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Articles 61 - 90 of 3475
Full-Text Articles in Computer Sciences
Moment-Preserving Piecewise Approximation For 1-D And 2-D Signals, Soha M. A. A. Seif
Moment-Preserving Piecewise Approximation For 1-D And 2-D Signals, Soha M. A. A. Seif
Archived Theses and Dissertations
No abstract provided.
Spatio-Temporal Relation Modeling For Few-Shot Action Recognition, Anirudh Thatipelli, Sanath Narayan, Salman Hameed Khan, Rao Muhammad Anwer, Fahad Shahbaz Khan, Bernard Ghanem
Spatio-Temporal Relation Modeling For Few-Shot Action Recognition, Anirudh Thatipelli, Sanath Narayan, Salman Hameed Khan, Rao Muhammad Anwer, Fahad Shahbaz Khan, Bernard Ghanem
Computer Vision Faculty Publications
We propose a novel few-shot action recognition framework, STRM, which enhances class-specific feature discriminability while simultaneously learning higher-order temporal representations. The focus of our approach is a novel spatio-temporal enrichment module that aggregates spatial and temporal contexts with dedicated local patch-level and global frame-level feature enrichment sub-modules. Local patch-level enrichment captures the appearance-based characteristics of actions. On the other hand, global framelevel enrichment explicitly encodes the broad temporal context, thereby capturing the relevant object features over time. The resulting spatio-temporally enriched representations are then utilized to learn the relational matching between query and support action sub-sequences. We further introduce a …
Analyzing And Detecting Android Malware And Deepfake, Md Shohel Rana
Analyzing And Detecting Android Malware And Deepfake, Md Shohel Rana
Dissertations
Rapid advances in artificial intelligence (AI), machine learning (ML), and deep learning (DL) over the past several decades have produced a variety of technologies and tools that, among numerous cybersecurity issues, have enticed cybercriminals and hackers to design malware for the Android operating systems and/or manipulate multimedia. For example, high-quality and realistic fake videos, images, or audios have been created to spread misinformation and propaganda, foment political discord and hate, or even harass and blackmail people; these manipulated, high-quality and realistic videos became known recently as Deepfake. There has been much work done in recent years on malware analysis and …
Machine Learning And Radiomic Features To Predict Overall Survival Time For Glioblastoma Patients, Lina Chato, Shahram Latifi
Machine Learning And Radiomic Features To Predict Overall Survival Time For Glioblastoma Patients, Lina Chato, Shahram Latifi
Electrical & Computer Engineering Faculty Research
Glioblastoma is an aggressive brain tumor with a low survival rate. Understanding tumor behavior by predicting prognosis outcomes is a crucial factor in deciding a proper treatment plan. In this paper, an automatic overall survival time prediction system (OST) for glioblastoma patients is developed on the basis of radiomic features and machine learning (ML). This system is designed to predict prognosis outcomes by classifying a glioblastoma patient into one of three survival groups: short-term, mid-term, and long-term. To develop the prediction system, a medical dataset based on imaging information from magnetic resonance imaging (MRI) and non-imaging information is used. A …
Exploring The Impact Of Social Influence Mechanisms And Network Density On Societal Polarization, Justin Mittereder
Exploring The Impact Of Social Influence Mechanisms And Network Density On Societal Polarization, Justin Mittereder
Departmental Honors & Graduate Capstone Projects
I present an agent-based model, inspired by the opinion dynamics
(OD) literature, to explore the underlying behaviors that may induce
societal polarization. My agents interact on a social network, in which
adjacent nodes can influence each other, and each agent holds an array
of continuous opinion values (on a 0-1 scale) on a number of separate
issues. I use three measures as a proxy for the virtual society’s “po-
larization:” the average assortativity of the graph with respect to the
agents’ opinions, the number of non-uniform issues, and the number
of distinct opinion buckets in which agents have the same …
Proquest Tdm Studio: A Text And Data Mining Solution, Anamika Megwalu, Anne Marie Engelsen
Proquest Tdm Studio: A Text And Data Mining Solution, Anamika Megwalu, Anne Marie Engelsen
Faculty Research, Scholarly, and Creative Activity
TDM Studio is an integrated platform offered by ProQuest for data and text mining. TDM stands for text and data mining. This cloud-based, all-in-one innovative product is designed to offer researchers a clean interface with rights-cleared content, Jupyter notebook, and data visualization tools. As a result, researchers can now search Pro-Quest databases, create large datasets, import data to Jupyter notebook for analysis, and download results within a day.
