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The network session constraints for Industrial Internet of Things (IIoT) applications are different and challenging. These constraints necessitates a high level of reconfigurability, so that the system can assess the impact of an event and adjust the network effectively. Software Defined Networking (SDN) in contrast to existing networks segregates the control and data plane to support network configuration which is programmable with smart cities requirement that shows the highest impact on the system but faces the problem of reliability. To address this issue, the SDN-IIoT based load balancing algorithm is proposed in this article and it is not application specific.Quality of service (QoS) aware architecture i.e., SDN-IIoT load balancing scheme is proposed and it deals with load on the servers. Huge load on the servers, makes them vulnerable to halt the system and hence leads to faults which creates the reliability problem for real time applications. In this article, load is migrated from one server to another server, if load on one server is more than threshold value. Load distribution has made the proposed scheme more reliable than already existing schemes. Further, the topology used for the implementation has been designed using POX controller and the results has been evaluated using Mininet emulator with its support in python programming. Lastly, the performance is evaluated based on the various Quality of Service (QoS) metrics; data transmission, response time and CPU utilization which shows that the proposed algorithm has shown 10% improvement over the existing LBBSRT, Random, Round-robin, Heuristic algorithms.
Himanshi Babbar; Shalli Rani; Aman Singh; Mohammed Abd-Elnaby; Bong Jun Choi. Cloud Based Smart City Services for Industrial Internet of Things in Software-Defined Networking. Sustainability 2021, 13, 8910 .
AMA StyleHimanshi Babbar, Shalli Rani, Aman Singh, Mohammed Abd-Elnaby, Bong Jun Choi. Cloud Based Smart City Services for Industrial Internet of Things in Software-Defined Networking. Sustainability. 2021; 13 (16):8910.
Chicago/Turabian StyleHimanshi Babbar; Shalli Rani; Aman Singh; Mohammed Abd-Elnaby; Bong Jun Choi. 2021. "Cloud Based Smart City Services for Industrial Internet of Things in Software-Defined Networking." Sustainability 13, no. 16: 8910.
The application placement strategies in the hierarchical fog-cloud environment based on the directed acyclic graph (DAG) for rapid execution is an NP-hard optimization problem. Although heuristics have been proposed to generate sub-optimal solutions based on non-preemptive placement policy, merging multiple DAG-based applications into one application is simple but ineffective for minimizing the overall makespan due to the lack of consideration of fairness among multiple DAG-based applications. We design an application placement strategy based on dynamic scheduling that can effectively utilize the schedule gaps in the virtual machines of the different layers to minimize the makespan that meets the deadlines.
Prasenjit Maiti; Bibhudatta Sahoo; Ashok Kumar Turuk; Ajit Kumar; Bong Jun Choi. Internet of Things applications placement to minimize latency in multi-tier fog computing framework. ICT Express 2021, 1 .
AMA StylePrasenjit Maiti, Bibhudatta Sahoo, Ashok Kumar Turuk, Ajit Kumar, Bong Jun Choi. Internet of Things applications placement to minimize latency in multi-tier fog computing framework. ICT Express. 2021; ():1.
Chicago/Turabian StylePrasenjit Maiti; Bibhudatta Sahoo; Ashok Kumar Turuk; Ajit Kumar; Bong Jun Choi. 2021. "Internet of Things applications placement to minimize latency in multi-tier fog computing framework." ICT Express , no. : 1.
With the increasing requirements for power system transient stability assessment, the research on power system transient stability assessment theory and methods requires not only qualitative conclusions about system transient stability but also quantitative analysis of stability and even development trends. Judging from the research and development process of this direction at home and abroad in recent years, it is mainly based on the construction of quantitative index models to evaluate its transient stability and development trend. Regarding the construction theories and methods of quantitative index models, a lot of results have been achieved so far. The research ideas mainly focus on two categories: uncertainty analysis methods and deterministic analysis methods. Transient stability analysis is one of the important factors that need to be considered. Therefore, this paper proposed an optimized algorithm based on deep learning for preventive control of the transient stability in power systems. The proposed algorithm accurately fits the generator’s power and transient stability index through a deep belief network (DBN) by unsupervised pre-training and fine-tuning. The non-linear differential–algebraic equation and complex transient stability are determined using the deep neural network. The proposed algorithm minimizes the control cost under the constraints of the contingency by realizing the data-driven acquisition of the optimal preventive control. It also provides an efficient solution to stability and reliability rules with similar safety into the corresponding control model. Simulation results show that the proposed algorithm effectively improved the accuracy and reduces the complexity as compared with existing algorithms.
