Method and apparatus to reduce cumulative effect of dynamic metric advertisement in smart grid/sensor networks

In one embodiment, a node in a computer network represented by a directed acyclic graph (DAG) may receive advertisements of smoothed path costs to a root node of the DAG, where the advertisements contain a field for a virtual gain factor (VGF) indicative of a difference between the smoothed path cost and an actual best path cost to the root. The node may then determine a local smoothed path cost from itself to the root, and also a local VGF for each link of the node (for the path as a whole including the particular link) based on all of the received advertisements and VGFs, as well as corresponding actual link costs (e.g., based on selecting alternative parents or actual link costs being smoothed within a dual threshold). The node may then compute a resulting smoothed path cost to the root along with an associated (cumulative) VGF based on the locally determined cost and VGF. Accordingly, the node may then advertise the resulting smoothed path cost along with the associated (cumulative) VGF on each link such that, for example, any node receiving a resulting smoothed path cost and/or VGF that surpasses a threshold may request a rebuild of the DAG (e.g., a portion or in its entirety).

TECHNICAL FIELD

The present disclosure relates generally to computer networks, and, more particularly, to directed acyclic graph (DAG) routing and management, e.g., for Low power and Lossy Networks (LLNs).

BACKGROUND

Low power and Lossy Networks (LLNs), e.g., sensor networks, have a myriad of applications, such as Smart Grid and Smart Cities. Various challenges are presented with LLNs, such as lossy links, low bandwidth, battery operation, low memory and/or processing capability, etc. One example routing solution to LLN challenges is a protocol called Routing Protocol for LLNs or “RPL,” which is a distance vector routing protocol that builds a Destination Oriented Directed Acyclic Graph (DODAG) in addition to a set of features to bound control traffic, support local (and slow) repair, etc. The RPL routing protocol provides a flexible method by which each node performs DODAG discovery, construction, and maintenance.

One problem that confronts LLNs is network stability, and as such, various measures to reduce management traffic have been established, such as limiting response to link failure and “smoothing” dynamic metric values so new metrics are only advertised when their values exceed some threshold. In particular, since electing a new parent in a DAG leads to unstable routing topologies, traffic flaps, jitter, etc., new metrics are advertised only if the metric values substantially change. The disadvantage of such an approach is the resulting cumulative effect (cumulative error), where for “deep” networks (networks having a large number of hops), the cumulative error could result in either a better unselected path being available or, conversely, a selected path that is worse than believed. Current solutions in RPL consist of rebuilding the entire DAG manually or upon the expiration of a timer, which can be costly, inefficient and not related to actual changes in the network.

DESCRIPTION OF EXAMPLE EMBODIMENTS

Overview

According to one or more embodiments of the disclosure, a node in a computer network represented by a directed acyclic graph (DAG) may receive advertisements of smoothed path costs from nodes in its vicinity and, in particular, its preferred parent in the DAG, where the advertisements contain a field for a virtual gain factor (VGF) indicative of a difference between the smoothed path cost and an actual best path cost to the root. The node may then determine a local smoothed path cost from itself to the root, by adding the received path cost to the local link cost, and also a local VGF for each link of the node (for the path as a whole including the particular link) based on all of the received advertisements and VGFs, as well as corresponding actual link costs (e.g., based on selecting alternative parents or actual link costs being smoothed within a dual threshold). The node may then compute a resulting smoothed path cost to the root along with an associated (cumulative) VGF based on the locally determined cost and VGF.

Accordingly, the node may then advertise the resulting smoothed path cost along with the associated (cumulative) VGF on each link, such that, for example, any node receiving a resulting smoothed path cost and/or VGF that surpasses a threshold may request a rebuild of the DAG (e.g., a portion or in its entirety).

Description

Smart object networks, such as sensor networks in particular, are a specific type of network consisting of spatially distributed autonomous devices such as sensors that cooperatively monitor physical or environmental conditions at different locations, such as, e.g., temperature, pressure, vibration, sound, radiation, motion, pollutants, etc. Other types of smart objects include actuators, e.g., objects responsible for turning on/off an engine or performing other actions. Sensor networks are typically wireless networks, though wired connections are also available. That is, in addition to one or more sensors, each sensor device (node) in a sensor network may generally be equipped with a radio transceiver or other communication port, a microcontroller, and an energy source, such as a battery. Generally, size and cost constraints on sensor nodes result in corresponding constraints on resources such as energy, memory, computational speed and bandwidth. Correspondingly, a reactive routing protocol may, though need not, be used in place of a proactive routing protocol for sensor networks.