Computer Program Simulation Of A Quantum Turing Machine With Circuit Model, Shixin Wu
Computer Program Simulation Of A Quantum Turing Machine With Circuit Model, Shixin Wu
Mathematical Sciences Technical Reports (MSTR)
Molina and Watrous present a variation of the method to simulate a quantum Turing machine employed in Yao’s 1995 publication “Quantum Circuit Complexity”. We use a computer program to implement their method with linear algebra and an additional unitary operator defined to complete the details. Their method is verified to be correct on a quantum Turing machine.
Hyperseed: An End-To-End Method To Process Hyperspectral Images Of Seeds, Tian Gao, Anil Kumar Nalini Chandran, Puneet Paul, Harkamal Walia, Hongfeng Yu
Hyperseed: An End-To-End Method To Process Hyperspectral Images Of Seeds, Tian Gao, Anil Kumar Nalini Chandran, Puneet Paul, Harkamal Walia, Hongfeng Yu
School of Computing: Faculty Publications
High-throughput, nondestructive, and precise measurement of seeds is critical for the evaluation of seed quality and the improvement of agricultural productions. To this end, we have developed a novel end-to-end platform named HyperSeed to provide hyperspectral information for seeds. As a test case, the hyperspectral images of rice seeds are obtained from a high-performance line-scan image spectrograph covering the spectral range from 600 to 1700 nm. The acquired images are processed via a graphical user interface (GUI)-based open-source software for background removal and seed segmentation. The output is generated in the form of a hyperspectral cube and curve for each …
Hyperseed: An End-To-End Method To Process Hyperspectral Images Of Seeds, Tian Gao, Anil Kumar Nalini Chandran, Puneet Paul, Harkamal Walia, Hongfeng Yu
Hyperseed: An End-To-End Method To Process Hyperspectral Images Of Seeds, Tian Gao, Anil Kumar Nalini Chandran, Puneet Paul, Harkamal Walia, Hongfeng Yu
School of Computing: Faculty Publications
High-throughput, nondestructive, and precise measurement of seeds is critical for the evaluation of seed quality and the improvement of agricultural productions. To this end, we have developed a novel end-to-end platform named HyperSeed to provide hyperspectral information for seeds. As a test case, the hyperspectral images of rice seeds are obtained from a high-performance line-scan image spectrograph covering the spectral range from 600 to 1700 nm. The acquired images are processed via a graphical user interface (GUI)-based open-source software for background removal and seed segmentation. The output is generated in the form of a hyperspectral cube and curve for each …
Aerial Flight Paths For Communication, Alisha Bevins, Brittany Duncan
Aerial Flight Paths For Communication, Alisha Bevins, Brittany Duncan
School of Computing: Faculty Publications
This article presents an understanding of naive users’ perception of the communicative nature of unmanned aerial vehicle (UAV) motions refined through an iterative series of studies. This includes both what people believe the UAV is trying to communicate, and how they expect to respond through physical action or emotional response. Previous work in this area prioritized gestures from participants to the vehicle or augmenting the vehicle with additional communication modalities, rather than communicating without clear definitions of the states attempting to be conveyed. In an attempt to elicit more concrete states and better understand specific motion perception, this work includes …
Class Scheduling Web App, Anubhav Rawal
Class Scheduling Web App, Anubhav Rawal
Honors Theses
This Scheduling Web Application in Django was built to allow a user to create a schedule for upcoming semesters. Users with appropriate privileges could upload an excel schedule to which instructors could be assigned. Additionally features included dynamic editing for admin users and viewing the main schedule for general users. Our goal was to create an application from the ground up using the Django framework to accomplish these tasks.
Mass Spectra Of Mesonic Molecules At Finite Temperature, Arezu Jahanshir, Mohammad Reza Soltani
Mass Spectra Of Mesonic Molecules At Finite Temperature, Arezu Jahanshir, Mohammad Reza Soltani
Karbala International Journal of Modern Science
At a finite temperature, exotic hadronic systems, mass spectrum was studied using the quark structure and the radial Schrödinger equation with the Cornell interaction potential representing the hadronic interaction. The projective unitary representation has been used in the study of hadronic ground states in physics. A relativistic bound state's mass spectrum with temperature dependence is shown to have a unique feature. The resulting values are compared to experimental and theoretical values, and the study showed a high level of conformity with additional values wherever feasible.
