Journal articles: 'Decentralized computing'

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Kelly, Terence. "Decentralized Computing." Queue 18, no. 5 (October 31, 2020): 41–53. http://dx.doi.org/10.1145/3434571.3436964.

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Farrens, Matt. "Distributed decentralized computing." ACM Computing Surveys 28, no. 4es (December 1996): 28. http://dx.doi.org/10.1145/242224.242259.

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Mohammad Badiezadegan, Sayed. "Secure Multiparty Computing: A Decentralized Approach to GPA Calculation." International Journal of Science and Research (IJSR) 12, no. 9 (September 5, 2023): 515–16. http://dx.doi.org/10.21275/sr23905191245.

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YAMAGUCHI, A. "Autonomous Decentralized Control in Ubiquitous Computing." IEICE Transactions on Communications E88-B, no. 12 (December 1, 2005): 4421–26. http://dx.doi.org/10.1093/ietcom/e88-b.12.4421.

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Miller, Daniel E., and Edward J. Davison. "On Computing Quotient Decentralized Fixed Modes." IFAC Proceedings Volumes 44, no. 1 (January 2011): 2546–51. http://dx.doi.org/10.3182/20110828-6-it-1002.03142.

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Yin, Yingying, and Leilei Deng. "A dynamic decentralized strategy of replica placement on edge computing." International Journal of Distributed Sensor Networks 18, no. 8 (August 2022): 155013292211150. http://dx.doi.org/10.1177/15501329221115064.

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Smart phone and its applications are used more and more extensively in our daily life. Short delay of arriving data is important to these applications, especially to some time-sensitive ones. To reduce transmission latency and improve user experience, a dynamic decentralized data replica placement and management strategy which works in edge nodes is proposed in this article. It studies the location, access frequency, latency improvement, and cost spent on placing replicas on edge nodes to seek a balance between cost spent for storage and reduced latency. Specifically, dynamic and decentralized replica placement strategy algorithm has load guarantee for edge nodes to avoid overload; it dynamically create or delete data replicas on edge nodes according to the request frequency. Dynamic and decentralized replica placement strategy is decentralized to relieve transmission cost. Experiment results show that dynamic and decentralized replica placement strategy algorithm in edge computing environments can greatly reduce transmission latency, balance edge nodes load, and improve system performance. Dynamic and decentralized replica placement strategy also considers the cost spent for storage, and it pursues a balance between many factors.

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Nafus, Dawn, Eve M. Schooler, and Karly Ann Burch. "Carbon-Responsive Computing: Changing the Nexus between Energy and Computing." Energies 14, no. 21 (October 21, 2021): 6917. http://dx.doi.org/10.3390/en14216917.

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While extensive research has gone into demand response techniques in data centers, the energy consumed in edge computing systems and in network data transmission remains a significant part of the computing industry’s carbon footprint. The industry also has not fully leveraged the parallel trend of decentralized renewable energy generation, which creates new areas of opportunity for innovation in combined energy and computing systems. Through an interdisciplinary sociotechnical discussion of current energy, computer science and social studies of science and technology (STS) literature, we argue that a more comprehensive set of carbon response techniques needs to be developed that span the continuum of data centers, from the back-end cloud to the network edge. Such techniques need to address the combined needs of decentralized energy and computing systems, alongside the social power dynamics those combinations entail. We call this more comprehensive range “carbon-responsive computing,” and underscore that this continuum constitutes the beginnings of an interconnected infrastructure, elements of which are data-intensive and require the integration of social science disciplines to adequately address problems of inequality, governance, transparency, and definitions of “necessary” tasks in a climate crisis.

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Wang, Yabin, Chenghao Guo, and Jin Yu. "Immune Scheduling Network Based Method for Task Scheduling in Decentralized Fog Computing." Wireless Communications and Mobile Computing 2018 (September 2, 2018): 1–8. http://dx.doi.org/10.1155/2018/2734219.

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Fog computing has changed the distributed computing rapidly by including the smart devices widely distributed at the network edges. It is able to provide less latency and is more capable of decreasing traffic jam in the network. However, it will bring more difficulties for resource managing and task scheduling especially in a decentralized ad hoc network. In this paper, we propose a method that takes advantages of the immune mechanism to schedule tasks in a decentralized way for fog computing. By using forward propagation and backward propagation in the ad hoc network, the power of distributed schedulers is used to generate the optimized scheduler strategies to deal with computing nodes overloaded and achieve the optimal task finishing time reducing. The experiment results show that our approach can beat similar methods.

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Haposan Yoga Pradika Napitupulu and I Gde Dharma Nugraha. "Fog Computing-Based System for Decentralized Smart Parking System by Using Firebase." Jurnal Nasional Teknik Elektro dan Teknologi Informasi 13, no. 1 (February 22, 2024): 44–52. http://dx.doi.org/10.22146/jnteti.v13i1.10095.

