Dr. Sharhabeel Alnabelsi is an associate professor at Computer Engineering Dept., Al Ain University, UAE. He received his Ph.D. in Computer Engineering from Iowa State University, USA, 2012. Also, he received his M.Sc. in Computer Engineering from The University of Alabama in Huntsville, USA, 2007. His research interests are cognitive radio networks, wireless sensors networks, network optimization, and cloud computing. He is a member of honorary societies including Eta Kappa Nu and Phi Kappa Phi.
- Distinguished Researcher Award, Al-Balqa Applied University, Jordan, 2016-2017.
- Judge and reviewer at National Technology Parade, Jordan, 2014 & 2017.
- Reviewer at IEEE conferences in Wireless and Cognitive Radio Networks: ICC 2018, ICC 2011, WCNC 2011, Globecom 2012, and Ad Hoc & Sensor Wireless Networks Journal 2011.
Ph.D., Computer Engineering, (Iowa State University), USA, 2012.
M.Sc., Computer Engineering, (The University of Alabama in Huntsville), USA, 2007
B.Sc., Computer Engineering, Faculty of Engineering Technology, (Al-Balqa Applied University), Jordan, 2005.
Cognitive Radio Networks, Wireless Sensor Networks, Internet of Things.
- Maha Aljarah, Mohammad Shurman, Sharhabeel H. Alnabelsi, “Cooperative-Hierarchical Based Edge-Computing Approach for Resources Allocation of Distributed Mobile and IoT Applications”, accepted to the International Journal of Electrical and Computer Engineering (IJECE), Vol.10, No.1, Jan 2020, (Scopus).
- Ramzi Saifan, Tahani Al-Qaisi, Andraws Sweidan, Sharhabeel H. Alnabelsi, Khalid Darabkh “A Novel Reduced Sensing Time Routing Protocol in Cognitive Radio Networks”, the International Journal on Communications Antenna and Propagation (IRECAP), Praise Worthy Prize, Italy, Vol.9, No.5, Dec 2019 (Scopus).
- Hisham Almasaeid, Osameh Al-Kofahi, Sharhabeel H. Alnabelsi, Ramzi Saifan, "Tree-Based Multicast Service Provisioning with Maximum Immunity in Cognitive Radio Networks", Journal of High Speed Networks, Vol.24, No.4, 2019, (Scopus).
- Shurman M., Al-Jarrah O., Esoh S., Alnabelsi, S. H., “An Enhanced Cross-Layer Approach Based on Fuzzy-Logic for Securing Wireless Ad-Hoc Networks from Black Hole Attacks”, International Journal on Communications Antenna and Propagation (IRECAP), Praise Worthy Prize, Italy, Vol. 8, No. 2, April 2018, (Scopus).
- Alnabelsi, S. H., “Finding an Immuned Path against Single Primary User Activity in Cognitive Radio Networks”, International Journal on Communications Antenna and Propagation (IRECAP), Praise Worthy Prize, Italy, Vol. 7, No. 7, Dec 2017, (Scopus).
- Khalid A. Darabkh, Laila Haddad, Saadeh Swidan, Mohammed Hawa, Ramzi Saifan, Sharhabeel H. Alnabelsi, “An efficient speech recognition system for arm-disabled students based on isolated words”, Computer Applications in Engineering Education, Nov 2017, (Scopus, ISI, impact factor: 0.694).
- Darabkh K. A., Al-Rawashdeh, W. S., Al-Zubi R. T., Alnabelsi, S. H., “C-DTB-CHR: Centralized Density – and threshold-based Cluster Head Replacement Protocols for Wireless Sensor Networks”, The Journal of Supercomputing, Springer, June 2017, (Scopus, ISI, impact factor: 1.326).
- Abdelwadood Mesleh, Omar Arabeyyat, Sharhabeel H. Alnabelsi, Jamal Al-Nabulsi, “On Arabic Object Character Recognition Using Dynamic Time Warping”, Journal of Theoretical and Applied Information Technology, Vol. 95, No. 19, Oct 2017, (Scopus).
