@article{MTMT:34167552,
	title = {Distributed scalability tuning for evolutionary sharding optimization with Random-equivalent security in permissionless Blockchain},
	url = {https://m2.mtmt.hu/api/publication/34167552},
	author = {Baniata, Hamza and Anaqreh, Ahmad and Kertész, Attila},
	doi = {10.1016/j.iot.2023.100955},
	journal-iso = {INTERNET THINGS-NETH},
	journal = {INTERNET OF THINGS},
	volume = {24},
	unique-id = {34167552},
	issn = {2543-1536},
	year = {2023},
	eissn = {2542-6605},
	orcid-numbers = {Baniata, Hamza/0000-0003-1978-3175; Anaqreh, Ahmad/0000-0002-3971-2684; Kertész, Attila/0000-0002-9457-2928}
}

@article{MTMT:32588616,
	title = {DONS: Dynamic Optimized Neighbor Selection for smart blockchain networks},
	url = {https://m2.mtmt.hu/api/publication/32588616},
	author = {Baniata, Hamza and Anaqreh, Ahmad and Kertész, Attila},
	doi = {10.1016/j.future.2021.12.010},
	journal-iso = {FUTUR GENER COMP SYST},
	journal = {FUTURE GENERATION COMPUTER SYSTEMS},
	volume = {130},
	unique-id = {32588616},
	issn = {0167-739X},
	abstract = {Blockchain (BC) systems mainly depend on the consistent state of the Distributed Ledger (DL) at different logical and physical places of the network. The majority of network nodes need to be enforced to use one or both of the following approaches to remain consistent: (i) to wait for certain delays (i.e. by requesting a hard puzzle solution as in PoW and PoUW, or to wait for random delays as in PoET, etc.) (ii) to propagate shared data through shortest possible paths within the network. The first approach may cause higher energy consumption and/or lower throughput rates if not optimized, and in many cases these features are conventionally fixed. Therefore, it is preferred to enhance the second approach with some optimization. Previous works for this approach have the following drawbacks: they may violate the identity privacy of miners, only locally optimize the Neighbor Selection method (NS), do not consider the dynamicity of the network, or require the nodes to know the precise size of the network at all times. In this paper, we address these issues by proposing a Dynamic and Optimized NS protocol called DONS, using a novel privacy-aware leader election within the public BC called AnoLE, where the leader anonymously solves the The Minimum Spanning Tree problem (MST) of the network in polynomial time. Consequently, miners are informed about the optimum NS according to the current state of network topology. We analytically evaluate the complexity, the security and the privacy of the proposed protocols against state-of-the-art MST solutions for DLs and well known attacks. Additionally, we experimentally show that the proposed protocols outperform state-of-the-art NS solutions for public BCs. Our evaluation shows that the proposed DONS and AnoLE protocols are secure, private, and they acutely outperform all current NS solutions in terms of block finality and fidelity. © 2021 The Author(s)},
	keywords = {Polynomial approximation; Energy utilization; MINERS; Minimum spanning tree; Selection methods; blockchain; blockchain; leader election; Distributed ledger; 'current; Block-chain; Optimized neighbor selection; Optimized neighbor selection; Anonymized leader election; Anonymized leader election; Minimum Spanning Tree problem; Minimums panning tree; Neighbour selections; Smart networking; Smart networking},
	year = {2022},
	eissn = {1872-7115},
	pages = {75-90},
	orcid-numbers = {Baniata, Hamza/0000-0003-1978-3175; Anaqreh, Ahmad/0000-0002-3971-2684; Kertész, Attila/0000-0002-9457-2928}
}

@article{MTMT:32161312,
	title = {Symbolic Regression for Approximating Graph Geodetic Number},
	url = {https://m2.mtmt.hu/api/publication/32161312},
	author = {Anaqreh, Ahmad and Gazdag-Tóth, Boglárka and Vinkó, Tamás},
	doi = {10.14232/actacyb.289041},
	journal-iso = {ACTA CYBERN-SZEGED},
	journal = {ACTA CYBERNETICA},
	volume = {25},
	unique-id = {32161312},
	issn = {0324-721X},
	abstract = {Graph properties are certain attributes that could make the structure of the graph understandable. Occasionally, standard methods cannot work properly for calculating exact values of graph properties due to their huge computational complexity, especially for real-world graphs. In contrast, heuristics and metaheuristics are alternatives proved their ability to provide sufficient solutions in a reasonable time. Although in some cases, even heuristics are not efficient enough, where they need some not easily obtainable global information of the graph. The problem thus should be dealt in completely different way by trying to find features that related to the property and based on these data build a formula which can approximate the graph property. In this work, symbolic regression with an evolutionary algorithm called Cartesian Genetic Programming has been used to derive formulas capable to approximate the graph geodetic number which measures the minimal-cardinality set of vertices, such that all shortest paths between its elements cover every vertex of the graph. Finding the exact value of the geodetic number is known to be NP-hard for general graphs. The obtained formulas are tested on random and real-world graphs. It is demonstrated how various graph properties as training data can lead to diverse formulas with different accuracy. It is also investigated which training data are really related to each property.},
	year = {2021},
	eissn = {2676-993X},
	pages = {151-169},
	orcid-numbers = {Anaqreh, Ahmad/0000-0002-3971-2684; Gazdag-Tóth, Boglárka/0000-0002-0927-111X; Vinkó, Tamás/0000-0002-3724-4725}
}

