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MATEC Web of Conferences 150, 05048 (2018) https://doi.org/10.1051/matecconf/201815005048 MUCET 2017

A Descriptive Study towards Green Practice Application for Data Centers in IT Based Industries

Bokolo Anthony Jnr.1,*, Mazlina Abdul Majid2, and Awanis Romli1

1Faculty of Computer Systems and , Universiti Malaysia Pahang, 26300 Gambang, Pahang, Malaysia

Abstract. The progressive upsurge in demand for processing and computing power has led to a subsequent upsurge in data center carbon emissions, cost incurred, unethical , depletion of natural resources and high energy utilization. This raises the issue of the attainment in data centers of (IT) based industries. Green computing practice can be applied to facilitate sustainability attainment as IT based industries utilizes data centers to provide services to staffs, practitioners and end users. But it is a known fact that enterprise servers utilize huge quantity of energy and incur other expenditures in cooling operations and it is difficult to address the needs of accuracy and efficiency in data centers while yet encouraging a greener application practice alongside cost reduction. Thus this research study focus on the practice application of Green computing in data centers which houses servers and as such presents the Green computing life cycle strategies and best practices to be practiced for better management in data centers in IT based industries. Data was collected through questionnaire from 133 respondents in industries that currently operate their in-house data centers. The analysed data was used to verify the Green computing life cycle strategies presented in this study. Findings from the data shows that each of the life cycles strategies is significant in assisting IT based industries apply Green computing practices in their data centers. This study would be of interest to knowledge and data management practitioners as well as environmental manager and academicians in deploying Green data centers in their organizations.

1 Introduction According to Uddin et al. [3] Green computing entails applications of ecological friendly IT based initiatives Over the years the increasing need for computer related focused on organizational objectives. Hence Green resources has resulted to a major growth in the figures of computing practices can be applied in IT based data center servers deployed along with an increase in industries data centers towards CO2 emissions reduction, the energy consumed by these servers. Data centers cost incurred lessening, proper ethical waste provides support to the present day digital economy management, depletion of natural resources lessening based on the prevalent application and usage of cloud and high energy utilization decrease. based services, but since data centers utilizes a Data center energy consumption is anticipated to substantial amount of power and also releases Carbon increase IT based industries costs and CO2 emissions. dioxide (CO2) emission to the atmosphere [1], hence Hence Green computing practice application in data there is need for strategies, technics and technologies centers can help lessen these negative effects [4]. In that can reduce CO2 emission from data center. continents such as Europe, the energy consumption of Green computing is one of these technologies that enterprise data centers for cooling and powering server can help lessen CO2 emissions in data centers. Green equipment institutes large proportion electricity. Hence computing aims to deploy and utilize technologies for a organizations such as IT based industries have called on cleaner and Greener planet. Green computing is mainly policy makers to resolve data center electricity efficiency the study and practice of utilizing computing resources in order to certify that the linked impacts, such as proficiently [2]. It is a paradigm towards practicing cost- societal, economic and environmental issues are effective and environment friendly use of energy. mitigated [5]. Green computing can also be referred to as optimal In IT based industries data centers signify the utilization of Information Technology (IT) for governing buildings, rooms and facilities which encompass the sustainability attainment of an organization. It enterprise servers, networks communication involves activities that emphases on tactical deployment infrastructures, cooling facilities and powering of IT to vigorously and ethically align organizations equipment that supports data providing services which aims and objectives with environmental protection in may include data handling for intranet, internet, web mind during the complete industrial operations. hosting, IT and telecommunication cables, routers, hubs

