Volume 34 - 2020 - Special Issue CARI 2020

Special issue dedicated to CARI 2020

1. Analysis of a mosquito life cycle model

Albert Kouchéré ; Hamadjam Abboubakar ; Irepran Damakoa.
The gonotrophic cycle of mosquitoes conditions the frequency of mosquito-human contacts. The knowledge of this important phenomenon in the mosquito life cycle is a fundamental element in the epidemiological analysis of a communicable disease such as mosquito-borne diseases.In this work, we analyze a deterministic model of the complete life cycle of mosquitoes which takes into account the principal phases of female mosquitoes' gonotrophic cycle, and the Sterile Insect technique combined with the use of insecticide as control measures to fight the proliferation of mosquitoes. We compute the corresponding mosquito reproductive number N ∗ and prove the global asymptotic stability of trivial equilibrium. We prove that the model admits two non-trivial equilibria whenever N^{∗} is greater than another threshold, N_c, which the total number of sterile mosquitoes depends on. Numerical simulations, using mosquito parameters of the Aedes species, are carried out to illustrate our analytical results and permit to show that the strategy which consists in combining the sterile insect technique with adulticides, when it is well done, effectively combats the proliferation of mosquitoes.

2. Algorithms to get out of Boring Area Trap in Reinforcement Learning

Landry Steve Noulawe Tchamanbe ; Paulin MELATAGIA YONTA.
Reinforcement learning algorithms have succeeded over the years in achieving impressive results in a variety of fields. However, these algorithms suffer from certain weaknesses highlighted by Refael Vivanti and al. that may explain the regression of even well-trained agents in certain environments : the difference in variance on rewards between areas of the environment. This difference in variance leads to two problems : Boring Area Trap and Manipulative consultant. We note that the Adaptive Symmetric Reward Noising (ASRN) algorithm proposed by Refael Vivanti and al. has limitations for environments with the following characteristics : long game times and multiple boring area environments. To overcome these problems, we propose three algorithms derived from the ASRN algorithm called Rebooted Adaptive Symmetric Reward Noising (RASRN) : Continuous ε decay RASRN, Full RASRN and Stepwise α decay RASRN. Thanks to two series of experiments carried out on the k-armed bandit problem, we show that our algorithms can better correct the Boring Area Trap problem.

3. Parallel Hybridization for SAT: An Efficient Combination of Search Space Splitting and Portfolio

Rodrigue Konan Tchinda ; Clémentin Tayou Djamegni.
Search space splitting and portfolio are the two main approaches used in parallel SAT solving. Each of them has its strengths but also, its weaknesses. Decomposition in search space splitting can help improve speedup on satisfiable instances while competition in portfolio increases robustness. Many parallel hybrid approaches have been proposed in the literature but most of them still cope with load balancing issues that are the cause of a non-negligible overhead. In this paper, we describe a new parallel hybridization scheme based on both search space splitting and portfolio that does not require the use of load balancing mechanisms (such as dynamic work stealing).

4. A Multi Ant Colony Optimization Approach For The Traveling Salesman Problem

Mathurin SOH ; Baudoin Nguimeya Tsofack ; Clémentin Tayou Djamegni.
In this paper, we propose a new approach to solving the Traveling Salesman Problem (TSP), for which no exact algorithm is known that allows to find a solution in polynomial time. The proposed approach is based on optimization by ants. It puts several colonies in competition for improved solutions (in execution time and solution quality) to large TSP instances, and allows to efficiently explore the range of possible solutions. The results of our experiments show that the approach leads to better results compared to other heuristics from the literature, especially in terms of the quality of solutions obtained and execution time.

5. A Nash-game approach to joint data completion and location of small inclusions in Stokes flow

Marwa Ouni ; Abderrahmane Habbal ; Moez Kallel.
We consider the coupled inverse problem of data completion and the determination of the best locations of an unknown number of small objects immersed in a stationary viscous fluid. We carefully introduce a novel method to solve this problem based on a game theory approach. A new algorithm is provided to recovering the missing data and the number of these objects and their approximate location simultaneously. The detection problem is formulated as a topological one. We present two test-cases that illustrate the efficiency of our original strategy to deal with the ill-posed problem.

6. Big Steps Towards Query Eco-Processing - Thinking Smart

Simon Pierre Dembele ; Ladjel Bellatreche ; Carlos Ordonez ; Nabil Gmati ; Mathieu Roche ; Tri Nguyen-Huu ; Laurent Debreu.
Computers and electronic machines in businesses consume a significant amount of electricity, releasing carbon dioxide (CO2), which contributes to greenhouse gas emissions. Energy efficiency is a pressing concern in IT systems, ranging from mobile devices to large servers in data centers, in order to be more environmentally responsible. In order to meet the growing demands in the awareness of excessive energy consumption, many initiatives have been launched on energy efficiency for big data processing covering electronic components, software and applications. Query optimizers are one of the most power consuming components of a DBMS. They can be modified to take into account the energetical cost of query plans by using energy-based cost models with the aim of reducing the power consumption of computer systems. In this paper, we study, describe and evaluate the design of three energy cost models whose values of energy sensitive parameters are determined using the Nonlinear Regression and the Random Forests techniques. To this end, we study in depth the operating principle of the selected DBMS and present an analysis comparing the performance time and energy consumption of typical queries in the TPC benchmark. We perform extensive experiments on a physical testbed based on PostreSQL, MontetDB and Hyrise systems using workloads generatedusing our chosen benchmark to validate our proposal.