Measuring mobile broadband performance in Nigeria: 2G and 3G

With increase in broadband penetration rate in Nigeria there is very little known customer-centric mobile broadband performance analysis in the country, despite the inherent advantages associated with performance monitoring to regulators, operators, content-developers, and most especially the customers. There exists an information gap and customers are curious to know the Quality of Service (QoS) offered them. This paper presents a host and crowdsourced based approach to mobile broadband performance metric measurement and evaluation. A mobile broadband performance measurement application (MBPerf) was developed using Java and Extensible Markup Language (XML) and installed on volunteers’ Android Smartphones to measure and collect data relating to 4 (four) QoS metrics – download and upload speeds, latency and DNS (Domain Name Service) lookup; and user data such as mobile phone information, network information, and location information. Measurements were taken for a period of 3 months within Akure and Ibadan metropolis from the 4 major MNOs’ (MNO-A, MNO-B, MNO-C and MNO-D) networks in Nigeria. Data was retrieved from he cloud, pre-processed, sorted and analysed using Microsoft Excel version 13 and SPSS (Statistical Package for the Social Sciences) Statistics 19. Findings reveal that 3G users are not getting the industry set speeds. They get about 10% below the lower limit of the benchmark (500 kilobits per second). However, 2G users get a better deal of about 61% above the lower limit of the benchmark (100 kilobits per second). It was inferred that network performance is highly unpredictable and variable during the day (between 8am and 5pm) but greatly improves at the early hours of the morning (between 12am to 6am) with a difference of about 69% between the peak and worst performance. The study indicates that performance deteriorates at peak times (between 7pm and 11pm). Lastly the DNS performance analysis suggests that the MNOs’ DNS servers operate effectively and do not add significant delay to end users’ queries.Keywords: Mobile broadband performance, Quality of Service (QoS), crowdsourcing, MBPerf application, hostbase

Evolution of Electricity Metering Technologies in Nigeria

Advancement in technology has continuously driven the evolution of metering devices and infrastructure in the world and has resulted in more accurate and user-friendly devices equipped with customer interaction interfaces. The evolution of metering technology in Nigeria arose with the unbundling of the National Electric Power Authority (NEPA) but have not progressed smoothly and successfully despite the implementation of various reforms and policies in the Nigerian electricity industry. The persisting problems in the electricity distribution system such as energy theft, vandalism, energy wastage, high line losses can be overcome by the deployment of appropriate metering infrastructure. In the second quarter of 2020, the Nigerian Electricity Regulatory Commission revealed that the total registered customers and total metered customers are 10,516,090 and 4,234,759 respectively leaving a metering gap of 59.73%; after 124 years of commercial electricity availability in Nigeria. This paper discusses Nigeria's metering history and the challenges encountered in the transition of policies, technologies and government reforms. The paper also proposes the way forward to a successful transitioning into a smart distribution grid

Analysis on geometry-aware received signal strength based positioning techniques

Positioning is an essential part of the ubiquitous world where there is ever-present computing services. Context-aware positioning makes position estimates available to location services based on the characteristics of parameters used for positioning. These handle different scenarios such as environment, adaptation, hybridization and the choice of context is dependent on user requirements. This paper present  geometry-aware received signal strength (RSS) based positioning techniques where the influences of the geometries of the BSs (where location estimation  measurements were obtained) are taken into consideration when estimating the location of the mobile station (MS). This is to alleviate the high variability in accuracy of RSS-based positioning due to varying influences in its relationship with parameters such as the wireless environment, geometry of the network, propagation model, change in infrastructure etc. This paper investigates through modeling and simulating the influence geometry has on the accuracy of some RSS-based geometric techniques. Results obtained indicated that the geometry of the cellular network is an important context required to increase the accuracy of RSS-based positioning. However, ability to predict within a limited margin of accuracy is challenging due to constantly varying parameters which affects the accuracy  obtained in unpredictable ways.Keywords: RSS, LBS, accuracy, context-aware, geometry-awar

Database management system for mobile crowdsourcing applications

The evaluation of mobile crowdsourcing activities and reports require a viable and large volume of data. These data are gathered in real-time and from a large number of paid or unpaid volunteers over a period. A high volume of quality data from smartphones or mobile devices is pivotal to the accuracy and validity of the results. Therefore, there is a need for a robust and scalable database structure that can effectively manage and store the large volumes of data collected from various volunteers without compromising the integrity of the data. An in-depth review of various database designs to select the most suitable that will meet the needs of a real-time, robust and large volunteer data handling system is presented. A non-relational database was proposed for the mobile- end database: Google Cloud Firestore specifically due to its support for mobile client implementation, this choice also makes the integration of data from the mobile end-users to the cloud-hosted database relatively easier with all proposed services being part of the Google Cloud Platform; although it is not as popular as some other database services. Separate comparative reviews of the Database Management System (DBMS) performance demonstrated that MongoDB (a non-relational database) performed better when reading large datasets and performing full-text queries, while MySQL (relational) and Cassandra (non-relational) performed much better for data insertion. Google BigQuery was proposed as an appropriate data warehouse solution. It will provide continuity and direct integration with Cloud Firestore and its Application Programming Interface (API) for data migration from Cloud Firestore to BigQuery, and the local server. Also Google BigQuery provides machine learning support for data analytics

Compression Techniques of Electrical Energy Data for Load Monitoring: A Review

In recent years, the electric grid has experienced increasing deployment, use, and integration of smart meters and energy monitors. These devices transmit big time-series load data representing consumed electrical energy for load monitoring. However, load monitoring presents reactive issues concerning efficient processing, transmission, and storage. To promote improved efficiency and sustainability of the smart grid, one approach to manage this challenge is applying data-compression techniques. The subject of compressing electrical energy data (EED) has received quite an active interest in the past decade to date. However, a quick grasp of the range of appropriate compression techniques remains somewhat a bottleneck to researchers and developers starting in this domain. In this context, this paper reviews the compression techniques and methods (lossy and lossless) adopted for load  monitoring. Selected top-performing compression techniques metrics were discussed, such as compression efficiency, low reconstruction error, and encoding-decoding speed. Additionally reviewed is the relation between electrical energy, data, and sound compression. This review will motivate further interest in developing standard codecs for the compression of electrical energy data that matches that of other domains