In certain configurations, the sensors in a sensor network transmit their data to one or more centralized or distributed database management nodes that obtain the data for use with one or more associated applications. Alternatively (or in addition), certain sensor networks provide for mechanisms by which an interested subscriber (e.g., “sink”) may specifically request data from devices in the network. In a “push mode,” the sensors transmit their data to the sensor sink/subscriber without prompting, e.g., at a regular interval/frequency or in response to external triggers. Conversely, in a “pull mode,” the sensor sink may specifically request that the sensors (e.g., specific sensors or all sensors) transmit their current data (or take a measurement, and transmit that result) to the sensor sink. (Those skilled in the art will appreciate the benefits and shortcomings of each mode, and both apply to the techniques described herein.)

FIG. 1is a schematic block diagram of an example computer network100illustratively comprising nodes/devices200, such as, e.g., routers, sensors, computers, etc., interconnected by various methods of communication (e.g., and labeled as shown, “LBR,” “11,” “12,” . . . “46”). For instance, the links of the computer network may be wired links or may comprise a wireless communication medium, where certain nodes200of the network may be in communication with other nodes200, e.g., based on distance, signal strength, current operational status, location, etc. Those skilled in the art will understand that any number of nodes, devices, links, etc. may be used in the computer network, and that the view shown herein is for simplicity. Illustratively, certain devices in the network may be more capable than others, such as those devices having larger memories, sustainable non-battery power supplies, etc., versus those devices having minimal memory, battery power, etc. For instance certain devices200may have no or limited memory capability. Also, one or more of the devices200may be considered “root nodes/devices” (or root capable devices) while one or more of the devices may also is be considered “destination nodes/devices.”

Data packets140(e.g., traffic and/or messages sent between the devices/nodes) may be exchanged among the nodes/devices of the computer network100using predefined network communication protocols such as the Transmission Control Protocol/Internet Protocol (TCP/IP), User Datagram Protocol (UDP), Multi-Protocol Label Switching (MPLS), various proprietary protocols, etc. In this context, a protocol consists of a set of rules defining how the nodes interact with each other. In addition, packets within the network100may be transmitted in a different manner depending upon device capabilities, such as source routed packets.

FIG. 2is a schematic block diagram of an example node/device200that may be used with one or more embodiments described herein, e.g., as a root node or sensor. The device may comprise one or more network interfaces210, one or more sensor components215(e.g., sensors, actuators, etc.), a power supply260(e.g., battery, plug-in, etc.), one or more processors220(e.g., 8-64 bit microcontrollers), and a memory240interconnected by a system bus250. The network interface(s)210contain the mechanical, electrical, and signaling circuitry for communicating data over physical and/or wireless links coupled to the network100. The network interface(s) may be configured to transmit and/or receive data using a variety of different communication protocols, including, inter alia, TCP/IP, UDP, wireless protocols (e.g., IEEE Std. 802.15.4, WiFi, Bluetooth®,), Ethernet, powerline communication (PLC) protocols, etc.

The memory240comprises a plurality of storage locations that are addressable by the processor(s)220and the network interface(s)210for storing software programs and data structures associated with the embodiments described herein. As noted above, certain devices may have limited memory or no memory (e.g., no memory for storage other than for programs/processes operating on the device). The processor(s)220may comprise necessary elements or logic adapted to execute the software programs and manipulate the data structures, such as routes or prefixes of a routing/forwarding table245(notably on capable devices only). An operating system242, portions of which are typically resident in memory240and executed by the processor(s), functionally organizes the device by, inter alia, invoking operations in support of software processes and/or services executing on the device. These software processes and/or services may comprise routing process/services244, which may include an illustrative directed acyclic graph (DAG) process246. Also, for root devices (or other management devices), a topology management process248and associated stored topologies249may be present in memory240, for use as described herein. It will be apparent to those skilled in the art that other processor and memory types, including various computer-readable media, may be used to store and execute program instructions pertaining to the techniques described herein. Also, while the description illustrates various processes, it is expressly contemplated that the various processes may be embodied as modules configured to operate in accordance with the techniques herein (e.g., according to the functionality of a similar process).

