2026-05-04T18:20:58Z https://nadre.ethernet.edu.et/oai2d

oai:zenodo.org:13488 2025-07-28T13:07:06Z user-001

Adugna Mekonnen 2025-07-28 Mobile ad hoc consists of mobile nodes that can move from one location to another location freely at any time to any directions. Mobile nodes are linked together to transfer data packet from source node to destination node. Two nodes can communicate to each other using the link between them. If the link between the two nodes is broken, the two nodes cannot communicate to each other. In MANET, two nodes can communicate directly if only if they are in the same range. In different range they use intermediate node to forward information. To transfer data packet from source to destination it needs enough energy and received power. Nodes are linked together to facilitate the routing protocol in MANETs. When nodes have no enough energy and received power the link between each node is not working properly to transfer the required information and it decreases the quality of services in the network. This problem makes the performance of whole network low. When the performance of network became low it reduces throughput, packet delivery ratio, increase packet loss and overhead etc. Some routing protocol selects shortest path but selecting only the shortest path is not enough to send data packet. Based on the above problem this thesis proposed to improve the performance of AODV routing protocol by computing the received signal strength and residual energy of nodes for mobile ad hoc network. In this work, network simulator 2 (NS2) is used for simulation purpose. The simulation results demonstrated in terms of packet delivery ratio, throughput, residual energy, consumed energy and end-to-end delay. The simulation result shows that the amount of energy consumed was reduced and but the amount of residual energy in the new solution increased in all scenarios, packet delivery ratio increased as number of nodes increased, end-to-end delay decreased and the average throughput increased in new solution when compared with the existing AODV routing protocol as shown under Table 3, 4,5,6,7. https://zenodo.org/record/13488 10.20372/nadre:13488 oai:zenodo.org:13488 eng doi:10.20372/nadre:13487 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by MANET, routing protocol, AODV, link breakage, link quality Improving the performance of Ad hoc on demand distance vector routing protocol by computing the residual energy and received signal strength of nodes for mobile ad hoc network info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:13492 2025-07-28T13:09:15Z user-001

ANCHINESH MOLLA 2025-07-28 The wheat crop is among the most significant staple cereal crops in the world. Ethiopia is first in both area and area output of wheat in sub-Saharan Africa, with a share of 55.5% and 47.82% capacity to become a regional exporter. The most prevalent diseases in wheat are wheat leaf rust, wheat yellow rust, and wheat stem rust. It affects the production and quality of wheat all over the world. Because rust disease spreads rapidly in a matter of days, early detection is a difficult task. The research problem addressed in this study is the lack of accurate and efficient methods for early detection and classification of wheat rust disease. Traditional methods of detecting and classifying wheat rust diseases are time-consuming and less accurate than deep learning techniques. Lack of studies that explore the use of deep learning techniques for the detection and classification of wheat rust disease in Ethiopia are research gaps we identified. The study aimed to fill this gap by exploring the effectiveness of deep learning techniques for this purpose. Adet and Arebaminch agricultural research centers were the institutes in Ethiopia where the images of wheat leaf and stem were taken. A total of 2538 images were gathered and compiled for this study we have 15,318 total dataset after augmentation. The suggested system incorporates image preprocessing elements like resizing and augmentation. To accomplish the key goal in this study, pre-trained VGG-19, ResNet-50, and convolution neural network techniques are employed. Regularization methods like dropout, L1 regularization, and early stopping were proposed in this study to improve the model's effectiveness and accuracy. The experimental result shows that the test accuracy obtained from the transfer learning models VGG19 and ResNnet_50 achieves an accuracy of 81.7% and 84.8%, respectively by using our dataset. Furthermore, the proposed model outperforms in terms of performance and successfully detects and classifies the examined images with a training accuracy of 97.07.8% and a testing accuracy of 96.23% with the softmax activation function after applying the regularization method. The research contribution of this study is the development of accurate model for detecting and classifying wheat rust disease. https://zenodo.org/record/13492 10.20372/nadre:13492 oai:zenodo.org:13492 eng doi:10.20372/nadre:13491 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by wheat rust disease, fine tuning, softmax, Convocational neural networks, transfer learning, deep learning Detection and Classification of Wheat Rust Disease Using Deep Learning info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:13502 2025-07-28T13:15:42Z user-001

