Leveraging multiple datasets, we evaluate the current status of African ccTLDs technical environment with regard to best practices. Compared to the top 10 ccTLDs, African ccTLDs appear to have enough IPs to maintain service availability while handling authoritative DNS queries. With regard to the early stage of IPv6 deployment in the AFRINIC region, it is interesting to note that 94% of African ccTLDs support IPv6. This is due to the huge adoption of or DNS anycast provider. The majority (84%) of African anycast traffic is handled by non-profit foundations and/or organisations using resources from other RIRs such as RIPE-NCC and ARIN. Furthermore, less than 30% (16) of African ccTLD have signed their zone. From this group, the majority is using the recommended algorithm RSASHA256 (Algorithm 8) as suggested by BCP 14. Strangely some African ccTLDs lack basic DNS configuration such as missing PTR records, lame delegation, EDNS compliance and consistent serial numbers. These misconfigurations can be easily fixed with consistent monitoring or the use of modern automated registry software which comes with internal checks. Overall, African ccTLDs are characterised by the usage of resources.

The design of a wireless mesh network is usually posed as a multi-objective optimization problem. In this paper, we consider the planning of a wireless mesh network in a rural region where the network coverage and the cost of the architecture must be optimized. In addition, mesh routers are heterogeneous, meaning that they may have different transmission ranges. In the network model, we assume that the region to serve is divided into a set of small zones of various types, including cost-effective locations and zones of interest for which the coverage is mandatory. The objective is then to minimize the number of routers, their types and locations which maximize the coverage percentage of mandatory zones in terms of coverage while minimizing the overall cost of the architecture. To achieve this, we propose three multi-objective approaches. We test the proposed approaches on several random topologies. The min-max regret metric is used to appreciate the quality of solutions of the Pareto front of different approaches.

Big data is large volume of data produced on a daily basis. Distributed storage systems (DSS) is environment that handles, manages and stores those data. The main drawbacks are the lack of system storage capacity, the network device failures that can appear anytime, on time data processing and the system efficiency. All above mentioned issues can be overcome by applying different coding techniques for data distribution. Till this moment many coding schemes are proposed by the researchers. Determining the most efficient code for usage is still a tricky question, which yields an adequate comparison strategy for code selection. The basic Dimakis comparison method offers analysis between the codes regarding the parameters storage per node and download bandwidth to be repair one node. Total comparison method includes in the analysis the total number of nodes in the system together with the overall storage and total downloaded bandwidth in the repair process, with notation that the file size for all codes must be same. In this paper, we are proposing new method for comparison, called Normalized, that enables consideration of broader spectrum of parameters and not necessarily the same file size of the proposed codes.

Software Defined Networking (SDN) definitely brings along benefits such as manageability, automation of network and management processes amongst others, however, at the expense of major drawbacks such as huge investment in SDN-capable hardware, vendor lock-in and backward incompatibility with legacy devices. SDN itself being based on a new concept, provides very few aspects in common with traditional networking devices with each SDN vendor usually limiting the SDN capabilities to their own devices only. Even with the introduction of open protocols such as OpenFlow with the aim to provide vendor neutrality, backward compatibility still remains a problem. This paper is geared towards addressing the main issues governing the migration towards SDN and hence provide the desired vendor neutrality, backward compatibility without compromising on networking features, security, ease of deployment and management inter alia. With this concept in mind, an SDN Middleware System has been conceptualized to offer the aforementioned features whereby the backend of the system would be responsible to intercept, inspect and process OpenFlow configurations from the SDN Manager and the SDN Controller and thereafter interpret these commands converting them into the desired configuration in legacy networking terms after which, the legacy nodes are configured with the equivalent of the legacy vendor OS.

Software-Defined Networking (SDN) has become a popular paradigm for modern day optimal performance of the network system as a result of the separation of the control component from other network elements. This enables the maintenance of the flow table structure on these devices while optimal forwarding of packets is enhanced via the central controller. Being a growing network architecture which is supposed to be able to meet up with increasing traffic demands in the future, it becomes apparently important that the mechanism that takes care of the QoS of the network demands is put in place. Such demands include the smooth running of big data transmission, D2D video exchange, Voice over IP and real-time multimedia applications which needed certain QoS requirements for optimal service delivery. However, fewer research articles have reported on the improvement on the QoS routing especially in connection with the SDN paradigm. We propose a multi-criteria routing algorithm that is based on deterministic Adaptive rendering technique called DARTMCP. Our DARTMCP QoS routing algorithm deployed Dijkstra’s algorithm to simplify the topology of the network before using multiple-criteria energy function to address the QoS requirements. We recorded a relatively stable bandwidth and user experience maximization under a low rate of network convergence in comparison with other approaches.