Qinggang Su; Habib Ullah Khan; Imran Khan; Bong Jun Choi; Falin Wu; Ayman A. Aly. An optimized algorithm for optimal power flow based on deep learning. Energy Reports 2021, 7, 2113 -2124.
AMA StyleQinggang Su, Habib Ullah Khan, Imran Khan, Bong Jun Choi, Falin Wu, Ayman A. Aly. An optimized algorithm for optimal power flow based on deep learning. Energy Reports. 2021; 7 ():2113-2124.
Chicago/Turabian StyleQinggang Su; Habib Ullah Khan; Imran Khan; Bong Jun Choi; Falin Wu; Ayman A. Aly. 2021. "An optimized algorithm for optimal power flow based on deep learning." Energy Reports 7, no. : 2113-2124.
Green wireless networking has attracted considerable research attention, especially in academics and industry from economic and ecological perspectives. Promoting wireless infrastructures by exploiting green power sources has the potential to enhance sustainability and address the adverse impact of conventional power sources. A sustainable optimal standalone solar-powered model for green cellular base stations in urban locations of South Korea is proposed in this work to extend 24-hour uninterrupted power supply support to LTE cellular base stations (BSs) and take advantage of integrated storage devices. The optimal system architecture, energy management, and economic analysis are examined using the hybrid optimization model for electric renewable optimization software based on actual prevailing conditions of regions and their technical feasibility. Results showed that the proposed solar photovoltaic system can achieve significant operational expenditure savings of up to 43% and 43.58% in on- and off-grid sites, respectively, and reduce greenhouse gas emissions in the telecommunications sector. Moreover, the results of this study can provide a stronger platform for a sustainable green wireless network paradigm that can ensure energy sustainability compared with conventional technology.
Mohammed H. Alsharif; Raju Kannadasan; Abu Jahid; Mahmoud A. Albreem; Jamel Nebhen; Bong Jun Choi. Long-Term Techno-Economic Analysis of Sustainable and Zero Grid Cellular Base Station. IEEE Access 2021, 9, 54159 -54172.
AMA StyleMohammed H. Alsharif, Raju Kannadasan, Abu Jahid, Mahmoud A. Albreem, Jamel Nebhen, Bong Jun Choi. Long-Term Techno-Economic Analysis of Sustainable and Zero Grid Cellular Base Station. IEEE Access. 2021; 9 (99):54159-54172.
Chicago/Turabian StyleMohammed H. Alsharif; Raju Kannadasan; Abu Jahid; Mahmoud A. Albreem; Jamel Nebhen; Bong Jun Choi. 2021. "Long-Term Techno-Economic Analysis of Sustainable and Zero Grid Cellular Base Station." IEEE Access 9, no. 99: 54159-54172.
Massive multiple-input multiple-output (MIMO) is a backbone technology in the fifth-generation (5G) and beyond 5G (B5G) networks. It enhances performance gain, energy efficiency, and spectral efficiency. Unfortunately, a massive number of antennas need sophisticated processing to detect the transmitted signal. Although a detector based on the maximum likelihood (ML) is optimal, it incurs a high computational complexity, and hence, it is not hardware-friendly. In addition, the conventional linear detectors, such as the minimum mean square error (MMSE), include a matrix inversion, which causes a high computational complexity. As an alternative solution, approximate message passing (AMP) algorithm is proposed for data detection in massive MIMO uplink (UL) detectors. Although the AMP algorithm is converging extremely fast, the convergence is not guaranteed. A good initialization influences the convergence rate and affects the performance substantially together and the complexity. In this paper, we exploit several free-matrix-inversion methods, namely, the successive over-relaxation (SOR), the Gauss–Seidel (GS), and the Jacobi (JA), to initialize the AMP-based massive MIMO UL detector. In other words, hybrid detectors are proposed based on AMP, JA, SOR, and GS with an efficient initialization. Numerical results show that proposed detectors achieve a significant performance enhancement and a large reduction in the computational complexity.