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The growth of vehicle number is unavoidable whilst the availability of parking is not directly proportional with this condition. Nowadays, many shopping centers do not have sufficient parking spot, causing customers to have difficulty in finding available parking spots. Research has been conducted to tackle the issue of finding available parking spots. Much of this research proposed the narrowband-Internet of things (NB-IoT) as a fog node. For communication purposes, this NB-IoT-based fog node has some shortcomings, such as security and privacy, lower data rate, higher cost in development, dependency with wireless system, and only covers one area. In this research, the fog computing was proposed to decentralize smart parking system by using Firebase to cover several areas or malls in one system and interface. Instead of using NB-IoT, this research employed decentralized local server as a fog node to deliver a fast data exchange. Firestore database (Firebase) was also used to secure, manage, and analyze the data in the cloud. Conjunctively, the Android application was created as a user interface to book and find the availability of parking spots. The Android application was built using Android Studio and implemented authentication to keep the data access secure and private. The testing scenario was done following the design unified modeling language (UML). The research results confirmed that the fog computing system successfully supported the decentralized smart parking system and was able to be implemented for covering several areas or malls in one system.

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Liu, Wei, Li Chen, and Wenyi Zhang. "Decentralized Federated Learning: Balancing Communication and Computing Costs." IEEE Transactions on Signal and Information Processing over Networks 8 (2022): 131–43. http://dx.doi.org/10.1109/tsipn.2022.3151242.

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Aral, Atakan, and Tolga Ovatman. "A Decentralized Replica Placement Algorithm for Edge Computing." IEEE Transactions on Network and Service Management 15, no. 2 (June 2018): 516–29. http://dx.doi.org/10.1109/tnsm.2017.2788945.

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Chen, Xu. "Decentralized Computation Offloading Game for Mobile Cloud Computing." IEEE Transactions on Parallel and Distributed Systems 26, no. 4 (April 1, 2015): 974–83. http://dx.doi.org/10.1109/tpds.2014.2316834.

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Debe, Mazin, Khaled Salah, Muhammad Habib Ur Rehman, and Davor Svetinovic. "Blockchain-Based Decentralized Reverse Bidding in Fog Computing." IEEE Access 8 (2020): 81686–97. http://dx.doi.org/10.1109/access.2020.2991261.

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Kamath, Goutham, Lei Shi, Edmond Chow, Wenzhan Song, and Junjie Yang. "Decentralized multigrid for in-situ big data computing." Tsinghua Science and Technology 20, no. 6 (December 2015): 545–59. http://dx.doi.org/10.1109/tst.2015.7349927.

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Zhang, Hongli, and Ying Li. "Resource Allocation in Decentralized Vehicular Edge Computing Network." Information 14, no. 4 (March 27, 2023): 206. http://dx.doi.org/10.3390/info14040206.

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Computation-intensive vehicle tasks sharply increase with the rapid growth of intelligent vehicles. The technology of Mobile Edge Computing (MEC) has the possibility of assisting vehicles with computation offloading. To solve the problem of computation resource management and guarantee the security of resource transaction, we jointly combine the MEC network and the blockchain networks to build a blockchain based MEC offloading model. The non-cooperative interactions between MEC server and vehicles formulate a two-stage Stackelberg game in an aim to maximize their benefits and information security. We theoretically demonstrate the unique existence of Nash equilibrium, which enables participants to decide their optimal strategies. Finally, the performance of the proposed model is analyzed by conducting simulation experiments. Our proposed model optimizes resource allocation and also improves the security of the whole network.

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Muhammad Usman Ashraf. "A Survey on Data Security in Cloud Computing Using Blockchain: Challenges, Existing-State-Of-The-Art Methods, And Future Directions." Lahore Garrison University Research Journal of Computer Science and Information Technology 5, no. 3 (September 12, 2021): 15–30. http://dx.doi.org/10.54692/lgurjcsit.2021.0503213.

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Cloud computing is one of the ruling storage solutions. However, the cloud computing centralized storage method is not stable. Blockchain, on the other hand, is a decentralized cloud storage system that ensures data security. Cloud environments are vulnerable to several attacks which compromise the basic confidentiality, integrity, availability, and security of the network. This research focus on decentralized, safe data storage, high data availability, and effective use of storage resources. To properly respond to the situation of the blockchain method, we have conducted a comprehensive survey of the most recent and promising blockchain state-of-the-art methods, the P2P network for data dissemination, hash functions for data authentication, and IPFS (InterPlanetary File System) protocol for data integrity. Furthermore, we have discussed a detailed comparison of consensus algorithms of Blockchain concerning security. Also, we have discussed the future of blockchain and cloud computing. The major focus of this study is to secure the data in Cloud computing using blockchain and ease for researchers for further research work.

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Byun, Siwoo. "Reused Shadow Recovery Scheme for Flash-based Edge Gateway Servers." International Journal of Circuits, Systems and Signal Processing 15 (December 6, 2021): 1695–701. http://dx.doi.org/10.46300/9106.2021.15.183.

