Green Computing Architecture on University Data Centre for Operation Cost Savings - Research Paper Example

Green computing architecture on university data centre for operation cost savings

DATA COLLECTION AND SAMPLING

Data collection

In a research or study there is always the collection of data and converting them into information that can be used in deriving a conclusion. However, for a research such as this one, the major worry might be exactly where and how the right data can be collected. This calls for the use of the most appropriate data collection methods. Any data collection method can be of a certain degree of effectiveness depending of the nature of study that is being undertaken. In this case the data collection methods that proved to be of the highest degree of effectiveness include: literature review; observation; case studies; interview; and surveys.

Literature review

The use of data that is collected from literature materials is always preferred for a number of reasons. The primary reasons as why researchers would prefer using literature materials as a source of data include: convenience of literature review; low cost of conducting literature review as a way of seeking data; and the dependability of literature materials because of the fact that the data that is entailed is always backed by facts from studies. There are a number of literature resources that are available for green computing architecture that can be of importance to a study like this one. This is a factor that made the whole research less complicated owing to the fact that there is not much seeking and verification of data as it would have been for the other sources of data. However, it should be noted that data collected through this method can only be effective if the data that is being used is accurate (Goebel & Plagemann 2015, p. 67). Otherwise, the conclusion made can be highly misleading.

In this research, literature review emerged to be the most used source of data owing to the nature of study. Given the time that was allocated for the study, it can be said that literature review helped in having an easy time in getting a better understanding of the requirements of the research. It was also through literature review that the other data collection methods were guided. Having had a chance of reviewing researches and studiesthat had previously been carried out on green computing architecture,it was easier to know exactly what kind of data that needed to be collected through the other methods of data collection with the aim of confirming the eligibility of the data that was collected throughliterature review.This method of data collection was also opted for owing to the fact that it was a convenient method for data collection in terms of the cost that was incurred.

Direct Observation

Given the fact that there were some prior knowledge on factors that contribute to the successful development and design of green architecture for data centres, it was easier to set the details that will be observed. This included the observation of various organizations that have adopted some of the green practices in design of data centre. Observation of the actual result of such practices in the performance of the data centres and their efficiency was a factor that proved to be of high importance in the determination of whether green design and architecture has an effect on the actual efficiency of the resulting data centres. In short, it can be said that this method of data collection of data involved the collection of data through analysis of the extent to which the organizations that have used the suggested practices in data centre design and architecture have been able to make their data centres efficient.

Case studies

There are a number of reasons as to why the use of case studies is a preferred method of data collection in researches such as this one. When a researcher uses case study to collect data, they have the advantage of being able to get information that will enable them to have a better understanding from practical point of view (Baskerville, Kaul & Storey 2015, p. 556). This is supported by the fact that case studies involve the evaluation of the application of important concepts. The university for which this data centre is being designed is not the first organization in the world to opt for green architecture in the designing of data centres. There are various organizations that have given this line of thought a try. There are cases where the use of the green architectures has been successful in enhancing the sustainability of the resultant data centres while there are cases that it has all been unsuccessful. The review of the practices in the successful cases is a way through which a researcher can be able to deduce some of the things that can be done in order to make the green computing architecture of the university data centre for operational cost savings a success.

There are many reasons as to why case study has been termed as a successful method of data collection. However, there are particular reasons as to why it was opted for in this case. One of the reasons was the ability of case study to provide a rich picture of practical application of green computing concepts and the possible outcomes in terms of sustainability. This is a factor that made this an important way through which data on the applicability of different concepts was determined. It also enabled there to be thorough exploring of contextual factors making the concept more applicable and understandable in the development of a report or proposal for the project. There are different concepts that play part in green computing. Case study was a way through which their relational applicability to the case could be determined by comparing the environment at the cases studied and the environment at the university.

Survey

Surveys were particularly used for the purpose of collecting information from the various stakeholders that are either directly or indirectly involved in the design, development, and use of data centres. This is a way through which the research was able to determine some of the aspects of green architecture for data centres that most of stakeholders think that are of the most importance in making sure that the cost of a data centre is reduced through enhancement of efficiency. Despite the fact that some of the stakeholders are not involved in the design and development of data centres, their contribution was of high importance because of the fact that they will be the ones who will be using the end products, and it is of high importance in getting their perspectives on matters relating to green computing architecture of the university data centre for operational cost savings.

The surveys in this case involved the giving out of questionnaires to various stakeholders so that they could be of contribution to some of the considerations that should be made in the development of the green computing architecture of the university data centre for operational cost savings. The participants were carefully chosen with the purpose of making sure that their contribution would be of meaningful contribution to the project. The questionnaires were also distributed through the online platform for developers and other relevant IT experts.