Mahmoud Albreem; Arun Kumar; Mohammed Alsharif; Imran Khan; Bong Choi. Comparative Analysis of Data Detection Techniques for 5G Massive MIMO Systems. Sustainability 2020, 12, 9281 .
AMA StyleMahmoud Albreem, Arun Kumar, Mohammed Alsharif, Imran Khan, Bong Choi. Comparative Analysis of Data Detection Techniques for 5G Massive MIMO Systems. Sustainability. 2020; 12 (21):9281.
Chicago/Turabian StyleMahmoud Albreem; Arun Kumar; Mohammed Alsharif; Imran Khan; Bong Choi. 2020. "Comparative Analysis of Data Detection Techniques for 5G Massive MIMO Systems." Sustainability 12, no. 21: 9281.
Conventional models in the intelligent transportation system (ITS) are confronted by large computational overheads and how they react during real-time scenarios. To appropriately manage the communication process in real-time, a trust-based mechanism can provide an efficient approach to acclimatize its deeds based on indecision sensory information. However, the computational models are not fully demoralized by the businesses owing to the lack of automated integration. In this study, we perform agent-based modeling (ABM) and population-based modeling (PBM) in the ITS mechanism during data transmission and record exchange for real-time communication. In addition, a trust evaluation process is performed to legitimize each device with the integration of ABM and PBM models. The simulation results show that the proposed mechanism is 89% more efficient than baseline methods in various networking scenarios, such as message alteration, distributed denial of service attacks, and information falsification threats.
Geetanjali Rathee; Sahil Garg; Georges Kaddoum; Bong Jun Choi; M. Shamim Hossain. Trusted Computation using ABM and PBM Decision Models for ITS. IEEE Access 2020, 8, 1 -1.
AMA StyleGeetanjali Rathee, Sahil Garg, Georges Kaddoum, Bong Jun Choi, M. Shamim Hossain. Trusted Computation using ABM and PBM Decision Models for ITS. IEEE Access. 2020; 8 ():1-1.
Chicago/Turabian StyleGeetanjali Rathee; Sahil Garg; Georges Kaddoum; Bong Jun Choi; M. Shamim Hossain. 2020. "Trusted Computation using ABM and PBM Decision Models for ITS." IEEE Access 8, no. : 1-1.
Shancheng Zhao; Jinming Wen; Shahid Mumtaz; Sahil Garg; Bong Jun Choi. Spatially Coupled Codes via Partial and Recursive Superposition for Industrial IoT With High Trustworthiness. IEEE Transactions on Industrial Informatics 2020, 16, 6143 -6153.
AMA StyleShancheng Zhao, Jinming Wen, Shahid Mumtaz, Sahil Garg, Bong Jun Choi. Spatially Coupled Codes via Partial and Recursive Superposition for Industrial IoT With High Trustworthiness. IEEE Transactions on Industrial Informatics. 2020; 16 (9):6143-6153.
Chicago/Turabian StyleShancheng Zhao; Jinming Wen; Shahid Mumtaz; Sahil Garg; Bong Jun Choi. 2020. "Spatially Coupled Codes via Partial and Recursive Superposition for Industrial IoT With High Trustworthiness." IEEE Transactions on Industrial Informatics 16, no. 9: 6143-6153.
Decision-making is of critical significance in Internet-of-Vehicles (IoV), where vehicles need to quickly make decisions in real-time when sharing or transferring the information. In addition, it is necessary to identify the significant factors of an entity while measuring its legitimacy or to record the real-time data generated by it. Traditional automated schemes in IoV are confronted by the issues related to real-time processing and the manner they respond, such as traffic congestion information, fastest route selection, and road accidental information. The exchange of accurate information among vehicles is critical, but the decision-making for IoV has still not been fully investigated in the literature. Further, the involvement of malicious devices in the network may disgrace the network performance by consuming network resources. In this paper, we propose a hybrid decision-making scheme in vehicular informatics for data transferring and processing through VIKOR and analytic hierarchy process (AHP) methods. The proposed model is scrutinized and verified rigorously through several sensing and decision-making metrics against a conventional solution. The simulation results depict that the proposed model leads to 93 percent competence in terms of decision-making, identification of legitimate sensors, and data alteration process when sharing the information through various sensors in IoV.
