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55 stored in the databases or plain files that provide the resource information, shown in Figure 3-25. In our study, we use a broker that uses the LDAP APIs provided by the Globus Toolkit 2.2 to send requests to the GIIS server located on machine m2. The complete source code for the broker is given in the file GridInfoSearch.java in Appendix E. m1.kmitnb.ac.th Broker LDAP query m2.kmitnb.ac.th GIIS GRIS Application GRIS GRIS m3.kmitnb.ac.th … FIGURE 3-25 Working with a broker When called, the GIIS server will return a list of available hosts within the grid. Each host has gathered the following resource information: - Host name - CPU speed (MHz) - Number of CPU(s) - Free CPU Percentage The list of available hosts will be sorted by the weight that measures CPU workload. CPU speed * CPU count * CPU load Weight host = Eq. 3-4 100 where CPU speed : CPU speed; CPU count : the number of CPU(s); and CPU load : the current CPU workload. The most available host will be selected to run a new job.
56 The complete source code for managing the available hosts is given in the file AvailableHost.java in Appendix E. 3.8.2 Job Scheduler The job scheduler schedules the individual jobs to run on the individual hosts. Hamscher et al. [40] presented three job scheduling paradigms for a grid – centralized, hierarchical and distributed. Our study uses a centralized scheduling system. In addition, because the Globus Toolkit does not have its own job scheduler, our study will propose a job scheduler. In a centralized scheduling paradigm, a central machine acts as a resource manager to schedule jobs to all the surrounding hosts within the grid environment. Figure 3-26 presents the architecture of this scheduling. Jobs Central scheduling Job 1 Job 2 Job 3 Host 1 Host 2 Host 3 FIGURE 3-26 Centralized scheduling In this scenario, the jobs are first submitted to the central scheduler that then dispatches the jobs to the appropriate hosts. The jobs that cannot be started on a host are normally stored in a central job queue for later start. In our study, the central scheduling is implemented in machine m1. In addition, there are two kinds of jobs: one is the centralized course scheduling job and two is the decentralized course scheduling job. These jobs will be run on machine m2 and m3. Figure 3-27 presents the proposed algorithm for the centralized scheduling.
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COURSE SCHEDULING IN MULTIPLE FACUL
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ชื่อ : นายฮูเ
Page 5 and 6:
TABLE OF CONTENTS Page Abstract (in
Page 7 and 8:
LIST OF TABLES Table Page 2-1 Cours
Page 9 and 10:
LIST OF FIGURES (CONTINUED) Figure
Page 11 and 12: 2 The classrooms are sometime share
Page 13 and 14: 4 Classroom i Time-slot Hour Mon Tu
Page 15 and 16: CHAPTER 2 LITERATURE REVIEW In this
Page 17 and 18: 9 teach effectively. However, in so
Page 19 and 20: 11 The set of vertexes are consider
Page 21 and 22: 13 Gueret et al. have implemented a
Page 23 and 24: 15 When the atoms are at a high tem
Page 25 and 26: 17 The outline of the basic genetic
Page 27 and 28: 19 As shown in Figure 2-6, first of
Page 29 and 30: 21 2.3.2.1 Crossover After we have
Page 31 and 32: 23 these chromosomes. According to
Page 33 and 34: 25 2.4.1 Application Considerations
Page 35 and 36: 27 Southern California, the Argonne
Page 37 and 38: 29 2.4.3.2 Application Programming
Page 39 and 40: 31 2.5 Summary The course schedulin
Page 41 and 42: 34 3.1.5 Phase 5: Measurement a) To
Page 43 and 44: 36 All the above problems can be pr
Page 45 and 46: 38 Client at a faculty Client at th
Page 47 and 48: 40 The Grid system is only used by
Page 49 and 50: 42 3.6 The Proposed Genetic Algorit
Page 51 and 52: 44 Chromosome x i Fitness = f(x i )
Page 53 and 54: 46 A population is a list of n chro
Page 55 and 56: 48 Lecturers register their busy ti
Page 57 and 58: 50 A course is booked to the time-l
Page 59 and 60: 52 As mentioned in the previous sec
Page 61: 54 GIIS from the client machine m1.
Page 65 and 66: 58 3.8.2.2 Stage 2 After the centra
Page 67 and 68: 60 3.8.3.3 The Gatekeeper The gatek
Page 69 and 70: 62 TABLE 4-1 (CONTINUED) Class Seme
Page 71 and 72: 64 26 lecturers are assigned to tea
Page 73 and 74: 66 TABLE 4-2 (CONTINUED) Course Sec
Page 75 and 76: 68 This result shows that the GA ra
Page 77 and 78: 70 should revise the chromosome rep
Page 79 and 80: 72 - Population size : 10 - Crossov
Page 81 and 82: 74 for network communication is muc
Page 83 and 84: 76 TABLE 4-5 Timetable created by t
Page 85 and 86: CHAPTER 5 CONCLUSION 5.1 Conclusion
Page 87 and 88: REFERENCES 1. Alkan, A. and Ozcan,
Page 89 and 90: 83 20. Burke, E. K. and Newall, J.
Page 91 and 92: 85 38. Globus Toolkit [Online]. Ava
Page 93 and 94: 88 This section presents the struct
Page 95 and 96: 90 A.5 Building TABLE A-5 Building
Page 97 and 98: 92 A.10 Program TABLE A-10 Program
Page 99 and 100: 94 A.14 Timetable TABLE A-14 Timeta
Page 101 and 102: 96 This section presents in detail
Page 103 and 104: 98 TABLE B-2 Group, user ID and pas
Page 105 and 106: 100 broadcastdelay 0.008 authentica
Page 107 and 108: 102 mycapw [enter] During the above
Page 109 and 110: 104 service gsigatekeeper { socket_
Page 111 and 112: 106 B.3.3 Starting the MDS on All o
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108 B.4 Checking the Installation T
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110 This section introduces the ste
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112 C.3.2 Configuration This sectio
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114 [root@m1 root]#grid-proxy-info
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116 The system will automatically p
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118 C.6 Installing JDBC Driver on L
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120 This section presents how to co
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122 All the following files are com
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124 } } } try { ctx.close(); } catc
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126 }//for }else if(attribute.equal
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128 public static void main(String
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130 System.out.println(CentralizedS
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132 gassJob[jobCount]=new GassJob(t
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134 /** * Init job out listeners fo
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136 // Start GASS server if (! star
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138 // waits for DONE or FAILED sta
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140 //get RSL of Job having index i
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142 class Job { private String jobn
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145 BIOGRAPHY Name : Mr. Nguyen Con
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