Papers by Mustafa ElNainay
2017 IEEE Wireless Communications and Networking Conference (WCNC)
Due to the tremendous and rapid growth of data traffic (e.g. video content), femtocaching has bee... more Due to the tremendous and rapid growth of data traffic (e.g. video content), femtocaching has been introduced in 5G networks to bring the data closer to the clients using small, low-power cellular base stations with storage capacity called femtocaches (FCs), hence offloading some traffic off the macrocell base station (MBS). The process of content delivery can efficiently benefit from FCs by optimizing the process of files distribution among the clients using network coding, hence, offloading bandwidth off the MBS and saving costs. In this paper, we propose a genetic algorithm-based approach to minimize the number of orthogonal MBS channels used to distribute files among the clients. Simulation results show that our proposed algorithm almost achieves the optimal solutions found by an exhaustive brute-force search in about 98% of the runs on average. These results significantly make use of the FCs and save the MBS' bandwidth.
Computers, 2022
Historical texts are one of the main pillars for understanding current civilization and are used ... more Historical texts are one of the main pillars for understanding current civilization and are used to reference different aspects. Hadiths are an example of one of the historical texts that should be securely preserved. Due to the expansion of the online resources, fabrications and alterations of fake Hadiths are easily feasible. Therefore, it has become more challenging to authenticate the online available Hadith contents and much harder to keep these authenticated results secure and unmanipulated. In this research, we are using the capabilities of the distributed blockchain technology to securely archive the Hadith and its level of authenticity in a blockchain. We selected a permissioned blockchain customized model in which the main entities approving the level of authenticity of the Hadith are well-established and specialized institutions in the main Islamic countries that can apply their own Hadith validation model. The proposed solution guarantees its integrity using the crowd wi...
Information, 2022
Determining hadith authenticity is vitally important in the Islamic religion because hadiths reco... more Determining hadith authenticity is vitally important in the Islamic religion because hadiths record the sayings and actions of Prophet Muhammad (PBUH), and they are the second source of Islamic teachings following the Quran. When authenticating a hadith, the reliability of the hadith narrators is a big factor that hadith scholars consider. However, many narrators share similar names, and the narrators’ full names are not usually included in the narration chains of hadiths. Thus, first, ambiguous narrators need to be identified. Then, their reliability level can be determined. There are no available datasets that could help address this problem of identifying narrators. Here, we present a new dataset that contains narration chains (sanads) with identified narrators. The AR-Sanad 280K dataset has around 280K artificial sanads and could be used to identify 18,298 narrators. After creating the AR-Sanad 280K dataset, we address the narrator disambiguation in several experimental setups. ...
SSRN Electronic Journal, 2022
2021 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), 2021
Smart health is a new paradigm that can significantly improve the healthcare systems. In smart he... more Smart health is a new paradigm that can significantly improve the healthcare systems. In smart health, novel sensing, computing and communication technologies are integrated in healthcare to improve the quality of service. In this paper, we use the smart health to improve the performance of ambulance service. In particular, we use the real-time traffic information and hospital waiting time to minimize the ambulance response time, ambulance travel time to hospitals, and waiting time at hospitals. Results indicate that the use of smart health improves the performance significantly especially with non-uniform hospital capacity and non-uniform traffic conditions.
2018 14th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2018
One of the main challenges in cognitive radios is spectrum sensing. Cooperative spectrum sensing ... more One of the main challenges in cognitive radios is spectrum sensing. Cooperative spectrum sensing scheme among mobile users can be used to determine the usage profile of wide spectrum bands in a large geographical region. In a large mobile crowdsensing environment, the key step is to assign the sensing task among mobile users to maximize the spectrum sensing performance while reducing the cost incurred by the mobile users during the sensing process. In this paper, we propose two genetic algorithm-based approaches to solve the NP-hard problem of spectrum sensing task assignment among mobile users. The first algorithm uses a centralized genetic algorithm scheme to maximize the spectrum sensing utility function. The second algorithm uses an island genetic algorithm to assign the sensing task among mobile users in a distributive way. Simulation results show that both algorithms achieve comparable spectrum utility measure to the one obtained by running recently proposed particle swarm optimization and greedy approximation algorithms while reducing the running time of the algorithm by a significant factor. In addition, the island algorithm massively outperforms both algorithms in the running time by running the algorithm independently at each sensing location and exchanging the necessary information for the overlapping locations, removing the bottleneck of having a central spectrum profiling unit to assign the sensing tasks among mobile users.
