nodes of common network are connected is known as network topology. Example of Network topology is found in local area network. We have five types of topologies : 1.) Mesh Topology 2.) Bus Topology 3.) Ring Topology 4.) Star Topology 5.) Hybrid Topology 1.) Mesh Topology : In mesh topology every device is connected with another device via a particular channel. 2.) Bus Topology : The bus topology is used when a network installation is small, simple and temporary. On a typical bus network cable is just one or more wires with no active electronics to amplify the signal or pass it along from computer to computer. This makes the bus a passive topology. Only one computer can send data at one time therefore the number of computers attached to a bus network can significantly affect the speed of the network a computer must wait until the bus is free before it can transmitted. Advantages of bus topology: E

DBMS: Normalization

Normalization : Normalization is the process of transformation of the conceptual schema of the database into a computer represent table form. Normalization is the process of removing the redundancies from incoming data. Normalization is a technique to which helps the user to group the data and place the data in a table. Normalization is a process which ensure the inconsistencies are not introduced into the database. Need of Normalization : we know with the time, most of databases grow time to time by adding new relations and relationships, the data may be used in different ways. Regularly the information may undergo series of updations in such situations, the performance of a database is entirely dependent upon its design. A bad database design may lead to certain undesirable things: Repetition of information Inability to represent certain information Loss of information Uses of Normalization: When data is large and scattered There is no defined group

Generalization and Specialization

Generalisation is an abstraction for sharing similarities among classes while preserving their differences. For example, each piece of equipment has a manufacturer weight and cost . Pumps also have suction pressure and flow rate. Tank also have volume and pressure we would like to define equipment features just once and then add details for pump, tank and other equipment types. Generalisation is a relationship between a class and one or more refined versions of it. The class being refined is called superclass and each refined version is called a subclass. For example equipment is the superclass of pump and tank. Attributes and operations common to a group of subclasses are attached to the superclass and shared by each subclass. Each subclass is set to inherit the feature of its superclass, for example, pump inherites attributes manufacturer, weight and cost from equipment. Generalisation is sometimes called the "is-a" relationship because each instance of a subclass is

Scheduling: preemptive scheduling

Preemptive Scheduling : In contrast to non preemptive scheduling, a scheduling decision can be made even while the job is executing whereas in non preemptive scheduling, a scheduling decision is made only after job completes its execution. Therefor preemptive scheduling may force a job in execution to release the processor, so that the execution of some other job can be undertaken, in order to improve throughput considerably. Types of preemptive scheduling: 1) Round Robin scheduling algorithm : the round Robin scheduling is designed for time sharing systems. The primary objective of round Robin scheduling are interactive use, good response time and sharing the resources equitable among processes. It is similar to FCFS, but preemption is added to switch between processes. The processes are alocated a small unit of time. Known as time Quantum or time slice is in rotation until the completion of processes. To implement round Robin scheduling, a FIFO(first in first out) queue

Scheduling: Non-Preemptive Scheduling

Scheduling : In multi-programmed computer, multiple processes competing for the CPU at the same time. This situation occurs whenever two or more processes are simultaneously in the ready state. If only one CPU is available. Then we need a system that decide which process run first and then next and this will be done by the scheduler. Scheduler : scheduler is an operating system module that she loves an axe top to be admitted into the system and then the next process to run. Scheduling is of two type: 1) Pre-emptive 2) Non pre-emptive Non Pre-emptive Scheduling : In batch non Pre-emptive scheduling implies that, once scheduled, selected job runs to completion. In other words, the running process not forced to relinquish ownership of the processor when a higher priority process becomes ready for execution. The scheduling techniques which use non preemptive scheduling are: 1) first come first serve (FCFS) scheduling 2) shortest job next (SJN) scheduling 3) dea

Data Mining

Data mining is the discovery of useful patterns in data. Data mining are used for prediction analysis and classification- e.g; what is the likelihood that a customer will migrate to a competitor. OLAP, online analytical processing, is used to analyse historical data and its lies the business information required. OLAP are often used by marketing managers. Slice of data that are useful for marketing managers can be- How many customers between the ages 24 -25, that live in New York state, buy over $2,000 worth of groceries a month? Reporting tools are used to provide reports on the data. That are displayed to show relevance to the business and keep track of key performance indicators. Data visualization tools is used to display data from the data repository. Often data visualization is combined with data mining and OLAP tools. Data visualization can allow the user to manipulate that are to show relevancy and patterns. Clustering: Intuitively, clustering was the problem of

Data Warehousing

Data Warehouse is open to an almost limitless range of definitions. Simply put, data warehouses store and aggregation of a company's data. Data warehouses are an important asset for organisations to maintain efficiency, profitability and competitive advantages, organisations collect data through many sources- online, call centre, sales needs, inventory management. The data collected have degrees values and business relevance. Figure shown below shows the architecture of a typical data warehouse and illustrate the gathering of data, the storage of data, and the quaring and data analysis support. Different steps involved in getting data into a warehouse are called as extract, transform and lode or ELT tasks; extraction refers to getting data from the sources, while loaders reference to loading the data into data warehouse. Characteristics of data warehouse: Multidimensional conceptual view Generic dimensionality Unlimited dimensions and aggregation le

OOP's( Object Oriented programming)

The object oriented approach views off problem in terms of objects involved rather than procedure for doing it. Object oriented program names is defined as a method of implementation in which programs organised are cooperative collections of objects, each of which is an instance of some class. The following general concept of oops are: 1) Object 2) Class 3) Data abstraction 4) Data encapsulation 5) Polymorphism 6) Dynamic binding 7) Message passing 8) Inheritance 1) Object : Object is an entity that can Store send and receive messages and an instance of a class. Each object contains both data and code to manipulate the data objects can interact without having to know details of each objects Data and code. For eg: person, place and table etc. 2) Class : A class is a collection of objects that share common properties and relationships. For example you can think of a buses as objects. They have characteristics like steering wheel, motor, seats etc. And