Geetanjali Rathee; Sahil Garg; Georges Kaddoum; Bong Jun Choi; M. Shamim Hossain. Trusted Orchestration for Smart Decision-Making in Internet of Vehicles. IEEE Access 2020, 8, 157427 -157436.
AMA StyleGeetanjali Rathee, Sahil Garg, Georges Kaddoum, Bong Jun Choi, M. Shamim Hossain. Trusted Orchestration for Smart Decision-Making in Internet of Vehicles. IEEE Access. 2020; 8 (99):157427-157436.
Chicago/Turabian StyleGeetanjali Rathee; Sahil Garg; Georges Kaddoum; Bong Jun Choi; M. Shamim Hossain. 2020. "Trusted Orchestration for Smart Decision-Making in Internet of Vehicles." IEEE Access 8, no. 99: 157427-157436.
There is a need for improvement of tools to deal with large volumes of multimedia data effectively. In particular, real-time data processing is one of the major problems for multimedia data computing in remote sensing systems. Such big data systems have to offer effective management and computational efficiency for applications in real-time. In this paper, we propose a large-scale geological processing method for aerial Light Detection and Ranging (LiDAR) clouds containing multimedia data that ensures mobility and timeliness. By utilizing Spark and Cassandra, our proposed approach can significantly reduce the execution time of the time-consuming process. We investigate fast ground-only raster generation from huge LiDAR datasets. We observed that filtered cloud data ensuing from impartial consideration of neighboring zones could lead to classification errors on the boundaries. Therefore, an integrated approach is proposed to correct these errors to improve the classification consistency, achieve faster processing time, provide automatic error correction, obtain Digital Terrain Models (DTM), and minimize user intervention. These features can provide a framework for an on-demand DTM output and scalable application services. Furthermore, the proposed approach can expect to benefit other real-time applications in LiDAR systems.
Rahul Malik; Aditya Khamparia; Sahil Garg; Deepak Gupta; Bong Jun Choi; M. Shamim Hossain. Reversible Data Hiding and Smart Multimedia Computing Using Big Data in Remote Sensing Systems. IEEE Access 2020, 8, 153546 -153560.
AMA StyleRahul Malik, Aditya Khamparia, Sahil Garg, Deepak Gupta, Bong Jun Choi, M. Shamim Hossain. Reversible Data Hiding and Smart Multimedia Computing Using Big Data in Remote Sensing Systems. IEEE Access. 2020; 8 (99):153546-153560.
Chicago/Turabian StyleRahul Malik; Aditya Khamparia; Sahil Garg; Deepak Gupta; Bong Jun Choi; M. Shamim Hossain. 2020. "Reversible Data Hiding and Smart Multimedia Computing Using Big Data in Remote Sensing Systems." IEEE Access 8, no. 99: 153546-153560.
Metropolitan transportation is a dynamic and non-linear complex system. In such a system, there are possibilities of altering, monitoring, forging, and accessing private, public, and resource information of depot staff and communicating agents by unauthorized agencies the metropolitan area. Existing solutions for the management of security and privacy of communicating agents in an intelligent public transportation system (IPTS) do not adapt to the dynamic occurrence of real-time event information. Therefore, existing solutions are insufficient to address the randomness and other characteristics pertaining to a non-linear complex system such as an intelligent transport system (ITS). To this end, in this paper, we propose a privacy and security management scheme for ITS depot staff in a metropolitan area. This scheme provides privacy and security management in the transportation industry during the exchange of information regarding vehicle allocation, dispatch, revocation, financial, and maintenance. Absence of such an aforementioned scheme leads to anomalies such as impersonation of genuine staff and malicious and greedy staff. We use the emergent intelligence (EI) technique to collect, analyze, and share information, and take dynamic decisions during the security and privacy management of the depot staff in transport industries. The EI technique provides autonomy, flexibility, adaptiveness, robustness, self-organization, and evolution to address the randomness and behavior of a non-linear complex system pertaining to the transportation system in metropolitan areas. The proposed scheme is implemented using the Crypto++ package, and the results indicate that the scheme efficiently manages the security and privacy in transportation industries in metropolitan areas.
Suresh Chavhan; Deepak Gupta; Sahil Garg; Ashish Khanna; Bong Jun Choi; M. Shamim Hossain. Privacy and Security Management in Intelligent Transportation System. IEEE Access 2020, 8, 148677 -148688.