Efficiency Of +Idonblender Photogrammetric Tool In Facial Prosthetics Rehabilitation – An Evaluation Study, Mohammed R. Falih, Fanar M. Abed, Rodrigo Salazar-Gamarra, Luciano Lauria Dib
Efficiency Of +Idonblender Photogrammetric Tool In Facial Prosthetics Rehabilitation – An Evaluation Study, Mohammed R. Falih, Fanar M. Abed, Rodrigo Salazar-Gamarra, Luciano Lauria Dib
Karbala International Journal of Modern Science
Several open-source 3D modeling software tools have recently been featured to reconstruct a 3D image-based model using Structure from Motion (SfM) algorithms such as +IDonBlender. It is, therefore, necessary to evaluate the accuracy of the models extracted from this tool to prove effectiveness for different applications. This paper aims to evaluate the +IDonBlender methodology tool in rehabilitating facial deformations. +IDonBlender is an add-on tool programmed within Blender software and designed for medical applications. In this research, two individuals from different genders have volunteered to contribute to this study, one with severe facial deformation and the other is healthy with no …
Proposed Hybrid Correlationfeatureselectionforestpanalizedattribute Approach To Advance Idss, Doaa Nteesha Mhawi, Prof. Soukaena H. Hashem
Proposed Hybrid Correlationfeatureselectionforestpanalizedattribute Approach To Advance Idss, Doaa Nteesha Mhawi, Prof. Soukaena H. Hashem
Karbala International Journal of Modern Science
NetworkIntrusionDetectionSystem(NIDS), widely used network infrastructure. Although many datamining has been used to increase the effectiveness of IDSs, current ID still struggle to perform well. therfore; proposed a new NIDS focused on feature_selection. The proposed CorrelationFeatureSelection_ForestPanalizedAttributes(CFS_FPA) used for dimensionality_reduction and selects the optimal_subset. based on two steps: first check each feature with a target(class) and choose only features that most effective by applying CFS filter using a statistical_method, then applied FPA to select only features will enhance ID and reduce_dimensionality. proposal tested with the NSLKDD experimental results of accuracy 0.997% and 0.004 FAR, wherein UNSWNB15_dataset accuracy and FAR are 0.995%, 0.008 …
Analysis Of Modern Communication Protocols For Iot Applications, Neerendra Kumar, Pragti Jamwal
Analysis Of Modern Communication Protocols For Iot Applications, Neerendra Kumar, Pragti Jamwal
Karbala International Journal of Modern Science
To facilitate increasing interactions of machines, various protocols are building up for IoT applications. Safeguarding communication among devices is necessary. In this paper, various protocols have been studied and compared using six parameters: Communication overhead, Security, Packet Loss, Throughput, Bandwidth and Support to QoS. LIDOR is found as the most successful communication protocol. A tabulated comparison of various communication protocols have been provided by comparing the parameters. Further, six star rating for the various protocols have been proposed. The study shows that LIDOR increases reliability under DoS attacks. Considering the existing literature, new research gaps and challenges have been presented.
The Effect Of Diode Laser On The Life And Appearance Of White Ant (Psammotermes Hypostoma), Estabraq Mahmood Mahdi Msc, Sahar Naji Rashid Msc., Saeed Maher Lafta Ph.D., Arshad Mahdi Hamad Msc
The Effect Of Diode Laser On The Life And Appearance Of White Ant (Psammotermes Hypostoma), Estabraq Mahmood Mahdi Msc, Sahar Naji Rashid Msc., Saeed Maher Lafta Ph.D., Arshad Mahdi Hamad Msc
Karbala International Journal of Modern Science
This work focused on studying effect of diode laser on external appearance of white ants, and finding the percentage of mortality resulting from this beam of (650nm),(5mW),exposure times (60,70,80,90,100)sec at (3,5)cm for each exposure. The results recorded showed a clear increase in death rates, and increase in deformations as laser exposure times increased (higher percentage at lower distance), where laser was used to capture results of this therapeutic effect after passage time periods (12,24,48,72)hours. These results, show laser thermal effects resulting from its interaction with tissues, thermal propagation leads to ravage to the structures, thus to an increase death rates.
