计算机科学
分布式计算
服务质量
弹性(材料科学)
编配
切片
多租户技术
移动边缘计算
启发式
计算机网络
服务器
软件
视觉艺术
人工智能
艺术
软件即服务
万维网
程序设计语言
软件开发
音乐剧
物理
热力学
作者
Dimitrios Michael Manias,Ibrahim Shaer,Joe Naoum‐Sawaya,Abdallah Shami
出处
期刊:IEEE Transactions on Network and Service Management
[Institute of Electrical and Electronics Engineers]
日期:2023-07-07
卷期号:21 (1): 187-199
被引量:1
标识
DOI:10.1109/tnsm.2023.3293027
摘要
With the rapid development and incoming implementation of 5G networks, many use cases, such as Intelligent Transportation Systems (ITS), are being realized. Utilizing networking technologies, including Network Function Virtualization and Mobile Edge Computing, along with 5G network slicing, the Next-Generation Service Placement Problem (NGSPP) is gaining significant attention due to the criticality of its services and its resource-constrained network nodes. The placement of services on Next-Generation (NG) networks has inherent challenges, mainly ultra-low latency requirements and the complexity of NG network management and orchestration. A candidate solution to the NGSPP should provide a placement that adheres to the strict Quality of Service (QoS) requirements. This work presents the formulation of a robust optimization problem that optimizes the high-availability placement of applications in resource-constrained and multi-tenant NG networks, which complies with QoS requirements and is capable of protecting the performance of the solution under adverse conditions. Finally, a set of hierarchical clustering-based heuristic algorithms, which reduce the time-complexity of the solution are proposed. Results demonstrate that formulating the robust solution is a proactive method of injecting resilience into the system and can preserve performance across various levels of system uncertainty.
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