Application of optimal control to the epidemiology of malaria

Malaria is a deadly disease transmitted to humans through the bite of infected female mosquitoes. In this paper a deterministic system of differential equations is presented and studied for the transmission of malaria. Then optimal control theory is applied to investigate optimal strategies for controlling the spread of malaria disease using treatment, insecticide treated bed nets and spray of mosquito insecticide as the system control variables. The possible impact of using combinations of the three controls either one at a time or two at a time on the spread of the disease is also examined

Comparative Cost Analysis Between Hydraform Interlocking Brick and Sandcrete Block as Walling Materials for Low-Cost Housing Development in Nigeria

This study analyzed the cost of production and construction of 225mm hollow sandcrete blocks and hydraform interlocking bricks and walls to compare the findings of the results. The study was conducted in Auchi, Estako West Local Government Area of Edo State, Nigeria. The study compared the construction of two models of 225mm hollow sandcrete blocks and hydraform interlocking bricks, materials employed for wall construction for the study are; clay, cement, sand, water and mould. The result of the study indicates that unit cost of 225mm hollow sandcrete block and hydraform interlocking bricks are ₦168.57 and ₦57.85 respectively. While the cost per square metre of 225mm hollow sandcrete block wall and hydraform interlocking brick wall are ₦3,199.40 and ₦3,079.52 respectively. The study also revealed that it is more costly to apply finishes to sandcrete block wall when compared with hydraform interlocking brick wall. Sandcrete block wall requires rendering or plastering to both faces of the walls, while hyraform interlocking wall requires rendering of not more than 300mm girth to vertical external corners of the brick wall. The study, therefore, recommends the use of hydraform interlocking bricks for low-cost housing to reduce the housing deficit in Nigeria. Keywords: Sandcrete block; hydraform interlocking brick; walling; cost analysis; Auchi; DOI: 10.7176/JNSR/11-22-07 Publication date: November 30th 202

Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks

لضمان الإستجابة للخطأ والإدارة الموزعة، يتم استخدام البروتوكولات الموزعة كأحد المفاهيم المعمارية الرئيسية التي تتضمنها شبكة الإنترنت. ومع ذلك، يمكن التغلب على عدم الكفاءة وعدم الاستقرار والقصور بمساعدة بنية الشبكات الجديدة التي تسمى الشبكات المعرفة بالبرمجيات SDN. الخاصية الرئيسية لهذه المعمارية هي فصل مستوى التحكم عن مستوى البيانات. إن تقليل التصادم سيؤدي إلى تحسين سرعة الإستجابة وزيادة البيانات المرسلة بصورة صحيحة، لهذا السبب يجب أن يكون هناك توزيع متجانس للحمل المروري عبر مسارات الشبكة المختلفة. تقدم هذه الورقة البحثية أداة توجيه ذكية SFSA لتوجيه تدفق البيانات بناءاً على ظروف الشبكة الحالية. لتحسين الإنتاجية وتقليل زمن الوصول، فإن الخوارزمية المقترحة SFSA تقوم بتوزيع حركة مرور البيانات داخل الشبكة على مسارات مناسبة ، بالإضافة إلى الإشراف على الإرتباطات التشعبية وحمل مسارات نقل البيانات. تم استخدام سيناريو خوارزمية توجيه شجرة الامتداد الدنياMST وأخرى مع خوارزمية التوجيه المعروفة بفتح أقصر مسار أولاً OSPF لتقييم جودة الخوارمية المقترحة SFSA . على سبيل المقارنة ، بالنسبة لخوارزميات التوجيه المذكروة آنفاً ، فقد حققت استراتيجيةSFSA المقترحة انخفاضاً بنسبة 2٪ في معدل ضياع حزم البيانات PDR ، وبنسبة تتراوح بين 15-45٪ في سرعة إستلام البيانات من المصدر إلى الالوجهة النهائية لحزمة البيانات وكذلك انخفاض بنسبة 23 ٪ في زمن رحلة ذهاب وعودة RTT . تم استخدام محاكي Mininet ووحدة التحكم POX لإجراء المحاكاة. ميزة أخرى من SFSA على MST و OSPF هي أن وقت التنفيذ والاسترداد لا يحمل تقلبات. يتقوم أداة التوجيه الذكية المقترحة في هذه الورقة البحثية من فتح أفقاً جديداً لنشر أدوات ذكية جديدة في شبكة SDN تعزز قابلية برمجة الشبكات وإدارتها .To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distributes network traffic to suitable paths, in addition to supervising link and path loads. A scenario with a minimum spanning tree (MST) routing algorithm and another with open shortest path first (OSPF) routing algorithms were employed to assess the SFSA. By comparison, to these two routing algorithms, the suggested SFSA strategy determined a reduction of 2% in packets dropped ratio (PDR), a reduction of 15-45% in end-to-end delay according to the traffic produced, as well as a reduction of 23% in round trip time (RTT). The Mininet emulator and POX controller were employed to conduct the simulation. Another advantage of the SFSA over the MST and OSPF is that its implementation and recovery time do not exhibit fluctuations. The smart flow steering agent will open a new horizon for deploying new smart agents in SDN that enhance network programmability and management

