Self-optimizing load balancing with backhaul-constrained radio access networks

Self-Organizing Network (SON) technology aims at autonomously deploying, optimizing and repairing the Radio Access Networks (RAN). SON algorithms typically use Key Performance Indicators (KPIs) from the RAN. It is shown that in certain cases, it is essential to take into account the impact of the backhaul state in the design of the SON algorithm. We revisit the Base Station (BS) load definition taking into account the backhaul state. We provide an analytical formula for the load along with a simple estimator for both elastic and guaranteed bit-rate (GBR) traffic. We incorporate the proposed load estimator in a self-optimized load balancing algorithm. Simulation results for a backhaul constrained heterogeneous network illustrate how the correct load definition can guarantee a proper operation of the SON algorithm.Comment: Wireless Communications Letters, IEEE, 201

Self Organizing strategies for enhanced ICIC (eICIC)

Small cells have been identified as an effective solution for coping with the important traffic increase that is expected in the coming years. But this solution is accompanied by additional interference that needs to be mitigated. The enhanced Inter Cell Interference Coordination (eICIC) feature has been introduced to address the interference problem. eICIC involves two parameters which need to be optimized, namely the Cell Range Extension (CRE) of the small cells and the ABS ratio (ABSr) which defines a mute ratio for the macro cell to reduce the interference it produces. In this paper we propose self-optimizing algorithms for the eICIC. The CRE is adjusted by means of load balancing algorithm. The ABSr parameter is optimized by maximizing a proportional fair utility of user throughputs. The convergence of the algorithms is proven using stochastic approximation theorems. Numerical simulations illustrate the important performance gain brought about by the different algorithms.Comment: Submitted to WiOpt 201

Distributed coordination of self-organizing mechanisms in communication networks

The fast development of the Self-Organizing Network (SON) technology in mobile networks renders the problem of coordinating SON functionalities operating simultaneously critical. SON functionalities can be viewed as control loops that may need to be coordinated to guarantee conflict free operation, to enforce stability of the network and to achieve performance gain. This paper proposes a distributed solution for coordinating SON functionalities. It uses Rosen's concave games framework in conjunction with convex optimization. The SON functionalities are modeled as linear Ordinary Differential Equation (ODE)s. The stability of the system is first evaluated using a basic control theory approach. The coordination solution consists in finding a linear map (called coordination matrix) that stabilizes the system of SON functionalities. It is proven that the solution remains valid in a noisy environment using Stochastic Approximation. A practical example involving three different SON functionalities deployed in Base Stations (BSs) of a Long Term Evolution (LTE) network demonstrates the usefulness of the proposed method.Comment: submitted to IEEE TCNS. arXiv admin note: substantial text overlap with arXiv:1209.123

Self-optimizing Strategies for Dynamic Vertical Sectorization in LTE Networks

International audience—Vertical Sectorization (VS) consists in creating ver-tically separated sectors in the original cell using an Active Antenna Systems (AAS) supporting two distinct beams with different downtilts. The total transmit power is split between the two sectors, while the frequency bandwidth can be reused by each sector, creating additional interference between the two sectors. For low traffic demand, VS may lead to performance degradation, while for high traffic demand in both sectors, VS is likely to bring about important capacity gains. Hence intelligent activation policy of VS is needed to fully benefit from this feature. In this paper, we propose an approach taking advantage of the more focused downtilted beam. A dynamic alpha fair bandwidth sharing is proposed for low and medium load. It is autonomously replaced by full bandwidth reuse for high load scenarios using a threshold-based controller. A flow-level dynamic simulator is used to numerically validate the proposed mechanisms