Interview

The use of interview as a method of data collection can only be of importance to a research if the interviewees are knowledgeable on the issue that is being studied. This is a factor that made it highly challenging to choose the interviewees for the research. This was made even worse by the fact that most of the people who have the experience and skill in these areas are hard to find because of the fact that there are always busy. This was of the effect to the number of interviews who were involved in this study, as the research settled for only three interviews. The individuals who were involved in the interviews as the interviewees include: Dr Patel Sing, who is a highly experienced system designers; Prof. Peter Williams, who has taught system development at various universities for the 18 years that he has been involved in education in systems development and software engineering; and Paul Russell of Vantage Data Centers.

The type of interview that was carried out in this research was indepth interviews. In depth interviews do not use a rigid set of questions. This was opted for because of the necessity of collecting information that might in a number of ways to exceed the expectations of the interviewer owing to the fact that there are some information that the interviewer might be willing to share owing to their importance to the research that the interviewer might not have had in mind. The questions that were used were also open ended so that to make sure that the interviews could collect as much information as possible. Given the fact that the interviewees are busy people the interviews were made as brief as possible so that the most information could be collected from the interviewees. Only one of the interviewees were interviewed through face-to-face method because of the fact that he was the only one who could be available on these terms. The rest were interviewed through phone interviews.

Sampling

For the sake of making sure that the research could be able to remain within the required cost, there was a need for sampling so that the research would not collect more than required data. The quantity of sources of data is high, but it is almost impossible to collect all the data that is available in the world. This is a factor that makes sampling of high importance for a research such as this one. The sampling technique that was used in this research is Stratified sampling. Stratified sampling was opted to over the alternative techniques of data collection, such as simple random sampling because of its ability to reduce the possibility of errors occurring (Mora 2012, p. 189). This is specifically of high importance for a research of this nature owing to the fact that simple error in the process of data collection will have a huge effect on the eligibility of the resultant conclusion. This would mean that the whole process of collection and analysis of data that is involved in the research would be in vein.

Stratified sampling method is commonly used because of its superiority to random sampling in numerous ways, including the reduction of the errors in the resultant data. In this case a stratum was taken to imply a subset of the population that has at least one common characteristic in common. In this case the common characteristic that was being looked for is the comprehension of data centre design and development and the related architectures. This does not imply that the used individuals would have to be people with the knowledge that is sufficient for the design and development of data centres, but the people with the sufficient knowledge to understand data centre architecture and the ways in which the efficiency of a data centre can be determined. This is the least required knowledge, though the selection of participants or the sampling process did not specifically focus on the people with only the knowledge of this nature, but also those with more important information that would be of importance to the accomplishment of the purpose of this research.

However, it should be noted that the use of Stratified sampling in this case did not some without the use of random sampling. After the identification of the relevant stratums there was the determination of the actual representation of the chosen stratum of the general population of the various stakeholders in the design, development, and use of data centres. Random sampling proved to be of importance after the division of the participants into stratums because random sampling was used in the selection of the participants of the research from each of the stratums that were created. The number of participants from every stratum was made high enough to give confidence in the representation of the opinion of the greater population of people who would have been eligible to participate in this research in the stratums. However, the number was also checked given the fact that the research had a schedule that has to be obeyed if in any case the research was to be concluded in the expected time.

DATA ANALYSIS

Collection of data does not mark the end of a result, even if it was a successful one. At some point a researcher has to state the conclusion made from the research carried out. The conclusion comes from making reasoning from the data that is collected in relation to the study that was being carried. This is exactly what took place in the research. Data analysis proved to be an important part of this research as it enabled further relating of the collected data to the research questions (Kuada 2012, p. 121). The data analysis methods that were used in this research include:evaluation of alternative explanations, Conceptualization, Categorizing, and coding, andthe examination of relationship of data through graphical representation of the same. The quantitative data analysis methods that were used in this research include: factor analysis, regression analysis, and comparison of means.

Conceptualization, Categorizing, and coding

Identifying and refining of concepts that are of logical importance to a study is always of high importance to the analysis of any data that is collected in a research such as this one. This is a factor that has made conceptualization a very important aspect of data analysis. In this research, conceptualization began with the simple observation that rather involved direct interpretation of the factors that would determine the efficiency of a data centre in accordance to the information that was collected through literature review (Khosrow-Pour 2014, p. 101). The focus of this method of data analysis was to get a clear explanation for some of the trends that were observed in the industry in termed of the design and development of green architectures for data centres and the green computing techniques that are used in the same. Having knowledge of the trend was not enough. There needed to be a logical explanation of the reason as to why the observations that were made in the data centre development industry or sector. There is a possibility that there was little of no connexion between the theory assertion and the actual occurrences in the industry as far as the development of green data centres is concerned. This is the reason as to why this method of data analysis was opted for as a way of determining whether or some of the recommended green computing practices and coding technology will be of positive influence to the need for green computing architecture of the university data centre for operational cost savings.

