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Consistency-Aware Multi-Server Network Design for Delay-Sensitive Applications Under Server Failures
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DOI：10.1109/TNSM.2026.3669840.png)
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Abstract
En 中文
Real-time applications require low latency and event order guarantees. Distributed server processing is effective for this purpose, and data consistency between servers is crucial. Although existing models in previous work handle data consistency, they do not address server failures. This paper proposes a server allocation model for a consistency-aware multi-server network for delay-sensitive applications with preventive start-time optimization (PSO) under single-server failures. The proposed model considers data consistency between servers and handles single-server failures with PSO. PSO determines the assignment to minimize the worst-case delay over all possible failure scenarios while avoiding service disruption for users connected to non-failed servers. We formulate the proposed model as an integer linear programming (ILP) problem. The decision version of the server allocation problem is proven to be NP-complete, and it becomes difficult to solve in a practical time when the problem size is large. We develop two polynomial-time approximation algorithms with theoretical performance analysis. Numerical results show that the proposed model outperforms start-time optimization in terms of the largest total delay and run-time optimization in terms of avoiding instability. The results also show that the faster of our two developed algorithms achieves a speedup ranging from $2.26 \times 10^{3}$ to $4.37 \times 10^{6}$ times compared to the ILP approach, while the maximum delay is, on average, only 1.029 times the optimal value. The results indicate that the speedup effect becomes more significant as the number of users and servers increases.
Keywords:
Server allocation
data consistency
preventive start-time optimization
server failure
approximation algorithm
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