Calculation And Comparison Of Certain Physical Properties Of Sample Irregular Galaxies With The Milky Way Galaxy, Hasanain Hassan Al-Dahlaki Msc
Calculation And Comparison Of Certain Physical Properties Of Sample Irregular Galaxies With The Milky Way Galaxy, Hasanain Hassan Al-Dahlaki Msc
Karbala International Journal of Modern Science
Irregular galaxies often include a mix of old and young celestial populations, as well as dust and gas. This study makes an early effort at the morphological classification of irregular galaxies. These sources have been chosen from (70) irregular galaxies data samples from a Catalogue survey. We present a statistical analysis of the physical properties for the chosen data from the database and a collection of tools that used to study the physics of galaxies and cosmology HYPERLEDA (http://atlas.obshp.fr/hyperleda/) and NASA /IPAC Extragalactic Database NED (https://ned.ipac.caltech.edu/) survey.
Seasonal Variation Of Microbiota In Shank Acanthopagrus Latus Living In Both Brackish And Fresh Water, Ali A. Al-Hisnawi Ph.D., Jassim M. Mustafa, Yass K. Yasser, Khalid A. Hussain, Ameera M. Jabur
Seasonal Variation Of Microbiota In Shank Acanthopagrus Latus Living In Both Brackish And Fresh Water, Ali A. Al-Hisnawi Ph.D., Jassim M. Mustafa, Yass K. Yasser, Khalid A. Hussain, Ameera M. Jabur
Karbala International Journal of Modern Science
The present study was conducted to monitor the microbiota in the posterior intestine of Shank fish living in the river (fresh water) and Al-Razzaza lake (salt or brackish water) in Kerbala, Iraq. Cultivable bacteria were calculated and identified from specimens obtained from the posterior intestine of mucosa (PM) and digesta (PD) during summer and winter seasons. The total culturable bacteria (TCB) of bacteria isolated from both intestinal regions from fresh water fish during summer time were higher than counterparts in winter time. In contrast, the TVC of bacteria isolated from the PM from salt water fish during winter time were …
Evaluation Of The Healing Activity Of Cucurbita Spp. Leaf And Seed Extracts On Experimental Thermal Burns, Sanaa Jameel Thamer Ph.D., Prof. Maha Khalil Ibrahim, Dr. Khalid Shanshal Alnema
Evaluation Of The Healing Activity Of Cucurbita Spp. Leaf And Seed Extracts On Experimental Thermal Burns, Sanaa Jameel Thamer Ph.D., Prof. Maha Khalil Ibrahim, Dr. Khalid Shanshal Alnema
Karbala International Journal of Modern Science
Burns are the most common skin injuries associated with many complications and high incidences of wound infections. Many compounds of plant products have been assessed to accelerate wound healing or reduce contamination. The possible healing effect of two Cucurbita spp. in skin burns was investigated. Cucurbita maxima and Cucurbita pepo leaves and seeds were extracted using ethanol and analyzed by gas chromatography–mass spectrometry. Second-degree burn wounds were made on laboratory rats, and the burn wounds were applied topically with extracts for 14 days and silver sulfadiazine (SS) for comparison. Serum vascular endothelial growth factor (VEGF) was analyzed post-treatment. Hydroxyproline content …
Energy Conservation Approach Of Wireless Sensor Networks For Iot Applications, Suha Abdulhussein Abdulzahra Msc, Ali Kadhum M. Al-Qurabat Ph.D., Prof. Dr. Ali Kadhum Idrees
Energy Conservation Approach Of Wireless Sensor Networks For Iot Applications, Suha Abdulhussein Abdulzahra Msc, Ali Kadhum M. Al-Qurabat Ph.D., Prof. Dr. Ali Kadhum Idrees
Karbala International Journal of Modern Science
Wireless Sensor Network is one of the most important contributors to IoT and performs significant role in people's lives due to its extensive use in many applications. Energy-saving is essential since sensor nodes are working by their restricted battery. In this article, data reduction method proposed to work at Gateway level of network. In GW, proposed method works as filtering via enabling GW to identify, then remove, sets of data that are redundant and produced by neighboring nodes. Principle idea of method recommended at this level is to exploit the advantage of spatial correlation between sensors to minimize energy depletion.
