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Thesis (M.S.)--University of Tennessee, Knoxville, 2002. / Title from title page screen (viewed Sept. 6, 2002). Thesis advisor: Michael Langston. Document formatted into pages (vi, 119 pages). Vita. Includes bibliographical references (p. 43-46).

Thesis (Ph.D.)--University of Melbourne, Dept. of Computer Science and Software Engineering, 2006. / Typescript. Includes bibliographical references (leaves 189-207).

Thesis (M. Eng.)--University of Louisville, 2004. / Department of Computer Engineering and Computer Science. Vita. "December 2004." Includes bibliographical references (leaves 50-58).

Opportunistic Grid Computing involves joining idle computing resources in enterprises into a converged high performance commodity infrastructure. The research described in this dissertation investigates the viability of public resource computing in offering a plethora of possibilities through seamless access to shared compute and storage resources. The research proposes and conceptualizes the Multi-Agent Opportunistic Grid (MAOG) solution in an Information and Communication Technologies for Development (ICT4D) initiative to address some limitations prevalent in traditional distributed system implementations. Proof-of-concept software components based on JADE (Java Agent Development Framework) validated Multi-Agent Systems (MAS) as an important tool for provisioning of Opportunistic Grid Computing platforms. Exploration of agent technologies within the research context identified two key components which improve access to extended computer capabilities. The first component is a Mobile Agent (MA) compute component in which a group of agents interact to pool shared processor cycles. The compute component integrates dynamic resource identification and allocation strategies by incorporating the Contract Net Protocol (CNP) and rule based reasoning concepts. The second service is a MAS based storage component realized through disk mirroring and Google file-system’s chunking with atomic append storage techniques. This research provides a candidate Opportunistic Grid Computing platform design and implementation through the use of MAS. Experiments conducted validated the design and implementation of the compute and storage services. From results, support for processing user applications; resource identification and allocation; and rule based reasoning validated the MA compute component. A MAS based file-system that implements chunking optimizations was considered to be optimum based on evaluations. The findings from the undertaken experiments also validated the functional adequacy of the implementation, and show the suitability of MAS for provisioning of robust, autonomous, and intelligent platforms. The context of this research, ICT4D, provides a solution to optimizing and increasing the utilization of computing resources that are usually idle in these contexts.

Στην παρούσα διπλωματική εργασία, ασχολούμαστε με μια καινοτόμα τεχνολογία, αυτή των υπολογιστικών πλεγμάτων (grids). Συγκεκριμένα μελετάμε την συμπεριφορά τέτοιων συστημάτων όσον αφορά τον τρόπο που εκτελούνται οι διάφορες εργασίες σε αυτά. Αρχικά λοιπόν αφότου κάνουμε μια γενική αναδρομή στο τι είναι τα grids, πώς υλοποιούνται και ποιές ανάγκες καλύπτουν, αναφερόμαστε σε ένα συγκεκριμένο υπολογιστικό πλέγμα, το οποίο είναι εγκατεστημένο στο Πανεπιστήμιο Πατρών σε χώρο του τμήματος Μηχανικών Η/Υ και Πληροφορικής και το οποίο έχει εναρμονιστεί με επιτυχία από τις αρχές του 2006 σε μια πανευρωπαϊκή δομή grids στα πλαίσια του έργου EGEE (Enabling Grids for E-science in Europe). Στο υπόλοιπο κομμάτι της μελέτης μας, ασχολούμαστε με την κατηγοριοποίηση και την μοντελοποίηση επικοινωνιακών και υπολογιστικών εργασιών στον κόμβο της Πάτρας. Αναλυτικότερα, αφού περιγράψουμε τα δομικά στοιχεία που αποτελούν τον τοπικό κόμβο και αναπτύξουμε τη μεθοδολογία για συγκέντρωση και στατιστική επεξεργασία των δεδομένων του (υπό μορφή log files), επικεντρωνόμαστε στην περιγραφή της διαδικασίας που ακολουθείται από τη διεθνή βιβλιογραφία για την κατηγοριοποίηση των παραπάνω εργασιών. Στη συνέχεια εφαρμόζουμε τα παραπάνω για την περίπτωσή μας και τέλος συγκρίνουμε τα αποτελέσματά μας με μεθόδους που προτείνονται από άλλους μελετητές για την κατηγοριοποίηση τέτοιων εργασιών. Η σύγκριση μας οδηγεί στο ασφαλές συμπέρασμα, πως το μοντέλο το οποίο προτείνουμε για την κατηγοριοποίηση των εργασιών είναι πιο αποδοτικό και πιο απλό από όσα έχουν προταθεί ως σήμερα. Η παραπάνω μελέτη βοηθά στην πληρέστερη κατανόηση της συμπεριφοράς ενός συστήματος πλέγματος, κάτι το οποίο είναι ιδιαίτερα σημαντικό κατά τον σχεδιασμό αλγορίθμων χρονοδρομολόγησης σε τέτοιου είδους συστήματα. Τελικός στόχος παραμένει η δίκαιη μεταχείριση των χρηστών και η μέγιστη αποδοτικότητα της όλης υποδομής. / -