TH1.2: Exploring Gendered Entry Points in the Goat Value Chain in Senegal

The goat value chain (VC) plays an important role in household economics and diets throughout Sub-Saharan Africa, particularly in Senegal. The resilience of goat production in unpredictable climates suggests the potential for increased importance as climate change effects become more disruptive to traditional food systems and diets. The primary research question of this study is: What is the role of goats and the goat VC for climate resilience, women's empowerment and improved nutrition in Senegal? By conducting interviews and focus group discussions (FGDs) with goat VC actors in urban/peri-urban, agricultural, and pastoralist areas of Senegal, this study seeks to identify potential entry points for interventions along the VC, especially for women. In June and July 2022, in collaboration with the IFPRI Gender, Climate Change and Nutrition Integration Initiative, researchers from the Institut Sénégalais de Recherche Agricole (ISRA) facilitated 12 FGDs, six with men and six with women, across two regions, Niakhar and Louga, and conducted 30 key informant interviews with various goat VC actors in the regions of Dakar, Niakhar, and Louga. Preliminary results indicate that more women are becoming engaged in goat rearing and production, becoming owners of the goats they manage and controlling the goat-related incomes. Women have developed climate resilient strategies, including storing foraging materials during winter and selling goats to purchase food during the hunger season. Supported by USAID, the findings of this study will inform future interventions that aim to enhance women's engagement in the goat VC, improve household nutrition, and increase women's empowerment

Use of HRP-2-based rapid diagnostic test for Plasmodium falciparum malaria: assessing accuracy and cost-effectiveness in the villages of Dielmo and Ndiop, Senegal

Background: In 2006, the Senegalese National Malaria Control Programme (NMCP) has recommended artemisinin-based combination therapy (ACT) as the first-line treatment for uncomplicated malaria and, in 2007, mandated testing for all suspected cases of malaria with a Plasmodium falciparum HRP-2-based rapid diagnostic test for malaria (RDT(Paracheck (R)). Given the higher cost of ACT compared to earlier anti-malarials, the objectives of the present study were i) to study the accuracy of Paracheck (R) compared to the thick blood smear (TBS) in two areas with different levels of malaria endemicity and ii) analyse the cost-effectiveness of the strategy of the parasitological confirmation of clinically suspected malaria cases management recommended by the NMCP. Methods: A cross-sectional study was undertaken in the villages of Dielmo and Ndiop (Senegal) nested in a cohort study of about 800 inhabitants. For all the individuals consulting between October 2008 and January 2009 with a clinical diagnosis of malaria, a questionnaire was filled and finger-prick blood samples were taken both for microscopic examination and RDT. The estimated costs and cost-effectiveness analysis were made considering five scenarios, the recommendations of the NMCP being the reference scenario. In addition, a sensitivity analysis was performed assuming that all the RDT-positive patients and 50% of RDT-negative patients were treated with ACT. Results: A total of 189 consultations for clinically suspected malaria occurred during the study period. The sensitivity, specificity, positive and negative predictive values were respectively 100%, 98.3%, 80.0% and 100%. The estimated cost of the reference scenario was close to 700(sic) per 1000 episodes of illness, approximately twice as expensive as most of the other scenarios. Nevertheless, it appeared to us cost-effective while ensuring the diagnosis and the treatment of 100% of malaria attacks and an adequate management of 98.4% of episodes of illness. The present study also demonstrated that full compliance of health care providers with RDT results was required in order to avoid severe incremental costs. Conclusions: A rational use of ACT requires laboratory testing of all patients presenting with presumed malaria. Use of RDTs inevitably has incremental costs, but the strategy associating RDT use for all clinically suspected malaria and prescribing ACT only to patients tested positive is cost-effective in areas where microscopy is unavailable

