# A Power Planning Algorithm Based on RPL for AMI Wireless Sensor Networks
## 1 Introduction  
Advanced Metering Infrastructure (AMI) is an architecture for two-way communication between smart utility meters and utility companies. The goal of AMI in the smart grid is to provide utility companies with real-time data about power consumption and allow customers to make informed choices about energy usage based on the price at the time of use. The smart grid includes many other features in addition to measuring energy consumption. The AMI network can provide bidirectional communication for services like distributed power generation, demand side management for customer load control in the customer's premises, and disconnections/re-connections of users due non-payment, among others. An important part of the AMI is communication in the neighborhood area, which usually involves a lot of communication nodes deployed in a large and complex geographical area. Accordingly, the communication network has to cover all metering devices, providing connections to all nodes. Considering the requirements of complexity and scalability of AMI, it is well accepted that wireless communication offers a larger degree of freedom for information collection and actuation over metering devices. In this study, we refer to an AMI network as the wireless sensor network that provides two-way communication for metering devices in the neighborhood area of the smart grid. The AMI network is structured in the sense that the positions of its nodes are fixed and known. Communicating nodes deployed in the AMI network have limited resources, that is, they use micro-controllers with low processing power and limited memory capacity. In addition, they are powered by the electric grid, which implies that there are not considerable concerns about power consumption, which could bea problem for battery-powered devices. Although some countries define in their local regulations the maximum power that is available to smart meters and connected communication devices, the defined limits are sufficient for most cases. However, as in most wireless sensor networks, devices are interconnected by unreliable links of low-bandwidth. These requirements are considered by the Internet Engineering Task Force (IETF) in the standardization of the routing protocol for low power and lossy networks (RPL) [1], which propose a routing protocol compatible with IPv6. Because RPL is designed for lossy networks, it is being considered as an important option for AMI network deployment [2; 3; 4; 5; 6]. As it operates in the unlicensed 915 MHz band, interferences from external devices may be present. However, the RPL is designed to react to changes in transmission conditions, and it is capable of mitigating possible interference problems coming from other electronic devices. RPL builds a routing topology formed by one or more destination oriented acyclic graphs (DODAG). Each DODAG is rooted in a single destination, usually representing a node that performs a connection to a back-haul. A DODAG differs from a traditional tree because it permits a node to have more than one parent in the direction of the root. RPL uses a \"slow\" proactive process to construct and maintain a routing topology, and a reactive and dynamic process to resolve route inconsistencies [7; 8; 9]. RPL uses the \"trickle algorithm\" [10] that determines that, in steady state, the protocol control messages are sent at a slow rate, but can be quickly increased to solve inconsistencies. The standard introduces the concept of RPL instance to allow different routing criteria to be considered on the same network. An RPL instance has an objective function that defines how the routing metric selects the parents of a node in a DODAG. The objective function computes a rank value, which represents the distance from the node up to the root with respect to a given metric. The expected transmission count (ETX) [4] is one of the most relevant metrics in wireless networks because it dynamically evaluates the quality of the communication link perceived by each node.