Low power and Lossy Networks (LLNs), e.g., certain sensor networks, may be used in a myriad of applications such as for “Smart Grid” and “Smart Cities.” A number of challenges in LLNs have been presented, such as:

1) Links are generally lossy, such that a Packet Delivery Rate/Ratio (PDR) can dramatically vary due to various sources of interferences, e.g., considerably affecting the bit error rate (BER);

2) Links are generally low bandwidth, such that control plane traffic must generally be bounded and negligible compared to the low rate data traffic;

3) A number of use cases require specifying a set of link and node metrics, some of them being dynamic, thus requiring specific smoothing functions to avoid routing instability, considerably draining bandwidth and energy;

4) Constraint-routing may be required by some applications, e.g., to establish routing paths that avoid non-encrypted links, nodes running low on energy, etc.;

5) Scale of the networks may become very large, e.g., on the order of several thousands to millions of nodes; and

6) Nodes may be constrained with a low memory, a reduced processing capability, a low power supply (e.g., battery).

In other words, LLNs are a class of network in which both the routers and their interconnects are constrained; LLN routers typically operate with constraints, e.g., processing power, memory, and/or energy (battery), and their interconnects are characterized by, illustratively, high loss rates, low data rates, and/or instability. The LLN may be sized with devices ranging from a few dozen to as many as thousands or even millions of LLN routers, and may support point-to-point traffic (between devices inside the LLN), point-to-multipoint traffic (from a central control point to a subset of devices inside the LLN) and multipoint-to-point traffic (from devices inside the LLN towards a central control point).

An example protocol specified in an Internet Engineering Task Force (IETF) Internet Draft, entitled “RPL: IPv6 Routing Protocol for Low Power and Lossy Networks”<draft-ietf-roll-rpl-15> by Winter, at al. (Nov. 6, 2010 version), provides a mechanism that supports multipoint-to-point (MP2P) traffic from devices inside the LLN towards a central control point (e.g., LLN Border Routers (LBRs) or “root nodes/devices” generally), as well as point-to-multipoint (P2MP) traffic from the central control point to the devices inside the LLN (and also point-to-point, or “P2P” traffic). RPL (pronounced “ripple”) may generally be described as a distance vector routing protocol that builds a Directed Acyclic Graph (DAG) for use in routing traffic/packets140, in addition to defining a set of features to bound the control traffic, support repair, etc.

A DAG is a directed graph that represents a computer network, such as computer network100, and that has the property that all edges are oriented in such a way that no cycles (loops) are supposed to exist. All edges are contained in paths oriented toward and terminating at one or more root nodes (e.g., “clusterheads or “sinks”), often to interconnect the devices of the DAG with a larger infrastructure, such as the Internet, a wide area network, or other domain. In addition, a Destination Oriented DAG (DODAG) is a DAG rooted at a single destination, i.e., at a single DAG root with no outgoing edges. A “parent” of a particular node within a DAG is an immediate successor of the particular node on a path towards the DAG root, such that the parent has a lower “rank” than the particular node itself, where the rank of a node identifies the node's position with respect to a DAG root (e.g., the farther away a node is from a root, the higher is the rank of that node). Further, a sibling of a node within a DAG may be defined as any neighboring node which is located at the same rank within a DAG. Note that siblings do not necessarily share a common parent, and routes between siblings are generally not part of a DAG since there is no forward progress (their rank is the same). Note also that a tree is a kind of DAG, where each device/node in the DAG generally has one parent or, as used herein, one preferred parent.

DAGs may generally be built based on an Objective Function (OF). The role of the Objective Function is generally to specify rules on how to build the DAG (e.g. number of parents, backup parents, etc.).