- Shurman M., Al-Mistarihi M., Alnabelsi S. H., Bani-Hani R. “A Novel Network Coding Approach: Packets Conflict Based for Matrix Optimization”, Journal of Theoretical and Applied Information Technology, Oct 2017, (Scopus).
- Alnabelsi, S. H., Saifan R., Almasaeid H., “Improving Routing Performance Using Cooperative Spectrum Sensing in Cognitive Radio Networks”, International Review on Computers and Software (IRECOS), Vol. 11, Issue 10, pages 923-930, Oct 2016, (Scopus).
- Alnabelsi, S. H., “On GPS Fault-Tolerance for City-Bus Tracking System using Wireless Sensor Networks”, International Journal of Networks and Communications, Vol. 6, Issue 4, pages 80-86, 2016.
- Huthifh Al-Rushdan, Mohammad Shurman, Sharhabeel H. Alnabelsi, Qutaibah Althebyan, “Zero-Day Attack Detection and Prevention in Software-Defined Networks”, accepted in the 20th International Arab Conference on Information Technology (ACIT'2019), UAE, Dec 2019.
- Ramzi Saifan, Tahani Qaisi, Andraws Swidan, Sharhabeel H. Alnabelsi, Khalid Darabkh, Ala' F. Khalifeh, "A Novel Reduced Sensing Time Routing Protocol in Cognitive Radio Networks", International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), IEEE, March, 2019.
- Alnabelsi, S. H., Kamal A. E., "Resilient Multicast Routing in CRNs Using a Multilayer Hyper-graph Approach ", IEEE International Conference on Communications (ICC) 2013.
- Alnabelsi, S. H., Kamal A. E., "Performance Modeling of Secondary Users in CRNs with Heterogeneous Channels", IEEE Globecom 2012.
- Alnabelsi, S. H., Kamal A. E., "Interference-Based Packet Recovery for Energy Saving in Cognitive Radio Networks", in the proceedings of the IEEE ICC workshop on Cognitive Radio and Cooperation for Green Networking, 2012.
- Alnabelsi, S. H., Kamal A. E., and Jawadwala T. H. "Uplink Channel Assignment in Cognitive Radio WMNs Using Physical Layer Network Coding", in proceedings of the IEEE International Conference on Communications (ICC) 2011.
- Alnabelsi, S. H.,2010.
Wireless networks, digital logic, embedded systems, computer architecture and organization, microprocessor and assembly, discrete structure.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all.
This person’s work contributes towards the following SDG(s):
Honor Societies and Associations
Eta Kappa Nu Honor Society, Phi Kappa Phi Honor Society, and IEEE member.
Mar 21, 2019
An Enhanced Cross-Layer Approach Based on Fuzzy-Logic for Securing Wireless Ad-Hoc Networks from Black Hole Attacks
Apr 30, 2018
Black holes attack in ad-hoc network systems can obstruct network functions, e.g.; successful packets delivery to destinations. Current conventional detection mechanisms are based on single layer information, lack of appropriate performance metrics, and/or the adequate accuracy. In this paper, a new cross layer Intrusion Detection System (IDS) is proposed, in order to mitigate the black hole attack in wireless ad-hoc networks. The proposed work modifies ad-hoc routing protocol for black hole attacks detection through extracting information from different OSI layers, and use these information as inputs into the fuzzy logic system, in which the algorithm precisely detects existing malicious nodes. Using NS2 simulation tool, a comprehensive simulation is conducted in order to compare our proposed approach performance with a recent cross layer-based approach for black hole intrusion detection . Simulation results reveal that our proposed system has a tremendous accuracy in detecting black holes with an acceptable additional overhead.