2017 IEEE 13th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2017
Energy harvesting has been gaining a lot of attention in the past decade due to its ability to pr... more Energy harvesting has been gaining a lot of attention in the past decade due to its ability to provide a-virtually-endless energy supply. Nodes in a Wireless Powered Communication Network (WPCN) depend, totally or partially, on the energy harvested from the Central Node (CN) which has a constant power supply. This work addresses a solution to the problem of lack of fairness in the distribution of energy broadcast to nodes from the CN. The solution presented here depends on cooperation between nodes, in which nodes that have harvested more energy can help other nodes with their transmission to achieve fairness. The main objective is to achieve a maximized common throughput by selecting the best relay node assuming Amplify-and-Forward relaying. An optimization problem is formulated to allocate time and energy resources for nodes' transmissions and relaying. The formulated optimization problem is proved to be convex, which allows for efficient solution calculation. Simulation results show the improved performance of our proposed cooperation and relay selection algorithms as compared to the no-cooperation scenario.
2017 IEEE Wireless Communications and Networking Conference (WCNC), 2017
Due to the increasing demand for higher data rates and the congestion in communication systems, n... more Due to the increasing demand for higher data rates and the congestion in communication systems, new research is focusing on the cooperation between the two most successful communication systems, LTE and WiFi. The overall performance of a WiFi system degrades with increasing the number of served users due to collisions. We propose in this paper a novel scheme for LTE and WiFi coexistence, where an LTE femto Base Station cooperates with a WiFi Access Point to maximize both of their profits. Our proposed scheme has the advantage of relieving a congested WiFi system. Thus, this creates a time gap for the LTE system to transmit its data. In addition, we investigate the capability of WiFi and LTE systems to work simultaneously under a certain maximum interference limit. We have formulated a multi- objective optimization problem for maximizing the rate of the WiFi system and the capacity of the LTE system. We developed an algorithm based on particle swarm optimization to determine the appropriate time ratios for WiFi and LTE transmission, the transmitting power of LTE under WiFi transmission, and the number of WiFi nodes to be transferred to LTE system. Simulation results confirm the capability for LTE to transmit besides WiFi without affecting its transmission rate.
Simulating large-scale network experiments requires powerful physical resources. However, partiti... more Simulating large-scale network experiments requires powerful physical resources. However, partitioning could be used to reduce the required power of the resources and to reduce the simulation time. Topology mapping is a partitioning technique that maps the simulated nodes to different physical nodes based on a set of conditions. In this paper, genetic algorithm-based mapping is proposed to solve the topology mapping problem. The obtained results prove a high reduction in simulation time, in addition to high utilization of the used resources (The number of used resources is minimum).
2017 13th Annual Conference on Wireless On-demand Network Systems and Services (WONS), 2017
Intensive research effort has been dedicated to tackle multi-hop network problems. Joint consider... more Intensive research effort has been dedicated to tackle multi-hop network problems. Joint consideration across multiple layers is required to achieve optimal performance. The general trend in solving these problems is to develop strong mathematical programming formulations that are capable of providing near-optimal solutions to practical-sized problems. For the class of problems studied, we show that a traditionally formulated model turns out to be insufficient from a problem-solving perspective. When the size of the problem increases, even state-of-the-art optimizers cannot obtain an optimal solution because of running out of memory. In this work, we show that augmenting the model with suitable additional constraints and structure enables the optimizer to derive optimal solutions, or significantly reduce the optimality gap, which were previously elusive given available memory restrictions.