Thesis (M.S.)--Florida State University, 2004. / Advisor: Dr. Larry Dennis, Florida State University, College of Arts and Sciences, Department of Physics. Title and description from dissertation home page (viewed Aug. 27, 2004). Includes bibliographical references.

Grid computing enables computers on different networks to share their resources in an organized way. Authorized users can deploy the resources as if they were in the same organization. This resource sharing environment is called a Virtual Organization (VOs). To enable an open Grid to support resource sharing between multiple heterogeneous VOs, an authorization policy management framework is required to support authorization for VOs using heterogeneous authorization systems. The challenges include dynamic Grid memberships, VO trust relationships, and heterogeneous authorization systems. / To solve these problems in a loose-coupling way, we propose a dynamic, distributive and heterogeneous authorization policy management framework. The framework is called Dynamic Policy Management Framework (DPMF). DPMF groups VOs of the same authorization systems to form a virtual cluster. Authorization policy management is divided into inter-cluster heterogeneous policy management, and intra-cluster homogeneous policy management. Inside a virtual cluster, the workloads of policy management can be distributed among the VOs according to their trust relationships. The Conflict Analysis with Partial Information (CAPI) mechanism is developed to make authorization decisions in open environments without complete policy information. A Heterogeneous Policy Management mechanism is developed for DPMF to support inter-cluster heterogeneous policy management. / Traditional authorization policy management frameworks work well in authorization for a single VO where the participating hosts agree to follow a global authorization system. However, they are not capable of authorization policy management for multiple VOs which deploys heterogeneous authorization systems. / Yu, Chiu Man. / "April 2007." / Adviser: Ng Kam Wing. / Source: Dissertation Abstracts International, Volume: 69-01, Section: B, page: 0447. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 200-206). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

