Sasan Zeinab, Khorsandi Siavash
Computer Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.
Sci Rep. 2025 Jul 2;15(1):22987. doi: 10.1038/s41598-025-06521-9.
Next-generation networks must address challenges such as exponential user growth, escalating traffic demands, and the proliferation of diverse services requiring both high data rates and ultra-low latency. Network slicing has emerged as a critical solution, enabling resource isolation to improve service efficiency. While traditional hard slicing ensures strict resource partitioning, it often results in significant underutilization. To mitigate this limitation, soft slicing allows dynamic resource sharing across slices, improving overall utilization. However, this approach introduces challenges, including potential violations of Quality of Service (QoS) guarantees and reductions in allocated resources compared to initial provisions. This paper presents a comprehensive soft slicing framework that addresses these key challenges by (1) ensuring user-level QoS guarantees, (2) incorporating slice dissatisfaction into the optimization model, (3) implementing a holistic resource management strategy, and (4) supporting hybrid 6G use cases. The problem is formulated as a Mixed Integer Linear Programming (MILP) model, aiming to maximize network utilization while minimizing slice dissatisfaction. Given the NP-hard nature of the problem, we propose the Heuristic Resource Allocation for Soft Slicing (HRASS) algorithm, which achieves near-optimal performance with significantly reduced computational complexity. Experimental results demonstrate that HRASS effectively improves resource utilization while mitigating the limitations of hard slicing.
下一代网络必须应对诸如用户呈指数级增长、流量需求不断攀升以及需要高数据速率和超低延迟的各种服务激增等挑战。网络切片已成为一种关键解决方案，可实现资源隔离以提高服务效率。虽然传统的硬切片可确保严格的资源划分，但往往会导致严重的资源利用率低下。为了缓解这一限制，软切片允许跨切片进行动态资源共享，从而提高整体利用率。然而，这种方法带来了一些挑战，包括可能违反服务质量（QoS）保证以及与初始配置相比分配资源减少。本文提出了一个全面的软切片框架，通过（1）确保用户级QoS保证，（2）将切片不满纳入优化模型，（3）实施整体资源管理策略，以及（4）支持混合6G用例来应对这些关键挑战。该问题被表述为一个混合整数线性规划（MILP）模型，旨在在最小化切片不满的同时最大化网络利用率。鉴于该问题的NP难性质，我们提出了软切片启发式资源分配（HRASS）算法，该算法以显著降低的计算复杂度实现了接近最优的性能。实验结果表明，HRASS有效地提高了资源利用率，同时缓解了硬切片的局限性。