* Corresponding author: [email protected] © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/). MATEC Web of Conferences 150, 05048 (2018) https://doi.org/10.1051/matecconf/201815005048 MUCET 2017

and switches [6]. Green computing in IT based industry that influence practices and technologies implementation data center involves the deployment of energy efficient towards energy efficiency improvement in data centres. IT such as electrical, lighting, computer systems and Pawlish and Varde [6] proposed a decision support mechanical equipment with negligible environmental system based on decision trees and case based reasoning impact on the environment [7-9]. that collects existing campus data in order to facilitate Therefore this research aims to conduct a descriptive decision-making for enhances data centers management study of how IT based industries can apply Green for Greening campus data centers. Uddin et al. [3] computing practices in their data centers in regards to utilized Green IT a developed framework for achieving cost saving decrease, energy efficiency, eco-friendly energy efficient of data centers alongside the application waste management, natural resource conservation and of technique. The authors deployed Green CO2 emission reduction towards sustainability IT to securely and seamlessly divide data center modules attainment. To achieve the aims of this study it is into different resource pools depending on different imperative to identify the Green computing life cycle metrics such as energy utilization ratio, workloads strategies to be applied for Greening data centers in IT consumption ratio, CO2 emission etc. The developed based industries framework is grounded on and But in order to identify the life cycle strategies to be virtualization to reduce the energy utilization ratio of applied in Greening data centers towards the application deployed servers. of best practices for cost saving decrease, energy OGCIS [10] summarized a list of guidelines for efficiency, eco-friendly waste management, natural implementing Green data center practices. The author resource conservation and CO2 emission reduction, this utilized Green IT to lessen energy consumption and CO2 research presents the life cycle strategies that are drawn emission of data centres in government organizations. from secondary data. The life cycle strategies are The report presented by the author can be used as a confirmed from primary data (questionnaire) collected quick reference for Greening data centers environment. from more than 133 respondents in IT based industries. Also the practice outlines sets of endorsed practices More specifically the benefits of this study would have applicable for attaining energy efficiency and positive implications for IT based industries data center minimising environmental impacts in data centre. The system practitioners and staffs by providing best practice practices are characterized based on 4 lifecycle phases towards the reductions of energy consumption and CO2 which comprises of design, procurement, operations and emissions. disposal. The remainder of this article is structured as follows. Findings from the reviewed literatures shows that The next section is the literature review. Then the data centre Greening has been a issues to be addressed research methodology is provided. Next, the results and by industries such as IT based industries, although findings from the questionnaire data collection are researchers such as Pichetpongsa and Campeanu [16] outlined. We then proceed to the discussion section, after believes that the implementing of Green practices can which the research and practical implications are help reduce the negative effects caused by IT usage in IT revealed. The article is concludes with conclusion, based industries. limitation and future work section. Each of the review papers aims to contribute to address climatic changes and environmental problems none of the reviewed studies simultaneously addressed 2 Literature review sustainability issues in data center in relation to energy A few studies has be published that contributes to efficiency, cost saving, natural resource preservation, support Greening data centers in organizations, among waste management, and CO2 emissions. The reviewed this studies, 5 studies related to data centers Greening are studies are mainly concerned about energy efficiency, reviewed in this section because they individually CO2 emission and waste management. Hence lifecycle contributed to the presentation of Green computing life strategies and metrics related cost saving and natural cycle strategies. Among the 5 studies that contributed to resource preservation was not fully addressed. Greening data centers in organizations Karanasios et al. [1] carried out an exploratory case study by identifying 3 Research methodology the antecedents towards the adoption of techniques, technologies and best practices for Greening data This descriptive study reports findings for data collected centres. The authors developed a conceptual framework to verify life cycle strategies for applying Green to explain the circumstances that might impact the computing practices in IT based industries data centers. implementation of the best practices in data centres The qualitative data for this study is collected from 133 Greening. respondents from IT based industries in Malaysia. The Molla and Cooper [9] investigated the motivation, survey instrument was prepared by based on the ability drivers and expectancy for Greening data centres. descriptive nature of the study and following Hair et al. The researchers resolved the issue relating to the [11] procedures on data collection instrument institutional, motivation ability and expectancy concepts development. Figure 1 shows the research methods based on survey data collected from 96 data centres. adopted in this study, each of the phase shown in Figure Findings form their research shows that effort 1 are carried out throughout this research paper. expectancy, ability and performance are the main drivers