Wong, Sze Wing. / Thesis submitted in: October 2007. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 176-180). / Abstracts in English and Chinese. / Abstract --- p.i / 論文摘要 --- p.iii / Acknowledgements --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Contributions of this thesis --- p.3 / Chapter 1.2 --- Thesis structure --- p.4 / Chapter 2 --- Background --- p.6 / Chapter 2.1 --- Web Services --- p.6 / Chapter 2.2 --- Grid Computing --- p.8 / Chapter 2.2.1 --- Open Grid Services Architecture (OGSA) --- p.9 / Chapter 2.2.2 --- Grid Services --- p.9 / Chapter 2.3 --- Globus Toolkit --- p.10 / Chapter 2.3.1 --- Components of Globus Toolkit 4 --- p.11 / Chapter 2.3.2 --- Grid Security Infrastructure (GSI) --- p.13 / Chapter 2.4 --- Mobile Agent --- p.13 / Chapter 2.4.1 --- Foundation for Intelligent Physical Agents (FIPA) --- p.14 / Chapter 2.5 --- Java Agent Development Framework (JADE) --- p.15 / Chapter 2.5.1 --- JADE-S --- p.17 / Chapter 3 --- Research Issues in Mobile Grid Services --- p.18 / Chapter 3.1 --- Mobile Grid Services --- p.18 / Chapter 3.2 --- Service Migration --- p.20 / Chapter 3.2.1 --- Using Mobile Agent with Weak Mobility --- p.20 / Chapter 3.2.2 --- Using Mobile Agent with Strong Mobility --- p.21 / Chapter 3.2.3 --- Using Snapshots --- p.22 / Chapter 3.2.4 --- Summary --- p.23 / Chapter 3.3 --- Service Sharing and Discovery --- p.24 / Chapter 3.3.1 --- Centralized Model --- p.24 / Chapter 3.3.2 --- Division into clusters --- p.25 / Chapter 3.3.3 --- Using Web Services Protocols --- p.26 / Chapter 3.3.4 --- Summary --- p.27 / Chapter 3.4 --- Security --- p.28 / Chapter 3.4.1 --- Resource control and accounting --- p.28 / Chapter 3.4.2 --- Using delegation document --- p.30 / Chapter 3.4.3 --- Summary --- p.31 / Chapter 4 --- Mobile Grid Service Framework --- p.32 / Chapter 4.1 --- Proposed Framework Overview --- p.32 / Chapter 4.1.1 --- Service Migration --- p.33 / Chapter 4.1.2 --- Service Sharing and Discovery --- p.34 / Chapter 4.1.3 --- Security --- p.34 / Chapter 4.2 --- Overall architecture --- p.35 / Chapter 4.3 --- Components of Mobile Grid Services --- p.36 / Chapter 4.3.1 --- Agent Manager --- p.37 / Chapter 4.3.2 --- Task Agent --- p.38 / Chapter 4.3.3 --- Monitor Agent --- p.39 / Chapter 4.4 --- Resource Information Service --- p.40 / Chapter 4.5 --- Scenario of Mobile Grid Service Execution --- p.41 / Chapter 5 --- MGSAPI --- p.43 / Chapter 5.1 --- API design --- p.43 / Chapter 5.2 --- API Implementation --- p.45 / Chapter 5.2.1 --- Overview --- p.45 / Chapter 5.2.2 --- Agent Manager Class --- p.46 / Chapter 5.2.3 --- Task Agent Templates --- p.52 / Chapter 5.2.4 --- Configurable Monitor Agent --- p.57 / Chapter 5.2.5 --- Resource Information Service --- p.61 / Chapter 5.2.6 --- Example Application --- p.66 / Chapter 6 --- Security Support for Mobile Grid Services --- p.68 / Chapter 6.1 --- Overview --- p.68 / Chapter 6.2 --- Authentication and Authorization --- p.70 / Chapter 6.3 --- Message Integrity and Confidentiality --- p.72 / Chapter 6.4 --- Permissions on Agents --- p.74 / Chapter 6.5 --- Security facilities in MGS API --- p.76 / Chapter 6.5.1 --- Major modifications for MGS components --- p.77 / Chapter 6.5.2 --- MGS Security Libraries --- p.79 / Chapter 6.5.3 --- MGS Security Configuration --- p.81 / Chapter 7 --- Agent Protection for Mobile Grid Services --- p.83 / Chapter 7.1 --- Overview --- p.83 / Chapter 7.2 --- Major modifications --- p.86 / Chapter 7.2.1 --- Exempting checking for