@inproceedings{scholars10158,
           pages = {13--18},
           title = {Green data center by incentive-based job scheduling approach},
         journal = {2018 IEEE Conference on Open Systems, ICOS 2018},
       publisher = {Institute of Electrical and Electronics Engineers Inc.},
             doi = {10.1109/ICOS.2018.8632811},
            year = {2018},
            note = {cited By 1; Conference of 2018 IEEE Conference on Open Systems, ICOS 2018 ; Conference Date: 21 November 2018 Through 22 November 2018; Conference Code:144760},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062850814&doi=10.1109\%2fICOS.2018.8632811&partnerID=40&md5=0f7379efd12ecc680f9a3dd886775bbc},
        keywords = {Air conditioning; Cooling; Green computing; Scheduling; Scheduling algorithms; Systems engineering; Tropics, Cooling energy; Datacenter; Electrical energy; Energies (power); Green data centers; Incentive-based; Job completion; Job completion deadline; Jobs scheduling; Tropical regions, Energy utilization},
        abstract = {Data centers (DC) need electrical energy (power) for high speed computing and for rooms/facilities cooling purposes. DCs are therefore fast becoming high consumer of electrical energy. Heavy computing loads on servers in DC lead to high heat dissipation that eventually amplifies the cooling demand in DC. High heat with inadequate cooling could lead to more frequent system failures thereby more jobs in DC to miss their job completion deadlines. Unfortunately, the conventional DC job scheduling approaches do not provide compensation to the resource users on their jobs that missed the deadlines. The absence of compensation may dissuade users from submitting jobs to the DCs. The energy consumed for cooling in DC dominates about one third of total DC energy consumption. While free air cooling strategy is used elsewhere, it is not generally applicable in tropical countries such as that in Malaysia. A constant artificial cooling (air conditioning) is needed to sustain the DC operation. To solve this issue in the tropical region, incentive-based scheduling algorithms were devised to significantly reduce the electricity consumption cost in DC and also to be able to compensate users (as an incentive) for their submitted jobs that missed the job completion deadline(s). Ultimately, the proposed job scheduling approach is aimed to produce green DCs. {\^A}{\copyright} 2018 IEEE.},
          author = {Jung, L. T. and Haruna, A. A.},
            isbn = {9781538666661}
}