AMA StyleSuresh Chavhan, Deepak Gupta, Sahil Garg, Ashish Khanna, Bong Jun Choi, M. Shamim Hossain. Privacy and Security Management in Intelligent Transportation System. IEEE Access. 2020; 8 (99):148677-148688.
Chicago/Turabian StyleSuresh Chavhan; Deepak Gupta; Sahil Garg; Ashish Khanna; Bong Jun Choi; M. Shamim Hossain. 2020. "Privacy and Security Management in Intelligent Transportation System." IEEE Access 8, no. 99: 148677-148688.
The power system worldwide is going through a revolutionary transformation due to the integration with various distributed components, including advanced metering infrastructure, communication infrastructure, distributed energy resources, and electric vehicles, to improve the reliability, energy efficiency, management, and security of the future power system. These components are becoming more tightly integrated with IoT. They are expected to generate a vast amount of data to support various applications in the smart grid, such as distributed energy management, generation forecasting, grid health monitoring, fault detection, home energy management, etc. With these new components and information, artificial intelligence techniques can be applied to automate and further improve the performance of the smart grid. In this paper, we provide a comprehensive review of the state-of-the-art artificial intelligence techniques to support various applications in a distributed smart grid. In particular, we discuss how artificial techniques are applied to support the integration of renewable energy resources, the integration of energy storage systems, demand response, management of the grid and home energy, and security. As the smart grid involves various actors, such as energy produces, markets, and consumers, we also discuss how artificial intelligence and market liberalization can potentially help to increase the overall social welfare of the grid. Finally, we provide further research challenges for large-scale integration and orchestration of automated distributed devices to realize a truly smart grid.
Syed Saqib Ali; Bong Jun Choi. State-of-the-Art Artificial Intelligence Techniques for Distributed Smart Grids: A Review. Electronics 2020, 9, 1030 .
AMA StyleSyed Saqib Ali, Bong Jun Choi. State-of-the-Art Artificial Intelligence Techniques for Distributed Smart Grids: A Review. Electronics. 2020; 9 (6):1030.
Chicago/Turabian StyleSyed Saqib Ali; Bong Jun Choi. 2020. "State-of-the-Art Artificial Intelligence Techniques for Distributed Smart Grids: A Review." Electronics 9, no. 6: 1030.
As more and more mobile multimedia services are produced, end users are increasingly demanding access to high-speed, low-latency mobile communication networks. Among them, device-to-device (D2D) communication does not need the data to be forwarded through the base station relay but allows the two mobile devices adjacent to each other to establish a direct local link under control of the base station. This flexible communication method reduces the processing bottlenecks and blind spots of the base station and can be widely used in dense user communication scenarios such as transportation systems. Aiming at the problem of high energy consumption and improved quality of service demands by the D2D users, this paper proposes a new scheme to effectively improve the user fairness and satisfaction based on the user grouping into clusters. The main idea is to create the interference graph between the D2D users which is based on the graph coloring theory and constructs the color lists of the D2D users while cellular users’ requirements are guaranteed. Finally, those D2D users who can share the same channel are grouped in the same cluster. Simulation results show that the proposed scheme outperforms the existing schemes and effectively improve system performance.
Raya Majid Alsharfa; Saleem Latteef Mohammed; Sadik Kamel Gharghan; Imran Khan; Bong Jun Choi. Cellular-D2D Resource Allocation Algorithm Based on User Fairness. Electronics 2020, 9, 386 .
AMA StyleRaya Majid Alsharfa, Saleem Latteef Mohammed, Sadik Kamel Gharghan, Imran Khan, Bong Jun Choi. Cellular-D2D Resource Allocation Algorithm Based on User Fairness. Electronics. 2020; 9 (3):386.
Chicago/Turabian StyleRaya Majid Alsharfa; Saleem Latteef Mohammed; Sadik Kamel Gharghan; Imran Khan; Bong Jun Choi. 2020. "Cellular-D2D Resource Allocation Algorithm Based on User Fairness." Electronics 9, no. 3: 386.
Geetanjali Rathee; Naveen Jaglan; Sahil Garg; Bong Jun Choi; Kim-Kwang Raymond Choo. A Secure Spectrum Handoff Mechanism in Cognitive Radio Networks. IEEE Transactions on Cognitive Communications and Networking 2020, 6, 959 -969.