2 MATEC Web of Conferences 150, 05048 (2018) https://doi.org/10.1051/matecconf/201815005048 MUCET 2017

3.1.3 Green procurement In Green procurement IT based industries can also apply environmental purchasing practice that involves reduction, and reuse of IT infrastructures in purchasing operations [14]. Moreover Green procurement promotes ecologically considerations and promotes the economically viability of the organization towards selecting and acquiring services and products that reduces environmental [13]. Other Green procurement activities may include the practice of considering the Green track record of IT services and software vendors toward environmental protection [15].

3.1.4 Green operations This strategy aims to save energy which leads to less

emission of CO2 to the atmosphere when data centers Fig. 1. Research process. servers are being deployment or implemented to facilitate IT based industries end users, staffs, Figure 1 displays the research methods followed in practitioners and management. Hence, data center this study. Each of the steps is further explored in sub administrator should be aware of how Green operation sections of section 3. can be applied towards to reducing energy consumption of data centers [12]. Green operation practices also aims to enhance power performance of IT based industries 3.1. Green computing life cycle strategies assets towards decreasing energy utilization of cooling This section provides a theoretical and practical and powering enterprise data centers assets, optimizing description of the process lifecycles strategies to be energy performance of data centers, reducing data applied in practicing Green computing in IT based centers induced CO2 emissions [17], practicing low industries data centers. In this regards the lifecycle carbon emitting corporate practices and lastly assessing strategies are presented below; the organizations total environmental footprint [15].

3.1.1 Green design 3.1.5 Green disposal Green design aims to analyse, create and synthesize Green disposal provides IT based industries data ecological friendly products with outstanding efficiency. centers with a flexible and audit policy solution for IT based industries usually disregarded environmental gathering; re-processing and recycling of end-of-life effects during design and as such hazardous wastes were redundant IT associated equipment [18]. Hence in Green discarded without the ecological issues being considered disposal IT base industries can plan to refurbish and [12]. Therefore Green design in IT based industries data reuse old data centers components, while other unwanted centers should consider energy proficient and electronics components can be prepared for recycling deployment of ecologically sound servers, cooling operations [13]. Also OGCIS [10]; Molla [15] equipment and computer components such as Light recommended that the reuse (extend life) or disposal of Emitting Diode (LED) monitor, etc. [13, 14]. obsolete data centers equipment and IT related facilities should be dismantled or refurbished for reuse, while discarding of out-dated infrastructures should adhere to 3.1.2 Green production relevant ecological legislations guidelines such as waste disposal ordinance for end of equipment life dumping This phase in IT based industries data centers involves policy or they can utilize information systems to track taken steps toward applying Greener prospect by changing their data centers operations to more competent the life-cycle of enterprise data center assets and activities and also increasing the reutilizing and ascertain the cost-benefit of different discarding methods reusability rate of the existing infrastructures deployed in [12]. Based on the identified and discussed life cycle the data center [12]. As suggested by Pichetpongsa and strategies a research model is developed as seen in Campeanu [13] in Green production every procedure Figure 2 to be verified by the questionnaire data. The involved in running the data center electronic components, computers and other related subsystems research model is verified to ascertain if each of the should indicate a low or no effect on the natural strategies are important and should be applied by IT environment. This statement was also supported by Saha based industries data centers in regards to energy efficiency, cost saving, natural resource preservation, [14] who mentioned that in Green production management, and CO2 emissions. equipment which has negligible impact or no effect on the environment should only be installed.

