Cost optimization of wireless-enabled metering infrastructures

• US 8,619,657 B2
• Filed: 05/20/2012
• Issued: 12/31/2013
• Est. Priority Date: 05/20/2011
• Status: Expired due to Fees

• Current Assignee: Arnab Das, Santanu Das
• Original Assignee: Arnab Das, Santanu Das
• Inventors: Das, Arnab, Das, Santanu
• Primary Examiner(s): O CONNOR, BRIAN T
• Application Number:
  US13/476,013
• Publication Number:
  US 20130107761A1
• Time in Patent Office: 590 Days
• Field of Search: 370/252, 370/256, 370/311, 370/318, 370/328, 370/331, 370/338
• US Class Current: 370/311
• CPC Class Codes: H04W 24/02 Arrangements for optimising operational condition
• CPC Class Codes: H04W 4/38 for collecting sensor information
• CPC Class Codes: H04W 84/18 Self-organising networks, e.g. ad-hoc networks or sensor networks

Abstract

Embodiments of the present disclosure include a system for managing cost in a wireless enabled advanced metering infrastructure (AMI). The system includes a remote server, a wide area network, and an access point device. The system further includes wireless enabled meters coupled to each other and to the access point through a neighborhood area network (NAN). The system includes datasinks. Each datasink is a wireless enabled meter capable of being a data coordinator and capable of receiving metering information from the sensors, processing metering information, and transmitting metering information to the access point. Moreover, each wireless enabled meter is capable of being a routing node and an endpoint node. Also, a first set of wireless enabled meters are configured to be routing nodes and a second set of wireless enabled meters are configured to be endpoint nodes based on a graph theoretic algorithm to reduce the cost of the AMI.

Claims

1. A system for managing cost in a wireless enabled advanced metering infrastructure, the system comprising:

(a) a remote server

(b) a wide area network coupled to the remote server;

(c) at least one access point device coupled to the remote server through the wide area network,

(d) at least one neighborhood area network that includes one or more wireless enabled meters coupled to each other and to the access point;

(e) one or more datasinks wherein each datasink is configured to being a data coordinator and configured to receiving metering information from the one or more wireless enabled meters, processing metering information, and transmitting metering information to at least one access point;

(i) wherein each wireless enabled meter is configured to be a node, wherein the node is selected from the group consisting of a routing node and an endpoint node;

(ii) wherein a first set of wireless enabled meters are configured to be one or more routing nodes and a second set of wireless enabled meters are configured to be one or more end point nodes based on a graph theoretic algorithm and to configure each wireless enabled meter to a minimum power level based on a bridging distance to a neighboring meter thereby reducing overall the cost of the wireless enabled advanced metering infrastructure;

(f) wherein implementing the graph theoretic algorithm results in generating a spanning tree that increases the ratio of wireless enabled meters to access points in a neighborhood area network.

2. The system of claim 1, wherein the graph theoretic algorithm includes:

selecting a link wherein the link couples a node pair and a node can be selected from the group consisting of an access point, datasink, routing node, or endpoint node;

mapping the distance between the selected node pairs to a corresponding bridging power level wherein the bridging power level between a node pair is designated as a weight of the link;

ranking the weighted links for each corresponding node pair in nondecreasing order of weight;

selecting a next least weighted link and corresponding node pair as part of a subgraph;

repeating the selecting of the next least weighted link and corresponding node pair as part of the subgraph until every node is part of the subgraph and generates a spanning tree used to configure routing information for the neighborhood area network.

3. The system of claim 1, wherein the remote server uses the graph theoretic algorithm to configure, over the wide area network and through the access point, the first set of wireless enabled meters as routing nodes and the second set of wireless enabled meters as end point nodes in a neighborhood network.

4. The system of claim 1, wherein the datasink:

(i) receives metering information corresponding to each of the one or more routing nodes and one or more end point nodes; and

(ii) processes the meter information to generate sub-network status information and transmits the sub-network status information to the access point.

5. The system of claim 1, wherein the access point transmits the metering information from one or more wireless enabled meters and the sub-network status information from one or more datasinks to the remote server over the wide area network.