Fekede Beshada 2025-07-28 Mobile ad hoc network (MANET) is wireless network that has feature of frequent topological changes, node mobility, and insufficient central coordination. In MANET routing scenario source & destination act as a host while other intermediate nodes act as a router this characteristic makes routing in MANET challenge. Again, Provide Quality of Services (QoS) application in MANET environments is more difficult task due to character of nodes. AOMDV routing is a typical MANET routing protocol which deliver services without any guarantee of QoS; only used best effort delivery techniques. Several empirical studies have discovered routing protocol with QoS improvement, but few relate to various protocols regarding routing and quality of service (QoS) and none of them are investigated AOMDV Routing protocol related to bandwidth and buffer size in MANET. Thus, this thesis proposed to modify AOMDV protocol to improve QoS by using available bandwidth and buffer size to select a path in addition to hop count in original AOMDV routing protocol which we named as modified AOMDV (MDAOMDV). To estimate the available bandwidth each node calculates by listening to its channel and finally to encapsulate route request (RREQ) packet during the route discovery process. In route reply (RREP) message back to that paths through different path from which RREQ have been received in MDAOMDV routing protocol. Source node receives multiple RREP messages from multiple paths. Finally, the source chooses the best path on basis of the available bandwidth and buffer size in addition to hop count as routing metric which is better from the available active path from multiple RREP message. The proposed MDAOMDV routing protocol implemented using NS2.35 simulator tool. We have evaluated the performance of MDAOMDV and AOMDV routing protocol using the following four output metrics: throughput, packet delivery ratio, end to end delay and residual energy. Finally, we have compared original AOMDV with MDAOMDV routing protocols within the selected four performance metrics and based on the summary of the simulation result in table 4.2, the MDAOMDV outperform the original AOMDV protocol. https://zenodo.org/record/13502 10.20372/nadre:13502 oai:zenodo.org:13502 eng doi:10.20372/nadre:13501 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by MANET, QOS, MDAOMDV, AOMDV, Available bandwidth, buffer size Improving Quality of Service in AOMDV Routing Protocol using Available Bandwidth and Buffer Size in MANET info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:13496 2025-07-28T13:12:32Z user-001

Chimdesa Gedefa 2025-07-28 MANET is a group of wireless mobile nodes that form a dynamic network without the need for any infrastructure. Because MANET is dynamic and has a finite amount of energy, it is vulnerable to many non-cooperative node types. However, traditional MANET routing protocols have no battery consideration parameter, and the node can get energy from the attached battery, which means there is no energy recharge or replacement technique. Numerous research techniques for identifying and preventing such non-cooperative node behaviors have been offered to promote trusted, stable communication in such networks. Participating nodes must collaborate in routing and forwarding for MANET to function as intended. Due to energy limitations, a node may choose not to participate. In this study, we suggest a "trusted stable energy-aware path selection" Ad -hoc on-demand Distance Vector Algorithm (Proposed-AODV) based approach designed to capture noncooperative nodes and select a proper forwarder node for improving overall packet delivery of the network and prolonging the network lifetime of MANETs. The approach takes into account individual node residual energy and hop count to terminate non-cooperative nodes, thereby extending the MANET network lifetime. To assess the proposed AODV routing protocols, we have used NS2.35 as a simulation tool. And also, we have used normalized energy consumption, PDR, E2E Delay, detection rate, and the lifetime of the network as performance metrics. Based on the performance of our Proposed-AODV routing algorithm shows an average detection rate of 8.7% more than the AODV routing algorithm, an Average extending network lifetime of 3.5% more than the AODV algorithm, respectively and an Average normalized energy consumption of ProposedAODV 2.2% less than AODV routing algorithm. Generally, the simulation values indicate better performance compared to the other existing strategies covered in the studies. https://zenodo.org/record/13496 10.20372/nadre:13496 oai:zenodo.org:13496 eng doi:10.20372/nadre:13495 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by MANETs, Residual Energy, Non-cooperative node, Network life time, AODV. Stable Energy-Aware Path Selection Method for Ad-hoc On-Demand Distance Vector Routing Protocol in Non-Cooperative Nodes info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:13504 2025-07-28T13:17:06Z user-001

