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1. Adaptive Sharding in Untrusted Environments

   https://doi.org/10.1145/3769756  

   Mehta, Bhavana; Baghel, Nupur; Amiri, Mohammad Javad; Loo, Boon Thau; Marcus, Ryan (December 2025, Proceedings of the ACM on Management of Data)

   Distributed data management systems employ data sharding techniques to achieve scalability. Traditional sharding approaches typically operate under the assumption of a trusted environment, where nodes may crash,but do not act adversarially. In untrustworthy environments, however, this assumption is no longer valid. This paper presents Marlin,an adaptive scalable data management system specifically designed for untrustworthy environments. Marlinleverages data sharding to enhance scalability while dynamically redistributing data across clusters to adapt to dynamic workloads. We propose two architectures: a centralized architecture serving as a baseline, which employs hypergraph partitioning within a trusted administrative domain, and a decentralized architecture that eliminates the need for such a trusted domain by managing shards across nodes in a decentralized manner. Both architectures utilize real-time monitoring and adaptive algorithms to dynamically adjust sharding in response to workload characteristics and adversarial conditions. Experimental results show that Marlinmaintain consistent performance under diverse dynamic scenarios in untrustworthy environments by continuously optimizing shard distributions. 

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2. Blockumulus: A Scalable Framework for Smart Contracts on the Cloud

   https://doi.org/10.1109/ICDCS51616.2021.00064  

   Ivanov, Nikolay; Yan, Qiben; Wang, Qingyang (July 2021, 2021 IEEE 41st International Conference on Distributed Computing Systems (ICDCS))

   Public blockchains have spurred the growing popularity of decentralized transactions and smart contracts, especially on the financial market. However, public blockchains exhibit their limitations on the transaction throughput, storage availability, and compute capacity. To avoid transaction gridlock, public blockchains impose large fees and per-block resource limits, making it difficult to accommodate the ever-growing high transaction demand. Previous research endeavors to improve the scalability and performance of blockchain through various technologies, such as side-chaining, sharding, secured off-chain computation, communication network optimizations, and efficient consensus protocols. However, these approaches have not attained a widespread adoption due to their inability in delivering a cloud-like performance, in terms of the scalability in transaction throughput, storage, and compute capacity. In this work, we determine that the major obstacle to public blockchain scalability is their underlying unstructured P2P networks. We further show that a centralized network can support the deployment of decentralized smart contracts. We propose a novel approach for achieving scalable decentralization: instead of trying to make blockchain scalable, we deliver decentralization to already scalable cloud by using an Ethereum smart contract. We introduce Blockumulus, a framework that can deploy decentralized cloud smart contract environments using a novel technique called overlay consensus. Through experiments, we demonstrate that Blockumulus is scalable in all three dimensions: computation, data storage, and transaction throughput. Besides eliminating the current code execution and storage restrictions, Blockumulus delivers a transaction latency between 2 and 5 seconds under normal load. Moreover, the stress test of our prototype reveals the ability to execute 20,000 simultaneous transactions under 26 seconds, which is on par with the average throughput of worldwide credit card transactions. 

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3. A Game Theoretical Analysis of Non-Linear Blockchain System

   https://doi.org/10.5555/3463952.3463995  

   Chen, L.; Xu, L.; Gao, Z.; Sunny, A.; Kasichainula, K.; Shi, W. (May 2021, International Conference on Autonomous Agents and MultiAgent Systems)

   null (Ed.)

   Recent advances in the blockchain research have been made in two important directions. One is refined resilience analysis utilizing game theory to study the consequences of selfish behavior of users (miners), and the other is the extension from a linear (chain) structure to a non-linear (graphical) structure for performance improvements, such as IOTA and Graphcoin. The first question that comes to mind is what improvements that a blockchain system would see by leveraging these new advances. In this paper, we consider three major properties for a blockchain system: α-partial verification, scalability, and finality-duration. We establish a formal framework and prove that no blockchain system can achieve ?-partial verification for any fixed constant ?, high scalability, and low finality-duration simultaneously. We observe that classical blockchain systems like Bitcoin achieves full verification (α=1) and low finality-duration, Ethereum 2.0 Sharding achieves low finality-duration and high scalability. We are interested in whether it is possible to partially satisfy the three properties. 

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4. Auroch: Auction based Multipath Routing for Payment Channel Networks

   Ababneh, Mohammed; Kolachala Kartick; Vishwanathan, Roopa (July 2024, ACM Asia Conference on Computer and Communications Security (ACM AsiaCCS))

   The Bitcoin blockchain scalability problem has inspired several offchain solutions for enabling cryptocurrency transactions, of which Layer-2 systems such as payment channel networks (PCNs) have emerged as a frontrunner. PCNs allow for path-based transactions between users without the need to access the blockchain. These path-based transactions are possible only if a suitable path exists from the sender of a payment to the receiver. In this paper, we propose Auroch, a distributed auction-based pathfinding and routing protocol that takes into account the routing fees charged by nodes along a path. Unlike other routing protocols proposed for PCNs, Auroch takes routing fees into consideration. Auroch maximizes the profit that can be achieved by an intermediate node at the same time minimizing the overall payment cost for the sender. 

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5. A Scalable Blockchain Framework for Secure Data and Computational Resource Management in SDN

   https://doi.org/10.1109/GCWkshp64532.2024.11100329  

   Das, Debashis; Landrum, La Chiara; Chatterjee, Pushpita; Ghosh, Uttam (December 2024, IEEE)

   The rapid evolution of Software-Defined Networking (SDN) has transformed network management by decoupling the control and data planes. It provides centralized control, enhanced flexibility, and programmability of network management services. However, this centralized control introduces security vulnerabilities and challenges related to data integrity, unauthorized access, and resource management. In addition, it brings forth significant challenges in secure and scalable data storage and computational resource management. These challenges are further increased by the need for real-time processing and the ever-increasing volume of data. To address these challenges, this paper presents a scalable blockchain-based framework for security and computational resource management in SDN architectures. The proposed framework ensures decentralized and tamper-resistant data handling and utilizes smart contracts for automated resource allocation. Due to the need for advanced security and scalability in SDN networks, this work incorporates sharding to improve parallel processing capabilities. The performance of sharded versus non-sharded blockchain systems under various network conditions is evaluated. Our findings demonstrate that the sharded blockchain model enhances scalability and throughput with robust security and fault tolerance. The framework is also assessed for its performance, scalability, and security to enhance SDN resilience against data breaches, malicious activities, and inefficient resource distribution. 

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