Efficient Scheduling Algorithm for drone power charging

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dc.contributor.advisorJai-Hoon Kim-
dc.contributor.authorTAJRIAN MEHEDI-
dc.date.accessioned2019-08-13T16:41:02Z-
dc.date.available2019-08-13T16:41:02Z-
dc.date.issued2019-08-
dc.identifier.other29103-
dc.identifier.urihttps://dspace.ajou.ac.kr/handle/2018.oak/15519-
dc.description학위논문(석사)--아주대학교 일반대학원 :컴퓨터공학과,2019. 8-
dc.description.tableofcontentsI. INTRODUCTION. 1 II. BACKGROUND. 2 a. Charging time 2 b. Transportation time. 2 c. Deadline time. 2 d. Laxity time. 3 e. Waiting time. 3 f. Turnaround time. 3 g. Remaining deadline time 3 h. Deadline miss ratio 3 i. Starvation. 3 III. RELATED WORKS AND THEIR PROBLEMS 4 a. FCFS 4 b. SJF 4 c. EDF. 4 d. LJF 4 IV. PROPOSED IDEA. 6 a. Theoretical assumption of ESADPC 7 b. Proposed algorithm. 7 c. Conditions to use ESADPC. 7 d. Why ESADPC is better 8 e. Analysis of ESADPC through calculation 10 f. Benefits of ESADPC. 10 g. Simulation. 11 V. EVOLUTION OF PROPOSED IDEA 21 a. Explanation by calculation 21 EPAFDPC. 21 FCFS 25 SJF. 28 EDF 31 LJF 34 b. Combination of 5 algorithms and comparison of 16 cases. 40 Case 1: SADPC for choosing ready battery and SJF for scheduling 40 Case 2: FCFS for choosing ready battery and EDF for scheduling 41 Case 3: SADPC for choosing ready battery and FCFS for scheduling 41 Case 4: SADPC for choosing ready battery and EDF for scheduling. 42 Case 5: SADPC for choosing ready battery and SADPC for scheduling. 43 Case 6: LJF for choosing ready battery and SJF for scheduling 44 Case 7: FCFS for choosing ready battery and SADPC for scheduling 44 Case 8: FCFS for choosing ready battery and FCFS for scheduling 45 Case 9: FCFS for choosing ready battery and SJF for scheduling 46 Case 10: LJF for choosing ready battery and SJF for scheduling. 46 Case 11: LJF for choosing ready battery and EDF for scheduling 47 Case 12: LJF for choosing ready battery and SADPC for scheduling 48 Case 13: EDF for choosing ready battery and SADPC for scheduling. 48 Case 14: EDF for choosing ready battery and FCFS for scheduling 49 Case 15: EDF for choosing ready battery and EDF for scheduling. 50 Case 16: EDF for choosing ready battery and LJF for scheduling. 50 Case 1 example. 51 Case 2 example. 52 c. Simulation. 53 VI. CONCLUSION. 55 VII. Appendix. 56 a. Code of ESADPC. 56 REFERENCES 61-
dc.language.isoeng-
dc.publisherThe Graduate School, Ajou University-
dc.rights아주대학교 논문은 저작권에 의해 보호받습니다.-
dc.titleEfficient Scheduling Algorithm for drone power charging-
dc.typeThesis-
dc.contributor.affiliationESADPC-
dc.contributor.department일반대학원 컴퓨터공학과-
dc.date.awarded2019. 8-
dc.description.degreeMaster-
dc.identifier.localId952026-
dc.identifier.uciI804:41038-000000029103-
dc.identifier.urlhttp://dcoll.ajou.ac.kr:9080/dcollection/common/orgView/000000029103-
dc.description.alternativeAbstractUnmanned Aerial Vehicle (UAV) is one of the most precious inventions of Internet of things (IOT). UAV face the necessity to charge itself from the charging stations during they provide services. It is very difficult to choose which UAV should get charged first among many and make order of priorities for UAVs, when there is a single charging station. We are proposing an efficient scheduling algorithm for drone power charging (ESADPC). With the help of ESADPC, charging station would have a scheduler to decide which drone can get charged earlier among many other drones. The scheduler will also check, are the drones able to deliver within its remaining deadline after charged or not. Using ESADPC, drones will be able to get charged with a sequential order and will charge one by one depending on their priority. It shows after simulating and analyzing ESADPC with C programming and mathematical calculation that our algorithm is efficient, time saving, better organized and there will be less chance to miss the deadline after using ESADPC.-
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Graduate School of Ajou University > Department of Computer Engineering > 3. Theses(Master)
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