3 MATEC Web of Conferences 150, 05048 (2018) https://doi.org/10.1051/matecconf/201815005048 MUCET 2017

GPT4 Gives weight to environmental considerations in equipment procurement. GPT5 Deploy environment-friendly IT procurement policy in our data center. GPT6 Purchase IT equipment from vendors that offers take back option. Green GON1 Environmental consideration in planning IT Operation usage and operations in our data center. GON2 Applied features of IT equipment regularly used in our data center. GON3 Turn off associated data center system when not in use to saves energy. GON4 Print data center report on both side of a paper to reduce paper wastage. GON5 Utilizes equipment that can monitor workloads and to shut down when unused. Fig. 2. Research model. GON6 Uses free cooling in data centers to reduce incurred energy cost. Figure 2 shows the research model developed based Green GDL1 Recycle consumable equipment (e.g. on the life cycle strategies that comprises of Green Disposal batteries, ink cartridges, and paper). design, Green production, Green procurement, Green GDL2 Disposes of IT equipment in an environmentally friendly manner. operation and Green disposal which influences Green GDL3 Carryout policy on managing electronic computing practice application in IT based industries waste. data centers towards cost saving decrease, energy GDL4 Reuse IT equipment. efficiency, eco-friendly waste management, natural GDL5 Refurbish old, outdated and obsolete IT equipment. resource conservation and lastly CO2 emission reduction. Table 1 show the life cycle strategies and metrics used to verify each life cycle, where “Green design” “Green procurement” and “Green operation” are all 3.2. Measurement metrics generation measured with 6 different metrics with a 5 point Likert scale ranging from not applied as “1” and fully applied To measure the life cycle strategies presented in section as “5”. “Green production” is measured with 8 different 3.1 and Figure 2, metrics are derived from the literatures items; with a 5 point Likert scale ranging from not to assess each life cycle strategy, hence each of the applied as “1” and fully applied as “5”. Lastly “Green metrics are shown in Table 1 to measures the degree to disposal” is measured with 5 different items; with a 5 which each life cycle strategy relates to the application point Likert scale ranging from not applied as “1” and of Green computing practices in data centers. fully applied as “5”. Table 1. Operationalization of life cycle strategies and metrics

Life Cycle Code Metrics 3.3. Data collection Strategies Green GDN1 Concerned about the energy consumption of Data was collected using questionnaire used to verify life Design cooling and lighting in our data center. cycle strategies, related to Green computing practice GDN2 Concerned about the efficiency of powering application in IT based industries data centers. Before our IT infrastructure. administering the questionnaire to randomly and GDN3 Considers environmental factors in the design of lighting, power delivery, cooling purposively selected respondents, 3 domain experts in systems and servers, storage and network. Green computing area assessed the validity of the GDN4 Relocate enterprise data center near clean questionnaire items which lead to the refinement of a sources of energy/. few questionnaire metrics or questions based on the GDN5 Use electricity supplied by Green energy feedback from the experts. In this study the reliability providers in our data center. GDN6 Enforces power management. was measured using Cronbach’s alpha which measure Green GPN1 Install software to make production more the internal consistency of a test and it is defined as Production environmentally friendly in our data center. number ranging from 0-9 [11]. Where the value of alpha GPN2 Retire energy inefficient systems is given as 0.986 as obtained from SPSS version 22. GPN3 Analyses IT’s energy bill separately from After which link to the questionnaire survey was sent to overall corporate bill in our data center. GPN4 Engaging the service of a professional the official email of IT practitioners, IT staffs in IT service provider to maintain our data center. based industries in Malaysia, the email addresses were GPN5 Install more energy efficient lightings. gotten from their organizations website. The respondents GPN6 Upgrades to efficient transformers and UPS. were more than 700 randomly and purposively sampled GPN7 Auditing the power efficiency for lesser from IT based industries in Malaysia. power consumption in our data center. GPN8 Eliminates and di-commission unused services and systems in our data center. Green GPT1 Install software to make material sourcing 3.4. Data analysis using descriptive Procurement more environmentally friendly. GPT2 Buys recycled IT equipment. The results were based on survey questionnaire from GPT3 Makes preference to IT hardware suppliers different IT based industries that possess data center. that have a Green track record. After sending the survey questionnaire link, data was