In addition, one or more metrics/constraints may be advertised by the routing protocol to optimize the DAG. Also, the routing protocol allows for including an optional set of constraints to compute a constrained path, such as where if a link or a node does not satisfy a required constraint, it is “pruned” from the candidate list when computing the best path. (Alternatively, the constraints and metrics may be separated from the OF.) Additionally, the routing protocol may include a “goal” that defines a host or set of hosts, such as a host serving as a data collection point, or a gateway providing connectivity to an external infrastructure, where a DAG's primary objective is to have the devices within the DAG be able to reach the goal. In the case where a node is unable to comply with an objective function or does not understand or support the advertised metric, it may be configured to join a DAG as a leaf node. As used herein, the various metrics, constraints, policies, etc., are considered “DAG parameters.”

Illustratively, example metrics used to select paths (e.g., preferred parents) may comprise cost, delay, latency, bandwidth, estimated transmission count (ETX), etc., while example constraints that may be placed on the route selection may comprise various reliability thresholds, restrictions on battery operation, multipath diversity, load balancing requirements, bandwidth requirements, transmission types (e.g., wired, wireless, etc.), and also a number of selected parents (e.g., single parent trees or multi-parent DAGs). Notably, an example for how routing metrics may be obtained may be found in an IETF Internet Draft, entitled “Routing Metrics used for Path Calculation in Low Power and Lossy Networks” <draft-ietf-roll-routing-metrics-12> by Vasseur, et al. (Nov. 10, 2010 version). Further, an example OF (e.g., a default OF) may be found in an IETF Internet Draft, entitled “RPL Objective Function 0” <draft-ietf-roll-of 0-03> by Thubert (Jul. 29, 2010 version).

Building of a DAG may utilize a discovery mechanism to build a logical representation of the network, and route dissemination to establish state within the network so that routers know how to forward packets toward their ultimate destinations. Note that a “router” refers to a device that can forward as well as generate traffic, while a “host” refers to a device that can generate but does not forward traffic. Also, a “leaf” may be used to generally describe a non-router that is connected to a DAG by one or more routers, but cannot itself forward traffic received on the DAG to another router on the DAG. Control messages may be transmitted among the devices within the network for discovery and route dissemination when building a DAG.

According to the illustrative RPL protocol, a DODAG Information Object (DIO) is a type of DAG discovery message that carries information that allows a node to discover a RPL Instance, learn its configuration parameters, select a DODAG parent set, and maintain the upward routing topology. In addition, a Destination Advertisement Object (DAO) is a type of DAG discovery reply message that conveys destination information upwards along the DODAG so that a DODAG root (and other intermediate nodes) can provision downward routes. A DAO message includes prefix information to identify destinations, a capability to record routes in support of source routing, and information to determine the freshness of a particular advertisement. Notably, “upward” or “up” paths are routes that lead in the direction from leaf nodes towards DAG roots, e.g., following the orientation of the edges within the DAG. Conversely, “downward” or “down” paths are routes that lead in the direction from DAG roots towards leaf nodes, e.g., generally going against the orientation of the edges within the DAG.

Generally, a DAG discovery request (e.g., DIO) message is transmitted from the root device(s) of the DAG downward toward the leaves, informing each successive receiving device how to reach the root device (that is, from where the request is received is generally the direction of the root). Accordingly, a DAG is created in the upward (UP) direction toward the root device. The DAG discovery reply (e.g., DAO) may then be returned from the leaves to the root device(s) (unless unnecessary, such as for UP flows only), informing each successive receiving device in the other direction how to reach the leaves for downward routes. Nodes that are capable of maintaining routing state may aggregate routes from DAO messages that they receive before transmitting a DAO message. Nodes that are not capable of maintaining routing state, however, may attach a next-hop parent address. The DAO message is then sent directly to the DODAG root which can, in turn, build the topology and locally compute downward routes to all nodes in the DODAG. Such nodes are then reachable using source routing techniques over regions of the DAG that are incapable of storing downward routing state.

FIG. 3illustrates an example message300with a simplified control message format that may be used for discovery and route dissemination when building a DAG, e.g., as a DIO or DAO. Message300illustratively comprises a header310having one or more fields312that identify the type of message (e.g., a RPL control message) and a specific code indicating the specific type of message, e.g., a DIO or a DAO (or a DAG Information Solicitation). A body/payload320of the message may comprise a plurality of fields used to relay pertinent information. In particular, the fields may comprise various flags/bits321, a sequence number322, a rank value323, an instance ID324, a (DO)DAG ID325, and other fields, each as may be appreciated in more detail by those skilled in the art. Further, for DAO messages, fields for a destination prefix326and a reverse route stack327may also be included. For either DIOs or DAOs, one or more additional sub-option fields328may be used to supply additional or custom information (such as, e.g., the VGF) within the message300. For instance, an objective code point (OCP) sub-option field may be used within a DIO to carry codes specifying a particular objective function (OF) to be used for building the associated DAG.

