Analyzing manpower data of higher learning institutions: A Markov chain approach

The approach to manpower policy in most Malaysian universities appears to be guided by the traditional method of putting the right number of people in the right place at the right time or arranging for suitable number of people to be allocated to various jobs usually in a hierarchical structure.The technique has been practiced for years.This traditional method is deficit in the sense that it neither offers computational tools that will enable administrators to determine possible line of action to be taken nor provide tools to generate alternative policies and strategies.The objective of this study was to design a planning model for projecting university faculty employment under alternative policy suggested by the government. The planning model was developed using Markov chain technique.Two scenarios were considered in the study; scenario 1 was based on historical data pattern between year 1999 – 2014 and scenario 2 was based on RMK 9 policies.The results showed the possibility average length of stay by position and probability of loss for both scenarios. The greater impact is expected for average length of stay of senior lecturers compared to other faculty position considering the new policy

Optimization of Workload Allocation Problem in a Network of Heterogeneous Computer Systems

Multiple Queue Multiple Server Queueing models are used to model workload allocation problems in a network of computers. The problem of determining optimal allocation of workload with single and multi class jobs to a parallel of computers is presented followed by a problem of determining optimal buffer size related to arrival of workload to a single computer. The generalized exponential (GE) distributional model with known first two moments has been used to represent general inter arrival and service time distributions as various jobs have various traffic characteristic. Other service distributional models such as exponential, Erlang-k and Gamma have also been used to expand the work applicability. A new algorithm of workload allocation scheme using First Come First Serve discipline in conjunction with optimization of GE queueing systems is proposed for minimizing mean queue length and mean response time in a network of computer systems. This has an advantage over a classical queueing allocation scheme, and is favorably compared. The performance measures, mean queue length and mean response time of the proposed scheme have practically shown improvement. The principle of optimization and GE distributional model are used to derive a new workload allocation model of single class jobs in a network of queueing system. The reusable concept is proposed to gain solution for determining individual job allocation in a multi class environment. This study is of interest whereby both single and multi class assumption can be done without repeatedly developing and solving new models. The convincing results of workload allocation models proposed has motivated the work to obtain the direct dependence of the buffer size on the given workload in the network of computer systems. A closed loop expression for buffer sizing of single class jobs and partial buffer sizing of multi class jobs are derived and show their dependency on workload arrival and processing rate in a computationally efficient way

Interpolating data in transition probability matrix of Markov chain to improvise average length of stay

Data interpolation is proposed for estimating transition probability matrix (TPM) of Markov chain model. We showed that interpolated estimator was unbiased. To show its applicability the model on the manpower recruitment policy is developed and analyzed on Excel spreadsheet. Based on the model, the new estimation of the state transition matrix for each category of manpower driven by interpolation technique is devised. The revised transition matrix of Markov chain was substituted by embedding interpolation and can be used as an equation solver to calculate mean time estimation for each category of manpower. The model results were then compared to the classical Markov chain for both old and new policies by means of mean time estimation. Two scenarios were considered in the study; scenario 1 was based on historical data pattern in five years and scenario 2 was based on the new policy. The results showed the possibility average length of stay by position and probability of loss for both scenarios. The proposed data interpolation based TPM approach has shown a new way of recruitment projection for policy changes. The results have indicated better estimation of average length of stay for each category compared to the traditional Markov chain approach

Developing triad design algorithms based on compatible factorization

We consider the problem of listing distinct triples that satisfy certain properties.This problem is known as triad design of order v; TD(v).This design exists for v = 1 or 5 (mod v).Much of our work deals with the enumeration of several triad design, for example TD(7); TD(11) and TD(13). These processes have helped us develop algorithm for triad design, the objective of this study.A new technique for triad design algorithm, known as Interval Generation Method was employed to construct TD(6n + 1) and TD(6n + 5).This method depends on analyzing the pattern of triples in the design to build starters.We begin by producing starters from Interval Generation Method as the initial block to begin with.Then the algorithm begins by cycling modular v from the initial block and finishes when the process approaches the initial block.The algorithms for TD(6n+1) and TD(6n+5) are presented in Chapter 4 and 5, respectively.As the entire study depends mainly on TD(v) algorithms, new and remarkable theorems and lemmas for TD(v) development are presented and proved

Development of a two-dimensional productivity measurement model for higher learning institutions

Measuring the performance of higher learning institutions (HLIs) is a must for these institutions to stay competitive and to move forward.Initiatives towards constructing a more appropriate and accurate measurement is vital. This paper focuses on formation of a productivity model that consists of efficiency and effectiveness dimensions by utilizing a non parametric method, data envelopment analysis (DEA). The identification of suitable input, output and outcome variables were done prior to the development of the model.The proposed model is validated by measuring the productivity of 16 public universities in Malaysia for year 2008. However, due to unavailability of one variable data, an estimate was used as a proxy to represent the real data.The results show average efficiency and effectiveness scores are 0.817 and 0.900 respectively and 0.754 is the overall productivity score.A total of six universities were both efficient and effective. The formation of this performance model would work as a complement method to the existing performance methods or as an alternative method in monitoring the level of performance of HLIs especially for the Malaysia public HLIs.The proposed model could be adopted in a different field or sector after priori identification of suitable and related variables of the selected context

Traffic modeling of web application

The main objective of this study is to develop a Generalised System-Level Model at a system-level point of view of Web server performance for UUM Web Portal. A system-level performance model views the system being modelled as a “black box” which only the arrival rate and service time is considered.It is important in order to measure Web server performance metrics such as server utilization, average server throughput, average number of packet in the server and average response time.This study refers to infinite population and finite queue.It is suitable model because it is easy to define and fast to interpret the results but still represents the real situation.In addition, the complex problem is easily to understand.The developed model can increase the knowledge and understanding about the importance of system-level in Web server performance.It also offers a basic result for Web server assessment in details.Finally, it can assist the management in making decision about system performance to enhance the server system at UUM Computer Center as well

Performance Evaluation of Web Portals

Performance of Web portals at the system level has not been given much attention. The evaluation at the system level is importance for systems maintenance or further improvement. This study develops an evaluation model based on queuing theory at a system level of web portals performance for a university. A system level performance model views the system being modeled as a ‘black box’ which considers the arrival rate of packets to the portals server and service rate of the portals server. These two parameters are important elements to measure web portals performance metrics such as server utilization, average server throughput, average number of packet in the server and mean response time. This study refers to infinite population and finite queue. The proposed analytical model is simple in such a way that it is easy to define and fast to interpret the results but still represents the real situation. The results present the performance of six parallel web portal

Measurement and analysis of web portal’s performance: a case study in UUM

The main objective of this study is to develop a generalised system-level model based on queuing system at a system level point of view of web server performance for UUM web portal. A system level performance model views the system being modelled as a ‘black box’ where only the arrival rate and service rate are considered. It is important in order to measure Web server performance metrics such as server utilisation, average server throughput, average number of packet in the server and mean response time. This study refers to infinite population and finite queue. It is a suitable model because it is easy to define and fast to interpret the results yet still represents the real situatio