4 MATEC Web of Conferences 150, 05048 (2018) https://doi.org/10.1051/matecconf/201815005048 MUCET 2017

collected from 1 staffs responsible for performing Instry etor IT ommniation an eia technical and operational functionalities at their ation an esear respective organiations data centers. he collected data ealt an ommnity eries helped to verify whether the lifecycle process presented ngineering an onstrtion in this research is feasible to be practically applicable inane aning an Insrane with ease for data centers Greening or not. oernment Aministration an est was carried out to ascertain if all the life cycle efene anfatring strategies; Green design, Green production, Green siness olesale an etail procurement, Green operation and Green disposal fulfils ersonal rofessional the desired dimensions of sustainability social, ters eries economic and environmental and also provides ob Title siness an ystems Analysts an recommendation as best practices on how based rogrammers industries can address energy efficiency related issues, IT anagers cost saving decrease, ecofriendly waste management, IT etor an pport rofessionals natural resource conservation and ensure that there is a on IT peialist anagers limited amount of C emission in the atmosphere. ief eties eneral anagers Lastly the collected data also helps to find out if the an egislators life cycle strategies presented in this study provides Tertiary ation etrers operational solutions in assisting based industries data atabase ystems Aministrators an IT erity peialists centers to apply more Greener practice. ters oring periene 3.5. Results and findings he instrument used for data collection was developed into two main sections. ection collects data regarding Instry ie elo employees respondents’ demographic information, whereas section employees contained 5 life cycle strategies with associated employees metrics that measured life cycle strategies. he metrics Aboe employees were derived from review of literature on Greening data Instry one efore center and Green computing practice application. he ate eteen data were analysed using descriptive statistics, responses eteen to the five life cycle strategies measuring Green eteen computing practice application in based industries rom Till ate Instry Annal or belo data centers was analysed and presented as freuency in eene to percentage, mean, standard deviation , maimum to ma, minimum min and median value. to to Table 2. Characteristic of the uestionnaire respondents or aboe Demographic Options Response Profile able shows the demographic characteristic of the ener ale uestionnaire respondents in relation to individual and emale industries characteristics. Age 3.5.1 Descriptive statistics n regards to the life cycle strategies and metrics ation ig ool presented in able 1, findings for the verification of each iploma life cycle strategy are presented below. he freuency Bachelor’s Degree response is represented as percentage distribution and Master’s Degree descriptive statistics for Green design is shown in able Instry ontry alaysia , where the metrics includes G1G. ters

Table 3. escriptive statistic results for Green design metrics

Life Items 1 2 3 4 5 Mean SD Min Max Median Cycle Not Applied Partly Applied Neutral Applied Fully Applied reen esign

5 MATEC Web of Conferences 150, 05048 (2018) https://doi.org/10.1051/matecconf/201815005048 MUCET 2017

ae shows the findings for reen design metrics ae on a scae of ae aso shows that the items to t can e seen that a metrics are standard deiation ae is ower for and f appied inding frther reeaed that , his shows that the responses are ite simiar in options and response freenc is higher than the seected in reation to reen design appication in their other metrics in terms of appication n reation to the data centers ercentage distrition and descriptie mean ae as seen in ae each of the hae a mean statistics for reen prodction is shown in ae , ae greater than which is the east reired mean where the metrics incdes

Table 4. escriptie statistic rests for reen prodction metrics

Life Cycle Items 1 2 3 4 5 Mean SD Min Max Median Not Applied Partly Applied Neutral Applied Fully Applied ree rocto

ae shows the findings for reen prodction , with and haing the highest mean of metrics to he rests shows that , in regards to the standard deiation aes a and a hae higher reeance priorit and metrics aes deiates a it frther from meaning are appied in reation to reen prodction in data that the response from the respondents are frther apart centers, athogh and are aerage from each other ercentage distrition and descriptie appied, whereas aes from and are statistics for reen procrement is shown in ae , perceied the respondents to netra eing appied where the metrics incdes or the mean a items possess mean ae greater than