Dec 31, 2017
Due to recent crowdedness in unlicensed spectrum, a new technology is introduced which allows unlicensed users, known as Secondary Users (SUs), to dynamically access licensed spectrum whenever they are not used by their licensed users, known as Primary Users (PUs). Routing in Cognitive Radio Networks (CRNs) is different from traditional routing in wireless networks, since it requires SUs to periodically sense licensed spectrum, channels availability changes over time, knowledge of tolerated interference by PUs. In this paper, a novel routing discovery technique is proposed to find a primary path, if exist, which is immuned to one PU, such that at most one SU fails (must back off transmission) when a PU becomes active again. Also, a backup path can be discovered using the same technique with the condition that it is channel-link disjoint from the primary path. The problem is modeled using a multi-layer graph where each layer corresponds to a channel in a network. The proposed strategy reduces number of required channel-links maintenance to two, if failed due to one PU activity.
Published in: Computer Applications in Engineering Education
Nov 07, 2017
Over the previous decades, a need has emerged to empower human-machine communication systems, which are essential to not only perform actions, but also obtain information especially in education applications. Moreover, any communication system has to introduce an efficient and easy way for interaction with a minimum possible error rate. The keyboard, mouse, trackball, touch-screen, and joystick are all examples of tools which were built to provide mechanical human-to-machine interaction. However, a system with the ability to use oral speech, which is the natural form of communication between humans instead of mechanical communication systems, can be more practical for normal students and even a necessity for arm-disabled students who cannot use their arms to handle traditional education tools like pens and notebooks. In this paper, we present a speech recognition system that allows arm-disabled students to control computers by voice as a helping tool in the educational process. When a student speaks through a microphone, the speech is divided into isolated words which are compared with a predefined database of huge number of spoken words to find a match. After that, each recognized word is translated into its related tasks which will be performed by the computer like opening a teaching application or renaming a file. The speech recognition process discussed in this paper involves two separate approaches; the first approach is based on double thresholds voice activity detection and improved Mel-frequency cepstral coefficients (MFCC), while the second approach is based on discrete wavelet transform along with modified MFCC algorithm. Utilizing the best values for all parameters in just mentioned techniques, our proposed system achieved a recognition rate of 98.7% using the first approach, and 98.86% using the second approach of which is better in ratio than the first one but slower in processing which is a critical point for a real time system. Both proposed approaches were compared with other relevant approaches and their recognition rates were noticeably higher.
Oct 31, 2017
Network coding (NC) is a technique used to improve wireless networks throughput, efficiency, and scalability. When employing this technique, wireless nodes collect several packets and combine them together in one single transmission. This technique is used to attain the maximum possible network flow with minimum number of transmissions. COPE, OpNC and FENC are widely known approaches in network coding that vary in complexity and optimality. COPE is the first proposed approach for network coding that is considered as a complex approach and may lead to a packet deadline termination; thus, transmitter should resend packets, and therefore, the overall throughput decreases. OpNC employs the COPE approach in order to find all possible codes for a set of packets, brute force searching, hence it is an exhaustive approach where the optimal solution is not always reachable. On the other hand, FENC utilizes division and conquers technique, in order to find an optimal network coding of a set of native packets, in which a repetitive algorithm is applied on the output queue more than once, in order to increase the possibility of finding an optimal coding solution. In this paper, we propose a novel technique which utilizes two basic concepts of network coding: matrix optimization and the notion of conflict between packets. This technique is called “Conflict based Matrix Optimization for Network Coding Enhancement” (CMO-NCE), in which the opportunity of recovering more packets within the transmitted encoded packets combination is increased. Our proposed technique chooses better packets combination when transmitting the encoded stream; consequently, more packets are recovered at destination nodes. Simulation results show that the proposed technique is better in terms of complexity and optimality than other existing techniques such as COPE and OpNC. Also, it shows that the proposed CMO-NCE mechanism results are close to FENC approach. However, CMO-NCE’s time complexity is less than FENC and it is linear, O(n), where n is number of wireless nodes, while FENC’s time complexity is not linear, O(P^2/log2P ), where P is number of packets.