The Domain Name System (DNS) is one of the most critical services for daily operation of the Internet. It is used to primarily resolve names to IP addresses and vice versa on the Internet through a distributed hierarchical system. This work aims at characterizing the authoritative DNS nameservers of two categories of domain (1) publicly available and reverse zones managed by AFRINIC, (2) 57 ccTLDs in the African region. We study several aspects such as the number of nameservers, the geographical and topological distribution, EDNS and TCP compliance. Overall, the authoritative servers of reverse zones of IP addresses allocated by AFRINIC to their members are 75% EDNS compliant and 72% TCP compliant while the authoritative servers of Africa ccTLDs are respectively 46% and 43.6% compliant for EDNS and TCP. The study also revealed other important information such as the clear domination of some authoritative nameservers, which represents a potential risk of service disruption should these servers become unavailable. Similarly, the geographic location of the authoritative nameservers may potentially have an impact on response times to DNS resolutions and affect user experience. Therefore, a series of efforts must be done in those areas to ensure the optimal functioning of the Internet in the region.

Internet security and Quality of Experience (QoE) are two antagonistic concepts that the research community has been attempting to reconcile. Internet security has of late received attention due to users’ online privacy and security concerns. One example is the introduction of encrypted Domain Name System (DNS) protocols. These protocols, combined with suboptimal routing paths and offshore hosting, have the potential to negatively impact the quality of web browsing experience for users in Africa. This is particularly the case in edge access networks that are far away from essential infrastructures such as DNS and content servers. In this paper, we analyse the QoE impact of using open public DoH and DoT resolvers when resolving websites that are hosted in Africa versus those hosted offshore. The study further compares the performance of DoT and DoH under different network conditions (mobile, community network, Eduroam and Campus wired network). Our results show that high latency and circuitous DNS resolution paths amplify the performance impact of secure DNS protocols on DNS resolution time and page load time. The study further shows that users’ DNS resolver preferences hugely determine the level of QoE. This study proposes wider adoption of Transport Layer Security version 1.3 (TLSv1.3) to leverage its latency-reduction features such as and (0/1-RTT). The study further proposes the localisation of content and secure DNS infrastructure. This, coupled with peering and cache sharing recommended by other works, will further minimise the impact of secure DNS protocols on Quality of Experience.

infrastructure makes great demands on network control methods for an efficient management of massive amounts of nodes and data. This network requires fine traffic control management to ensure an adequate for data transmission process, especially in a low-cost network that covers smart territories deployed in so-called “technological lag” areas. Software-Defined Networking () enables to handle dynamically network traffic as well as flexible traffic control on real-time. However, technology exhibits several issues with regard to additional processing time or loss that are associated to control plan. These factors can lead to performance degradation of the control traffic flows within data plane which is not tolerated in medium/low capacity environment.

Remote teaching and learning (RTL) is a system of education, wherein teachers and learners are not in the same location but separated by time and space. Global pandemics such as the COVID-19, necessitate social distance, thereby rendering traditional “contact” based classroom learning unfeasible. e-Learning which is a viable alternative often depends on reliable Internet. Unfortunately, Internet penetration in many areas of the world is still abysmally low. RTL in these under-served regions of the world is thus a major challenge. In this paper, we review the state of RTL and consider feasible options for under-served communities. Requirement for RTL, including data and associated cost of attending classes online are also considered. Finally, recommendations for achieving least cost RTL for under-served communities are given.

There is relentless effort in combating the issue of crime in South Africa and many parts of the world. This challenge is heightened in under-resourced settings, where there is limited knowledge support, thus resulting in increasing negative perceptions of public safety. This work presents a predictive policing model as an addition to a burglar alarm system deployed in a community policing project to improve crime prevention performance. The proposed model uses feature-oriented data fusion method based on a deep learning crime prediction mechanism. Feed-Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) models are employed to predict the amount of calls made to police stations on a monthly basis. Device installation and census data are used in the feature selection process to predict monthly calls to a police station. Coefficient of correlation function is used to isolate the relevant features for the analysis. To provide a viable way of achieving crime reduction targets, the models are implemented and tested on a real-life community policing network system called MeMeZa, which is currently deployed in low-income areas of South Africa. Furthermore, the model is evaluated using coefficient of determination function and the accuracy of the predictions assessed using an independent dataset that was not used in the models’ development. The proposed solution falls under the Machine Learning and AI applications in networks paradigm, and promises to promote smart policing in under-resourced settings.