AMA StyleGeetanjali Rathee, Naveen Jaglan, Sahil Garg, Bong Jun Choi, Kim-Kwang Raymond Choo. A Secure Spectrum Handoff Mechanism in Cognitive Radio Networks. IEEE Transactions on Cognitive Communications and Networking. 2020; 6 (3):959-969.
Chicago/Turabian StyleGeetanjali Rathee; Naveen Jaglan; Sahil Garg; Bong Jun Choi; Kim-Kwang Raymond Choo. 2020. "A Secure Spectrum Handoff Mechanism in Cognitive Radio Networks." IEEE Transactions on Cognitive Communications and Networking 6, no. 3: 959-969.
The Internet-of-things (IoT) has been gradually paving the way for the pervasive connectivity of wireless networks. Due to the ability to connect a number of devices to the Internet, many applications of IoT networks have recently been proposed. Though these applications range from industrial automation to smart homes, healthcare applications are the most critical. Providing reliable connectivity among wearables and other monitoring devices is one of the major tasks of such healthcare networks. The main source of power for such low-powered IoT devices is the batteries, which have a limited lifetime and need to be replaced or recharged periodically. In order to improve their lifecycle, one of the most promising proposals is to harvest energy from the ambient resources in the environment. For this purpose, we designed an energy harvesting protocol that harvests energy from two ambient energy sources, namely radio frequency (RF) at 2.4 GHz and thermal energy. A rectenna is used to harvest RF energy, while the thermoelectric generator (TEG) is employed to harvest human thermal energy. To verify the proposed design, extensive simulations are performed in Green Castalia, which is a framework that is used with the Castalia simulator in OMNeT++. The results show significant improvements in terms of the harvested energy and lifecycle improvement of IoT devices.
Omar A. Saraereh; Amer Alsaraira; Imran Khan; Bong Jun Choi. A Hybrid Energy Harvesting Design for On-Body Internet-of-Things (IoT) Networks. Sensors 2020, 20, 407 .
AMA StyleOmar A. Saraereh, Amer Alsaraira, Imran Khan, Bong Jun Choi. A Hybrid Energy Harvesting Design for On-Body Internet-of-Things (IoT) Networks. Sensors. 2020; 20 (2):407.
Chicago/Turabian StyleOmar A. Saraereh; Amer Alsaraira; Imran Khan; Bong Jun Choi. 2020. "A Hybrid Energy Harvesting Design for On-Body Internet-of-Things (IoT) Networks." Sensors 20, no. 2: 407.
Crowdsourcing can be applied to provide scalable and efficient services to support various tasks. As the driving force of crowdsourcing is the interaction among participants, various incentive mechanisms have been proposed to attract and retain a sufficient number of participants to provide a sustainable crowdsourcing service. However, there exist some gaps between the modeled entities or markets in the existing works and those in reality: 1) dichotomous task valuation and workers’ punctuality, and 2) crowdsourcing service market monopolized by a platform. To bridge those gaps of such impractical assumption, we model workers’ heterogeneous punctuality behavior and task depreciation over time. Based on those models, we propose an Expected Social Welfare Maximizing (ESWM) mechanism that aims to maximize the expected social welfare by attracting and retaining more participants in the long-term, i.e., multiple rounds of crowdsourcing. In the evaluation, we modeled the continuous competition between the ESWM and one of the existing works in both short-term and long-term scenarios. Simulation results show that the ESWM mechanism achieves higher expected social welfare and platform utility than the benchmark by attracting and retaining more participants. Moreover, we prove that the ESWM mechanism achieves the desirable economic properties: individual rationality, budget-balance, computational efficiency, and truthfulness.
Duin Baek; Jing Chen; Bong Jun Choi. Small Profits and Quick Returns: An Incentive Mechanism Design for Crowdsourcing Under Continuous Platform Competition. IEEE Internet of Things Journal 2019, 7, 349 -362.
AMA StyleDuin Baek, Jing Chen, Bong Jun Choi. Small Profits and Quick Returns: An Incentive Mechanism Design for Crowdsourcing Under Continuous Platform Competition. IEEE Internet of Things Journal. 2019; 7 (1):349-362.
