With the rapid advancement of edge computing and network function virtualization, it is promising to provide flexible and low-latency network services at the edge. However, due to the vulnerability of edge services and the volatility of edge computing system states, i.e., service request rates, failure rates, and resource prices, it is challenging to minimize the online service cost while providing the availability guarantee. This paper considers the problem of online virtual network function backup under availability constraints (OVBAC) for cost minimization in edge environments. We formulate the problem based on the characteristics of the volatility system states derived from real-world data and show the hardness of the formulated problem. We use an online backup deployment scheme named Drift-Plus-Penalty (DPP) with provable near-optimal performance for the AVBAC problem. In particular, DPP needs to solve an integer programming problem at the beginning of each time slot. We propose a dynamic programming-based algorithm that can optimally solve the problem in pseudo-polynomial time. Extensive real-world data-driven simulations demonstrate that DPP significantly outperforms popular baselines used in practice.
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Optimal Request Clustering for Link Reliability Guarantee in Wireless Networked Control
In wireless networked control systems, ensuring predictable communication link reliabilities among sensors, controllers, and actuators is critical. In such scenarios, different data gathered at the application layer of each sender require different packet delivery ratios (i.e., reliabilities). The lower layers try to accommodate these requests by first mapping each of them into a service level and then deliver the associated data packets to the receiver at the mapped service level. Due to resource constraints and maintenance overhead, the number of supported service levels is usually limited. An important question is then how to determine the set of service levels to maintain and how to map each request to an appropriate service level, such that the requested reliabilities are guaranteed and the total cost of mapping is minimized? We formally formulate this as an optimal request clustering problem since each service level acts as a cluster and can host multiple requests. In particular, we formulate the Migratory Clustering Problem and the Non-Migratory Clustering Problem, depending on whether a request can migrate from one service level to another after its initial assignment. We propose two optimal algorithms to solve both problems.
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- Award ID(s):
- 1647200
- NSF-PAR ID:
- 10039694
- Date Published:
- Journal Name:
- IEEE Wireless Communications and Networking Conference (WCNC), 2017
- Page Range / eLocation ID:
- 1 to 6
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/WCNC.2017.7925790