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Edge computing refers to decentralized computing technology to reduce cloud computing's overload or security problems that redirect local data to a central data center. Edge computing is emerging as a technology that complements cloud computing in an IoT environment where huge amounts of data are generated in real time. Recently, solid state drives using flash memory have recently been recognized as a suitable storage for massive IoT data services. In this study, we propose a new data recovery scheme based on shadow paging using flash memory for effective and safe data services in IoT edge gateways. The proposed scheme recycles invalidated old data blocks that are discarded when new data is stored. Thus, The proposed scheme minimizes the burden of additional storage space required to traditional shadow paging schemes, and reduces I/O performance degradation. Simulation results show that the space gain of the proposed scheme reaches even to 29%.

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Gómez-Marín, Ernesto, Luis Parrilla, Gianfranco Mauro, Antonio Escobar-Molero, Diego P. Morales, and Encarnación Castillo. "RESEKRA: Remote Enrollment Using SEaled Keys for Remote Attestation." Sensors 22, no. 13 (July 5, 2022): 5060. http://dx.doi.org/10.3390/s22135060.

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This paper presents and implements a novel remote attestation method to ensure the integrity of a device applicable to decentralized infrastructures, such as those found in common edge computing scenarios. Edge computing can be considered as a framework where multiple unsupervised devices communicate with each other with lack of hierarchy, requesting and offering services without a central server to orchestrate them. Because of these characteristics, there are many security threats, and detecting attacks is essential. Many remote attestation systems have been developed to alleviate this problem, but none of them can satisfy the requirements of edge computing: accepting dynamic enrollment and removal of devices to the system, respecting the interrupted activity of devices, and last but not least, providing a decentralized architecture for not trusting in just one Verifier. This security flaw has a negative impact on the development and implementation of edge computing-based technologies because of the impossibility of secure implementation. In this work, we propose a remote attestation system that, through using a Trusted Platform Module (TPM), enables the dynamic enrollment and an efficient and decentralized attestation. We demonstrate and evaluate our work in two use cases, attaining acceptance of intermittent activity by IoT devices, deletion of the dependency of centralized verifiers, and the probation of continuous integrity between unknown devices just by one signature verification.

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Jiang, Jingyan, Liang Hu, Chenghao Hu, Jiate Liu, and Zhi Wang. "BACombo—Bandwidth-Aware Decentralized Federated Learning." Electronics 9, no. 3 (March 5, 2020): 440. http://dx.doi.org/10.3390/electronics9030440.

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The emerging concern about data privacy and security has motivated the proposal of federated learning. Federated learning allows computing nodes to only synchronize the locally- trained models instead of their original data in distributed training. Conventional federated learning architecture, inherited from the parameter server design, relies on highly centralized typologies and large nodes-to-server bandwidths. However, in real-world federated learning scenarios, the network capacities between nodes are highly uniformly distributed and smaller than that in data centers. As a result, how to efficiently utilize network capacities between computing nodes is crucial for conventional federated learning. In this paper, we propose Bandwidth Aware Combo (BACombo), a model segment level decentralized federated learning, to tackle this problem. In BACombo, we propose a segmented gossip aggregation mechanism that makes full use of node-to-node bandwidth for speeding up the communication time. Besides, a bandwidth-aware worker selection model further reduces the transmission delay by greedily choosing the bandwidth-sufficient worker. The convergence guarantees are provided for BACombo. The experimental results on various datasets demonstrate that the training time is reduced by up to 18 times that of baselines without accuracy degrade.

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Tošić, Aleksandar, Jernej Vičič, Michael Burnard, and Michael Mrissa. "A Blockchain Protocol for Real-Time Application Migration on the Edge." Sensors 23, no. 9 (May 2, 2023): 4448. http://dx.doi.org/10.3390/s23094448.

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The Internet of Things (IoT) is experiencing widespread adoption across industry sectors ranging from supply chain management to smart cities, buildings, and health monitoring. However, most software architectures for the IoT deployment rely on centralized cloud computing infrastructures to provide storage and computing power, as cloud providers have high economic incentives to organize their infrastructure into clusters. Despite these incentives, there has been a recent shift from centralized to decentralized architectures that harness the potential of edge devices, reduce network latency, and lower infrastructure costs to support IoT applications. This shift has resulted in new edge computing architectures, but many still rely on centralized solutions for managing applications. A truly decentralized approach would offer interesting properties required for IoT use cases. In this paper, we introduce a decentralized architecture tailored for large-scale deployments of peer-to-peer IoT sensor networks and capable of run-time application migration. We propose a leader election consensus protocol for permissioned distributed networks that only requires one series of messages in order to commit to a change. The solution combines a blockchain consensus protocol using Verifiable Delay Functions (VDF) to achieve decentralized randomness, fault tolerance, transparency, and no single point of failure. We validate our solution by testing and analyzing the performance of our reference implementation. Our results show that nodes are able to reach consensus consistently, and the VDF proofs can be used as an entropy pool for decentralized randomness. We show that our system can perform autonomous real-time application migrations. Finally, we conclude that the implementation is scalable by testing it on 100 consensus nodes running 200 applications.