Chicago/Turabian StyleDuin Baek; Jing Chen; Bong Jun Choi. 2019. "Small Profits and Quick Returns: An Incentive Mechanism Design for Crowdsourcing Under Continuous Platform Competition." IEEE Internet of Things Journal 7, no. 1: 349-362.
The performance of the future mobile communication system could greatly improve as a result of Device-to-Device (D2D) communication and Non-Orthogonal Multiple Access (NOMA). Reduction of the interference between the D2D users and cellular users is crucial in improving the overall throughput and efficiency of the D2D communication based on NOMA. This paper proposes a joint sub-channel and power allocation algorithm for D2D communication based on NOMA to maximize the uplink energy efficiency and throughput of the mobile communication system. The algorithm uses the Kuhn-Munkres (KM) technique to allocate a channel for each D2D group and formulates an optimal power allocation problem using Karush-Kuhn-Tucker (KKT) conditions. Simulations indicate that the proposed algorithm outperforms the current state-of-the-art algorithms in regards to energy efficiency and throughput under different network conditions.
Salem Alemaishat; Omar A. Saraereh; Imran Khan; Bong Jun Choi. An Efficient Resource Allocation Algorithm for D2D Communications Based on NOMA. IEEE Access 2019, 7, 120238 -120247.
AMA StyleSalem Alemaishat, Omar A. Saraereh, Imran Khan, Bong Jun Choi. An Efficient Resource Allocation Algorithm for D2D Communications Based on NOMA. IEEE Access. 2019; 7 (99):120238-120247.
Chicago/Turabian StyleSalem Alemaishat; Omar A. Saraereh; Imran Khan; Bong Jun Choi. 2019. "An Efficient Resource Allocation Algorithm for D2D Communications Based on NOMA." IEEE Access 7, no. 99: 120238-120247.
Channel state information (CSI) feedback in massive MIMO systems is too large due to large pilot overhead. It is due to the large channel matrix dimension which depends on the number of base station (BS) antennas and consumes the majority of scarce radio resources. To solve this problem, we proposed a scheme for efficient CSI acquisition and reduced pilot overhead. It is based on the separation mechanism for the channel matrix. The spatial correlation among multiuser channel matrices in the virtual angular domain is utilized to split the channel matrix. Then, the two parts of the matrix are estimated by deploying the compressed sensing (CS) techniques. This scheme is novel in the sense that the user equipment (UE) directly transmits the received symbols from the BS to the BS, so a joint CSI recovery is performed at the BS. Simulation results show that the proposed channel estimation scheme effectively estimates the channel with reduced pilot overhead and improved performance as compared with the state-of-the-art schemes.
Imran Khan; Joel J. P. C. Rodrigues; Jalal Al-Muhtadi; Muhammad Irfan Khattak; Yousaf Khan; Farhan Altaf; Seyed Sajad Mirjavadi; Bong Jun Choi. A Robust Channel Estimation Scheme for 5G Massive MIMO Systems. Wireless Communications and Mobile Computing 2019, 2019, 1 -8.
AMA StyleImran Khan, Joel J. P. C. Rodrigues, Jalal Al-Muhtadi, Muhammad Irfan Khattak, Yousaf Khan, Farhan Altaf, Seyed Sajad Mirjavadi, Bong Jun Choi. A Robust Channel Estimation Scheme for 5G Massive MIMO Systems. Wireless Communications and Mobile Computing. 2019; 2019 ():1-8.
Chicago/Turabian StyleImran Khan; Joel J. P. C. Rodrigues; Jalal Al-Muhtadi; Muhammad Irfan Khattak; Yousaf Khan; Farhan Altaf; Seyed Sajad Mirjavadi; Bong Jun Choi. 2019. "A Robust Channel Estimation Scheme for 5G Massive MIMO Systems." Wireless Communications and Mobile Computing 2019, no. : 1-8.
Primary Frequency Control (PFC) is a fast acting mechanism used to ensure high-quality power for the grid that is becoming an increasingly attractive option for load participation. Due to speed requirement and other considerations, it is often desirable to have distributed control laws. Current distributed PFC designs assume that the costs at each geographic location are independent. However, many networked systems, such as those for cloud computing, have interdependent costs across locations and therefore need geographic coordination. In this paper, distributed control laws are designed for interdependent, geo-distributed loads in PFC based on the optimality conditions of the global system. The controlled frequencies are provably stable, and the final equilibrium point is proven to strike an optimal balance between load participation and the frequency's deviation from its nominal set point. We evaluate the proposed control laws with realistic numerical simulations. Under current technology, the proposed control laws achieve a convergence time that is smaller than droop control alone and is comparable to that of distributed control without interdependent costs. Results also highlight significant cost savings over existing approaches under a variety of settings.