Haile-eyesus Tassew 2025-07-28 The use of portable devices is staggeringly increased in the past decade with it comes many compute intensive applications and services such as image processing and online gaming. Even though these devices support user’s mobility efficiently they also have some limitations that include limited battery energy, lower processing capacity and limited storage space compared to the common stationed computing devices. A cloudlet-based mobile cloud computing architecture is introduced to circumvent the limitations of these devices. A cloudlet is a single or cluster of computers that allow users to offload their compute intensive applications thus the cloudlets process the applications and return the output back to the users. The cloudlets are connected with remote cloud servers so they can upload and download services and files their user’s request. Cloudlet based architecture should support mobility of the users while accessing the services. Multiple cloudlets must be deployed in nearby locations to offer their service on multiple locations. To support user’s mobility a data exchange approach among these cloudlets is required. The data exchange helps the cloudlets to distinguish other cloudlets activity. In this research work, a new data exchange approach is proposed aiming to improve the data flow. The approach offers some methods for predicting the user’s next location as well as predicting user hosting capacity of other cloudlets. The approach is designed to provide high quality cloudlet services and other location dependent services while facilitating mobility of the user’s that are accessing the system. It also reduces the delay time associated with the movement of the users. The proposed system is implemented and tested on CloudSim and CloudExp simulation tools. https://zenodo.org/record/13504 10.20372/nadre:13504 oai:zenodo.org:13504 eng doi:10.20372/nadre:13503 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by Cloud Computing, Cloudlets, Mobile Cloud Computing, Multi-Cloudlets. An Extensive Data Exchange Approach among Cloudlets in Multi-Cloudlet Mobile Cloud Computing Environment info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:13498 2025-07-28T13:14:06Z user-001

EYASU BEYENE 2025-07-28 Wireless sensor networks (WSNs) used in different areas such as in military and defense, process control industry and health monitoring applications area. In WSNs sensors are small size with constraint battery capacity and there are different sources contribute to energy inefficiency in MAC- protocols like ours research problem idle listening. In this study we are used logistic regression based duty-cyclemethod to efficient energy in WSNs. In logistic regression based, all the nodes are allocated to the equivalent levels according to the hop count to the sink node, and calculate their minimum transmission delay to the sink node based on the shortest pathwayarrangement. Finally, simulation results show that their proposed algorithm can accomplish better performance compared with older AODV. After simulation, it was found that MAC with logistic regression is Power-Efficient over MAC without logistic regression without losing on the performance using MATLAB. It is conducted using MATLAB simulator based on 802.11 IEEE MAC layer standards. The Simulation evaluation is performed based on residual energy, throughput , packet delivery ratio , end-to-end delay ,and network life time. when we are appling logistic regration on MAC protocol 50% PDR, 70%Resudial enrgy, 25%throghput, and network life time are emproved but less in delay. https://zenodo.org/record/13498 10.20372/nadre:13498 oai:zenodo.org:13498 eng doi:10.20372/nadre:13497 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by Performance analysis; energy- efficient: idle listening; MAC Protocol: Wireless sensor networks Energy Efficiency of MAC in Wireless Sensor Networks using logistic Regression Based Dynamic Duty Cycle info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:13494 2025-07-28T13:10:40Z user-001

Chala Geleta 2025-07-28 Software-defined networking (SDN) is a network architecture in which the network traffic may be operated and managed dynamically according to user requirements and demands. This research work mainly focuses on the Design of SDN with a Hybrid cryptography Algorithm (RSA-AES) to improve the security of MANET where security challenges arise due to MANET’s Self-configuration and Self-maintenance capability. The simulation model was used to run a program by configuring RSA (Rivest, Shamir, Adleman)-AES (Advanced Encryption Standard) Cryptography Algorithm with SDN. The proposed Hybrid cryptography algorithm Based SDN mainly creates strong detection, prevention, and authentication mechanism for MANET. The proposed secure data channels throughput increased by 0.4% and The suggested system Delay was 1.7% lower than the Normal MANET. It is already proved that the Hybrid cryptography algorithm also generates a key for security faster than both AES and RSA. It is already proved that the hybrid cryptography algorithm also generates a key for security faster than both AES and RSA so it consumes less memory space than both AES and RSA. This is an appropriate choice for a wireless network like MANET, VANET, and WSN with limited resources like memory space, bandwidth, and power. https://zenodo.org/record/13494 10.20372/nadre:13494 oai:zenodo.org:13494 eng doi:10.20372/nadre:13493 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by Software-Defined Network, SDMN, HCA_SDN, Mobile Ad-hoc Networks, Security, NS-3, Python programming language. Improving Security of Mobile Ad Hoc Network by Hybrid cryptography algorithm (RSA-AES) Based Software Defined Network info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:13508 2025-07-28T13:19:41Z user-001