Prediction Of Iraqi Stock Exchange Using Optimized Based-Neural Network, Ameer Al-Haq Al-Shamery, Prof. Dr. Eman Salih Al-Shamery
Prediction Of Iraqi Stock Exchange Using Optimized Based-Neural Network, Ameer Al-Haq Al-Shamery, Prof. Dr. Eman Salih Al-Shamery
Karbala International Journal of Modern Science
Stock market prediction is an interesting financial topic that has attracted the attention of researchers for the last years. This paper aims at improving the prediction of the Iraq-Stock-Exchange (ISX) using a developed method of feedforward Neural-Networks based on the Quasi-Newton optimization approach. The proposed method reduces the error factor depending on the Jacobian vector and Lagrange multiplier. This improvement has led to accelerating convergence during the learning process. A sample of companies listed on ISX was selected. This includes twenty-six banks for the years from 2010 to 2020. To evaluate the proposed model, the research findings are compared with …
Biosynthesis, Characterization And Antiproliferative Activity Of Green Synthesized Gold Nanoparticles Using Lantadene A Extracted From Lantana Camara, Dawood Ali Salim Dawood, Lee Suan Chua Ph.D, Tian Swee Tan Ph.D, Ahmed F. Alshemary Ph.D
Biosynthesis, Characterization And Antiproliferative Activity Of Green Synthesized Gold Nanoparticles Using Lantadene A Extracted From Lantana Camara, Dawood Ali Salim Dawood, Lee Suan Chua Ph.D, Tian Swee Tan Ph.D, Ahmed F. Alshemary Ph.D
Karbala International Journal of Modern Science
This study was focused on the biosynthesis of gold nanoparticles loaded with lantadene A (LA-AuNPs) from Lantana camara extract and the antiproliferative effects on prostate cancer cells (LNCaP). The synthesized LA-AuNPs had smooth surface, and nearly spherical in shape (67.94 nm) with the zeta potential (-30.11±0.83 mV). LAAuNPs showed a dose dependent cytotoxic activity with IC50, 126.82 µg/mL against LNCaP, but non-cytotoxic to normal prostate cells. The intrinsic pathway of apoptosis was caused by the increase of caspases-3/7 and -9 activity and cell cycle arrest at the G0/G1 phase. Therefore, LA-AuNPs could be a potent lead to inhibit LNCaP
The Detection Of Sexual Harassment And Chat Predators Using Artificial Neural Network, Noor Amer Hamzah, Ban N. Dhannoon
The Detection Of Sexual Harassment And Chat Predators Using Artificial Neural Network, Noor Amer Hamzah, Ban N. Dhannoon
Karbala International Journal of Modern Science
The vast increase in using social media sites like Twitter and Facebook led to frequent sexual_harassment on the Internet, which is considered a major societal problem. This paper aims to detect sexual_harassment and cyber_predators in early phase. We used deeplearning like Bidirectionally-long-short-term memory. Word representations are carefully reviewed in text specific to mapping to real number vectors. The chat sexual predators Detection_approach with the proposed_model. The best results obtained by the performance measured with F0.5-score were the result is_0.927 with proposed_models. The accuracy measured is_97.27% in the proposed_model. The comments sexual_harassment Detection_approach the result is_0.925 F0.5-score, and accuracy measured is_99.12%.