Cumulative Error Management

As stated above, one problem that confronts LLNs is network stability. By contrast with other IGPs (in particular, link states) where fast convergence technologies have been developed, fast reaction/convergence to link failure would be catastrophic for an LLN, potentially leading to short life cycle in battery operated environments, as well as potentially high levels of congestion due to routing packet control traffic. This also applies to routing metric changes, since in many networks these metrics are dynamic, where metric values are “smoothed out” and new metrics are only advertised when their values exceed some thresholds (“dual-thresholds,” i.e., upper and lower thresholds surrounding a current metric).

In other words, to reduce management traffic, techniques limit response to link failure and smooth dynamic metric values so new metrics are only advertised when their values exceed some threshold. In particular, since electing a new parent in a DAG may lead to unstable routing topologies, traffic flaps, jitter, etc., new metrics are advertised only if the metric values substantially change. The disadvantage of such an approach is the resulting cumulative effect (cumulative error), where for “deep” networks (networks having a large number of hops, e.g., 20 hops), the cumulative error could result in either a better unselected path being available or, conversely, a selected path that is worse than believed. For instance, a potential metric value change, e.g., a path cost gain of 5% at each hop, would lead to a fairly sub-optimal path for a node deep in the network (if the actual path cost is significantly lower than the advertised path cost, the node could have attracted more nodes, thus offering a more optimal path). Conversely, if the advertised path cost (via the same parent or a different parent) at each hop is actually 5% higher, it may be worthwhile for a node to change its parent. Current solutions in RPL consist of rebuilding the entire DAG manually or upon the expiration of a timer, which can be costly, inefficient, and not related to actual changes in the network.

According to one or more embodiments herein, therefore, a method and apparatus is described to reduce the cumulative effect of such dynamic metric advertisements, e.g., those governed by dual-thresholds, in a distributed fashion. Specifically, according to one or more embodiments of the disclosure, a node in a computer network represented by a DAG may receive advertisements of smoothed path costs to a root node of the DAG, where the advertisements contain a field for a virtual gain factor (VGF) indicative of a difference between the smoothed path cost and an actual path cost to the root. The node may then determine a local smoothed path cost from itself to the root, and also a local VGF for each link of the node (for the path as a whole including the particular link) based on all of the received advertisements and VGFs, as well as corresponding actual link costs (e.g., based on selecting alternative parents or actual link costs being smoothed within a dual threshold). The node may then compute a resulting smoothed path cost to the root along with an associated (cumulative) VGF based on the locally determined cost and VGF. Accordingly, the node may then advertise the resulting smoothed path cost along with an associated (cumulative) VGF on each link, such that, for example, any node receiving a resulting smoothed path cost and/or VGF that surpasses a threshold may request a rebuild of the DAG (e.g., a portion or in its entirety).

Illustratively, the techniques described herein may be performed by hardware, software, and/or firmware, such as in accordance with DAG process246, which may contain computer executable instructions executed by the processor(s)220to perform functions relating to the novel techniques described herein, e.g., in conjunction with routing process244.

Operationally, as a distance vector routing protocol, RPL advertises (e.g., using a link local IPv6 Multicast address) a number of parameters including a set of path costs (if using more than one metric and constraint). Each node in the vicinity of the advertising router may then elect a best parent by adding a locally estimated link cost, which may or may not be symmetrical (i.e., the link cost may not be the same for both directions over the link). The use of a threshold based cost update may be used to stabilize such a network by, e.g., minimizing the routing traffic and energy used by the routing protocol with too frequent topology changes. But even a 5% threshold effect on the link cost (path cost is not updated unless there is at least a 5% variation of the uplink cost) ineluctably leads to a potential sub-gain detrimental to a number of applications in Smart Grid networks.