Proceedings of the 2020 9th International Conference on Software and Information Engineering (ICSIE), 2020
Small to Medium-sized Enterprises (SMEs) benefit from the advantages of the cloud computing envir... more Small to Medium-sized Enterprises (SMEs) benefit from the advantages of the cloud computing environment. These enterprises have limited resources. Consequently, SMEs require a structured software process model to develop a reliable and good quality cloud software. Existing cloud software process (CSP) models focused only on the processes of software development and ignored the other aspects of software production. In this paper, a conceptual view for Cloud Software Life Cycle Process (CSLCP) model is proposed. This model overcomes the deficiencies of existing CSP models. Also, it satisfies the development of a reliable and high quality cloud software. The CSLCP model is compatible with level two and three of the capability maturity model integration (CMMI). It extends the software process improvement (SPI) model, developed in Egypt for SMEs, to suit the cloud environment. The application of the CSLCP model in SMEs would improve their level of maturity
We present a new architecture design with implementation to handle the unified testbed federation... more We present a new architecture design with implementation to handle the unified testbed federation System, created initially for all the faculties and research centers in Egypt. It is based on self-management testbed with synchronize data and shared interfaces. The architecture includes the functions required to enable, manage and control testbeds over multiple sites for research and educational purposes. The main target of this research is to propose an architecture for the federation of Internet experimentation facilities, which extends across a diverse research community. This paper comes out of Collaborative Research Cloud (CRC) project funded by the National Telecommunications Regulatory Authority to create a unified testbed federation system to allow for remote access for existing research equipment in some faculties and research centers in Egypt as a bootstrapping to apply it later to all other research centers in Egypt. The main target of CRC project is to build a system that...
ArXiv, 2019
Intelligent Transportation Systems (ITSs) is the backbone of transportation services in smart cit... more Intelligent Transportation Systems (ITSs) is the backbone of transportation services in smart cities. ITSs produce better-informed decisions using real-time data gathered from connected vehicles. In ITSs, Vehicular Ad hoc Network (VANET) is a communication infrastructure responsible for exchanging data between vehicles and Traffic Management Centers (TMC). VANET performance (packet delay and drop rate) can affect the performance of ITS applications. Furthermore, the distribution of communicating vehicles affects the VANET performance. So, capturing this mutual impact between communication and transportation is crucial to understanding the behavior of ITS applications. Thus, this paper focuses on studying the mutual impact of VANET communication and mobility in city-level ITSs. We first introduce a new scalable and computationally fast framework for modeling large-scale ITSs including communication and mobility. In the proposed framework, we develop and validate a new mathematical mo...
Traffic and Granular Flow '17, 2019
Intelligent transportation systems (ITSs) are key components of future smart cities. These system... more Intelligent transportation systems (ITSs) are key components of future smart cities. These systems attempt to enhance the transportation system efficiency. ITSs utilize vehicular ad hoc networks (VANETs) to collect and disseminate data to be used in ITS applications. Consequently, the performance of the communication network can significantly impact the performance of ITS applications. Consequently, in this paper, we develop a large-scale modeling framework that is capable of modeling large-scale transportation and communication networks. First, we develop and validate a communication model that estimates the packet drop probability and delay for a single hop communication system using a Markov chain and the M/M/1/K queuing model. Then, we integrate this model with a connected vehicle (CV) eco-routing navigation system within a microscopic traffic assignment and simulation software. The fully integrated vehicular and VANET tool is then used to model and evaluate the performance of the CV eco-routing application on a real large-scale road network with a realistic calibrated vehicular traffic demand.
2017 IEEE Wireless Communications and Networking Conference (WCNC), 2017
Software-defined networking (SDN) abstracts and centralizes the network control functions in a so... more Software-defined networking (SDN) abstracts and centralizes the network control functions in a software entity that runs on a server, known as SDN controller. The controller needs to respond to its controlled elements in a strictly timely manner, and the controller placement has a prominent effect on its response time. Originally, all SDN architectures assumed a physical wired connection between the SDN controller and its controlled elements, and the controller placement problem (CPP) has been only studied under such wired settings. Recently, novel SDN architectures have been proposed in which a direct wireless connection is assumed between the controller and its controlled elements. In this paper, we consider the 'wireless CPP,' when the link between the controller and the controlled element is wireless. Specifically, our contributions are as follows. First, we propose two joint controller placement and assignment formulations, assuming wired links between the controllers and their controlled elements; the first formulation considers an average response time constraint, whereas the second one considers a per-link response time constraint. Then, using chanceconstrained stochastic programming (CCSP), we extend our formulation to the case when the links between the controllers and their controlled elements are wireless. Finally, we evaluate our joint placement and assignment schemes under various system parameters. Our results demonstrate the advantage of our joint scheme, in terms of reducing the required number of controllers, compared to a recent sequential assignment and placement scheme in the literature. They also show the ability of our CCSP-based scheme in probabilistically satisfying the controllers response time constraints.
