Decentralized storage of data is one of the typical applications in the blockchain network. However, most of the existing works neglected the storage balancing problem in the blockchain network, which has an immediate impact on the availability and stability of the network. Therefore, this paper proposes a storage balancing problem for non-local data storage in the blockchain network and proves that the problem is non-deterministic polynomial (NP)-hard. The criterion of the storage balance is established by a balanced coefficient in the proposed scheme. A heuristic matching algorithm (HMA), a genetic algorithm (GA) and a tabu search algorithm (TSA) are customized to solve the problem of imbalanced storage formalized in this paper. Compared with our previous algorithm fast matching algorithm (FMA), experimental results demonstrate that HMA achieves better performance in terms of accuracy, computation overhead and storage overhead. Specifically, the computation overhead of HMA is lower than that of FMA by 84.45% on average, whereas the storage overhead of HMA is lower than that of FMA by 32.26% on average. By using the initial solution of HMA, TSA achieves the highest accuracy among GA, TSA and moth-flame optimization (MFO). Meanwhile, by using the initial solution of FMA, TSA achieves the highest accuracy among GA, TSA and MFO.

中文翻译：

---

区块链网络中外包数据存储负载均衡的高效算法

数据的分散存储是区块链网络中的典型应用之一。但是，大多数现有工作都忽略了区块链网络中的存储平衡问题，这直接影响了网络的可用性和稳定性。因此，本文提出了区块链网络中非本地数据存储的存储平衡问题，并证明该问题是非确定性多项式（NP）-hard的。在所提出的方案中，通过平衡系数来建立存储平衡的标准。针对启发式匹配算法（HMA），遗传算法（GA）和禁忌搜索算法（TSA）进行了定制，以解决本文中形式化的存储不平衡问题。与我们之前的算法快速匹配算法（FMA）相比，实验结果表明，HMA在准确性，计算开销和存储开销方面都具有更好的性能。具体而言，HMA的计算开销平均比FMA低84.45％，而HMA的存储开销比FMA平均低32.26％。通过使用HMA的初始解决方案，TSA在GA，TSA和飞蛾优化（MFO）中达到了最高的准确性。同时，通过使用FMA的初始解决方案，TSA在GA，TSA和MFO中达到了最高的精度。TSA在GA，TSA和飞蛾优化（MFO）中达到了最高的准确性。同时，通过使用FMA的初始解决方案，TSA在GA，TSA和MFO中达到了最高的精度。TSA在GA，TSA和飞蛾优化（MFO）中达到了最高的准确性。同时，通过使用FMA的初始解决方案，TSA在GA，TSA和MFO中达到了最高的精度。