Oct 15, 2017
Due to the large volume of Arabic texts in many generated and historical documents, it is essential to use computers in order to make generated texts editable, this is actually the main task of Arabic Object Character Recognition (OCR) systems. The task of automatically OCRing is to type documents within close-to-human performance, such OCR system is still an open research problem. In this paper, we propose an Arabic OCR based on Dynamic Time Warping (DTW) algorithm that is empowered to properly recognize Arabic words. Rather than using the usual practice of character segmentation, this paper proposes a segmentation of Arabic texts into lines and characters. The proposed Arabic OCR algorithm overlaps the segmentation and the recognition processes-an online segmentation-recognition. That is, in order to overcome the challenges of segmenting highly cursive Arabic texts into isolated characters. The accuracy of the proposed Arabic OCR algorithm is tested on randomly selected articles from Jordanian newspapers. Interestingly, results demonstrate the robustness of our proposed Arabic OCR algorithm that achieves 96.2% character recognition accuracy in the worst case.
C-DTB-CHR: Centralized Density – and threshold-based Cluster Head Replacement Protocols for Wireless Sensor Networks
Published in: The Journal of Supercomputing
Jun 01, 2017
Advances introduced to electronics and electromagnetics leverage the production of low-cost and small wireless sensors. Wireless sensor networks (WSNs) consist of large amount of sensors equipped with radio frequency capabilities. In WSNs, data routing algorithms can be classified based on the network architecture into flat, direct, and hierarchal algorithms. In hierarchal (clustering) protocols, network is divided into sub-networks in which a node acts as a cluster head, while the rest behave as member nodes. It is worth mentioning that the sensor nodes have limited processing, storage, bandwidth, and energy capabilities. Hence, providing energy-efficient clustering protocol is a substantial research subject for many researchers. Among proposed cluster-based protocols, low-energy adaptive clustering hierarchy (LEACH) and threshold LEACH (T-LEACH), as well as modified threshold-based cluster head replacement (MT-CHR) protocols are of a great interest as of being energy optimized. In this article, we propose two protocols to cluster a WSN through taking advantage of the shortcomings of these protocols (i.e., LEACH, T-LEACH, and MT-CHR), namely centralized density- and threshold-based cluster head replacement (C-DTB-CHR) and C-DTB-CHR with adaptive data distribution (C-DTB-CHR-ADD) protocols that mainly aim at optimizing energy through minimizing the number of re-clustering operations, precluding cluster heads nodes premature death, deactivating some nodes located at dense areas from cluster’s participation, as well as reducing long-distance communications. In particular, in C-DTB-CHR protocol, some nodes belong to dense clusters are put in the sleeping mode based on a certain node active probability, thereby reducing the communications with the cluster heads and consequently prolonging the network lifetime. Moreover, the base station is concerned about setting up the required clusters and accordingly informing sensor nodes along with their corresponding active probability. C-DTB-CHR-ADD protocol provides more energy optimization through adaptive data distribution where direct and multi-hoping communications are possible. Interestingly, our simulation results show impressive improvements over what are closely related in the literature in relation to network lifetime, utilization, and network performance degradation period.