Hussein Abdumalik 2025-07-28 Ad Hoc Network is wireless networks that get more attention from past to present. Mobile ad hoc network (MANET) is one of the types of ad hoc networks, it deployed rapidly because it infrastructure-less. Node in mobile ad hoc network communicates through wireless links without wired channels. When source nodes want to communicate with the destination outside its transmission range it uses multi-hop mechanisms. Intermediate node forwards the data packet to the next node until the data packet reaches destinations. Due wireless links and lack of centralized administration device, mobile ad hoc network is more vulnerabile for security attacks. Rushing attack is one of the most dangerous attacks in the on-demand routing protocol of mobile ad hoc networks. Rushing attack highly transmit route request with higher transmission power than the genuine nodes and become participate between source and destination nodes, after that it delay or drop actual data pass through it. In this study, the researcher incorporate rushing attack in one of the most commonly used mobile ad hoc network routing protocol namely Ad hoc on-demand multipath distance vector and provides rushing attack prevention method based on time threshold value and random route selection. Based on the time RREQ arrives a node takes a decision, if the RREQ packet arrives before threshold value, the RREQ packet consider as came from an attacker and discarded else RREQ packet received then randomly select RREQ to forward. In this study performance metrics like packet delivery ratio, end to end delay and throughput have been evaluated using Network simulation (NS-2.35). As a result of simulation shows newly proposed prevention mechanism improves network performance in all cases than the network under attacker. For example average packet delivery ratio enhanced from 54.37% to 97.69%, throughput increased from 20.84bps to 33.06bps and the average delay decreased from 1147.22ms to 908.04ms. We concluded that new proposed techniques show improvement in all evaluated performance metrics. https://zenodo.org/record/13508 10.20372/nadre:13508 oai:zenodo.org:13508 eng doi:10.20372/nadre:13507 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by AOMDV, MANET, Rushing Attack, Random route selection, time threshold value Technique, Simulation Network (NS2). Prevention of Rushing Attack in AOMDV using Random Route Selection Technique in Mobile Ad-hoc Network. info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:13514 2025-07-28T13:23:33Z user-001

Tilahun Tadege 2025-07-28 Crime is a serious social issue, and criminal acts are increasing from time to time. Analyzing committed crime datasets and preventing crime is a challenging task for law enforcement bodies due to the increasing number of crime records. One possible means to prevent the increase in crime issues could be based on the analysis and understanding of past committed crime records using classification machine learning algorithms. This study aims to build a model for crime analysis and predict crime using a stacked-based classification model. For this study, the secondary crime dataset has been collected from the Gedeo Zone police commission and has been recorded from the year 2005 up to 2013 E.C. The total size of the collected data after preprocessing is 11,159, which is used to develop the proposed model. The train-test option has used 70%–30%, respectively. The KDD process model has been followed for this research. Python 3 programming language technology and five classification machine learning techniques such as LR, DT, ANN, KNN, and stacked classification techniques were used to carry out the experimentations. Five experiments have been performed iteratively to build a model based on selected crime features, which include: crime cause, crime category, crime type, criminal sex, criminal age, criminal job, criminal marital status, criminal education status, crime incident place, crime incident time, and crime incident month. The comparison of the developed model is based on the accuracy of crime-type prediction performance. The prediction accuracy rate of each developed model is 87.46%, 96.59%, 97.7%, 98.72%, and 99.64% for DT, KNN, ANN, LR, and stacked models, respectively. Depending on the accuracy rate of the model, the stacked classification technique is the selected model for this study. The result of this model can support the Gedeo Zone Police Commission in preventing future crimes and helping to optimize resource allocation. We recommended improving the performance of accuracy in this area by applying more crime datasets and more stacking classification algorithms. https://zenodo.org/record/13514 10.20372/nadre:13514 oai:zenodo.org:13514 eng doi:10.20372/nadre:13513 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by Stacked classification, machine learning, crime prediction, crime data. Crime Analysis and Prediction Model using Stacked Classification Machine Learning Algorithms: Case of Gedeo Zone Police Commission info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:13506 2025-07-28T13:18:22Z user-001

