Browsing by Author "Tuyishimire, Emmanuel"

Now showing 1 - 5 of 5
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    Open Access
    Detecting Learning Patterns in Tertiary Education Using K-Means Clustering
    (2022-02-17) Tuyishimire, Emmanuel; Mabuto, Wadzanai; Gatabazi, Paul; Bayisingize, Sylvie
    We are in the era where various processes need to be online. However, data from digital learning platforms are still underutilised in higher education, yet, they contain student learning patterns, whose awareness would contribute to educational development. Furthermore, the knowledge of student progress would inform educators whether they would mitigate teaching conditions for critically performing students. Less knowledge of performance patterns limits the development of adaptive teaching and learning mechanisms. In this paper, a model for data exploitation to dynamically study students progress is proposed. Variables to determine current students progress are defined and are used to group students into different clusters. A model for dynamic clustering is proposed and related cluster migration is analysed to isolate poorer or higher performing students. K-means clustering is performed on real data consisting of students from a South African tertiary institution. The proposed model for cluster migration analysis is applied and the corresponding learning patterns are revealed.
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    Open Access
    An Enhanced Heterogeneous Gateway-Based Energy-Aware Multi-Hop Routing Protocol for Wireless Sensor Networks
    (2022-03-25) Jibreel, Fuseini; Tuyishimire, Emmanuel; Daabo, Mohammed Ibrahim
    Wireless Sensor Networks (WSNs) continue to provide essential services for various applications such as surveillance, data gathering, and data transmission from hazardous environments to safer destinations. This has been enhanced by the energy-efficient routing protocols that are mostly designed for such purposes. Gateway-based Energy-Aware Multi-hop Routing protocol (MGEAR) is one of the homogenous routing schemes that was recently designed to more efficiently reduce the energy consumption of distant nodes. However, it has been found that the protocol has a high energy consumption rate, lower stability period, and poorer data transmission to the Base station (BS) when it was deployed for a longer period of time. In this paper, an enhanced Heterogeneous Gateway-based Energy-Aware multi-hop routing protocol (HMGEAR) is proposed. The proposed routing scheme is based on the introduction of heterogeneous nodes in the existing scheme, selection of the head based on the residual energy, introduction of multi-hop communication strategy in all the regions of the network, and implementation of energy hole elimination technique. All these strategies are aiming at reducing energy consumption and extend the life of the network. Results show that the proposed routing scheme outperforms two existing ones in terms of stability period, throughputs, residual energy, and the lifetime of the network.
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    Open Access
    Internet of things : least interference beaconing algorithms
    (2014) Tuyishimire, Emmanuel; Bagula, Antoine; Sanders, J W
    The emerging sensor networking applications are predicting the deployment of sensor devices in thousands of computing elements into multi-technology and multi-protocol platforms. Access to information will be available not only anytime and anywhere, but also using anything in a first-mile of the Internet referred to as the internet-of-things (IoT). The management of such a large-scale and heterogeneous network, would benefit from some of the traditional IP-based network management techniques such as load and energy balancing, which can be re-factored to achieve efficient routing of sensor network traffic. Research has shown that minimizing the path interference on nodes was necessary to improve traffic engineering in connection oriented networks. The same principle has been applied in past research in the context of the IoT to reveal that the least interference beaconing protocol (LIBP); a protocol derived from the least interference beaconing algorithm (LIBA) outperforms the Collection Tree Protocol (CTP) and Tiny OS Beaconing (ToB) protocol, in terms of energy efficiency and lifetime of the sensor network. However for the purpose of efficiency and accuracy, it is relevant, useful and critical to revisit or reexamine the LIBA algorithm in terms of correctness and investigate potential avenues for improvement. The main contributions of this research work are threefold. Firstly, we build upon formal methods to verify the correctness of the main principles underlying the LIBA, in terms of energy efficiency and interference minimization. The interference is here defined at each node by the number of routing paths carrying the sensor readings from the motes to the sink of the network that traverse the node. Our findings reveal the limitations in LIBA. Secondly, building upon these limitations, we propose two improvements to the algorithm: an algorithm called LIBA+ that improves the algorithm performance by keeping track of the energy usage of the sensor nodes, and a multi-sink version of the algorithm called LIBAMN that extends the algorithm to account for multiple sinks or gateways. These enhancements present preventive mechanisms to include in IoT platforms in order to improve traffic engineering, the security of network protocols and network stability. Lastly, we present analytical results, which reveal that the LIBA algorithm can be improved by more than 84% in terms of energy balancing. These results reveal that formal methods remain essential in the evaluation and performance improvement of wireless sensor network algorithms and protocols.
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    A Novel Epidemic Model for the Interference Spread in the Internet of Things
    (2022-04-02) Tuyishimire, Emmanuel; Niyigena, Jean de Dieu; Tubanambazi, Fidèle Mweruli; Rutikanga, Justin Ushize; Gatabazi, Paul; Bagula, Antoine; Niyigaba, Emmanuel
    Due to the multi-technology advancements, internet of things (IoT) applications are in high demand to create smarter environments. Smart objects communicate by exchanging many messages, and this creates interference on receivers. Collection tree algorithms are applied to only reduce the nodes/paths’ interference but cannot fully handle the interference across the underlying IoT. This paper models and analyzes the interference spread in the IoT setting, where the collection tree routing algorithm is adopted. Node interference is treated as a real-life contamination of a disease, where individuals can migrate across compartments such as susceptible, attacked and replaced. The assumed typical collection tree routing model is the least interference beaconing algorithm (LIBA), and the dynamics of the interference spread is studied. The underlying network’s nodes are partitioned into groups of nodes which can affect each other and based on the partition property, the susceptible–attacked–replaced (SAR) model is proposed. To analyze the model, the system stability is studied, and the compartmental based trends are experimented in static, stochastic and predictive systems. The results shows that the dynamics of the system are dependent groups and all have points of convergence for static, stochastic and predictive systems.
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    Trajectory planing for cooperating unmanned aerial vehicles in the IoT
    (2022-02-24) Tuyishimire, Emmanuel; Bagula, Antoine; Rekhis, Slim; Boudriga, Noureddine
    The use of Unmanned Aerial Vehicles (UAVs) in data transport has attracted a lot of attention and applications, as a modern traffic engineering technique used in data sensing, transport, and delivery to where infrastructure is available for its interpretation. Due to UAVs’ constraints such as limited power lifetime, it has been necessary to assist them with ground sensors to gather local data, which has to be transferred to UAVs upon visiting the sensors. The management of such ground sensor communication together with a team of flying UAVs constitutes an interesting data muling problem, which still deserves to be addressed and investigated. This paper revisits the issue of traffic engineering in Internet-of-Things (IoT) settings, to assess the relevance of using UAVs for the persistent collection of sensor readings from the sensor nodes located in an environment and their delivery to base stations where further processing is performed. We propose a persistent path planning and UAV allocation model, where a team of heterogeneous UAVs coming from various base stations are used to collect data from ground sensors and deliver the collected information to their closest base stations. This problem is mathematically formalised as a real-time constrained optimisation model, and proven to be NP-hard. The paper proposes a heuristic solution to the problem and evaluates its relative efficiency through performing experiments on both artificial and real sensors networks, using various scenarios of UAVs settings.