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Jin, Wenquan, Yinan Xu, Yilin Dai, and Yihu Xu. "Blockchain-Based Continuous Knowledge Transfer in Decentralized Edge Computing Architecture." Electronics 12, no. 5 (February 27, 2023): 1154. http://dx.doi.org/10.3390/electronics12051154.

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Edge computing brings computational ability to network edges to enable low latency based on deploying devices close to the environment where the data is generated. Nevertheless, the limitation of size and energy consumption constrain the scalability and performance of edge device applications such as deep learning, although, cloud computing can be adopted to support high-performance tasks with centralized data collection. However, frequently communicating with a central cloud server brings potential risks to security and privacy issues by exposing data on the Internet. In this paper, we propose a secure continuous knowledge transfer approach to improve knowledge by collaborating with multiple edge devices in the decentralized edge computing architecture without a central server. Using blockchain, the knowledge integrity is maintained in the transfer process by recording the transaction information of each knowledge improvement and synchronizing the blockchain in each edge device. The knowledge is a trained deep-learning model that is derived by learning the local data. Using the local data of each edge device, the model is continuously trained to improve performance. Therefore, each improvement is recorded as the contribution of each edge device immutably in the decentralized edge computing architecture.

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Vaidya, Chandu. "Statistical Approach for Load Distribution in Decentralized Cloud Computing." HELIX 8, no. 5 (August 31, 2018): 3884–87. http://dx.doi.org/10.29042/2018-3884-3887.

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Yin, Hao, Dongchao Guo, Kai Wang, Zexun Jiang, Yongqiang Lyu, and Ju Xing. "Hyperconnected Network: A Decentralized Trusted Computing and Networking Paradigm." IEEE Network 32, no. 1 (January 2018): 112–17. http://dx.doi.org/10.1109/mnet.2018.1700172.

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Heiskanen, Pirja. "Decentralized method for computing Pareto solutions in multiparty negotiations." European Journal of Operational Research 117, no. 3 (September 1999): 578–90. http://dx.doi.org/10.1016/s0377-2217(98)00276-8.

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Zhang, Daqiang, Zhijun Yang, Hongyu Huang, and Qin Zou. "Decentralized Checking Context Inconsistency in Ubiquitous Mobile Computing Environments." Physics Procedia 25 (2012): 700–707. http://dx.doi.org/10.1016/j.phpro.2012.03.146.

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Zhang, Daqiang, Min Chen, Hongyu Huang, and Minyi Guo. "Decentralized checking of context inconsistency in pervasive computing environments." Journal of Supercomputing 64, no. 2 (August 9, 2011): 256–73. http://dx.doi.org/10.1007/s11227-011-0661-x.

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Darby, Paul J., and Nian-Feng Tzeng. "Decentralized QoS-Aware Checkpointing Arrangement in Mobile Grid Computing." IEEE Transactions on Mobile Computing 9, no. 8 (August 2010): 1173–86. http://dx.doi.org/10.1109/tmc.2010.80.

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Nair, Rajit, Syed Nasrullah Zafrullah, P. Vinayasree, Prabhdeep Singh, Musaddak Maher Abdul Zahra, Tripti Sharma, and Fardin Ahmadi. "Blockchain-Based Decentralized Cloud Solutions for Data Transfer." Computational Intelligence and Neuroscience 2022 (May 30, 2022): 1–12. http://dx.doi.org/10.1155/2022/8209854.

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Cloud computing has increased its service area and user experience above traditional platforms through virtualization and resource integration, resulting in substantial economic and societal advantages. Cloud computing is experiencing a significant security and trust dilemma, requiring a trust-enabled transaction environment. The typical cloud trust model is centralized, resulting in high maintenance costs, network congestion, and even single-point failure. Also, due to a lack of openness and traceability, trust rating findings are not universally acknowledged. “Blockchain is a novel, decentralised computing system. Its unique operational principles and record traceability assure the transaction data’s integrity, undeniability, and security. So, blockchain is ideal for building a distributed and decentralised trust infrastructure. This study addresses the difficulty of transferring data and related permission policies from the cloud to the distributed file systems (DFS). Our aims include moving the data files from the cloud to the distributed file system and developing a cloud policy. This study addresses the difficulty of transferring data and related permission policies from the cloud to the DFS. In DFS, no node is given the privilege, and storage of all the data is dependent on content-addressing. The data files are moved from Amazon S3 buckets to the interplanetary file system (IPFS). In DFS, no node is given the privilege, and storage of all the data is dependent on content-addressing.

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Froiz-Míguez, Iván, Paula Fraga-Lamas, and Tiago M. Fernández-Caramés. "Decentralized P2P Broker for M2M and IoT Applications." Proceedings 54, no. 1 (August 20, 2020): 24. http://dx.doi.org/10.3390/proceedings2020054024.