Hassen Haile 2025-07-28 The wireless sensor network accumulates and processes data in a cooperative way to manage a variety of wireless sensor networks, such habitat and environmental monitoring. In WSN applications, sensor placement is a crucial task. The deployment's performance, precision, and cost will be determined by the number of sensors and where they are placed. Node deployment dictates where the sensor nodes should be located to achieve the required objectives, such as maximizing the effective minimizing network size and cost of the coverage area ratio is a challenge in the application of WSNs. The coverage offered by the sensors deployment strategy heavily influences how effective these networks are. We presented the details of a grid-based heterogeneous node deployment in this thesis, in which sensor nodes have various processing and hardware functionality by node in a hex scheme, cover a limited number of sensor nodes, and reduce sensor node prices. In comparison to the previous system, the proposed technique used smaller sensor nodes to cover the area than the previous one. For the proposed system's implementation and performance evaluation, we used MATLAB. Moreover, we examine the performance of heterogeneous WSNs protocols in this paper under multi-level and three-level heterogeneous networks. Based on the evaluation results, we compared the efficiency of DEEC, DDEEC, and EDEEC, where, for example, when the number of iterations is 5000, DEEC, DDEEC, and EDEEC packets are sent to the base station in percentages of 80.1%, 86.3%, and 91.2%, respectively. The results obtained by the implementation of proposed node deployment algorithm with EDEEC routing algorithm are compared with previous deployment approach (existing state of art work) using mathematical modeling, theoretical analysis and formula deduction. The results show that the proposed approach consumes minimum number of node and minimum amount of deployment cost and better network lifetime. https://zenodo.org/record/13506 10.20372/nadre:13506 oai:zenodo.org:13506 eng doi:10.20372/nadre:13505 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by Coverage, Deployment Scheme, Sensor Node, Network Lifetime, Hexagonal Scheme, Heterogeneous Wireless Sensor Networks Heterogeneous Wireless Sensor Network with Grid Based Node Deployment Strategy info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:13510 2025-07-28T13:20:57Z user-001

OBSA DEGEBASA 2025-07-28 Wireless sensor network (WSN), are composed of sensor nodes and base station, having unique characteristics of self-organizing nature, low battery power supply, limited bandwidth support, distributed operations using open wireless medium, and multi-hop traffic forwarding. As a result WSN are vulnerable to various security attacks particularly to DoS attacks which disrupt the network operations and degrade the network performance. Specifically LEACH protocol, which is clustering algorithm used for WSN, is very exposed to the most DoS attack, which is Balckhole attack. So classification and detection system which must be compatible with the specified characteristics of LEACH based WSN and which has a capability of detecting Balckhole attack, with a low false alarm rate and high detection rate has required proposing. A novel deep learning based classification and detection system has proposed to solve those problems. For the training and testing of proposed system the dataset called Simulation-DS collected using Matlab has used. Python programming language has used for the implementation of proposed models on a Jupyter notebook of Anaconda platform. The performance metrics used were True Positive Rate (TPR), True Negative Rate (TNR), False Positive Rate (FPR), False Negative Rate (FNR), Accuracy, precision, Recall, and F1-score. Three deep learning based classification and detection models were proposed, from which CNN has outperformed the other proposed models and other related works, with high detection rates of 99.86%, and 99.99% for Blackhole attack, and Normal traffic respectively, and with low false alarm rates of 0.007%, and 0.14% for Blackhole attack, and Normal cases respectively. https://zenodo.org/record/13510 10.20372/nadre:13510 oai:zenodo.org:13510 eng doi:10.20372/nadre:13509 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by DoS attacks, Classification and Detection System, Wireless Sensor Network, Deep Learnin A Blackhole attack classification and detection system for LEACH based Wireless Sensor Network using Deep Learning approach info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:13516 2025-07-28T13:24:47Z user-001

