Abstract
Advanced Metering Infrastructure (AMI) is a system that measures, collects, and analyzes information by communicating with metering devices such as electric meters, gas meters, temperature meters, and water meters, either on request or on a schedule. The Advanced Metering Infrastructure consists of a collection of Neighborhood Area Networks (NANs) which include smart, wireless-enabled mesh-connected meters or sensor nodes. Each NAN is controlled by a gateway or Access Point (AP). These devices in turn are usually mesh-connected using wireless or wire-line backhaul links to a server or servers. Because of the sheer number of meters or sensor nodes involved in AMI applications, it is imperative that the overall network is optimized for cost, power, and ease of operations including network management, provisioning, etc. This contribution develops an elegant graph-theoretic approach for optimizing the cost of an AMI by maximizing the ratio of the number of sensors nodes (number of meters) in a NAN to that of gateways or APs. A MATLAB program has been implemented to automate our approach which can deal with random and complex NAN topologies.
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