executions on home host --- p.86 / Chapter 7.2.2 --- New definition of stage --- p.87 / Chapter 7.2.3 --- Extra operations in Task Agent and Agent Manager --- p.88 / Chapter 7.2.4 --- Handling of attack --- p.88 / Chapter 7.3 --- Implementation details --- p.91 / Chapter 7.3.1 --- Agent Manager --- p.91 / Chapter 7.3.2 --- Task Agent --- p.97 / Chapter 7.3.3 --- Monitor Agent --- p.101 / Chapter 7.3.4 --- Checker --- p.102 / Chapter 7.4 --- Discussions --- p.108 / Chapter 7.4.1 --- Against modification of code and data --- p.108 / Chapter 7.4.2 --- Against masquerade --- p.108 / Chapter 7.4.3 --- Against fake information in trace --- p.109 / Chapter 7.4.4 --- Against escape from re-execution --- p.109 / Chapter 7.4.5 --- Against collaboration of different hosts --- p.109 / Chapter 7.4.6 --- Detection of malicious host --- p.110 / Chapter 7.4.7 --- Weaknesses --- p.110 / Chapter 8 --- Performance Evaluation --- p.111 / Chapter 8.1 --- Experimental Setup --- p.111 / Chapter 8.2 --- MGS Performance --- p.117 / Chapter 8.2.1 --- Experiment details --- p.112 / Chapter 8.2.2 --- Experiment results --- p.113 / Chapter 8.2.3 --- Discussions --- p.116 / Chapter 8.3 --- MGS Overheads --- p.117 / Chapter 8.3.1 --- Experiment details --- p.117 / Chapter 8.3.2 --- Experiment results --- p.119 / Chapter 8.3.3 --- Discussions --- p.123 / Chapter 8.4 --- Agent Protection Overheads --- p.124 / Chapter 8.4.1 --- Experiment details --- p.124 / Chapter 8.4.2 --- Experiment results --- p.125 / Chapter 8.4.3 --- Discussions --- p.128 / Chapter 9 --- Conclusion and Future Works --- p.130 / Appendix A Administrator Guide for MGS API --- p.132 / Chapter A.l --- Installation of MGS API --- p.132 / Chapter A.1.1 --- Installation of pre-requisites --- p.132 / Chapter A.1.2 --- Installation of MGS API library --- p.135 / Chapter A.2 --- Setup of MGS platform --- p.135 / Chapter A.2.1 --- Setup of JADE platform --- p.135 / Chapter A.2.2 --- Setup of Globus containers --- p.136 / Appendix B Developer Guide for MGS API --- p.137 / Chapter B.1 --- Steps of developing a Mobile Grid Service --- p.137 / Chapter B.1.1 --- Design Mobile Grid Service --- p.137 / Chapter B.1.2 --- Define WSDL --- p.138 / Chapter B.1.3 --- Implement the service --- p.138 / Chapter B.1.4 --- Configure deployment in WSDD --- p.138 / Chapter B.1.5 --- Compile and deploy the service --- p.139 / Chapter B.2 --- Mobile Grid Service Implementation --- p.140 / Chapter B.2.1 --- Implement Task Agent --- p.140 / Chapter B.2.2 --- Implement Monitor Agent (optional) --- p.143 / Chapter B.2.3 --- Implement Agent Manager --- p.144 / Chapter B.3 --- Convert tool --- p.146 / Chapter B.4 --- Service configuration --- p.147 / Chapter B.4.1 --- TaskSetting object --- p.147 / Chapter B.4.2 --- MonitorSetting object --- p.147 / Chapter B.4.3 --- MGS Configuration file --- p.148 / Chapter B.4.4 --- Configuration for Resource Information Service --- p.149 / Chapter B.4.5 --- Globus-side security configuration of the service --- p.151 / Chapter B.5 --- MGS Configuration Helper --- p.151 / Chapter B.5.1 --- “Main Container´ح Panel --- p.152 / Chapter B.5.2 --- “Container´ح Panel --- p.154 / Chapter B.5.3 --- “Service´ح Panel --- p.156 / Chapter B.6 --- Interface details --- p.158 / Chapter B.6.1 --- Package mgs.manager --- p.158 / Chapter B.6.2 --- Package mgs.monitor --- p.165 / Chapter B.6.3 --- Package mgs.task --- p.167 / Chapter B.6.4 --- Package mgs.ftsFramework --- p.174 / Bibliography --- p.176 / Publications --- p.181