An Online E-Voting System Based On An Adaptive Ledger With Singular Value Decomposition Technique, Rihab Habeeb Sahib, Prof. Dr. Eman Salih Al-Shamery
An Online E-Voting System Based On An Adaptive Ledger With Singular Value Decomposition Technique, Rihab Habeeb Sahib, Prof. Dr. Eman Salih Al-Shamery
Karbala International Journal of Modern Science
Regular E-voting systems for elections may count the votes in less time,less cost,save the privacy of citizens,but still considered risky as votes can be tampered.E-voting systems based on a network distributed ledger show fast results,more trusted,save privacy,cannot be tampered,and distributed in which no central organization controls the system.This paper illustrate an e-voting system to solve the challenge of a massive ledger that is distributed among network-nodes using a data reduction technique as a security-matching-tool,singular value decomposition(SVD) that handle a copy of election results in another form and matched with the SQL-database results to announce a successful election-event representing a transparency-powerful-secured-system
Detecting Malicious Dns Queries Over Encrypted Tunnels Using Statistical Analysis And Bi-Directional Recurrent Neural Networks, Mohammad Al-Fawa'reh, Zain Ashi, Mousa Tayseer Jafar
Detecting Malicious Dns Queries Over Encrypted Tunnels Using Statistical Analysis And Bi-Directional Recurrent Neural Networks, Mohammad Al-Fawa'reh, Zain Ashi, Mousa Tayseer Jafar
Karbala International Journal of Modern Science
The exponential rise in the number of malicious threats targeting computer networks and digital services puts network infrastructure in jeopardy. Domain name protocol attacks are one of the most pervasive network attacks posing a threat to networks, whereby attackers send harmful information to the network; this type of threat is identified as DNS tunneling. The DNS protocol has recently gained increased attention from cyber-attackers, targeting organizations with a web presence or reliance on e-commerce businesses. Cyber-attackers can subtly exploit the contents of encrypted DNS packets that are sent across covert network tunnels, which are difficult for firewalls and blacklist detection …
Artificial Intelligence For Para Rubber Identification Combining Five Machine Learning Methods, Chairote Yaiprasert Ph.D.
Artificial Intelligence For Para Rubber Identification Combining Five Machine Learning Methods, Chairote Yaiprasert Ph.D.
Karbala International Journal of Modern Science
This study aims to identify Para rubber species using a combination of five machine learning techniques to classify leaf images. The learning process is defined using a dataset for each classification method. Approximately 1,472 leaf images are prepared consisting of various sizes, shapes, quality provided for the model. The classification indicators are defined with the help of an algorithm to identify at least three of the top five potential classification outcomes. The algorithm accurately predicts 100% of the five classification methods. Methods can provide precise and rapid classification of large quantities, without the need for image preprocessing prior to classification.
Synergistic Extraction Of Silver From Nitric Acid Medium With Dithizone In The Presence Of A Secondary Amine- Amberlite La-2 Using 110mag-Radioisotope, Madhusudan Mandal Ph.D.
Synergistic Extraction Of Silver From Nitric Acid Medium With Dithizone In The Presence Of A Secondary Amine- Amberlite La-2 Using 110mag-Radioisotope, Madhusudan Mandal Ph.D.
Karbala International Journal of Modern Science
Synergistic extraction of silver has been investigated in the presence of two different kinds of extractants, one of which is a chelating ligand, dithizone and the other is a long-chain secondary amine amberlite LA-2 at pH 3.0 using a radiotracer technique. The apparent formation constant, overall equilibrium constant and adduct formation constants were calculated from distribution coefficients. Interestingly, it was observed that the adduct formation constant is too high when the ligand concentration is increased by keeping the amine concentration fixed at 0.044 M compared to that obtained when the ligand concentration is kept fixed at 8.74×10-4 M.
Pranayama Breathing Detection With Deep Learning, Bikash Shrestha
Pranayama Breathing Detection With Deep Learning, Bikash Shrestha
Theses
Yoga, a complementary health approach, according to a 2017 National Health Interview Survey by the Center for Disease Control and Prevention (CDC), is a choice of around 14.3% adults in the US. Kapalbhati pranayama, a yoga practice of alternating fast exhales and longer passive inhales, is understood to improve our health. Incorrect and irregular practices, however, can cause injuries and adverse effects. To avoid these undesired effects, it is essential to maintain a pace fit for the practitioner. In the absence of any tools to observe a pace of practice, this work develops a deep learning method that listens to …
Optimal Container Migration For Mobile Edge Computing: Algorithm, System Design And Implementation, Taewoon Kim, Motassem Al-Tarazi, Jenn-Wei Lin, Wooyeol Choi
Optimal Container Migration For Mobile Edge Computing: Algorithm, System Design And Implementation, Taewoon Kim, Motassem Al-Tarazi, Jenn-Wei Lin, Wooyeol Choi
School of Computing: Faculty Publications
Edge computing is a promising alternative to cloud computing for offloading computationally heavy tasks from resource-constrained mobile user devices. Placed at the edge of the network, edge computing is particularly advantageous to delay-limited applications for having a short distance to end- users. However, when a mobile user moves away from the service coverage of the associated edge server, the advantage gradually vanishes, increasing response time. Although service migration has been studied to address this problem focusing on minimizing the service downtime, both zero-downtime and the amount of traffic generated as a result of migration need further study. In this paper, …