@article{MTMT:32161290,
	title = {Algorithmic upper bounds for graph geodetic number},
	url = {https://m2.mtmt.hu/api/publication/32161290},
	author = {Anaqreh, Ahmad and Gazdag-Tóth, Boglárka and Vinkó, Tamás},
	doi = {10.1007/s10100-021-00760-7},
	journal-iso = {CEJOR},
	journal = {CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH},
	volume = {30},
	unique-id = {32161290},
	issn = {1435-246X},
	abstract = {Graph theoretical problems based on shortest paths are at the core of research due to their theoretical importance and applicability. This paper deals with the geodetic number which is a global measure for simple connected graphs and it belongs to the path covering problems: what is the minimal-cardinality set of vertices, such that all shortest paths between its elements cover every vertex of the graph. Inspired by the exact 0-1 integer linear programming formalism from the recent literature, we propose new method to obtain upper bounds for the geodetic number in an algorithmic way. The efficiency of these algorithms are demonstrated on a collection of structurally different graphs.},
	year = {2021},
	eissn = {1613-9178},
	pages = {1221-1237},
	orcid-numbers = {Anaqreh, Ahmad/0000-0002-3971-2684; Gazdag-Tóth, Boglárka/0000-0002-0927-111X; Vinkó, Tamás/0000-0002-3724-4725}
}

@article{MTMT:31623462,
	title = {PF-BTS: A Privacy-Aware Fog-enhanced Blockchain-assisted task scheduling},
	url = {https://m2.mtmt.hu/api/publication/31623462},
	author = {Baniata, Hamza and Anaqreh, Ahmad and Kertész, Attila},
	doi = {10.1016/j.ipm.2020.102393},
	journal-iso = {INFORM PROCESS MANAG},
	journal = {INFORMATION PROCESSING & MANAGEMENT},
	volume = {58},
	unique-id = {31623462},
	issn = {0306-4573},
	abstract = {In recent years, the deployment of Cloud Computing (CC) has become more popular both in research and industry applications, arising form various fields including e-health, manufacturing, logistics and social networking. This is due to the easiness of service deployment and data management, and the unlimited provision of virtual resources (VR). In simple scenarios, users/applications send computational or storage tasks to be executed in the cloud, by manually assigning those tasks to the available computational resources. In complex scenarios, such as a smart city applications, where there is a large number of tasks, VRs, or both, task scheduling is exposed as an NP-Hard problem. Consequently, it is preferred and more efficient in terms of time and effort, to use a task scheduling automation technique. As there are many automated scheduling solutions proposed, new possibilities arise with the advent of Fog Computing (FC) and Blockchain (BC) technologies. Accordingly, such automation techniques may help the quick, secure and efficient assignment of tasks to the available VRs. In this paper, we propose an Ant Colony Optimization (ACO) algorithm in a Fog-enabled Blockchain-assisted scheduling model, namely PF-BTS. The protocol and algorithms of PF-BTS exploit BC miners for generating efficient assignment of tasks to be performed in the cloud's VRs using ACO, and award miner nodes for their contribution in generating the best schedule. In our proposal, PF-BTS further allows the fog to process, manage, and perform the tasks to enhance latency measures. While this processing and managing is taking place, the fog is enforced to respect the privacy of system components, and assure that data, location, identity, and usage information are not exposed. We evaluate and compare PF-BTS performance, with a recently proposed Blockchain-based task scheduling protocol, in a simulated environment. Our evaluation and experiments show high privacy awareness of PF-BTS, along with noticeable enhancement in execution time and network load. © 2020 The Authors},
	keywords = {Scheduling; automation; Information Management; Multitasking; NP-hard; fog; Industrial research; Computational resources; MINERS; Cloud computing; Digital storage; Simulated environment; Internet of Things; Ant colony optimization; Ant colony optimization; Fog computing; Fog computing; blockchain; blockchain; Industry applications; Ant Colony Optimization algorithms; task scheduling; service deployment; Social sciences computing; Privacy awareness; Automation techniques; Scheduling models},
	year = {2021},
	eissn = {1873-5371},
	orcid-numbers = {Baniata, Hamza/0000-0003-1978-3175; Anaqreh, Ahmad/0000-0002-3971-2684; Kertész, Attila/0000-0002-9457-2928}
}