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The recent increase in the number of connected IoT devices, as well as the heterogeneity of the environments where they are deployed, has derived into the growth of the complexity of Machine-to-Machine (M2M) communication protocols and technologies. In addition, the hardware used by IoT devices has become more powerful and efficient. Such enhancements have made it possible to implement novel decentralized computing architectures like the ones based on edge computing, which offload part of the central server processing by using multiple distributed low-power nodes. In order to ease the deployment and synchronization of decentralized edge computing nodes, this paper describes an M2M distributed protocol based on Peer-to-Peer (P2P) communications that can be executed on low-power ARM devices. In addition, this paper proposes to make use of brokerless communications by using a distributed publication/subscription protocol. Thanks to the fact that information is stored in a distributed way among the nodes of the swarm and since each node can implement a specific access control system, the proposed system is able to make use of write access mechanisms and encryption for the stored data so that the rest of the nodes cannot access sensitive information. In order to test the feasibility of the proposed approach, a comparison with an Message-Queuing Telemetry Transport (MQTT) based architecture is performed in terms of latency, network consumption and performance.

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Wang, Jian, Yancong Wang, and Hongchang Ke. "Joint Optimization for MEC Computation Offloading and Resource Allocation in IoV Based on Deep Reinforcement Learning." Mobile Information Systems 2022 (August 13, 2022): 1–11. http://dx.doi.org/10.1155/2022/9230521.

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In the Internet of Vehicle (IoV), the limited computing capacity of vehicles hardly processes the intensive computation tasks locally. The computation tasks can be offloaded to multiaccess edge computing (MEC) servers for processing, where MEC provides the required computing capacity to the nearby vehicles. In this paper, we consider a scenario where there are cooperation and competition between vehicles, the offloading decision of any vehicle will affect the decisions of the others, and the computing resource allocation strategies by MEC will dynamically change. Therefore, we propose a joint optimization scheme for computation offloading decisions and computing resource allocation based on decentralized multiagent deep reinforcement learning. The proposed scheme learns the optimal actions to minimize the total weighted cost which is designed as the vehicles’ satisfaction based on the type of stochastic arrival tasks and dynamic interaction between MEC server and vehicles within different RSUs coverages. The numerical results show that the proposed algorithms based on decentralized multiagent deep deterministic policy gradient (DDPG) which is named De-DDPG can autonomously learn the optimal computation offloading and resource allocation policy without a priori knowledge and outperform the other three baseline algorithms in terms of the rewards.

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Nyamtiga, Sicato, Rathore, Sung, and Park. "Blockchain-Based Secure Storage Management with Edge Computing for IoT." Electronics 8, no. 8 (July 25, 2019): 828. http://dx.doi.org/10.3390/electronics8080828.

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As a core technology to manage decentralized systems, blockchain is gaining much popularity to deploy such applications as smart grid and healthcare systems. However, its utilization in resource-constrained mobile devices is limited due to high demands of resources and poor scalability with frequent-intensive transactions. Edge computing can be integrated to facilitate mobile devices in offloading their mining tasks to cloud resources. This integration ensures reliable access, distributed computation and untampered storage for scalable and secure transactions. It is imperative therefore that crucial issues of security, scalability and resources management be addressed to achieve successful integration. Studies have been conducted to explore suitable architectural requirements, and some researchers have applied the integration to deploy some specific applications. Despite these efforts, however, issues of anonymity, adaptability and integrity still need to be investigated further to attain a practical, secure decentralized data storage. We based our study on peer-to-peer and blockchain to achieve an Internet of Things (IoT) design supported by edge computing to acquire security and scalability levels needed for the integration. We investigated existing blockchain and associated technologies to discover solutions that address anonymity, integrity and adaptability issues for successful integration of blockchain in IoT systems. The discovered solutions were then incorporated in our conceptual design of the decentralized application prototype presented for secure storage of IoT data and transactions.

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He, Dong, Qingyu Xiong, Xuyang Zhang, Yunchuang Dai, and Ziyan Jiang. "A Decentralized, Flat-Structured Control System for Chiller Plants." Applied Sciences 9, no. 22 (November 10, 2019): 4811. http://dx.doi.org/10.3390/app9224811.

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This paper presents a novel control system for chiller plants that is decentralized and flat-structured. Each device in chiller plant system is fitted with a smart node. It is a smart agent, which collects, handles and sends out information to its neighbours. All the smart nodes form a network that can realize self-organization and self-recognition. Different kinds of control strategies can be converted into series of decentralized computing processes carried on by the smart nodes. The principle and mechanism of this decentralized, flat-structured control system for chiller plants are described in detail. Then a case study is presented to show how to build the decentralized, flat-structured control system actually. The measured data shows that the decentralized control method is energy efficiency. Moreover, it is much more flexible and scalable compared with the traditional centralized control method.

