Volume 38 - Special issue CARI 2022 - 2023

Special issue - CARI 2022.


1. Non-Recursive LSAWfP Models are Structured Workflows

Milliam Maxime Zekeng Ndadji ; Daniela Marionne Nguedia Momo ; Franck Bruno Tonle Noumbo ; Maurice Tchoupé Tchendji.
Workflow languages are a key component of the Business Process Management (BPM) discipline: they are used to model business processes in order to facilitate their automatic management by means of BPM systems. There are numerous workflow languages addressing various issues (expressiveness, formal analysis, etc.). In the last decade, some workflow languages based on context-free grammars (having then formal semantics) and offering new perspectives to process modelling, have emerged: LSAWfP (a Language for the Specification of Administrative Workflow Processes) is one of them. LSAWfP has many advantages over other existing languages, but it is its expressiveness (which has been very little addressed in previous works) that is studied in this paper. Indeed, the work in this paper aims to demonstrate that any non-recursive LSAWfP model is a structured workflow. Knowing that the majority of commercial BPM systems only implement structured workflows, the result of this study establishes that, although LSAWfP is still much more theoretical, it is a language with commercial potential.

2. Epidemic threshold : A new spectral and structural approach of prediction

Claude Kanyou ; Etienne Kouokam ; Yves Emvudu.
Epidemiological modelling and epidemic threshold analysis in the networks are widely used for the control and prediction of infectious disease spread. Therefore, the prediction of the epidemic threshold in networks is a challenge in epidemiology where the contact network structure fundamentally influences the dynamics of the spread. In this paper, we design and experiment a new general structural and spectral prediction approach of the epidemic threshold. This more captures the full network structure using the number of nodes, the spectral radius, and the energy of graph. With data analytic and data visualization technics, we drive simulations overall on 31 different types and topologies networks. The simulations show similar qualitative and quantitative results between the new structural prediction approach of the epidemic threshold values compared to the earlier MF, HMF and QMF widely used benchmark approaches. The results show that the new approach is similar to the earlier one, further captures the full network structure, and is also accurate. The new approach offers a new general structural and spectral area to analyse the spreading processes in a network. The results are both fundamental and practical interest in improving the control and prediction of spreading processes in networks. So these results can be particularly significant to advise an effective epidemiological control policy.

3. Coarse-grained multicomputer parallel algorithm using the four-splitting technique for the minimum cost parenthesizing problem

Jerry Lacmou Zeutouo ; Vianney Kengne Tchendji ; Jean-Frédéric Myoupo.
Dynamic programming is a technique widely used to solve several combinatory optimization problems. A well-known example is the minimum cost parenthesizing problem (MPP), which is usually used to represent a class of non-serial polyadic dynamic-programming problems. These problems are characterized by a strong dependency between subproblems. This paper outlines a coarse-grained multicomputer parallel solution using the four-splitting technique to solve the MPP. It is a partitioning technique consisting of subdividing the dependency graph into subgraphs (or blocks) of variable size and splitting large-size blocks into four subblocks to avoid communication overhead caused by a similar partitioning technique in the literature. Our solution consists in evaluating a block by computing and communicating each subblock of this block to reduce the latency time of processors which accounts for most of the global communication time. It requires O(n^3/p) execution time with O(k * \sqrt{p}) communication rounds. n is the input data size, p is the number of processors, and k is the number of times the size of blocks is subdivided.