Published in: International Review on Computers and Software (IRECOS)
Oct 01, 2016
The traditional fixed spectrum assignment policy, in wireless networks, has led to significant underutilization (both spatially and temporally) of some licensed spectrum bands and crowdedness of unlicensed spectrum bands. These challenges gave birth to the new spectrum utilization paradigm called “Opportunistic Spectrum Access (OSA)”. Networks that operate under this new paradigm are called Cognitive Radio Networks, named after the enabling technology of OSA. The new paradigm allows unlicensed wireless users, also called Secondary Users (SUs), to use licensed spectrum bands as long as they are not in use by their licensed users, also called Primary Users (PUs). One of the most important properties of CRNs is that channel availability changes over time depending on the activity of PUs. Therefore, SUs must be able to detect PU activity on licensed spectrum bands, in order to use those bands for data communication when they are not in use by their PUs. This nature affects many functions in the network including routing. Routing in CRNs is different from traditional network routing, since it requires spectrum availability awareness. Therefore in CRNs, all intermediate SUs must sense channels availability periodically. However, the overall sensing time over a selected route cannot be neglected. In fact, the overall transmission time for SUs along a route is reduced, due to the time spent on the required periodic sensing for these SUs. In this paper, we introduce a novel Cooperative Spectrum Sensing (CSS) strategy, in which SUs along a selected route cooperate with their neighboring SUs to monitor PUs’ activities. In our proposed strategy, a SU along the route selects a neighboring SU, if exists, to conduct spectrum sensing on its behalf for a particular channel. This selection is based on the required channel sensing time, and the remaining available time of the candidate SU. Simulation results show that the proposed model improves routing performance such that it reduces the overall required sensing time along selected routes, and therefore, the available time that SUs can offer for data transmission is increased. Also, the end-to-end delay and the achieved bottleneck link rate are enhanced.
Published in: International Journal of Networks and Communications
Aug 01, 2016
In modern crowded cities, public transportation is one of primary ways for people to go to work, shopping, etc. Therefore, it is necessary to provide an application which estimates buses’ real-time current location, supported by Google map application which displays bus location and expected arrival time. In this work, we propose a city-bus tracking system which contains two localization methods: First, using GPS method. Second, a fault-tolerance method using Wireless Sensor Networks (WSNs), in case of GPS signal failure, e.g.; due to weather conditions or physical obstacles. In this method, wireless sensor boards are deployed in selected locations along buses routes in city, and each bus is equipped by a wireless sensor board and GPS. When GPS signal is bad, the second method is considered, where bus-sensor node sends a “Hello” packet, while bus moving, to nodes deployed over bus route. Based on the Received Signal Strength Indicator (RSSI) and number of route nodes which received the “Hello” packet, the proposed localization method is used to estimate bus location.
Cervical Cancer Diagnostic System Using Adaptive Fuzzy Moving K-Means Algorithm and Fuzzy Min-Max Neural Network
Nov 10, 2013
Pap smear screening is the most successful attempt of medical science and practice for the early detection of cervical cancer. Manual analysis of the cervical cells is time consuming, laborious and error prone. This paper presents a Neural Network (NN) based system for classifying cervical cells as normal, low-grade squamous intra-epithelial lesion (LSIL) and high-grade squamous intra-epithelial lesion (HSIL). The system consists of three stages. In the first stage, cervical cells are segmented using the Adaptive Fuzzy Moving K-means (AFMKM) clustering algorithm. In the second stage, the feature extraction process is performed. In the third stage, the extracted data is classified using Fuzzy Min-Max (FMM) NN. The empirical results show that the proposed method can achieve acceptable results.
Published in: IEEE International Conference on Communications (ICC)
Jun 09, 2013
Cognitive Radio Networks (CRNs) have a dynamic nature where channels availability changes over time. In this paper, we introduce a strategy to route multicast sessions in CRNs and to protect them against failures or disappearance of channels. We model the network as a Multilayer Hyper-Graph (MLHG), such that a group of Secondary Users (SUs) which have a common channel are modeled by a hyper-edge. Also, each layer in the MLHG represents a different channel. Primary paths from a source SU to destination SUs are selected by considering channels' switching delay, and transmission delay. To protect the multicast session, we select a backup path for primary path, if feasible, such that the primary and backup paths are Shared Risk Hyper-edge Groups (SRHEGs) disjoint. We develop an Integer Linear programming (ILP) model, in order to find the multicast primary paths and their backup paths, minimize the maximum path delay, and minimize the number of selected channel links. Our simulation results show that when the number of available channels increases, the number of primary and backup paths that can be routed in the CRN increases, and the maximum path delay decreases almost linearly.