Yihenew Gebru 2025-07-28 Mobile Ad-hoc Network is a type of wireless network, which consists of mobile wireless nodes and the communication between mobile nodes is carried out without any centralized administrator. Vehicular ad-hoc network is a type of wireless network and it is a particular kind of Mobile Ad-hoc Network, which is exists in the form of vehicle to vehicle, vehicle to Infrastructure, and Infrastructure to Vehicle communication. So vehicular ad-hoc network is one of the interesting research areas in mobile networks. Routing protocols used in networking environment are considered to play an important role towards the performance, reliability and efficiency of the communication system. Among the different types of routing protocols, those are used in VANET environments to support the transportation system, reactive topology-based routing protocols are selected because of their dynamic characteristics in designing the routing table when it is needed. In this research we attempt to enhancing TORA and analyze the performance with AODV routing protocol in traffic engineering to ensure the quality of service issues for the help of intelligent transportation system. In this research, network simulator version 2 is used for the implementation and performance evaluation of the protocols. Moreover, evaluation of AODV and TORA performance was made through three different scenarios based on the number of nodes participating in the network. The result obtained by the simulation is compared in different scenarios by using the network performance metrics. The result shows that the average simulation result of AODV and TORA by using different performance metrics, AODV delivers superior quality of service than TORA, but based on throughput performance metric alone TORA outperforms when the number of nodes is smaller. https://zenodo.org/record/13516 10.20372/nadre:13516 oai:zenodo.org:13516 eng doi:10.20372/nadre:13515 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by VANET, AODV, TORA, VANET Routing Protocol, Traffic Engineering Enhancing TORA and Analyze with AODV Routing Protocol in Vehicular Ad-hoc Network for Traffic Engineering info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:13512 2025-07-28T13:22:14Z user-001

Sultan Redi 2025-07-28 Very Small Aperture Terminal (VSAT) network services are widely used in Ethiopia in Schoolnet systems of secondary and preparatory schools mainly for two services such as TV broadcast learning and Internet. There is also used in remote area worades for Woredanet system to access different services like Videoconferencing, however the widest use of very small aperture terminal (VSAT) network service is for SchoolNet purpose. The main aim of Very Small Aperture Terminal (VSAT) network service in Ethiopian Schoolnet is for quality and unified education over the entire country. The purpose of this paper is to effective VSAT service analysis in Silte Zone Ethiopia by analyzing the effect of Time division multiple access architecture (TDMA) and Frequency Division Multiple Access Architecture (FDMA), Internet speed, response time and delay, to identify the main factors which affect VSAT service performance. In this paper the weather effect on VSAT service is measured by using different tolls such as Coal soft caps enterprise, Wireshark, speakeasy/speed.net and signal quality and intensity is measured by using signal tester in different weather conditions with purposefully selected 10 secondary and preparatory schools. The measurement result is presented graphically and theoretically. In this study the proposed system to access VSAT service properly for its main target the network framework is recommended. The architecture of VSAT service in SchoolNet effect is also identified, frequency division multiplexing architecture (FDMA) is used to allocate channels with different frequency level. Time division multiple access architecture (TDMA) is used in existing architecture of VSAT network service to allocate channels with different time schedule. This two architectures lack of flexibility to access program in current SchoolNet system. https://zenodo.org/record/13512 10.20372/nadre:13512 oai:zenodo.org:13512 eng doi:10.20372/nadre:13511 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by SchoolNet, capsa, VSAT, wireshark EFFECTIVE ANALYSIS OF VSAT SERVICE PERFORMANCE IN ETHIOPIA SCHOOLNET SILTE ZONE info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:17816 2025-09-08T12:02:16Z user-001

