λ-augmented tree for robust data collection in Advanced Metering Infrastructure
- Prairie View A&M Univ., Prairie View, TX (United States)
- Texas Southern Univ., Houston, TX (United States)
- Univ. of Houston, Houston, TX (United States)
In this study, 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.
- Research Organization:
- Prairie View A&M Univ., Prairie View, TX (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA); National Science Foundation (NSF)
- Grant/Contract Number:
- NSF-1238859; FA8750-15-2-0119
- OSTI ID:
- 1258754
- Journal Information:
- International Journal of Distributed Sensor Networks (Online), Vol. 2016; ISSN 1550-1477
- Publisher:
- HindawiCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
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