Published in: IEEE Globecom
Dec 03, 2012
The goal of this paper is to model heterogeneous channel Access in Cognitive Radio Networks (CRNs). In CRNs, when licensed users, known as Primary Users (PUs), are idle, unlicensed users, known as Secondary Users (SUs) can use their assigned channels. In the model we consider in this paper, there are two types of licensed channels, where one type has a larger bandwidth, and hence a higher service rate for SUs. Therefore, SUs prefer to use such channels, if available, over channels in the second type which have a lower service rate. SUs may also switch from the second to the first type of channels when they become available, even if their current channels are still available. Moreover in our performance model, we model the SUs' sensing process, and its dependence on the system load, and number of sensing users. We use a Continuous Time Markov Chain (CTMC) modeling approach, and derive SUs' performance metrics, which include SUs admission and blocking probabilities, and their average waiting time in the system. We also develop a baseline model and compare its performance to our proposed model.
Jun 10, 2012
In this paper, we propose to recover collided packets between Primary Users (PUs) and Secondary Users (SUs) in Cognitive Radio Networks (CRNs) for two scenarios. When a collision occurs between an SU and a PU transmitters, the SU's receiver considers the PU's transmitted packet's signals as an interference, and hence, cancels its effect in order to recover its corresponding received packet's signals. Recovering collided packets, instead of retransmitting them saves transmitters' energy. In the first scenario, we assume PUs and SUs employ the standard Binary Phase-Shift keying (BPSK) and a 90 degree phase shifted version, i.e., orthogonal to BPSK, respectively, as their modulation techniques. In the Second scenario, we assume PUs and SUs employ BPSK and QPSK as their modulation techniques, respectively, or vice versa. In both scenarios, we propose protocols to recover the SU collided packets, depending on the received phase shifts. We show through numerical analysis that a significant fraction of collided packets can be recovered. We also derive an energy saving performance metric for our proposed mechanisms, in order to assess the saved energy due to recovering the collided packets. Our numerical analysis also shows that a high percentage of energy can be saved over the traditional scheme, in which our packets recovery mechanisms are not employed.
Jun 01, 2011
In this paper, we introduce a low overhead scheme for the uplink channel allocation within a single cell of Cognitive Radio Wireless Mesh Network (CR-WMNs). The scheme does not rely on using a Common Control Channel (CCC). The mechanism is based on Physical layer Network Coding (PNC), in which two Secondary Users (SUs) are allowed to transmit synchronously over a randomly selected channel from a set of available channels, and without coordination for the purpose of requesting channels. The Mesh Router (MR) can detect up to 2 requests on the same channel due to the use of PNC, and replies back with a control packet which contains information about the assigned channel. We propose two PNC modulation schemes, PNC1 and PNC2, where initially SUs choose one of them to employ through the network operation. Decoding the received signals in PNC1 and PNC2 depend on their received energy and phases shifts, respectively. Simulation results show that the proposed mechanism signicantly outperforms traditional schemes that rely on using one CCC, or do not use PNC in terms of channel allocation time.
Published in: IEEE symposium on Computers and Communications (ISCC)
Jun 22, 2010
Network fragmentation is a potential problem in wireless sensor networks (WSNs) due to many reasons like, node failures or environmental conditions (obstacles) that prevent connected deployments. One approach to cope with this problem is to have a mobile sink node (MS) patrol the network field and collect the data from all the fragments across the network. In this paper, we use a dynamic programming (DP) approach to determine the mobility trajectory of the MS within each fragment such that the energy consumption at the sensor nodes within the fragment is minimized. Moreover, we study the problem of finding the shortest route (cycle) that the MS should take in its journey between fragments in order to reduce a fragment's inter-visit time. For this purpose, we propose an Integer Linear Programming (ILP) formulation to find the optimal route. As finding the optimal route is NP-hard, we also propose a heuristic approach to find a near optimal solution.