λ-Augmented Tree for Robust Data Collection in Advanced Metering Infrastructure
Document Type
Article
Publication Date
1-1-2016
Abstract
Tree multicast configuration of smart meters (SMs) can maintain the connectivity and meet the latency requirements for the Advanced Metering Infrastructure (AMI). However, such topology is extremely weak as any single failure suffices to break its connectivity. On the other hand, the impact of a SM node failure can be more or less significant: a noncut SM node will have a limited local impact compared to a cut SM node that will break the network connectivity. In this work, we design a highly connected tree with a set of backup links to minimize the weakness of tree topology of SMs. A topology repair scheme is proposed to address the impact of a SM node failure on the connectivity of the augmented tree network. It relies on a loop detection scheme to define the criticality of a SM node and specifically targets cut SM node by selecting backup parent SM to cover its children. Detailed algorithms to create such AMI tree and related theoretical and complexity analysis are provided with insightful simulation results: sufficient redundancy is provided to alleviate data loss at the cost of signaling overhead. It is however observed that biconnected tree provides the best compromise between the two entities.
Recommended Citation
Kamto, Joseph; Qian, Lijun; Li, Wei; and Han, Zhu, "λ-Augmented Tree for Robust Data Collection in Advanced Metering Infrastructure" (2016). Faculty Publications. 250.
https://digitalscholarship.tsu.edu/facpubs/250