Examination of relationship of data through graphical representation

Examination of relationship was also another analysis method that proved to be of high importance in this research. This is a technique that enabled the research to use a simple description of the desired traits of an efficient data centre and the influence that this kind of efficiency might have on the cost. This was necessitated by the fact that there is no assurance that the green computing architecture of the university data centre can actually be of effect to operational cost savings. There was the need for the relation of the data that was collected through case studies and theories so that it can indeed be proved that the use of green architecture would be important in the reduction of the operating cost of a data centre that is used by a university. It is easy to reach literature materials on green computing, but it is a different thing to make sure that the green computing concepts are taken into consideration in the design of architectures for a data centre at a university, such as the one that is being recommended in this research. Graphical representation was particularly effective in making sure that there is an understanding of the differences that there were in the cost of operation under different conditions, and if there was any agreement of disagreement of the data as presented by the graphs from the data that was collected through literature review (Runeson 2012, p. 219). Agreement and disagreement of the data collected in both cases, was able to confirm the viability of the data that was collected.

Evaluation of alternative techniques and technologies

Theoretically speaking, there are very many approaches of evaluation of alternative explanations green computing architecture that would have been effective in the design and development of an efficient data centre in a university. However, it should be noted that the focus of this research was to make sure that any approach that will be used will be driven towards making the cost of operation cost of the resultant data centre as low as possible, while making sure that the effectiveness of the data centre is not compromised. This is an indication that there was the need for reviewing all the possibilities that were available approaches of green computing, having it in mind that only the most appropriate approaches would be selected.

This is an indication that the approaches that were recommended by the study ere not the only approaches that were put under analysis. After all, this was the only way through which the effectiveness of the approaches would be determined without having to over rely on the assertions that are made by literature materials. All the suggested approaches were reviewed with consideration of the case studies where there had been a successful reduction of the cost of operation of data centres through green computing architecture. Both successful and unsuccessful cases were used in the determination of the viability of the assertions made by the literature material. This proved to be an effective way through which the determination of the most effective approach to the use of green computing architecture in the development of efficient data centres in terms of the cost of operation.

Factor analysis

This is a method of data analysis that involves the use of reduction for the sake of identification of the internal structure of a group of variables. This method was particularly opted for as a result of its ability to identify the presence of relationships between all the variables that were included in the research (Ayash 2014, p. 89). In this case factor analysis was used for the purpose of determining the factors that would be of influence to the variables of the research such as cost of production, efficiency, and the number of technologies and approaches that are used in the determination of the green computing architecture approach that will be opted for. It was also of importance in the determination of theextent to which the variables that were used in the research are related. It further proved to be of importance in the interpretation of the common factors such as the cooling cost and the difference in the need for cooling in dependence to the architecture chosen.

Regression analysis

Regression analysis is adata analysis method that is used in the testing of predictor variables ona criterion variable. This is achieved through the tests on the deviation about the means. In this case the variables used had to be interval scaled. In is always carried out through either a correlation matrix or a raw data matrix. This is a factor that proved to be of high importance in qualifying regression analysis as one of the appropriate methods of data analysis owing to the fact that there were datathat had already been collected through literature review that had predictions of the possible effect of green computing architecture of the efficiency of a data centre and its operating cost. As a result, there needed for there to be a way through which the qualitative data that was collected through other data collection methods such as case studies and surveys could be mapped against the data that was collected through literature review. It should be noted that the data that was collected through literaturereview was conclusive and the eligibility had to be determined through the data that was collected by the other methods of data collection. This is a way through which errors in the final conclusion made by the research was minimized because some of the data that were collected during the research would have been misleading if they would have been used without analysis.

Comparison of means

Given the fact that there are various aspects of green computing architecture that were taken into consideration in this research, there were more than one means that were related. However, despite the fact that the means were derived from different sets of data, their comparison proved to be of high importance in coming up with a conclusion for the research. Despite the fact that there are a number of sets of data that were being collected, there is exactly one aspect of efficiency that is being looked into. Therefore, it will be of high importance to make sure that the means that was deduced from the sets of data collected can be collected with the sole aim of making sure that the means can be used to relate some practices and technologies that are used in green computing architecture for the development of data centres with the resultant efficiency in terms of the cost of operation. This helped in making sure that all the means can be of contribution to the findings that were recorded and the conclusion that was made from the research on the use of green computing architecture in the enhancement of the efficiency of data centers.