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Jia, Xudong, Ning Hu, Shi Yin, Yan Zhao, Chi Zhang, and Xinda Cheng. "A2 Chain: A Blockchain-Based Decentralized Authentication Scheme for 5G-Enabled IoT." Mobile Information Systems 2020 (December 21, 2020): 1–19. http://dx.doi.org/10.1155/2020/8889192.

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The fifth-generation mobile communication technology (5G) provides high-bandwidth and low-latency data channels for massive IoT terminals to access the core business network. At the same time, it also brings higher security threats and challenges. Terminal identity authentication is an important security mechanism to ensure the core business network; however, most of the existing solutions adopt a centralized authentication model. Once the number of authentication requests exceeds the processing capacity of the authentication center service, it will cause authentication request congestion or deadlock. The decentralized authentication model can effectively solve the above problems. This article proposes a decentralized IoT authentication scheme called A2 Chain. First, A2 Chain uses edge computing to decentralize the processing of authentication requests and eliminate the burden on authentication services and the network. Second, to implement cross-domain identity verification of IoT devices, A2 Chain uses blockchain, and sidechain technologies are used to securely share the identity verification information of IoT devices. Additionally, A2 Chain replaces public key infrastructure (PKI) algorithm with identity-based cryptography (IBC) algorithm to eliminate the management overhead caused by centralized authentication model.

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B, Shadaksharappa. "High Availability and Fault Tolerance in AWS." International Journal of Innovative Research in Information Security 09, no. 03 (June 23, 2023): 66–72. http://dx.doi.org/10.26562/ijiris.2023.v0903.03.

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With the increasing adoption of cloud computing, ensuring high availability and fault tolerance has become paramount for organizations. Amazon Web Services (AWS) offers a robust infrastructure for hosting applications, but it requires careful architectural design and implementation to achieve desired levels of availability and fault tolerance. This research paper explores two innovative concepts, namely Cloud Fractal and Decentralized Replication and Orchestration, and their application in achieving high availability and fault tolerance in AWS. We present a comprehensive analysis of these concepts and provide practical guidelines for their implementation in real-world scenarios. Our findings demonstrate the effectiveness of Cloud Fractal and Decentralized Replication and Orchestration in enhancing the reliability and resilience of AWS deployments. Keywords: Fault Isolation, High Availability, Load Balancing, Auto-scaling, Disaster Recovery, Data Replication, Backup and Restore, Fault Tolerance, Cloud Computing, Amazon Elastic Compute Cloud (EC2), Amazon Relational Database Service (RDS), Amazon Simple Storage Service (S3), AWS Elastic Load Balancer (ELB), Complexity, Operational Management, Cloud Fractal, AWS Lambda, Amazon SQS, Decentralized Replication and Orchestration (DOI).

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Wang, Xiaoying, Xiaojing Liu, Lihua Fan, and Xuhan Jia. "A Decentralized Virtual Machine Migration Approach of Data Centers for Cloud Computing." Mathematical Problems in Engineering 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/878542.

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As cloud computing offers services to lots of users worldwide, pervasive applications from customers are hosted by large-scale data centers. Upon such platforms, virtualization technology is employed to multiplex the underlying physical resources. Since the incoming loads of different application vary significantly, it is important and critical to manage the placement and resource allocation schemes of the virtual machines (VMs) in order to guarantee the quality of services. In this paper, we propose a decentralized virtual machine migration approach inside the data centers for cloud computing environments. The system models and power models are defined and described first. Then, we present the key steps of the decentralized mechanism, including the establishment of load vectors, load information collection, VM selection, and destination determination. A two-threshold decentralized migration algorithm is implemented to further save the energy consumption as well as keeping the quality of services. By examining the effect of our approach by performance evaluation experiments, the thresholds and other factors are analyzed and discussed. The results illustrate that the proposed approach can efficiently balance the loads across different physical nodes and also can lead to less power consumption of the entire system holistically.

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Sarridis, Ioannis, Vasiliki Gkatziaki, Emmanouil Krasanakis, Nikos Giatsoglou, Nikos Sarris, Symeon Papadopoulos, and Ioannis Kompatsiaris. "Helios.TALK: A decentralised messaging framework that preserves the privacy of users." Open Research Europe 2 (March 4, 2022): 29. http://dx.doi.org/10.12688/openreseurope.14421.1.

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Communication via digital means, such as mobile messaging applications (apps), plays an increasingly important role in everyday life. However, most messaging apps employ centralized computing principles that relinquish control of their users' personal data to social network platform providers. Decentralization has been proposed as an alternative that provides trustworthiness and data confidentiality, but this comes at expense of fewer provided features and non-intuitive user experience. To address this issue, we hereby present two interconnected decentralized messaging tools, developed in the scope of the HELIOS platform, which can support new decentralized social networks. The first tool is a framework that supports the development of context-aware decentralized messaging apps in mobile Android devices by organically tying together many of the platform's standalone decentralized operations. The second is a decentralized messaging app, called helios.TALK, that builds on the framework but accommodates additional design considerations from the perspective of end-users.

