Using Self-Announcer Approach for Resource Availability Detection in Grid Environment
- Bouyer, Asgarali, Mohebi, Ehsan, Abdullah, Abdul Hanan
- Authors: Bouyer, Asgarali , Mohebi, Ehsan , Abdullah, Abdul Hanan
- Date: 2009
- Type: Text , Conference paper
- Relation: Computing in the Global Information Technology, 2009. ICCGI '09. Fourth International Multi-Conference
- Full Text: false
- Reviewed:
- Description: Since the Grid is a dynamic environment, the detection of available resources and prediction of resource availability in near future is important for resource scheduling. In a Grid environment, prediction and evaluation of resource availability is the prerequisite for a reasonable resource selection and good scheduling guarantee. There are many approaches for discovery and prediction of the resource availability that have some weaknesses (e.g., complexity time, predicting, using out of date data, etc). In this paper, we present a new method for detection of available resource based on online-announcer with no inquiry from Grid scheduler. We use a rough set analysis in each grid node to get some useful rules for predicting about nodepsilas behavior in the grid. The experiment results show that our proposed approach is fast algorithm and it applies effectively a reliable method to predict of proper resources for scheduling.
Implementation of evidence-based weekend service recommendations for allied health managers : a cluster randomised controlled trial protocol
- Sarkies, Mitchell, White, Jennifer, Morris, Meg, Taylor, Nicholas, Martin, Jennifer
- Authors: Sarkies, Mitchell , White, Jennifer , Morris, Meg , Taylor, Nicholas , Martin, Jennifer
- Date: 2018
- Type: Text , Journal article
- Relation: Implementation Science Vol. 13, no. 1 (2018), p.
- Full Text:
- Reviewed:
- Description: Background: It is widely acknowledged that health policy and practice do not always reflect current research evidence. Whether knowledge transfer from research to practice is more successful when specific implementation approaches are used remains unclear. A model to assist engagement of allied health managers and clinicians with research implementation could involve disseminating evidence-based policy recommendations, along with the use of knowledge brokers. We developed such a model to aid decision-making for the provision of weekend allied health services. This protocol outlines the design and methods for a multi-centre cluster randomised controlled trial to evaluate the success of research implementation strategies to promote evidence-informed weekend allied health resource allocation decisions, especially in hospital managers. Methods: This multi-centre study will be a three-group parallel cluster randomised controlled trial. Allied health managers from Australian and New Zealand hospitals will be randomised to receive either (1) an evidence-based policy recommendation document to guide weekend allied health resource allocation decisions, (2) the same policy recommendation document with support from a knowledge broker to help implement weekend allied health policy recommendations, or (3) a usual practice control group. The primary outcome will be alignment of weekend allied health service provision with policy recommendations. This will be measured by the number of allied health service events (occasions of service) occurring on weekends as a proportion of total allied health service events for the relevant hospital wards at baseline and 12-month follow-up. Discussion: Evidence-based policy recommendation documents communicate key research findings in an accessible format. This comparatively low-cost research implementation strategy could be combined with using a knowledge broker to work collaboratively with decision-makers to promote knowledge transfer. The results will assist managers to make decisions on resource allocation, based on evidence. More generally, the findings will inform the development of an allied health model for translating research into practice. © 2018 The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Jennifer Martin” is provided in this record**
- Authors: Sarkies, Mitchell , White, Jennifer , Morris, Meg , Taylor, Nicholas , Martin, Jennifer
- Date: 2018
- Type: Text , Journal article
- Relation: Implementation Science Vol. 13, no. 1 (2018), p.
- Full Text:
- Reviewed:
- Description: Background: It is widely acknowledged that health policy and practice do not always reflect current research evidence. Whether knowledge transfer from research to practice is more successful when specific implementation approaches are used remains unclear. A model to assist engagement of allied health managers and clinicians with research implementation could involve disseminating evidence-based policy recommendations, along with the use of knowledge brokers. We developed such a model to aid decision-making for the provision of weekend allied health services. This protocol outlines the design and methods for a multi-centre cluster randomised controlled trial to evaluate the success of research implementation strategies to promote evidence-informed weekend allied health resource allocation decisions, especially in hospital managers. Methods: This multi-centre study will be a three-group parallel cluster randomised controlled trial. Allied health managers from Australian and New Zealand hospitals will be randomised to receive either (1) an evidence-based policy recommendation document to guide weekend allied health resource allocation decisions, (2) the same policy recommendation document with support from a knowledge broker to help implement weekend allied health policy recommendations, or (3) a usual practice control group. The primary outcome will be alignment of weekend allied health service provision with policy recommendations. This will be measured by the number of allied health service events (occasions of service) occurring on weekends as a proportion of total allied health service events for the relevant hospital wards at baseline and 12-month follow-up. Discussion: Evidence-based policy recommendation documents communicate key research findings in an accessible format. This comparatively low-cost research implementation strategy could be combined with using a knowledge broker to work collaboratively with decision-makers to promote knowledge transfer. The results will assist managers to make decisions on resource allocation, based on evidence. More generally, the findings will inform the development of an allied health model for translating research into practice. © 2018 The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Jennifer Martin” is provided in this record**
What factors do allied health take into account when making resource allocation decisions?