Model of fire safety management for the assessment of an office building in FCT Abuja Nigeria

Fire safety management is essential in the aspects of achieving absolute fire safety standards in a building. Various Fire safety assessment methodologies and fire risk evaluation process has been developed over time, in spites of this, the fire risk keeps increasing, which implied that, there is a poor fire safety management. This study proposes a model of fire safety management for the fire risk assessment of an office building in Nigeria. The ten components of fire safety management were selected from the literature review, which was later structured to form criteria. The relative importance index was used to rank the level of compliance of fire safety management base on their influence. The questionnaires were the distribution to 30 fire safety practitioners and experts with substantial experience and knowledge in fire safety management. The data were analyzed using the relative importance index analytical approach. The evaluation model was suggested base on fire safety practitioners and experts’ perceptions. The inspection/observation of an office building was conducted in Nigeria in order to validate the model. The findings revealed that there is higher fire risk due to non- compliance with the standard fire safety management

SD–NFV as an Energy Efficient Approach for M2M Networks Using Cloud–Based 6LoWPAN Testbed

Machine–to–Machine (M2M) communication is the leading technology for realising the Internet–of–Things (IoT). The M2M sensor nodes are characterised by low–power and low–data rates devices which have increased exponentially over the years. IPv6 over Low power Wireless Personal Area Network (6LoWPAN) is the first protocol that provides IPv6 connectivity to the wireless M2M sensor nodes. Having a tremendous number of M2M sensor nodes execute independent control decision leads to difficulty in network control and management. In addition, these ever–growing devices generate massive traffic and cause energy scarcity which affects the M2M sensor node lifetime. Recently, Software–Defined Networking (SDN) and Network Functioning Virtualisation (NFV) are being used in M2M sensor networks to add programmability and flexibility features in order to adopt the exponential increment in wireless M2M traffic and enable network configuration even after deployment. This paper presents a proof–of–concept implementation which aims to analyse how SDN, NFV, and cloud computing can interact together in the 6LoWPAN gateway to provide simplicity and flexibility in network management. The proposed approach is called customised Software Defined–Network Functioning Virtualisation (SD–NFV), and has been tested and verified by implementing a real–time 6LoWPAN testbed. The experimental results indicated that the SD–NFV approach reduced the network discovery time by 60% and extended the node’s lifetime by 65% in comparison to the traditional 6LoWPAN network. The implemented testbed has one sink which is the M2M 6LoWPAN gateway where the network coordinator and the SDN controller are executed. There are many possible ways to implement 6LoWPAN testbed but limited are based on open standards development boards (e.g., Arduino, Raspberry Pi, and Beagle Bones). In the current testbed, the Arduino board is chosen and the SDN controller is customised and written using C++ language to fit the 6LoWPAN network requirements. Finally, SDN and NFV have been envisioned as the most promising techniques to improve network programmability, simplicity, and management in cloud–based 6LoWPAN gateway

Optimized Artificial Intelligence Model for DDoS Detection in SDN Environment

© Copyright 2023 The Authors. Distributed denial of service (DDoS) attacks continue to be a major security concern, threatening the availability and reliability of network services. Software-defined networking (SDN) has emerged as a promising solution to address this issue, enabling centralized network control and management. However, conventional SDN-based DDoS mitigation techniques often struggle to detect and mitigate sophisticated attacks due to their limited ability to analyze complex traffic patterns. This paper proposes an innovative and optimized approach that effectively combines mininet, Ryu controller, and one dimensional-convolutional neural network (1D-CNN) to detect and mitigate DDoS attacks in SDN environments. The proposed approach involves training the 1D-CNN model with labeled network traffic data to effectively identify abnormal patterns associated with DDoS attacks. Furthermore, seven hyperparameters of the trained 1D-CNN model were tuned using non-dominated sorting genetic algorithm II (NSGA-II) to achieve the best accuracy with minimum training time. Once the optimized 1D-CNN model detects an attack, the Ryu controller dynamically adapts the network policies and employs appropriate mitigation techniques to protect the network infrastructure. To evaluate the effectiveness of the optimized 1D-CNN model, extensive experiments were conducted using a simulated SDN environment with a realistic DDoS attack dataset. The experimental results demonstrate that the developed approach achieves significantly improved detection accuracy of 99.99% compared to other machine learning (ML) models. The NSGA-II enhances the optimized model accuracy with an improvement rate of 9.5%, 8%, 5.4%, and 2.6% when it is compared to logistic regression (LR), random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN) optimized models respectively. This research paves the way for future developments in leveraging deep learning (DL) driven techniques and SDN architectures to address evolving cybersecurity challenges