2019 International Conference on Advances in the Emerging Computing Technologies (AECT), 2020
It was proven that the cost of fixing errors escalates as a project moves through its life cycle ... more It was proven that the cost of fixing errors escalates as a project moves through its life cycle in an exponential fashion. Identifying buggy classes, as soon as they are committed to the Version Control System, would have a significant impact on reducing such cost. Mining in software repositories is a growing research area, where innovative techniques and models are designed to analyze software repositories data and uncover useful information that can help in software bug prediction. Previous studies showed that Deep Learning has achieved remarkable results in many fields and it keeps evolving.In this paper, experiments are carried out to study the effect of feature selection on the performance of bug prediction models and to check if better results can be obtained by using the promising Deep Learning techniques. Results show that applying feature selection, using a simple filter approach, such as selecting the highly ranked 9 and 5 features out of the 17 features, did not enhance the performance measures in most cases. On the other hand, results show that Deep Learning model (DL) achieves higher performance measures than the selected set of base classifiers for small and balanced datasets.
2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), 2019
One of the main characteristics in cognitive radios is situation awareness. By classifying the mo... more One of the main characteristics in cognitive radios is situation awareness. By classifying the modulation schemes used in surrounding transmissions, a secondary user (SU) can identify the existing users in the system and adjust his/her transmission parameters accordingly. In this paper, we propose a multi-task learning (MTL) approach to recognize the modulation scheme used among a specific set of analog and digital modulations. This approach uses a deep convolutional neural network (CNN) to extract the necessary features in order to classify the different modulation schemes. The MTL is used to separately train the modulation classes that normally cause a considerable confusion and therefore improve the overall classification accuracy. Our results on the RadioML dataset show that the suggested architecture achieves higher overall classification accuracy compared to the recently proposed Convolutional, Long Short Term Memory (LSTM), Deep Neural Network (CLDNN). Our classification accuracy of 86.97% at 18 dB SNR outperforms the state-of-the-art with 5% relative improvement.
2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA), 2016
Regression testing is the way to ensure the current version of the program is up and running. Con... more Regression testing is the way to ensure the current version of the program is up and running. Continuous testing throughout the development cycle leads to detecting bugs as early as possible; however, it imposes huge overhead if the entire test suite has to be run. In this paper, powered by the goal of early detection of bugs, a regression test selection technique is proposed. The proposed technique uses a cache to keep the potentially error prone files and link them with test cases in a dynamic way that evolves with the evolution of code and test cases. Rather than running the entire test suite, only test cases that are linked with the most error prone files are selected and run on a regular frequent basis. Our cache outperforms previous related cache technique in terms of cache hit rate on 5 Apache projects. Based on the modified cache, the test selection module of the proposed technique can achieve a fault detection rate that exceeded 80% in all projects.
2018 IEEE Symposium on Computers and Communications (ISCC), 2018
Indoor localization of mobile nodes is receiving great interest due to the recent advances in mob... more Indoor localization of mobile nodes is receiving great interest due to the recent advances in mobile devices and the increasing number of location-based services. Fingerprinting based on Wifi received signal strength (RSS) is widely used for indoor localization due to its simplicity and low hardware requirements. However, its positioning accuracy is significantly affected by random fluctuations of RSS values caused by fading and multi-path phenomena. This paper presents a convolutional neural network (CNN) based approach for indoor localization using RSS time-series from wireless local area network (WLAN) access points. Applying CNN on a time-series of RSS readings is expected to reduce the noise and randomness present in separate RSS values and hence improve the localization accuracy. The proposed model is implemented and evaluated on a multi-building and multi-floor dataset, UJIIndoorLoc dataset. The proposed approach provides 100% accuracy for building prediction, 100% accuracy for floor prediction and the mean error in coordinates estimation is 2.77 m.
Ain Shams Engineering Journal, 2021
Abstract Small to medium-sized enterprises take advantage of the strengths and opportunities of c... more Abstract Small to medium-sized enterprises take advantage of the strengths and opportunities of cloud computing. These enterprises require a well-defined software process model to produce reliable and quality cloud software, given their limited resources. Existing related work is surveyed, and the needed missing features are determined. A cloud software life cycle process model is proposed, validated, and verified to handle the shortcomings of existing cloud software process models. A case study is used to illustrate all the activities required throughout the software life cycle of the proposed model. The proposed cloud software life cycle process model is a cyclic iterative prototyping model. It is compatible with levels two and three of the capability maturity model integration and extends the Egyptian software process improvement model to fit the cloud environment. The model helps small enterprises develop quality, maintainable, and sustainable cloud software at a reasonable cost.
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Papers by Mustafa ElNainay