Anesthesie au cours des ventriculocisternostomies au Mali : Une serie de 31 cas

Introduction La ventriculocisternostomie est une technique moderne du traitement des hydrocéphalies. Elle est peu fréquente en Afrique. Objectif:  Décrire la prise en charge anesthésique et l’évolution des patients opérés par ventriculocisternostomie. Patients et Méthode: Etude de cohorte prospective de 15 mois de janvier 2014 au 31 mars 2015. La saisie et l’analyse des données ont été effectuées par Microsoft word 2010 Epi info 3.5.3.fr. Résultats:  Les nourrissons prédominaient avec un sexe ratio de 1,81 en faveur du sexe masculin. Un antécédent de méningite ou d’infection respiratoire à répétition a été retrouvé chez 10 patients (32,2%). L’indication de la ventriculocisternostomie était une hydrocéphalie chez 30 patients (96, 8%). La classe ASA était II chez 19 patients (61,3%). L’intubation était prévue difficile chez 28 patients (90,3%).Tous les patients ont été opérés sous anesthésie générale. Une antibioprophylaxie a été faite chez tous les patients. La tachycardie isolée a été le seul évènement indésirable per opératoire observé chez 13 patients (41,9%). La durée de la chirurgie était de 62, 25 ± 20,9 minutes celle de l’anesthésie était de 93,5 ± 25,4 minutes. En postopératoire, une complication a été observée chez 7 patients (22,6%). Il s’agissait d’une méningite chez 3 patients (42,9%), d’une souffrance cérébrale, d’une obstruction de la stomie, d’un abcès cérébral et une paralysie du nerf III dans 14,3% chacune (1 patient). L’évolution était favorable chez 29 patients (93,5%). La durée médiane d’hospitalisation était de 3 jours. Conclusion:  Au Mali, la prise en charge anesthésique au cours de la ventriculocisternostomie s’adresse à une population pédiatrique avec un terrain précaire.   English title: Anesthesia during endoscopic third ventriculostomy in Mali: A series of 31 cases Introduction: Endoscopic Third Ventriculostomy (ETV) is a modern technique for the treatment of hydrocephalus. It is uncommon in Africa. Objective To describe ananesthesic management and the outcome of patients operated on by ETV. Patients and Methods Prospective cohort study over 15 months to January 2014 at 31 march 2015. The data entry and analysis were done by word office, Epi info 3.5.3.fr. Results: Infants predominated with a sex ratio of 1.81 in favor of men. A history of meningitis or recurrent respiratory infection was found in 10 patients (32.2%). The indication of ETV was hydrocephalus in 30 patients (96.8%). The ASA class was II in 19 patients (61.3%).  Intubation was expected to be difficult in 28 patients (90.3%). All patients were operated on under general anesthesia. Antibiotic  prophylaxis was done in all patients. Isolated tachycardia was the only peroperative adverse event observed in 13 patients (41.9%). The duration of the surgery was 62.25 ± 20.9 minutes that of the anesthesia was 93.5 ± 25.4 minutes. Postoperatively, a complication was observed in 7 patients (22.6%). It was meningitis in 3 patients (42.9%), brain pain, obstruction of the stoma, brain abscess and nerve III paralysis in 14.3% each (1 patient). The outcome was favorable in 29 patients (93.5%). The median hospital stay was 3 days. Conclusion:  In Mali, anesthetic management during ETV is aimed at a pediatric population with precarious terrain

An Exhaustive, Non-Euclidean, Non-Parametric Data Mining Tool for Unraveling the Complexity of Biological Systems – Novel Insights into Malaria

Complex, high-dimensional data sets pose significant analytical challenges in the post-genomic era. Such data sets are not exclusive to genetic analyses and are also pertinent to epidemiology. There has been considerable effort to develop hypothesis-free data mining and machine learning methodologies. However, current methodologies lack exhaustivity and general applicability. Here we use a novel non-parametric, non-euclidean data mining tool, HyperCube®, to explore exhaustively a complex epidemiological malaria data set by searching for over density of events in m-dimensional space. Hotspots of over density correspond to strings of variables, rules, that determine, in this case, the occurrence of Plasmodium falciparum clinical malaria episodes. The data set contained 46,837 outcome events from 1,653 individuals and 34 explanatory variables. The best predictive rule contained 1,689 events from 148 individuals and was defined as: individuals present during 1992–2003, aged 1–5 years old, having hemoglobin AA, and having had previous Plasmodium malariae malaria parasite infection ≤10 times. These individuals had 3.71 times more P. falciparum clinical malaria episodes than the general population. We validated the rule in two different cohorts. We compared and contrasted the HyperCube® rule with the rules using variables identified by both traditional statistical methods and non-parametric regression tree methods. In addition, we tried all possible sub-stratified quantitative variables. No other model with equal or greater representativity gave a higher Relative Risk. Although three of the four variables in the rule were intuitive, the effect of number of P. malariae episodes was not. HyperCube® efficiently sub-stratified quantitative variables to optimize the rule and was able to identify interactions among the variables, tasks not easy to perform using standard data mining methods. Search of local over density in m-dimensional space, explained by easily interpretable rules, is thus seemingly ideal for generating hypotheses for large datasets to unravel the complexity inherent in biological systems