Yihenew Gebru Mengistu 2025-09-08 Abstract Mobile Ad-hoc Network is a type of wireless network, which consists of mobile wireless nodes and the communication between mobile nodes is carried out without any centralized administrator. Vehicular ad-hoc network is a type of wireless network and it is a particular kind of Mobile Ad-hoc Network, which is exists in the form of vehicle to vehicle, vehicle to Infrastructure, and Infrastructure to Vehicle communication. So vehicular ad-hoc network is one of the interesting research areas in mobile networks. Routing protocols used in networking environment are considered to play an important role towards the performance, reliability and efficiency of the communication system. Among the different types of routing protocols, those are used in VANET environments to support the transportation system, reactive topology-based routing protocols are selected because of their dynamic characteristics in designing the routing table when it is needed. In this research we attempt to enhancing TORA and analyze the performance with AODV routing protocol in traffic engineering to ensure the quality of service issues for the help of intelligent transportation system. In this research, network simulator version 2 is used for the implementation and performance evaluation of the protocols. Moreover, evaluation of AODV and TORA performance was made through three different scenarios based on the number of nodes participating in the network. The result obtained by the simulation is compared in different scenarios by using the network performance metrics. The result shows that the average simulation result of AODV and TORA by using different performance metrics, AODV delivers superior quality of service than TORA, but based on throughput performance metric alone TORA outperforms when the number of nodes is smaller. https://zenodo.org/record/17816 10.20372/nadre:17816 oai:zenodo.org:17816 eng doi:10.20372/nadre:17815 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by VANET, AODV, TORA, VANET Routing Protocol, Traffic Engineering Enhancing TORA and Analyze with AODV Routing Protocol in Vehicular Ad-hoc Network for Traffic Engineering info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:20089 2025-10-15T07:32:57Z user-001

Mesfin Kiflu 2025-10-15 Abstract: Mobile Ad Hoc Networks (MANETs) are a prominent category of wireless networks that operate without fixed infrastructure, offering great flexibility in dynamic environments such as battlefields, remote areas, and smart cities. However, due to their decentralized structure and limited security in routing protocols, MANETs are more vulnerable to attacks compared to traditional wired networks. Specifically, black and gray hole attacks represent a serious threat, as malicious nodes exploit network resources, significantly degrading overall network performance. This thesis presents an efficient attack detection system aimed at enhancing the security of the Ad-hoc On Demand Distance Vector (AODV) routing protocol to detect both black hole and gray hole attacks in MANETs different nodes using deep learning techniques. The research is conducted in two key phases. The first phase involves dataset preparation, where network traffic data is generated through simulations in NS-2 (Network Simulator version 2). These simulations incorporate both normal and malicious behaviors, representing black and gray hole attacks within the context of AODV. After pre-processing and analysis, a refined dataset consisting of 28,691 records with 21 features is extracted from the trace files. In the second phase, the proposed detection system is developed and evaluated. The dataset is divided into training (80%) and testing (20%) subsets. Feature selection is carried out using the Categorical Boosting (CatBoost) importance score, with a threshold applied to select the most relevant features. Additionally, the Synthetic Minority Over sampling Technique (SMOTE) is utilized to ensure balanced data for the model. The system employs advanced deep learning architectures, including Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid CNN-LSTM model. The experimental results show that the proposed system achieves high detection accuracy across various models: LSTM (98.57%), GRU (98.46%), CNN_LSTM (98.60%), and CNN (98.48%). These results demonstrate hybrid CNN_LSTM model show high accuracy and how well the suggested method works to improve MANET security by precisely identifying black hole and gray hole attacks. https://zenodo.org/record/20089 10.20372/nadre:20089 oai:zenodo.org:20089 eng doi:10.20372/nadre:20088 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by MANET, Deep Learning, XGBoost, CatBoost, Black Hole, Gray Hole. Deep Learning-Based Detection for Black Hole and Gray Hole Attacks in AODV routing protocol MANETs info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:20085 2025-10-15T07:30:06Z user-001

