Resource Selection Policies Research Articles

Human Resources Policies and Employees’ Attitude: A Study of Federal University of Petroleum Resources, Effurun, Delta State

This study examined the influence of human resources policies on employees’ attitudes using the Federal University of Petroleum Resources, Effurun, Delta State as a case study. The study used the survey research design and the instrument of data collection was the questionnaire which was administered to two hundred (200) academic and non-academic staff of the Federal University of Petroleum Resources. Data obtained in the survey were analyzed using linear regression technique. It was found that human resource recruitment and selection policy had a significant influence on employees’ attitudes (F-value = 3.246; P-value = 0.003). In addition, we found that human resource staff training and development policy had a significant effect on employees’ attitudes (F-value = 5.017; P-value = 0.026). The study recommends that the management of Nigerian public institutions of higher learning should sustain and improve on their recruitment and selection and staff training and development policies in order to enhance employees’ attitude to work. More so, there is a need for the management of Nigerian public institutions of higher learning to embrace diverse types of human resource policies that will improve employees’ attitudes to work.

Problems of Human Resource Selection and Career Policy in Georgian Higher Education Institutions

This paper discusses the staff recruitment process policy as a systematic one, carried out by higher education institutions to attract the human resources that have the knowledge, skills and qualifications necessary to achieve the goals of the University. During the process of selection, the higher education institutions identify the applicants, according to the requirements and criteria for the vacancies. A fair, open and acceptable selection procedure enhances the image and credibility of the University. The study aimed to determine the extent to which the human resource selection and career policy in Georgian higher education institutions responds to the above mentioned, generally accepted and recognized visions. The problems of human resource selection and career policy in Georgian higher education institutions may pose a serious threat to the future of the university and society as a whole. The survey was conducted by a sociological research method. Participation in the study was offered to all authorized universities in Georgia that implement accredited programs. 11 universities agreed to participate. Participation in the survey was voluntary. It involved both academic and administrative staff. 805 respondents were interviewed. The questionnaire included open as well as closed questions. The questionnaire was based on the results of the research of contemporary scientific works related to the research problem by both international and national higher education researchers.

A Generic Stochastic Model for Resource Availability in Fog Computing Environments

Fog computing is an increasingly popular method with which to process the huge amount of data generated by the Internet of Things (IoT) devices and applications at the edge-level, using the heterogeneous autonomous end-devices of the participating users. To meet the requirements of the IoT and time-sensitive applications, a Fog computing platform needs to select appropriate resources, the availability of which can be guaranteed during the execution of the application. For the proper selection of resources, the platform must be able to predict future availability. Hence, a proper resource availability model which provides knowledge about the future availability of resources in the Fog computing environment is required. However, designing an efficient resource availability model, in a highly distributed and mobile environment like the Fog, is a complex task due to the multidimensional characteristics of Fog devices, such as mobility, lack of centralised control, limited resources, and being battery powered. Existing resource availability models did not consider all the characteristics of a real Fog environment. Therefore, this study aims to provide a generic continuous-time Markov chain (CTMC), based resource availability model for Fog computing environments. The applicability of the model is shown by integrating the model input with the nearest-location best fit (NLBF) and Best-Fit resource selection policies.

HTC‐Sim: a trace‐driven simulation framework for energy consumption in high‐throughput computing systems

SummaryHigh‐throughput computing (HTC) is a powerful paradigm allowing vast quantities of independent work to be performed simultaneously across many loosely coupled computers. These systems often exploit the idle time available on computers provisioned for other purposes – volunteer computing. However, until recently, little evaluation has been performed on the energy impact of HTC. Many organisations now seek to minimise energy consumption across their IT infrastructure. However, it is unclear how this will affect the usability of HTC systems especially when exploiting volunteer computers. We present here HTC‐Sim, a simulation system that allows the evaluation of different energy reduction policies across an HTC system. We model systems that comprised both collections of computational resources dedicated to HTC work and resources provided through volunteer computing – a desktop grid. We demonstrate that our simulation software scales linearly with increasing HTC workload. We go further to evaluate a number of resource selection policies in terms of the overheads/slowdown incurred and the energy impact on the HTC system. Copyright © 2016 John Wiley & Sons, Ltd.

Evolutionary multi-objective resource allocation and scheduling in the Chinese navigation satellite system project

The development of appropriate project management techniques for Research and Development (R&D) projects has received significant academic and practical attention over the past few decades. Project managers typically face the problem of allocating resources and scheduling activities, for which the underlying combinatorial problem is NP-hard. The inherent uncertainty in many R&D environments increases the complexity of the problem.This paper addresses the problem of resource allocation and activity scheduling with a focus on R&D projects. The work is different from the existing literature in at least three aspects: (1) the problem formulation is based on a real-world Chinese aerospace project, (2) each individual resource unit can have a different resource efficiency, and (3) the uncertainty of the duration of an activity is time-dependent (efficiency-dependent) in nature.The problem is formulated as a multi-objective optimization model with simultaneous consideration of makespan and balance of resource efficiency. A cooperative coevolutionary multi-objective algorithm (CCMOA) is designed to produce high-quality solutions. Two chromosome representations and three resource selection policies are tested for the algorithm. The proposed CCMOA is found to be competitive when compared to MOEA/D and NSGA–II, which are two popular algorithms for multi-objective optimization.