Browsing by Author "Bilen T."
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Item Proof of Evaluation-based energy and delay aware computation offloading for Digital Twin Edge Network(Elsevier B.V., 2023) Bozkaya E.; Erel-Özçevik M.; Bilen T.; Özçevik Y.The increasing availability of Internet of Things (IoT) applications has led to the development of new technologies. Specifically, the deployment of edge servers close to IoT devices has strengthened the edge computing paradigm. With the collaboration of Mobile Edge Computing (MEC) and cloud computing, delay-sensitive and computation-intensive tasks can be offloaded to the edge/cloud servers to improve system performance in terms of the delay and energy consumption of IoT devices. However, there is a need to schedule the computation tasks for an efficient management. More importantly, the task scheduling strategy can face data tampering attacks to deliberately modify, destroy or manipulate the decisions. To solve the above problems, in this paper, we newly propose to integrate digital twin and blockchain into the edge networks. However, it is unclear (i) how energy and delay-aware computation should be combined, and (ii) which mining computations should be executed for a secure task scheduling. The state-of-the-art focuses on task scheduling and blockchain mining, separately. Therefore, we propose a novel blockchain-based digital twin-edge network architecture where our proposed algorithm solves these two challenges at the same execution. We design a three-layer system architecture, composed of physical entity layer, digital twin edge layer and blockchain layer. In the physical entity layer, we formulate an energy and delay-aware task scheduling problem. In the digital twin edge layer, we propose a novel Proof of Evaluation (PoE)-based secure energy and delay-aware task scheduling algorithm where optimization is executed by the genetic algorithm implementation of Warehouse Location Problem (WLP). In the blockchain layer, the best-found solutions are shared with the topology in a blockchain. Here, each block includes the hash of the previous block, a genetic algorithm-based solution, nonce value, and a hash of whole blocks in the blockchain. Thus, we aim to execute the computation tasks with an acceptable delay in an energy-efficient manner and prevent data tampering attacks against the optimal computation decisions. We validate the outcomes of our PoE-based secure digital twin-edge network model with extensive evaluations. Since the proposed model distributes the task not only to the local device but also to the MEC and cloud server for delay awareness, it reduces the delay but consumes more energy. Nevertheless, the additional energy consumption can be neglected against the delay reduction. The proposed scheme is also more scalable to compare with the conventional solution. The numerical results clearly show that the proposed model provides energy and delay awareness, maintaining both data integrity and trustworthiness at the same execution of algorithm. © 2023 Elsevier B.V.Item Energy-Aware Task Scheduling for Digital Twin Edge Networks in 6G(Institute of Electrical and Electronics Engineers Inc., 2023) Bozkaya E.; Bilen T.; Erel-Ozcevik M.; Ozcevik Y.With the recent surge in the Internet of Things (IoT) devices and applications, computation offloading services in Mobile Edge Computing (MEC) have provided the significant potential to upcoming 6G networks for a better Quality of Service (QoS). However, IoT devices are typically resource and energy-constrained, so this challenge can be compensated by incorporating energy-efficient approaches into the solution. Digital Twin is a candidate technology to reshape the future of the industry and energy-efficiently manage tremendous growth in data traffic at the network edge. Thus, we propose a Digital Twin Edge Network (DTEN) architecture for energy-aware task scheduling. More specifically, we formulate an energy optimization problem and identify a set of computation strategies to minimize both the task processing time and energy consumption. Due to being NP-hard, we compare it by Warehouse Location Problem (WLP) and solve it with the genetic algorithm-based approach in an energy and time-efficient manner. To achieve these, we present our digital twin-assisted energy-aware task scheduling algorithm by using both real-time and historical data in virtualization and service layers. After this, IoT devices can compute their tasks locally or offload to the edge/cloud server with the assistance of digital twins of the physical assets. Simulations are carried out to show the superiority of the proposed energy-aware task scheduling algorithm in terms of the task processing time and consumed energy in DTEN. © 2023 IEEE.Item Optimal Location Assignment for Data-Driven Warehouse Towards Digital Supply Chain Twin(Institute of Electrical and Electronics Engineers Inc., 2023) Erel-Ozcevik M.; Ozcevik Y.; Bozkaya E.; Bilen T.Warehouses, as one of the critical