Table 5. escriptie statistic rests for reen procrement metrics

Life Items 1 2 3 4 5 Mean SD Min Max Median Cycle Not Applied Partly Applied Neutral Applied Fully Applied ree rocre et

ae shows the findings for reen procrement is aso gien as which is sti greater than the metrics to he rests show that a metrics reired threshod ae he standard deiation were appied in the respondents data centers ecept from aes of each metrics were aso greater that “1” which measre if the respondents organiations showing the response from the respondents are part s recced eipment for data center se he spatia deiated in terms of the respondents perception percentage was ow for this metrics showing that toward reen procrement appication in their ased indstries do not recced eipment to e organiations data centers ercentage distrition and depoed and sed in their data centers n regards to the descriptie statistics for reen operation is shown in mean, a aes where greater than , mean ae ae , where the metrics incdes

Table 6. escriptie statistic rests for reen operation metrics

Life Items 1 2 3 4 5 Mean SD Min Max Median Cycle Not Applied Partly Applied Neutral Applied Fully Applied ree erato

ae shows the findings for reen operation strateg ased on the fact that more than metrics to he rests show that a respondents as seen from metrics to metrics are appied in their indstr for reen operation metrics agreed that the app reen operation

orresog athor argalco 6 MATEC Web of Conferences 150, 05048 (2018) https://doi.org/10.1051/matecconf/201815005048 MUCET 2017

tratee ther tr ata eter he ea ere a a etr 1 t he ret h that ae ae th e a ea a etr are ae ae tre ata eter 1 t that the reet a ata ae the eretae ae the a the etr eter the rt ata eter rert th e a hh rae r a t hh aer t ree aer atae th a the ee a ae he ea are a ae eret r the taar eat ae eah a the taar eat the e etr are etr are etee r hh er at ar ra r 1 r t 1 r ae ae the ae eare t 1 a the hhet eretae trt a erte tatt taar eat ae 1 r hh t r ree a h ae here the aetae ae h the r ree etr e 1

Table 7. erte tatt ret r ree a etr

Life Items 1 2 3 4 5 Mean SD Min Max Median Cycle Not Applied Partly Applied Neutral Applied Fully Applied ree D Dsosal D D D D

ae tre h e er errae 4 Discussion aaeet ata eter ate t erea h reearh t a t atate the ree eer tat there erea e ata eter ae tre a ree r ata eter ta the ret ree t rate the re th aer a et th e e trate t ate eret e e tratee ere ere r teratre ree t rate ae ae tre ree a ere ere ae aate etr r th e th reete a 1 h te r etare ata et r th t reearh ea taae eeet here h that a the e e tratee t e ae r the athr ete that t raat ree t rate ae tre ata rate re ree a rerh eter are rtat a h e ere ata ratrtre a ree t rate ther eter atratr ratter a ta tra erat ae tre ata eter reer e e e trate a ere r the ata ete 5 Practical and research implication r the etare e r th t h the ree e he rata at th t rreate t rate h e ae ae tre ata the e e tratee hh re ree eter th tet th reearh arre t e ree rt ree rreet ree ea et a 1 here the reearher erae the erat a ree a that re a arah aat eet ea erer t ere h ata eter aaer ratter eet a ter et h a a ta a a ree t t ther tr ata eter r th t e r et ata eter t ae the et e rear ree rt ar th re eer eet a there re t t arre t heta a aea 1 rre he ree t e e tratee a here the athr ete the ta a ae ehae the ee ata eter ae te t eetr et ter a ther reate e ae t rer e ae tre ata te ata eter that ee r eter ae etr that a e te ata eet the atra eret eter atratr ratter a ta t rtherre rear ree rreet eare the taat ata eter ter rt 1 ee here ree rreet eer ee t a atra rere ere a e the e e hae r ree reerat ate aaeet a e rate eetat r a he reearh at th t aate t rrrate th ae t reete the ree t e e tratee a aate tho a Ma 1 a 1 here the athr ree etr hh a e te a a ehar ete that tre ahere t r ata eter aaer ae tre t a a ree rha ee he rha ree rate tate ther ata eter t ae the ate a eet he are rear ata eter re ere he e e tratee ree erat ar t ret reete a e t er erta ere aet 1 ther reearh here the athr ete that ree t t a a e e a a ee t t ae the atte eee t a ree t tate t at a t