End-to-End Delay Enhancement in 6LoWPAN Testbed Using Programmable Network Concepts

This paper introduces a proof-of-concept 6LoWPAN testbed to study the integration of programmable network technologies in relaxed throughput and low-power IoT devices. Open source software and hardware platforms are used in the implemented testbed to increase the possibility of future network extension. The proposed architecture offers end-to-end connectivity via the 6LoWPAN gateway to integrate IPv6 hosts and the low data rate devices directly. Nowadays, SoftwareDefined Networking (SDN) and Network Function Virtualization (NFV) are the most promising technologies for dealing with the massive increase in M2M devices and achieving agile traffic. The developed approach in this paper is entitled tailored Software Defined-Network Function Virtualization (SD-NFV), which is aimed at reducing the end-to-end delay and improving the energy depletion in sensor nodes. Experimental scenarios of the implemented testbed are conducted using a simple sensing application and the obtained results indicate that the introduced approach is appropriate for constrained IoT devices. By utilizing SD-NFV scheme in 6LoWPAN network, the data delivery ratio increased by 5-14%, the node operational time prolonged by 70%, the end-to-end latency for gathering sensor data minimized by ≈160%, and the latency for transmitting control messages to a specified node diminished by ≈63% when compared to a traditional (non SDN-enabled) 6LoWPAN network

Adequate fire safety training for the occupants knowledge and awareness of fire safety

Achievement of fire safety objectives in buildings for the safety of lives, property conservation and business continuity is a collective responsibility of all the stakeholder, and its depends on the level of fire safety knowledge and awareness of the concern stakeholders. Therefore, this research was conducted to determine the fire safety training needs of fire safety practitioners and building managers for adequate fire safety knowledge and awareness of the building occupants in Nigeria. The research adopted questionnaires survey research design. The research population for the study comprises of 349 building manager and fire safety practitioners from six (6) north-central states of Nigeria. A research questionnaires was design for the study, the questionnaires was distributed to collect the data from the participants and was validated by experience fire safety experts; the Cronbach alpha reliability approach was used to identified the internal consistency of the questionnaires items at 0.933. the collected data were analyzed through CFA using SPSS and AMOS software, after the analysis, the data from the participants were adjudge appropriate for inclusion into the confirmatory factor analysis. The CFA was carried out and finding from the analysis is in agreement with one-factor model of fire safety training program for the enhancement of the occupant’s fire safety knowledge and awareness. The research found that fire safety practitioners and building manager requires the components for effective fire safety training. Therefore, it was suggested that the stakeholders should prioritize adequate fire safety training of the occupants and public in the fire safety for boosting their knowledge and awareness of fire safety

SELECTED WELFARE PARAMETERS OF BROILER CHICKENS ON DIFFERENT FEED QUANTITY AND TIME

This study was conducted to determine welfare of broiler chickens fed ad libitum and restricted feed during early (08.00hour) and late (16:00hour) of the day. One hundred and eighty (21d old) broiler chickens were randomly allocated to 4 treatments in a 2x2 factorial arrangement comprising of ad libitum and restricted feeding (75% of ad libitum) quantity at 8 and 16 hours feeding time in three replicates. Data were collected on leg problem, dust bathing, body temperature, mortality and haematology. Result revealed that neither feed quantity nor time had significant (P>0.05) effect on leg problem, dust bathing and mortality of broiler chickens. Broiler chickens under ad lib feed quantity and 16:00hours feeding time had (P<0.05) highest body temperature (40.93oC) while those under ad libitum morning (08:00hours) recorded the least (40.75°C). Pack Cell Volume had similar (P>0.05) increase from 26.75% at the beginning (21d) to 31.25 (%) at 56d with broiler chickens under restricted feeding and fed at 16:00hours feeding time. Basophil count reduced from a range of 0.5-2% (P<0.05) to 1% (P>0.05) with restricted feeding. Also eosinophil reduced from 2-4% (P<0.05) range to 0-2.5% (P>0.05) with restricted feeding while birds under ad lib increased from 0-1% (P<0.05) at 21d to 2.75% (P>0.05) at 56d. Better welfare (good body temperature) of broiler chicken could be achieved with early feeding time irrespective of quantity. However, restricted feeding could be explored in broiler production where reduced basophil, eosinophil and stress are vital for enhanced welfare and performance.   &nbsp