components of supply chain management in Industry 4.0, play an important role in e-commerce operational efficiency. A crucial prerequisite for managing warehouses is to decide the locations of products (blocks) that can maximize overall space utilization, called a Block Location Problem (BLP). BLP basically determines the product locations to achieve maximum space utilization. One of the most innovative approaches to solving BLP is the use of drones as a block transportation strategy. Existing works have been mainly focused on 2D grid models while 3D flight movement is ignored. Thus, in this paper, we develop a novel data-driven warehouse model for digital supply chain twins. For this purpose, a warehouse digital twin (WDT) architecture is defined by creating a virtual replica of a warehouse that contains the features and interactions of its real-world counterpart. Then, we formalize the BLP in a 3D grid model to decide the location of blocks in a warehouse and to provide efficient space utilization by minimizing the energy consumption of drone cargo equipment. Finally, we propose a genetic algorithm-based solution to solve the storage location assignment. Performance evaluation results demonstrate that our proposed algorithm achieves more block utilization and less energy consumption when compared to the greedy solution. © 2023 IEEE.Item Work-in-Progress: Merkle Tree-Based Secure Routing for Digital Twin-Assisted Aircraft Network in 6G Wireless(Institute of Electrical and Electronics Engineers Inc., 2023) Bilen T.; Erel-Ozcevik M.; Bozkaya E.; Ozcevik Y.Providing Internet access above-the-clouds has made the development of aircraft networks more important than ever. However, new and emerging Internet applications have increased the challenge of providing seamless and real-time connectivity with traditional routing algorithms for aircraft networks in the upcoming 6G due to the highly-dynamic and unstable topology. Moreover, traditional routing mechanisms are prone to routing attacks, which can increase the packet transfer delay. To this end, in this paper, we present Merkle Tree-based secure routing mechanism with the assistance of digital twin. First, we construct a blockchain-based system with decentralized and distributed characteristics for the clustering of aircraft. Then, we propose a novel Merkle-Tree-based secure routing algorithm by combining real-time and historical data with digital twins. A Merkle tree is a data structure that contains gathered data from sender and receiver aircraft. Merkle root in an aircraft cluster forwards the gathered data to a satellite or a ground station in a secure manner. Accordingly, Secure Hash Algorithm (SHA)-256 is used for data integrity and a tree-based structure is built to reduce the number of transactions so that it is aimed to prevent malicious aircraft attacks. Finally, we show through a simulation environment, how blockchain processing time and the number of transactions can be reduced by meeting the strict Quality of Service (QoS) requirements for aircraft networks in 6G. Furthermore, we also use Proof of Stake (PoS) to reduce the computational time for mining a block as well as reducing the packet delivery ratio and packet transfer delay. © 2023 IEEE.Item Metaverse-Based Order Picking Optimization for Supply Chain of Things(Institute of Electrical and Electronics Engineers Inc., 2024) Erel-Ozcevik M.; Bozkaya-Aras E.; Bilen T.In recent years, with the rise of e-commerce and digital services, customers' expectations have affected supply chain management operations. The logistics industry reacts proactively by integrating new technologies into its systems to meet changing customer expectations. Among these technologies, a relatively new concept called Supply Chain of Things (SCoT) is an enabling technology for supply chain operations to increase productivity and automation. However, a large number of customer orders and increasing concerns about operating costs challenge efficient management and quality of service in SCoT. In this regard, this paper addresses the order-picking problem of minimizing delivery time and operating costs, including travel costs and total costs to the employer. Metaverse can be considered a feasible solution to address this problem due to its advantages of seamless and intelligent interaction between the physical world and the digital world. In this paper, we present a metaverse-based system architecture and design the network digital twin to enable intelligent real-time management of the SCoT environment. We formulate the order-picking problem and propose a genetic algorithm-based solution to satisfy customer demands on time with minimal operating costs by creating a digital twin of the supply chain system in the Metaverse. The simulation results show that the proposed solution achieves significant gains compared with baseline strategies in terms of the total cost to the employer while keeping order delivery time under the acceptable customer level. © 2024 IEEE.