7 MATEC Web of Conferences 150, 05048 (2018) https://doi.org/10.1051/matecconf/201815005048 MUCET 2017

eaat t the e e tratee at th a a cetres cocetal raeor a elorator trate ree t rate aat re case st a a a ter reeree aa r a art Beo reeg trateges or a a trate e a rear ata eter staale orl Harvard Bus. Rev. 75 eet r eterre a M M alha aha hah haer Meo ree orato echolog 6 Conclusion, limitation and future work raeor or eerg ecet ata ceters h reearh t ere ree t sg rtalato International Journal of rate aat tar rt ae Physical Sciences 7 tre ata eter rear t t a ereae Mrgesa og ree th or eer ee ere ate aaeet esoslt toar roetal staalt Cutter Business-IT Strategies Executive Report 10, atra rere erat a e ret tar taat attaet he reete e e tratee a ta a Boolo ora raeor or etr t atere ata eter rate t oto a leetato o ree eareae t tet ear the rte ractce oerace Proceedings of Third ata eter ter t a ereae eer International Conference on Green Computing, ee ere ate aaeet atra Technology and Innovation D erag Malasa rere erat a e ret th erte t ear ata a ete M alsh are ecso sort r et teratre ata eter ree a sste or gree ata ceters Proceedings of the ree t ater hh the e e tratee 3rd workshop on Ph. D. students in information and hh re ree e ree rt knowledge management ree rreet ree erat a ree a cht r M egar a ere rar ata a ete ae a halleges o Data eter heral Maageet etare r re tha 1 reet IBM Journal 49 ae tre t er eah the ere e e chl he ree a rtal Data eter tratee ae a etr r the ress alor racs aae etare ata h that a the e e Molla ooer reeg ata cetres he tratee are at a h e ere otato eectac a alt rers ae tre ree ther ata eter ogcogoh gree ata cetre ractce taat attaet ar Blac B Ba erso he arah reete th t re a atha Mltarate Data rate e hh e reete a alss th e earso retce all er ae e ratter a ta h are ale er e t ehar a ree ata eter h aa atle ra ree o gree t th re a eete a ear arah cotg or ecorel a sstaale t reet the eera ree t rate Journal of Computational Intelligence and aat et ee ar r Electronic Systems 1 th t reet a reat rata a chetogsa aea alss o ree ate e e tratee hh a ea e orato echolog a osha ee rea r eret he e e oaes IDT: Malardalen University tratee are eae r tta ata eter errae B aha ree cotg International Journal of a aaeet a eet tr taar r ata Computer Trends and Technology (IJCTT), 14 eter h era t erh a at re a e eth r terat Molla he reach a rchess o gree a ehar ear et tar ata eter rcal cooet aalss Australian ree he tat th t reate t the Conference on Information Systems ata et hh e reet ae tre aaa ee r th B tho M Ma Deeloet o a t at e eerae t ther tre tre ree Moel or staale terrse r ata e ete r ther tre a trateg Journal of Soft Computing and Decision ther a t er the ret e ae r Support Systems 3 eret a a e e e tratee eere ag oel or eroetall the ae ata et sstaale orato sstes eeloet Journal of Computer Information Systems 49 References roetal rotecto gec eort to ogress o erer a Data eter erg araasos ooer Deg Molla cec – lc a roetal ttaachaa teceets to greeg ata rotecto gec ashgto D

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