- Lane, Haylee, Sturgess, Tamica, Philip, Kathleen, Markham, Donna, Martin, Jennifer
- Authors: Lane, Haylee , Sturgess, Tamica , Philip, Kathleen , Markham, Donna , Martin, Jennifer
- Date: 2018
- Type: Text , Journal article
- Relation: International Journal of Health Policy and Management Vol. 7, no. 5 (2018), p. 412-420
- Full Text:
- Reviewed:
- Description: Background: Allied health comprises multiple professional groups including dietetics, medical radiation practitioners, occupational therapists, optometrists and psychologists. Different to medical and nursing, Allied health are often organized in discipline specific departments and allocate budgets within these to provide services to a range of clinical areas. Little is known of how managers of allied health go about allocating these resources, the factors they consider when making these decisions, and the sources of information they rely upon. The purpose of this study was to identify the key factors that allied health consider when making resource allocation decisions and the sources of information they are based upon. Methods: Four forums were conducted each consisting of case studies, a large group discussion and two hypothetical scenarios to elicit data. A thematic content analysis commenced during post-forum discussions of key factors by forum facilitators. These factors were then presented to an expert working party for further discussion and refinement. Transcripts were generated of all data recordings and a detailed thematic analysis was undertaken by one author to ensure coded data matched the initial thematic analysis. Results: Twelve factors affecting the decision-making of allied health managers and clinicians were identified. One of these factors was disendorsed by the expert working party. The 11 remaining factors can be considered to be key decision-making principles that should be consistently applied to resource allocation. These principles were clustered into three overarching themes of readiness, impact and appropriateness. Conclusion: Understanding these principles now means further research can be completed to more effectively integrate research evidence into health policy and service delivery, create partnerships among policy-makers, managers, service providers and researchers, and to provide support to answer difficult questions that policy-makers, managers and service providers face. © 2018 The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Jennifer Martin” is provided in this record**
- Authors: Lane, Haylee , Sturgess, Tamica , Philip, Kathleen , Markham, Donna , Martin, Jennifer
- Date: 2018
- Type: Text , Journal article
- Relation: International Journal of Health Policy and Management Vol. 7, no. 5 (2018), p. 412-420
- Full Text:
- Reviewed:
- Description: Background: Allied health comprises multiple professional groups including dietetics, medical radiation practitioners, occupational therapists, optometrists and psychologists. Different to medical and nursing, Allied health are often organized in discipline specific departments and allocate budgets within these to provide services to a range of clinical areas. Little is known of how managers of allied health go about allocating these resources, the factors they consider when making these decisions, and the sources of information they rely upon. The purpose of this study was to identify the key factors that allied health consider when making resource allocation decisions and the sources of information they are based upon. Methods: Four forums were conducted each consisting of case studies, a large group discussion and two hypothetical scenarios to elicit data. A thematic content analysis commenced during post-forum discussions of key factors by forum facilitators. These factors were then presented to an expert working party for further discussion and refinement. Transcripts were generated of all data recordings and a detailed thematic analysis was undertaken by one author to ensure coded data matched the initial thematic analysis. Results: Twelve factors affecting the decision-making of allied health managers and clinicians were identified. One of these factors was disendorsed by the expert working party. The 11 remaining factors can be considered to be key decision-making principles that should be consistently applied to resource allocation. These principles were clustered into three overarching themes of readiness, impact and appropriateness. Conclusion: Understanding these principles now means further research can be completed to more effectively integrate research evidence into health policy and service delivery, create partnerships among policy-makers, managers, service providers and researchers, and to provide support to answer difficult questions that policy-makers, managers and service providers face. © 2018 The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Jennifer Martin” is provided in this record**
Equity in healthcare resource allocation decision making : a systematic review
- Lane, Haylee, Sarkies, Mitchell, Martin, Jennifer, Haines, Terry
- Authors: Lane, Haylee , Sarkies, Mitchell , Martin, Jennifer , Haines, Terry
- Date: 2017
- Type: Text , Journal article , Review
- Relation: Social Science and Medicine Vol. 175, no. (2017), p. 11-27
- Full Text: false
- Reviewed:
