Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing

Hybrid metaheuristic algorithms have the ability to produce better solution than stand-alone approach and no algorithm could be concluded as the best algorithm for scheduling algorithm or in general, for combinatorial problems.This study presents the low and high level hybridization of ant colony system and genetic algorithm in solving the job scheduling in grid computing.Two hybrid algorithms namely ACS(GA) as a low level and ACS+GA as a high level are proposed.The proposed algorithms were evaluated using static benchmarks problems known as expected time to compute model. Experimental results show that ant colony system algorithm performance is enhanced when hybridized with genetic algorithm specifically with high level hybridization

Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing

Grid computing is a distributed system with heterogeneous infrastructures. Resource management system (RMS) is one of the most important components which has great influence on the grid computing performance. The main part of RMS is the scheduler algorithm which has the responsibility to map submitted tasks to available resources. The complexity of scheduling problem is considered as a nondeterministic polynomial complete (NP-complete) problem and therefore, an intelligent algorithm is required to achieve better scheduling solution. One of the prominent intelligent algorithms is ant colony system (ACS) which is implemented widely to solve various types of scheduling problems. However, ACS suffers from stagnation problem in medium and large size grid computing system. ACS is based on exploitation and exploration mechanisms where the exploitation is sufficient but the exploration has a deficiency. The exploration in ACS is based on a random approach without any strategy. This study proposed four hybrid algorithms between ACS, Genetic Algorithm (GA), and Tabu Search (TS) algorithms to enhance the ACS performance. The algorithms are ACS(GA), ACS+GA, ACS(TS), and ACS+TS. These proposed hybrid algorithms will enhance ACS in terms of exploration mechanism and solution refinement by implementing low and high levels hybridization of ACS, GA, and TS algorithms. The proposed algorithms were evaluated against twelve metaheuristic algorithms in static (expected time to compute model) and dynamic (distribution pattern) grid computing environments. A simulator called ExSim was developed to mimic the static and dynamic nature of the grid computing. Experimental results show that the proposed algorithms outperform ACS in terms of best makespan values. Performance of ACS(GA), ACS+GA, ACS(TS), and ACS+TS are better than ACS by 0.35%, 2.03%, 4.65% and 6.99% respectively for static environment. For dynamic environment, performance of ACS(GA), ACS+GA, ACS+TS, and ACS(TS) are better than ACS by 0.01%, 0.56%, 1.16%, and 1.26% respectively. The proposed algorithms can be used to schedule tasks in grid computing with better performance in terms of makespan

Federal Register

Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii

Federal Register

Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii

Computer Science & Technology Series : XVI Argentine Congress of Computer Science - Selected papers

CACIC’10 was the sixteenth Congress in the CACIC series. It was organized by the School of Computer Science of the University of Moron. The Congress included 10 Workshops with 104 accepted papers, 1 main Conference, 4 invited tutorials, different meetings related with Computer Science Education (Professors, PhD students, Curricula) and an International School with 5 courses. (http://www.cacic2010.edu.ar/). CACIC 2010 was organized following the traditional Congress format, with 10 Workshops covering a diversity of dimensions of Computer Science Research. Each topic was supervised by a committee of three chairs of different Universities. The call for papers attracted a total of 195 submissions. An average of 2.6 review reports were collected for each paper, for a grand total of 507 review reports that involved about 300 different reviewers. A total of 104 full papers were accepted and 20 of them were selected for this book.Red de Universidades con Carreras en Informática (RedUNCI

Pharmacist collaborative practice and the development and implementation of team-based care in outpatient healthcare settings: A case study at El Rio Community Health Center

Background: The United States is experiencing a primary care physician shortage that will grow in the next decade as demand for primary care services is projected to increase. The growth in physician, Nurse Practitioner, and Physician Assistant supply alone will not be adequate to meet the demand for primary care services by 2020. Creating pharmacist-inclusive collaborative care teams for outpatient clinical care can help alleviate this health care delivery shortage. Methods: A qualitative mixed-methods case study was conducted in Tucson, Arizona to determine the supports and structures behind the Pharmacy-Based Diabetes Management Program (PBDMP) at El Rio Community Health Center. Using key informant interviews from El Rio, other outpatient clinical pharmacy programs (OCPPs), and the Tucson Accountable Care Organization, coupled with Lean Management brainstorming group sessions, the study elicited information about how the experience of El Rio with the PBDMP can inform nationwide development and implementation guidelines for other OCPPs. Results: The PBDMP at El Rio provides a blueprint for other programs interested in creating an OCPP. Key contributing factors to program success within El Rio and the other OCPPs interviewed included a focus on six key practices. Challenges inhibiting success were pharmacist provider status and reimbursement of clinical services provided. Translation: Three public health practice products were developed as a framework to provide future OCPPs interested in implementing a pharmacist-inclusive practice model: 1) implementation guidelines, 2) a self-assessment outpatient clinical pharmacy program worksheet for clinics looking to create or expand an OCPP, and 3) a student management decision case study. Conclusion: This study demonstrates the value of considering all potential members of a care team for diabetes care management. The decision by a clinic to create an OCPP should be based on team-based approaches to patient-centered chronic disease care management. Clinics looking to participate in a CDTM model OCPP need to identify if organizational transformation is needed for program buy-in and consider relational coordination between clinical roles as a major component of the coordinated work needed for a successful OCPP

Federal Register

Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii

2020 year in review

Meeting proceedings of a seminar by the same name, held December 10-11, 2020