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Sarridis, Ioannis, Vasiliki Gkatziaki, Emmanouil Krasanakis, Nikos Giatsoglou, Nikos Sarris, Symeon Papadopoulos, and Ioannis Kompatsiaris. "Helios.TALK: A decentralised messaging framework that preserves the privacy of users." Open Research Europe 2 (October 18, 2023): 29. http://dx.doi.org/10.12688/openreseurope.14421.2.

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Communication via digital means, such as mobile messaging applications (apps), plays an increasingly important role in everyday life. However, most messaging apps employ centralized computing principles that relinquish control of their users’ personal data to social network platform providers. Decentralization has been proposed as an alternative that provides trustworthiness and data confidentiality, but this comes at expense of fewer provided features and non-intuitive user experience. To address this issue, we hereby present two interconnected decentralized messaging tools, developed in the scope of the HELIOS platform, which can support new decentralized social networks. The first tool is a framework that supports the development of context-aware decentralized messaging apps in mobile Android devices by organically tying together many of the platform’s standalone decentralized operations. The second is a decentralized messaging app, called helios.TALK, that builds on the framework but accommodates additional design considerations from the perspective of end-users.

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Chen, Hao, Yu Ye, Ming Xiao, Mikael Skoglund, and H. Vincent Poor. "Coded Stochastic ADMM for Decentralized Consensus Optimization With Edge Computing." IEEE Internet of Things Journal 8, no. 7 (April 1, 2021): 5360–73. http://dx.doi.org/10.1109/jiot.2021.3058116.

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Sangwan, Arun, Gaurav Kumar, and Sorabh Gupta. "To Convalesce Task Scheduling in a Decentralized Cloud Computing Environment." Review of Computer Engineering Research 3, no. 1 (2016): 25–34. http://dx.doi.org/10.18488/journal.76/2016.3.1/76.1.25.34.

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JIANG, Yan-hua. "Decentralized approach for metadata management in computing resource sharing platform." Journal of Computer Applications 31, no. 2 (April 6, 2011): 462–65. http://dx.doi.org/10.3724/sp.j.1087.2011.00462.

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Patil, Mohini Tanaji. "A Survey on Different Techniques Used in Decentralized Cloud Computing." International Journal of Science and Engineering Applications 5, no. 2 (March 19, 2016): 92–94. http://dx.doi.org/10.7753/ijsea0502.1007.

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Josilo, Sladana, and Gyorgy Dan. "Decentralized Algorithm for Randomized Task Allocation in Fog Computing Systems." IEEE/ACM Transactions on Networking 27, no. 1 (February 2019): 85–97. http://dx.doi.org/10.1109/tnet.2018.2880874.

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SHENG, Yiqiang, Jinlin WANG, Chaopeng LI, and Weining QI. "Max-Min-Degree Neural Network for Centralized-Decentralized Collaborative Computing." IEICE Transactions on Communications E99.B, no. 4 (2016): 841–48. http://dx.doi.org/10.1587/transcom.2015adp0013.

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Harjula, Erkki, Pekka Karhula, Johirul Islam, Teemu Leppanen, Ahsan Manzoor, Madhusanka Liyanage, Jagmohan Chauhan, Tanesh Kumar, Ijaz Ahmad, and Mika Ylianttila. "Decentralized Iot Edge Nanoservice Architecture for Future Gadget-Free Computing." IEEE Access 7 (2019): 119856–72. http://dx.doi.org/10.1109/access.2019.2936714.

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Qu, Youyang, Longxiang Gao, Tom H. Luan, Yong Xiang, Shui Yu, Bai Li, and Gavin Zheng. "Decentralized Privacy Using Blockchain-Enabled Federated Learning in Fog Computing." IEEE Internet of Things Journal 7, no. 6 (June 2020): 5171–83. http://dx.doi.org/10.1109/jiot.2020.2977383.

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Liu, Song, Xiong Wang, Longshuo Hui, and Weiguo Wu. "Blockchain-Based Decentralized Federated Learning Method in Edge Computing Environment." Applied Sciences 13, no. 3 (January 28, 2023): 1677. http://dx.doi.org/10.3390/app13031677.

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In recent years, federated learning has been able to provide an effective solution for data privacy protection, so it has been widely used in financial, medical, and other fields. However, traditional federated learning still suffers from single-point server failure, which is a frequent issue from the centralized server for global model aggregation. Additionally, it also lacks an incentive mechanism, which leads to the insufficient contribution of local devices to global model training. In this paper, we propose a blockchain-based decentralized federated learning method, named BD-FL, to solve these problems. BD-FL combines blockchain and edge computing techniques to build a decentralized federated learning system. An incentive mechanism is introduced to motivate local devices to actively participate in federated learning model training. In order to minimize the cost of model training, BD-FL designs a preference-based stable matching algorithm to bind local devices with appropriate edge servers, which can reduce communication overhead. In addition, we propose a reputation-based practical Byzantine fault tolerance (R-PBFT) algorithm to optimize the consensus process of global model training in the blockchain. Experiment results show that BD-FL effectively reduces the model training time by up to 34.9% compared with several baseline federated learning methods. The R-PBFT algorithm can improve the training efficiency of BD-FL by 12.2%.

