Evaluation of loadsharing algorithms for heterogeneous distributed systems

The performance of loadsharing algorithms for heterogeneous distributed systems is investigated by simulation. The systems considered are networks of workstations (nodes) which differ in processing power. Two parameters are proposed for characterising system heterogeneity, namely the variance and skew of the distribution of processing power among the network nodes. A variety of networks are investigated, with the same number of nodes and total processing power, but with the processing power distributed differently among the nodes. Two loadsharing algorithms are evaluated, at overall system loadings of 50% and 90%, using job response time as the performance metric. Comparison is made with the ideal situation of ‘perfect sharing’, where it is assumed that the communication delays are zero and that complete knowledge is available about job lengths and the loading at the different nodes, so that an arriving job can be sent to the node where it will be completed in the shortest time. The algorithms studied are based on those already in use for homogeneous networks, but were adapted to take account of system heterogeneity. Both algorithms take into account the differences in the processing powers of the nodes in their location policies, but differ in the extent to which they ‘discriminate’ against the slower nodes. It is seen that the relative performance of the two is strongly influenced by the system utilisation and the distribution of processing power among the nodes.

Tree diameter distribution modelling: introducing the logitlogistic distribution

Johnson's SB distribution is a four-parameter distribution that is transformed into a normal distribution by a logit transformation. By replacing the normal distribution of Johnson's SB with the logistic distribution, we obtain a new distributional model that approximates SB. It is analytically tractable, and we name it the "logitlogistic" (LL) distribution. A generalized four-parameter Weibull model and the Burr XII model are also introduced for comparison purposes. Using the distribution "shape plane" (with axes skew and kurtosis) we compare the "coverage" properties of the LL, the generalized Weibull, and the Burr XII with Johnson's SB, the beta, and the three-parameter Weibull, the main distributions used in forest modelling. The LL is found to have the largest range of shapes. An empirical case study of the distributional models is conducted on 107 sample plots of Chinese fir. The LL performs best among the four-parameter models.

A case study of the effectiveness of the electronic survey as a research tool for measuring students' experience of e-learning

This paper uses a case study approach to consider the effectiveness of the electronic survey as a research tool to measure the learner voice about experiences of e-learning in a particular institutional case. Two large scale electronic surveys were carried out for the Student Experience of e-Learning (SEEL) project at the University of Greenwich in 2007 and 2008, funded by the UK Higher Education Academy (HEA). The paper considers this case to argue that, although the electronic web-based survey is a convenient method of quantitative and qualitative data collection, enabling higher education institutions swiftly to capture multiple views of large numbers of students regarding experiences of e-learning, for more robust analysis, electronic survey research is best combined with other methods of in-depth qualitative data collection. The advantages and disadvantages of the electronic survey as a research method to capture student experiences of e-learning are the focus of analysis in this short paper, which reports an overview of large-scale data collection (1,000+ responses) from two electronic surveys administered to students using surveymonkey as a web-based survey tool as part of the SEEL research project. Advantages of web-based electronic survey design include flexibility, ease of design, high degree of designer control, convenience, low costs, data security, ease of access and guarantee of confidentiality combined with researcher ability to identify users through email addresses. Disadvantages of electronic survey design include the self-selecting nature of web-enabled respondent participation, which tends to skew data collection towards students who respond effectively to email invitations. The relative inadequacy of electronic surveys to capture in-depth qualitative views of students is discussed with regard to prior recommendations from the JISC-funded Learners' Experiences of e-Learning (LEX) project, in consideration of the results from SEEL in-depth interviews with students. The paper considers the literature on web-based and email electronic survey design, summing up the relative advantages and disadvantages of electronic surveys as a tool for student experience of e-learning research. The paper concludes with a range of recommendations for designing future electronic surveys to capture the learner voice on e-learning, contributing to evidence-based learning technology research development in higher education.