- Description: Objective To identify elements of endorsed definitions of equity in healthcare and classify domains of these definitions so that policy makers, managers, clinicians, and politicians can form an operational definition of equity that reflects the values and preferences of the society they serve. Design Systematic review where verbatim text describing explicit and implicit definitions of equity were extracted and subjected to a thematic analysis. Data sources The full holdings of the AMED, CINAHL plus, OVID Medline, Scopus, PsychInfo and ProQuest (ProQuest Health & Medical Complete, ProQuest Nursing and Allied Health Source, ProQuest Social Science Journals) were individually searched in April 2015. Eligibility criteria for selecting studies Studies were included if they provided an original, explicit or implicit definition of equity in regards to healthcare resource allocation decision making. Papers that only cited earlier definitions of equity and provided no new information or extensions to this definition were excluded. Results The search strategy yielded 74 papers appropriate for this review; 60 of these provided an explicit definition of equity, with a further 14 papers discussing implicit elements of equity that the authors endorsed in regards to healthcare resource allocation decision making. Five key themes emerged i) Equalisation across the health service supply/access/outcome chain, ii) Need or potential to benefit, iii) Groupings of equalisation, iv) Caveats to equalisation, and v) Close enough is good enough. Conclusions There is great inconsistency in definitions of equity endorsed by different authors. Operational definitions of equity need to be more explicit in addressing these five thematic areas before they can be directly applied to healthcare resource allocation decisions. © 2016 Elsevier Ltd
Software-defined networks for resource allocation in cloud computing : a survey
- Mohamed, Arwa, Hamdan, Mosab, Khan, Suleman, Abdelaziz, Abdelaziz, Babiker, Sharief, Imran, Muhammad, Marsono, M.
- Authors: Mohamed, Arwa , Hamdan, Mosab , Khan, Suleman , Abdelaziz, Abdelaziz , Babiker, Sharief , Imran, Muhammad , Marsono, M.
- Date: 2021
- Type: Text , Journal article
- Relation: Computer Networks Vol. 195, no. (2021), p.
- Full Text:
- Reviewed:
- Description: Cloud computing has a shared set of resources, including physical servers, networks, storage, and user applications. Resource allocation is a critical issue for cloud computing, especially in Infrastructure-as-a-Service (IaaS). The decision-making process in the cloud computing network is non-trivial as it is handled by switches and routers. Moreover, the network concept drifts resulting from changing user demands are among the problems affecting cloud computing. The cloud data center needs agile and elastic network control functions with control of computing resources to ensure proper virtual machine (VM) operations, traffic performance, and energy conservation. Software-Defined Network (SDN) proffers new opportunities to blueprint resource management to handle cloud services allocation while dynamically updating traffic requirements of running VMs. The inclusion of an SDN for managing the infrastructure in a cloud data center better empowers cloud computing, making it easier to allocate resources. In this survey, we discuss and survey resource allocation in cloud computing based on SDN. It is noted that various related studies did not contain all the required requirements. This study is intended to enhance resource allocation mechanisms that involve both cloud computing and SDN domains. Consequently, we analyze resource allocation mechanisms utilized by various researchers; we categorize and evaluate them based on the measured parameters and the problems presented. This survey also contributes to a better understanding of the core of current research that will allow researchers to obtain further information about the possible cloud computing strategies relevant to IaaS resource allocation. © 2021
- Authors: Mohamed, Arwa , Hamdan, Mosab , Khan, Suleman , Abdelaziz, Abdelaziz , Babiker, Sharief , Imran, Muhammad , Marsono, M.
- Date: 2021
- Type: Text , Journal article
- Relation: Computer Networks Vol. 195, no. (2021), p.
- Full Text:
- Reviewed:
- Description: Cloud computing has a shared set of resources, including physical servers, networks, storage, and user applications. Resource allocation is a critical issue for cloud computing, especially in Infrastructure-as-a-Service (IaaS). The decision-making process in the cloud computing network is non-trivial as it is handled by switches and routers. Moreover, the network concept drifts resulting from changing user demands are among the problems affecting cloud computing. The cloud data center needs agile and elastic network control functions with control of computing resources to ensure proper virtual machine (VM) operations, traffic performance, and energy conservation. Software-Defined Network (SDN) proffers new opportunities to blueprint resource management to handle cloud services allocation while dynamically updating traffic requirements of running VMs. The inclusion of an SDN for managing the infrastructure in a cloud data center better empowers cloud computing, making it easier to allocate resources. In this survey, we discuss and survey resource allocation in cloud computing based on SDN. It is noted that various related studies did not contain all the required requirements. This study is intended to enhance resource allocation mechanisms that involve both cloud computing and SDN domains. Consequently, we analyze resource allocation mechanisms utilized by various researchers; we categorize and evaluate them based on the measured parameters and the problems presented. This survey also contributes to a better understanding of the core of current research that will allow researchers to obtain further information about the possible cloud computing strategies relevant to IaaS resource allocation. © 2021
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