6. The system of claim 5, wherein the remote server:

processes the metering information for a subset of the one or more routing nodes and one or more end point nodes and the network and sub-network status information;

detects a faulty wireless enabled meter and modifies the configuration of the one or more routing nodes and one or more end point nodes based on the metering information and network and sub-network status information to generate an updated spanning tree used to reconfigure routing information for the neighborhood area network.

7. The system of claim 1, the system further comprising a remote computing device coupled to the access point and the remote server over the wide area network, the remote computing device having a user interface configured to receiving user input and retrieving and displaying metering information and network and sub-network status information.

8. The system of claim 7, wherein the remote computing device is configured to modify a configuration of a subset of neighborhood area networks based on user input and the metering information and network and sub-network status information.

9. The system of claim 1, wherein the graph theoretic algorithm is Kruskal'"'"'s algorithm which generates a spanning tree for configuring the routing information in the neighborhood area network.

10. The system of claim 1, wherein placement of one or more dummy nodes in the neighborhood area network maximizes a ratio of wireless enabled meters to access points wherein the dummy nodes are placed between two wireless enabled meters that have distance exceeding a predetermined threshold.

11. The system of claim 1, location of the one or more access points corresponds to location of one or more nodes as a result of selection by the graph theoretic algorithm.

12. The system of claim 1 wherein a datasink function is implemented by a node selected from the group consisting of a wireless enabled meter and an access point.

13. A system for managing cost in a wireless enabled advanced metering infrastructure, the system comprising:

(a) a remote server

(b) a wide area network coupled to the remote server;

(c) at least one access point device coupled to the remote server through the wide area network,

(d) one or more wireless enabled meters coupled to each other and to the access point through a neighborhood area network;

(e) one or more datasinks wherein each datasink is a wireless enabled meter configured to being a data coordinator and configured to receiving metering information from the one or more wireless enabled meters processing metering information, and transmitting metering information to at least access point;

(i) wherein each wireless enabled meter is configured to be a node, wherein the node is selected from a group consisting of a routing node and an endpoint node;

(ii) wherein a first set of wireless enabled meters are configured to be one or more routing nodes and a second set of wireless enabled meters are configured to be one or more end point nodes based on a graph theoretic algorithm and to configure each wireless enabled meter to a minimum power level based on a bridging distance to a neighboring meter thereby reducing overall cost of the wireless enabled advanced metering infrastructure;

(f) wherein graph theoretic algorithm results in generating a spanning tree that increases the ratio of wireless enabled meters to access points in a neighborhood area network;

(g) wherein one more neighborhood area networks are bridged by one or more dummy nodes to increase ratio of wireless enabled meters to access points.

14. The system of claim 13, wherein the access point device includes:

a processor;

a memory coupled to the processor;

one or more communication interfaces coupled to the processor;

wherein the device (i) stores the metering information and the network information in the memory;

(ii) receives metering information corresponding to each of the one or more routing nodes and one or end point nodes from the one or more communication interfaces;

(iii) processes the metering information to generate a spanning tree using the processor implementing a graph theoretic algorithm; and

(iv) transmits the metering information and the network configuration information to the one or more communication interfaces;

(v) wherein each wireless enabled meter is configured to a minimum power level thereby reducing overall cost in the neighborhood area network;

(vi) wherein implementing the graph theoretic algorithm results in increasing the ratio of wireless enabled meters to access points in a neighborhood area network.

15. The system of claim 13, wherein a remote server device includes:

a processor;

a memory coupled to the processor;

one or more communication interfaces coupled to the processor;

wherein the device;

(i) stores the metering information and the network information in the memory;

(ii) processes the metering information for a subset of the one or more routing nodes and generates a spanning tree to reduce overall cost in the neighborhood area network using the processor implementing a graph theoretic algorithm;

(iii) transmits reconfiguration data of the one or more routing nodes and one or more end point nodes based on the metering information and network configuration information using the processor through the one or more communication interfaces.

16. The system of claim 13, wherein location of the one or more access points corresponds to location of one or more nodes as a result of selection by the graph theoretic algorithm.