Green Computing - The solution to reduce carbon footprints in IT industries.

The production of a generic laptop results in generation of about 130-200 lbs. CO2e and over its life cycle, it will have generated around twice that amount of total CO2e greenhouse gas emissions. A 10-year-old tree absorbs almost 48.5 lbs. of CO2 per year. Taking the average 75.2 lbs. as the amount produced, this means that for a laptop alone, there need to be 2 full grown trees to absorb the emissions. Meaning that one would have to plant 2 trees each year for the carbon footprint of his/her laptop to be 0 in 10 years’ time.

Performing two Google searches from a desktop computer can generate about the same amount of carbon dioxide as boiling a kettle for a cup of tea, according to new research.

• As our computing capabilities and the amount of data that we generate each year continue to grow, so do their contributions to carbon emissions.
• Even though these emissions are not direct they are abstract in nature.
• Data centers contribute to carbon emissions through electricity consumption, both in terms of powering computers for computing and for long-term data storage, resulting in an estimated 100 megatonnes of CO2 emissions produced per year. On considering the important parameters like how long the algorithm runs for, what hardware (CPU, GPU, memory) is used one can estimate the carbon footprint in grams of C02 equivalent.
• The computing technology and high-powered computing is here to stay because of its many benefits. So, adopting green computing is a great solution to tackle emissions of greenhouse gases.

So, how can an organization implement green computing in order to reduce their carbon footprint?
Some steps to be implemented are as follows:
Proclamation of the Green Intentions - It is always best to begin Green IT initiatives by communicating intentions to adopt an environment-friendly IT infrastructure. The push for energy efficiency should be cascaded down to every staff, setting the stage for collaboration between various departments.
Measurement of Current Carbon Footprints Produced by IT Components - Where the company stands in terms of carbon footprint brought about by information technology services, is an important information to be known. Quickly establish a carbon footprint reference point. Check on the power usage in the IT center and compare it with existing power efficiency standards and metrics for industry.
Usage of More Efficient Computer Applications- By using more powerful computer applications, your IT systems can better deal with inefficiencies. Besides, faster software spares the servers from regularly operating at maximum capacity, thereby consuming lesser power.
Usage of More Efficient Cooling Systems: - To reduce your CRAC (Computer Room Air Conditioning) power consumption for green computing, invest in supplemental cooling systems that are placed in between the rows of servers in data center.
Result Monitoring and Continuous IT Optimization: - Lastly, you should always check the results of green IT initiatives. Compare this data with the benchmarks and metrics that is set for the company. A good example is checking total power consumption for each month.

Hope that further implementations of Green Computing will soon be seen and we all will move forward with the goal of reductionm of carbon footprints in Computing via green methods.

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Role of data structure in Project development:

Data structures plays a very important role in a project development as data structure is the heart of any operation to be performed without data structure a project will be very bad and the user could only perform basic operations.

•Helps to solve a problem more efficiently:
Suppose a person develops a software module for solving business problems They may involve all software development lifecycle including requirement analysis, coding, design and maintenance of software. To perform the following operations data structure pplays a very important role. Also when the person develops the software and if he does not know the concepts of data structures properly then he will not be able to use the api(The Application programming interface (API) hides the internal implementation of data structure and the algorithm using object oriented programming principals) properly
How to choose correct data structure for solving a problem? When selecting a data structure to solve a problem, you should follow these steps. 1. Analyze your problem to determine the basic operations that must be supported. Examples of basic operations include inserting a data item into the data structure, deleting a data item from the data structure, and finding a specified data item. 2. Quantify the resource constraints for for each operation. 3. Select the data structure that best meets these requirements. This three-step approach to selecting a data structure operationalizes a data-centered view of choosing the data structure. The first concern is for the data and the operations to be performed on them, the next concern is the representation for those data, and the final concern is the implementation of that representation. To select data structure based on Implementation centered view of implementation following question should be asked

1. Are all data items inserted into the data structure at the beginning, or are insertions interspersed with other operations? Static applications (where the data are loaded at the beginning and never change) typically get by with simpler data structures to get an efficient implementation, while dynamic applications often require something more complicated. 2. Can data items be deleted? If so, this will probably make the implementation more complicated. 3. Are all data items processed in some well-defined order, or is search for specific data items allowed? “Random access” search generally requires more complex data structures.

Conclusion:
I would like to conclude by saying that data structures and algorithm indeed plays a very important role in project development as since it can make a project offer many functionalities also a person whose data structure and algorithm concepts are clear will be of great importance in project development.

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The importance of Data Structures

A software has two parts front end and back end. The front end provides an interface and the back end is called a database which contains records of customers. There can be million or trillion of customers. If we have to find out the record of a particular or a number of customers, it is done by a searching method which is an operation on the data structure.

If any software is to be run, at first it is fed into computer memory. In computer memory jobs are entered into queues. And the queue is also a concept of data structure. As we know when jobs and processes are entered then queues are formed. These queues can have too many jobs or processes. In queues, jobs are processed in the same order as they entered. If any job is created it is placed at the end of a queue. Suppose we have to add or delete any job in any order then the concept of the queue will be failed and the concept of link list will be used. If data is to be arranged alphabetically or numerically then it is done by sorting method which is an operation on the data structure. Data structure provides the right way to organize information in the digital space. If any data is to be stored in a hierarchical fashion then the concept of tree is used. It stores data in a hierarchical fashion. In windows, all the directories are stored using the concept of trees.

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Real life applications of DSA in Project development

DSA is a wide topic and has its implementation in various fields.Here we can understand the usage of Data structures in project development.

Arrays
Arrays are the simplest data structures that stores items of the same data type. A basic application of Arrays can be storing data in tabular format.
Applications of arrays for project development are as follows:
1.Arrangement of leader-board of a game can be done simply through arrays to store the score and arrange them in descending order to clearly make out the rank of each player in the game.
2.A simple question Paper is an array of numbered questions with each of them assigned to some marks.

Linked List
A linked list is a sequence data structure, which connects elements, called nodes, through links.
Applications of linked lists for project development are as follows:
1.Images are linked with each other. So, an image viewer software uses a linked list to view the previous and the next images using the previous and next buttons.
2.Web pages can be accessed using the previous and the next URL links which are linked using linked list.
3.The music players also use the same technique to switch between music.

Stacks
A stack is a data structure which uses LIFO order.
Applications of stack for project development are as follows:
1.Syntaxes in languages are parsed using stacks.
2.It is used in many virtual machines like JVM.
3.Forward – backward surfing in browser
4.History of visited websites

Queue
A queue is a data structure that uses FIFO order.
Applications of queue for project development are as follows:
1.To handle congestion in networking queue can be used.
2.Data packets in communication are arranged in queue format.
3.Sending an E-mail, it will be queued.
4.Uploading and downloading photos

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