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Karimi, Elham, Yuanzhu Chen, and Behzad Akbari. "Intelligent and Decentralized Resource Allocation in Vehicular Edge Computing Networks." IEEE Internet of Things Magazine 6, no. 4 (December 2023): 112–17. http://dx.doi.org/10.1109/iotm.001.2200268.

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K, Aswin. "DECENTRALIZED QUANTUM COMPILATION FRAMEWORK: EMPOWERING DISTRIBUTED QUANTUM COMPUTING THROUGH MODULARITY." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (May 5, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem32617.

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Quantum algorithms require large resources in terms of qubit number, much larger than those available with current NISQ processors. With the network and communication functionalities provided by the Quantum Internet, Distributed Quantum Computing (DQC) is considered as a scalable approach for increasing the number of available qubits for computational tasks. For DQC to be effective and efficient, a quantum compiler must find the best partitioning for the quantum algorithm and then perform smart remote operation scheduling to optimize EPR pair consumption. At the same time, the quantum compiler should also find the best local transformation for each partition. In this paper we present a modular quantum compilation framework for DQC that takes into account both network and device constraints and characteristics. We implemented and tested a quantum compiler based on the proposed framework with some circuits of interest, such as the VQE and QFT ones, considering different network topologies, with quantum processors characterized by heavy hexagon coupling maps. We also devised a strategy for remote scheduling that can exploit both TeleGate and TeleData operations and tested the impact of using either only TeleGates or both. The evaluation results show that TeleData operations may have a positive impact on the number of consumed EPR pairs, while choosing a more connected network topology helps reduce the number of layers dedicated to remote operations. Keywords— Distributed quantum computing (DQC), quantum compilation, quantum Internet

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Kratzke, Nane. "A Brief History of Cloud Application Architectures." Applied Sciences 8, no. 8 (August 14, 2018): 1368. http://dx.doi.org/10.3390/app8081368.

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This paper presents a review of cloud application architectures and its evolution. It reports observations being made during a research project that tackled the problem to transfer cloud applications between different cloud infrastructures. As a side effect, we learned a lot about commonalities and differences from plenty of different cloud applications which might be of value for cloud software engineers and architects. Throughout the research project, we analyzed industrial cloud standards, performed systematic mapping studies of cloud-native application-related research papers, did action research activities in cloud engineering projects, modeled a cloud application reference model, and performed software and domain-specific language engineering activities. Two primary (and sometimes overlooked) trends can be identified. First, cloud computing and its related application architecture evolution can be seen as a steady process to optimize resource utilization in cloud computing. Second, these resource utilization improvements resulted over time in an architectural evolution of how cloud applications are being built and deployed. A shift from monolithic service-oriented architectures (SOA), via independently deployable microservices towards so-called serverless architectures, is observable. In particular, serverless architectures are more decentralized and distributed, and make more intentional use of separately provided services. In other words, a decentralizing trend in cloud application architectures is observable that emphasizes decentralized architectures known from former peer-to-peer based approaches. This is astonishing because, with the rise of cloud computing (and its centralized service provisioning concept), the research interest in peer-to-peer based approaches (and its decentralizing philosophy) decreased. However, this seems to change. Cloud computing could head into the future of more decentralized and more meshed services.

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Srivastava, Prateek. "A Decentralized Cloud Firewall Framework with Resources Provisioning Cost Optimization." Mathematical Statistician and Engineering Applications 70, no. 1 (January 31, 2021): 164–72. http://dx.doi.org/10.17762/msea.v70i1.2296.

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A new flexible method for supplying more computer power in a shared media is called cloud computing. It offers a distributed paradigm based on self-evaluation methods to increase the system's processing power with less managerial worries. Clients, applications, platforms, servers, and infrastructures make up its components. This computing architecture provides end users with calculation skills as a computed service from the aforementioned components. Security management will lose importance when more devices and their integration become available. One needs to manage data, system, and confidentiality problems carefully since cloud users are growing daily. Therefore, in order to address protected access and integrity concerns in a cloud environment, new security firewall services must be deployed in addition to the current system. Numerous network-related issues, including load balancing, scheduling, traffic divergence, filtering, regulating the rate of arrival, instance management, and attack detection, make it difficult to implement firewalls for cloud computing. A centralised cloud firewall makes it very difficult to predict the response time. Consequently, a new line of work has been established for actually implementing the new firewall techniques for the cloud. In order to reduce the cost of ownership and operation, it also strives to achieve resource optimization-based provisions and guidelines.

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Journal articles on the topic 'Decentralized computing'

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