Joshua Comden; Tan N. Le; Yue Zhao; Bong Jun Choi; Zhenhua Liu. Geographically Coordinated Primary Frequency Control. IEEE Transactions on Control of Network Systems 2019, 6, 1246 -1255.
AMA StyleJoshua Comden, Tan N. Le, Yue Zhao, Bong Jun Choi, Zhenhua Liu. Geographically Coordinated Primary Frequency Control. IEEE Transactions on Control of Network Systems. 2019; 6 (3):1246-1255.
Chicago/Turabian StyleJoshua Comden; Tan N. Le; Yue Zhao; Bong Jun Choi; Zhenhua Liu. 2019. "Geographically Coordinated Primary Frequency Control." IEEE Transactions on Control of Network Systems 6, no. 3: 1246-1255.
In this paper, we present a joint power allocation and adaptive link selection protocol for an orthogonal frequency division multiplexing (OFDM)-based network consists of one source node i.e., base station (BS), one destination node i.e., (MU) and a buffer aided decode and forward (DF) relay node. Our objective is to maximize the average throughput of the system via power loading over different subcarriers at source and relay nodes. A separate power budget is assumed at each transmitting node to make the system more practical. In order to form our solution more tractable, a decomposition framework is implemented to solve the mixed integer optimization problem. Further, less complex suboptimal approaches have also been presented and simulation results are provided to endorse the efficiency of our designed algorithms.
Tayyaba Jabeen; Zain Ali; Wali Ullah Khan; Furqan Jameel; Imran Khan; Guftaar Ahmad Sardar Sidhu; Bong Jun Choi. Joint Power Allocation and Link Selection for Multi-Carrier Buffer Aided Relay Network. Electronics 2019, 8, 686 .
AMA StyleTayyaba Jabeen, Zain Ali, Wali Ullah Khan, Furqan Jameel, Imran Khan, Guftaar Ahmad Sardar Sidhu, Bong Jun Choi. Joint Power Allocation and Link Selection for Multi-Carrier Buffer Aided Relay Network. Electronics. 2019; 8 (6):686.
Chicago/Turabian StyleTayyaba Jabeen; Zain Ali; Wali Ullah Khan; Furqan Jameel; Imran Khan; Guftaar Ahmad Sardar Sidhu; Bong Jun Choi. 2019. "Joint Power Allocation and Link Selection for Multi-Carrier Buffer Aided Relay Network." Electronics 8, no. 6: 686.
This paper proposes a robust scheme for optimizing the power flow in a photovoltaic system. The scheme utilizes distributed saddle point dynamics and a decentralized approach to solve the power flow problem. It converts the convex optimization problem of the dynamic system control into asymptotically stable dynamic systems and employs a linear approximation of power flow equations; specifically, a quadratic programming model is deployed with the aim of minimizing real-power losses to guarantee a globally optimal solution. Then, the photovoltaic inverters and electric network are analyzed independently in a decentralized manner to exchange injection power among nodes while maintaining their independence to support the plug-and-play feature. Case study and experimental results show that the proposed scheme achieves higher optimization accuracy and is more economical than the existing state-of-the-art schemes.
Qais Alsafasfeh; Omar A. Saraereh; Imran Khan; Bong Jun Choi. A Robust Decentralized Power Flow Optimization for Dynamic PV System. IEEE Access 2019, 7, 63789 -63800.
AMA StyleQais Alsafasfeh, Omar A. Saraereh, Imran Khan, Bong Jun Choi. A Robust Decentralized Power Flow Optimization for Dynamic PV System. IEEE Access. 2019; 7 (99):63789-63800.
Chicago/Turabian StyleQais Alsafasfeh; Omar A. Saraereh; Imran Khan; Bong Jun Choi. 2019. "A Robust Decentralized Power Flow Optimization for Dynamic PV System." IEEE Access 7, no. 99: 63789-63800.