Kabtimer Kassa Laymektu 2025-10-15 ABSTRACT: A key element of heterogeneous wireless networks is the existence of many Radio Access Technologies (RATs) within the same service region. Based on the enhancement of vertical handoff RAT selection in HWN, it is desired to maintain uninterrupted connectivity of vertical handoff while maximizing QoS to satisfy user needs. The Main challenging issue in the vertical handoff RAT selection algorithm in an HWN, is the complexity of choosing the most appropriate network when the mobile user seamlessly roams across different RATs based on user context QoS criteria. This study focuses on network selection strategies based on QoS class to enhance vertical handoff between different RATs like LTE, WLAN, and WiMAX. This paper proposed a Fuzzy-Based Hybrid FAHP-FTOPSIS algorithm for Enhancing Vertical Handoff RAT Selection in HWN. The hybrid algorithm was developed by combining the Fuzzy Analytical hierarch process (FAHP) methods for computing weight scores with the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) methods for ranking RATs. This hybrid algorithm developed considered the current and the new RSSI threshold and enabled fuzzy inference system IF then rule to monitor the QoS classes. This hybrid algorithm was evaluated and simulated by MATLAB software simulation tool. The simulation result shows that the hybrid algorithms reduce handoff decision delay by 1.49%, 4.5 %, and 5% on conventional, 2 %, 2.51% and 2.98% on interactive, 2.96%, 4.99%, and 7.1% on background, and 2.13%, 6.2%, 7.97% on streaming class. Handoff failure reduced by 1.8%, 2.7%, and 3.2% on conventional, 5.1%, 7.15%, and 9% on interactive, 6%, 9.1%, and 15% on the background, and 3.12%, 7.1%, and 22% on streaming application compared to FTOPSIS, TOPSIS, and SAW algorithms respectively. Finally, the hybrid FAHP-FTPOSIS algorithm enhances vertical handoffs compared to FTOPSIS, TOPSIS, and SAW, algorithms in terms of best network selection by prioritizing user QoS handoff criteria. However, this paper does not consider security and RAT load balance. Therefore, in future work, will consider expanding the hybrid algorithm in this study by adding security and RAT load balancing. https://zenodo.org/record/20085 10.20372/nadre:20085 oai:zenodo.org:20085 eng doi:10.20372/nadre:20084 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by Fuzzy logic, Vertical handoff, QoS, RATs, FAHP, FTOPSIS, HWN Fuzzy-Based Hybrid FAHP-FTOPSIS Algorithm for Enhancing Vertical Handoff RAT Selection in Heterogeneous Wireless Network info:eu-repo/semantics/doctoralThesis publication-thesis

oai:zenodo.org:20482 2025-10-22T11:41:12Z user-001

Natan Tesfaye 2025-10-22 Abstract: The need for scalable and effective data center networks has grown as a result of the big data analytics, cloud computing, and internet of things (IoT) industries' explosive growth. Traditional network architectures often struggle to keep track with the dynamic and resourceintensive needs of modern data centers. By separating the control plane from data plane, software defines network (SDN) has become a viably way to overcome this obstacles and allow for more programmable and adaptable network administration. The scalability, flexibility and manageability issues I medium-scale data centers can be addressed by the new and promising concept known as Software Defined Networking (SDN). This study aims to evaluate the performance of SDN implementations within such environments. Through a comprehensive review of existing literature, coupled with empirical analysis, this study investigates the impact of SDN on key performance metrics including throughput, latency, scalability, and resource utilization. Various SDN architectures, protocols, and deployment strategies are examined to identify their efficacy in medium-scale data center settings. By establishing a planned topology, the results offer important insights into the advantages and disadvantages of SDN in terms of maximizing network performance and scalability in the context of medium-sized data centers. First, a thorough analysis of SDN controllers was conducted, and the superior ONOS controller was chosen. After that, LXC is used to create three ONOS controllers and Python to develop tree topologies in Mininet. It is then examined the latency and throughput of these three ONOS controllers. The throughput and latency results for three, five, and seven ONOS controllers have finally been given. It is then, examined, and assessed the throughput and latency, of these three ONOS controllers. Three, five, and seven ONOS controllers' throughput and latency results have been shown by the researcher. The three ONOS controllers have a latency of 252.12 to 298.01 responses/ms and a flow/s throughput of 218916.5 to 229388.9. The five ONOS controllers have a latency of 761.82 to 894.03 responses/ms and a flow/s throughput of 656749.5 to 688166.7. The throughput of the Seven ONOS controller ranges from 1970248.50 to 2064500.10 flows/s, while the latency ranges from 2264.08 to 2667.09 responses/ms. https://zenodo.org/record/20482 10.20372/nadre:20482 oai:zenodo.org:20482 eng doi:10.20372/nadre:20481 url:https://nadre.ethernet.edu.et/communities/001 info:eu-repo/semantics/openAccess http://www.opendefinition.org/licenses/cc-by Performance Analysis of Software Defined Networking (SDN) in MediumScale Data Centers by Using Distributed Con info:eu-repo/semantics/doctoralThesis publication-thesis