Jul 2026· International Conference on Computer Communications and Networks· pp. 1-9· 0 citations· 16 references
Abstract
Priority scheduling techniques aim to schedule tasks with higher priority and tighter deadlines to be executed before other tasks. However, traditional blockchain systems do not work well with priority scheduling due to issues regarding consensus mechanisms, throughput, and scalability. In this work, we propose three transaction scheduling schemes which employ a fee-based model to differentiate priority levels of transactions and select transactions for validation and inclusion based on criteria other than the order of arrival. The Priority-Based Scheduling scheme focuses on the priority level of individual transactions, the Contract-Based Scheduling scheme emphasizes the satisfaction of more customer contracts, whereas the Latency-Based Scheduling scheme prioritizes transactions with closer deadlines when bursts of transactions overwhelm the blockchain network. We implement prototypes of our transaction scheduling schemes in a private Algorand-inspired simulation and evaluate their performance by testing them under scenarios representing different transaction distribution ratios. The results show that the three transaction scheduling schemes outperform the baseline in which no scheduling is applied, and each scheme performs best in the transaction distribution scenario it is designed to handle.
The openness and disaggregation of Open radio access network (O-RAN) facilitate resource sharing and coordination across networks, creating new demands for efficient and trustworthy cross-operator scheduling. However, such scheduling is beyond the scope and capability of conventional proportional fair scheduling (PFS), which lacks mechanisms for establishing trust among independent operators. To fulfill this gap, we propose the blockchain-based proportional fair scheduling (BC-PFS) that enables trustworthy inter-network coordination and resource pooling across operators in O-RAN. Specifically, we design four core smart contracts including registration, status reporting, scheduling, and settlement contracts with corresponding Solidity implementations to ensure trustworthy on-chain execution. Theoretically, to evaluate the BC-PFS performance, we develop an analytical framework to derive the user average throughput via both probabilistic and ordinary differential equation (ODE) approaches, and provide a simplified closed-form solution. Based on the above performance assessment, we quantify the pooling effect in O-RAN achieved through trustworthy cross-operator collaboration via BC-PFS, and point out that this effect grows monotonically in both the numbers of operator networks and users. Simulations validate the theoretical analysis and show the performance of the BC-PFS in O-RAN.
Kun Huang, Xintong Ling, Mei-Ning Wu et al.· 0 citations
Existing sharded blockchain systems suffer from excessive cross-shard communication overhead and workload imbalance. Although state-of-the-art account allocation schemes partially alleviate these problems, they still fail to simultaneously achieve effective cross-shard transaction reduction and balanced workload distribution, while also lacking adaptability to dynamic workloads. In particular, current methods lack mechanisms for efficient incremental allocation of newly joined accounts and cannot dynamically adjust workloads during surges, resulting in performance degradation until the next account allocation occurs. To address these limitations, we propose Mecury, the first scheme to realize account allocation and scheduling that span entire blockchain epochs. We propose a Fine-Grained Label Propagation Algorithm combined with a Workload-Aware Incremental Allocation Algorithm to achieve high-quality allocation of both historical and newly joined accounts. Furthermore, Mecury introduces an account proxy mechanism equipped with a dynamic proxy algorithm that reduces cross-shard transactions by establishing temporary proxy relationships, thereby adaptively mitigating workload surges. In addition, we design a secure cross-shard state migration protocol to ensure the liveness and consistency of state migration between accounts involved in the proxy relationship. By integrating these mechanisms, Mecury effectively addresses the challenges of excessive cross-shard transactions and workload imbalance inherent in sharded blockchains during consensus. Experimental evaluations on real Ethereum data demonstrate that Mecury consistently delivers superior performance, achieving up to 72% higher throughput and 53% lower latency compared to state-of-the-art baselines.
Zitong Zhang, Hao-Xiang Han, Chao-Ming Shi et al.· IEEE Transactions on Network...· 0 citations
The proposed OIBTO framework employs a lightweight Proof-of-Authority consensus within a two-tier architecture consisting of a vehicle layer and an edge layer, and proposes an Improved Starfish Optimization Algorithm (ISFOA) that utilizes chaotic mapping and genetic mutation to optimize offloading decisions and task partitioning ratios, aiming to minimize a priority-weighted combination of latency and energy consumption.
A web-based expert system designed to support the selection of blockchain consensus mechanisms according to specific user-defined operational requirements, which contributes a transparent and extensible decision-support framework intended to simplify architectural planning and management of blockchain-based distributed systems.
Ivica Lukić, Nikola Ramčić, Iván Ivkovic et al.· Network· 0 citations
Blockchain is an efficient method to manage and secure data, but scalability remains a limitation. The proposed work concentrates on a novel consensus algorithm, Proof of Useful Work-Authorization-Storage Availability. It underlines the challenges of scalability and trust issues on blockchain-based smart contracts. The primary step in the proposed technique is to verify authorization by the hash code of the preceding block to generate a digital signature. After information is legitimized, check whether enough storage space is available or not. Transactions are recorded to a block only after validation, and if there is enough storage capacity. Finally, a transaction is available in a block only after it has been mined. To measure the proposed consensus performance in terms of energy consumption, latency, and transaction throughput, the Python and Solidity programming languages are used. The proposed work reduced computational energy by 39% and had a 17% improvement in transactional through-put, followed by limiting the network’s latency by 49% when compared with the proof of useful work consensus algorithm. This proves that the improved consensus gave clarity on how to scale without compromising security or decentralization. The contribution of this work is useful when efficient node selection is in a consensus layer.
Kolli Lalitha Kumari, P. Kumari· Sigma Journal of Engineering...· 0 citations
Distributed consensus algorithms are the core mechanism for ensuring data consistency and fault tolerance in distributed systems. Their evolution, from classical algorithms like Paxos and Raft to blockchain, reflects the diverse requirements for consistency, security, and performance in different application scenarios. This article analyzes the classification system of distributed consensus algorithms and divides them into two major categories based on fault models: Byzantine fault-tolerant and non-Byzantine fault-tolerant. On this basis, the system systematically organized the processes and characteristics of Paxos, Raft, Practical Byzantine Fault Tolerance (PBFT), and blockchain consensus algorithms, and performed a comparative analysis of two key performance indicators: throughput and consensus latency. Research has found that as the number of nodes increases, the performance of the traditional PBFT algorithm decreases significantly, while the Byzantine Fault Tolerant (TBFT) algorithm shows better scalability in both throughput and latency. Finally, this article combines the characteristics of various algorithms, summarizes their applicable scenarios, and provides theoretical basis and practical reference for the selection of consensus algorithms in distributed systems.
Y. Rao· Mathematical Modeling and Al...· 0 citations
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