Efficient Resource Matching in Heterogeneous Grid Using Resource Vector

In this paper, a method for efficient scheduling to obtain optimum job throughput in a distributed campus grid environment is presented; Traditional job schedulers determine job scheduling using user and job resource attributes. User attributes are related to current usage, historical usage, user priority and project access. Job resource attributes mainly comprise of soft requirements (compilers, libraries) and hard requirements like memory, storage and interconnect. A job scheduler dispatches jobs to a resource if a job's hard and soft requirements are met by a resource. In current scenario during execution of a job, if a resource becomes unavailable, schedulers are presented with limited options, namely re-queuing job or migrating job to a different resource. Both options are expensive in terms of data and compute time. These situations can be avoided, if the often ignored factor, availability time of a resource in a grid environment is considered. We propose resource rank approach, in which jobs are dispatched to a resource which has the highest rank among all resources that match the job's requirement. The results show that our approach can increase throughput of many serial / monolithic jobs.Comment: 10 page

Two ways to Grid: the contribution of Open Grid Services Architecture (OGSA) mechanisms to service-centric and resource-centric lifecycles

Service Oriented Architectures (SOAs) support service lifecycle tasks, including Development, Deployment, Discovery and Use. We observe that there are two disparate ways to use Grid SOAs such as the Open Grid Services Architecture (OGSA) as exemplified in the Globus Toolkit (GT3/4). One is a traditional enterprise SOA use where end-user services are developed, deployed and resourced behind firewalls, for use by external consumers: a service-centric (or ‘first-order’) approach. The other supports end-user development, deployment, and resourcing of applications across organizations via the use of execution and resource management services: A Resource-centric (or ‘second-order’) approach. We analyze and compare the two approaches using a combination of empirical experiments and an architectural evaluation methodology (scenario, mechanism, and quality attributes) to reveal common and distinct strengths and weaknesses. The impact of potential improvements (which are likely to be manifested by GT4) is estimated, and opportunities for alternative architectures and technologies explored. We conclude by investigating if the two approaches can be converged or combined, and if they are compatible on shared resources

e-HRM in a Cloud Environment Implementation and its Adoption: A Literature Review

[EN] As the digitization of HR processes in companies continues to increase, at the same time, the underlying technical basis is also developing at a rapid pace. Electronic human resources (e-HRM) solutions are used to map a variety of HR processes. However, the introduction of such systems has various consequences, which are not only technical but also imply organizational and functional changes within the organization. Additionally, the cloud environment contributes to enhancing e-HRM capabilities and introduces new factors in its adoption. A systematic review of the available literature on the different dimensions of electronic resources management was conducted to assess the current state of research in this field. This review includes topics such as the evolution of e-HRM, its practical application, use of technology, implementation as well as HR analytics. By identifying and reviewing articles under e-HRM, IT technology, and HR journals, it was possible to identify relevant controversial themes and gaps as well as limitations.Ziebell, R.; Albors Garrigós, J.; Schoeneberg, KP.; Perelló Marín, MR. (2019). e-HRM in a Cloud Environment Implementation and its Adoption: A Literature Review. International Journal of Human Capital and Information Technology Professionals. 10(4):16-40. https://doi.org/10.4018/IJHCITP.2019100102S1640104Acito, F., & Khatri, V. (2014). Business analytics: Why now and what next? Business Horizons, 57(5), 565-570. doi:10.1016/j.bushor.2014.06.001Alam, M. G. R., Masum, A. K. M., Beh, L.-S., & Hong, C. S. (2016). Critical Factors Influencing Decision to Adopt Human Resource Information System (HRIS) in Hospitals. PLOS ONE, 11(8), e0160366. doi:10.1371/journal.pone.0160366Alamelu, R., Amudha, R., Nalini, R., Aishwarya, V., & Aarthi, A. (2016). Techno-Management Perspective of HRIS- An Urban Study. 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An Energy Sharing Game with Generalized Demand Bidding: Model and Properties

This paper proposes a novel energy sharing mechanism for prosumers who can produce and consume. Different from most existing works, the role of individual prosumer as a seller or buyer in our model is endogenously determined. Several desirable properties of the proposed mechanism are proved based on a generalized game-theoretic model. We show that the Nash equilibrium exists and is the unique solution of an equivalent convex optimization problem. The sharing price at the Nash equilibrium equals to the average marginal disutility of all prosumers. We also prove that every prosumer has the incentive to participate in the sharing market, and prosumers' total cost decreases with increasing absolute value of price sensitivity. Furthermore, the Nash equilibrium approaches the social optimal as the number of prosumers grows, and competition can improve social welfare.Comment: 16 pages, 7 figure

Credibility-Based Binary Feedback Model for Grid Resource Planning

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