The first component of these embodiments involves propagating (advertising) the actual (smoothed) best path cost, as conventionally performed by RPL, along with an additional virtual gain factor (VGF) associated with the advertised path cost. Upon receiving the advertised path cost to the root and VGF from, e.g., a node “i,” a receiving node M determines the current best path cost and adds its own local VGF to the received VGF(i). In other words, the receiving node M determines the local link cost for the link to node i, as well as the VGF associated with that cost, computes a resulting smoothed path cost to the root along with a resulting (cumulative) VGF (i+M) based on the locally determined cost and VGF by, e.g., adding the locally determined cost and locally determined VGF to the received path cost and received VGF, and then advertises the resulting smoothed path cost to the root along with resulting VGF (i+M). This advertisement reflects the best possible path cost assuming an upper node in the DAG changes its routing decision and elects a parent that would provide the advertised best path cost (including the potential gain). If the path cost gain exceeds a pre-defined threshold, it may then be worth rebuilding the DAG shape or a portion of the DAG (since with this described technique is not necessary to build the entire DAG).

For example, in the DAG shown inFIG. 4A, suppose that the node22advertises a smoothed path cost of 20 to the root, i.e., along the path of node22to node12(link cost of 10) and node12to root (link cost of 10). However, node22also advertises a VGF(22)=1 because it selects node11as best parent upon, e.g., discovering that the cost of the link22-11has decreased (to 9) or, perhaps, discovering a lower link cost (of 9) to node11after selecting node12as its parent. Node22thus advertises a VGF(22)=1 should it elect a new parent (11). Suppose also that the current link cost for the link32-22is 5 with VGF=1. At this point, the node32advertises a smoothed path cost of 25 with VGF(32)=2, the cumulated effect.

As the path cost propagates deeper in the DAG, it may very well be that the cumulative VGF(K) is greater than some constant (threshold), thus justifying a DODAG rebuild. For example, node32could send a request to node22, requesting a DAG rebuild. In response, node22would select node11as a new best parent, and the new cost of link32-22is accurately reflected (FIG. 4B). In this example, the VGF could be obtained by changing a parent (at node22) or because of a link cost decrease (32-22). Note that the scenario may be more complex, with an advertised path cost having an even higher VGF (for example by electing21as the best parent for32).

According to these embodiments, therefore, a second component involves rebuilding a DAG (or at least portions thereof, i.e., global versus local repair). Upon receiving a smoothed path cost and/or VGF that crosses (surpasses) pre-defined thresholds (e.g., on a per topology basis since RPL supports Multi-topology routing), a node can request a DAG re-shape that will recursively travel in the UP direction to trigger its ancestor(s) to effectively change their parent selection for the benefit of their children. Propagation of such changes in the UP direction in the DAG may be limited by adding the node's rank in the VGF. Note that this does not generally add substantial traffic control since control traffic for prefix advertisement travels in the UP direction. Upon receiving such a request, nodes can effectively decide whether or not to satisfy the request according to the number of requesters and other factors. Conventional routing oscillation avoidance mechanisms may still be used at all levels of the DAG.

Note that multiple nodes along the path may have to change their parent selection, thus resulting in changes at multiple levels/ranks. Note also that the request may stop at an ancestor that is not the DAG root, thus limiting the impact of rebuilding the DAG shape for the best cost benefit.

Moreover, it should be noted that the same technique can be used as link cost increases (resulting, e.g., in VGF(i)<0). In this case, a node may simply elect a new parent to thereby allow (partial) rebuild of the DAG when the cost becomes unacceptably sub-optimal for some nodes. In other words, a VGF value may be a negative value (e.g., reflecting an increase cost or gain) or a positive value (e.g., reflecting a decrease cost or loss) and, at each hop, the cumulative effect of each hop is accounted for, accordingly.

FIG. 5illustrates an example simplified procedure for managing cumulative error in a DAG that smoothes metrics in accordance with one or more embodiments described herein. The procedure500starts at step505, and continues to step510, where a node200may receive one or more advertisements of smoothed path costs to a root node of a computer network represented by the DAG, where each advertisement contains a field for a VGF indicative of a difference between the smoothed path cost and an actual best path cost to the root. In step515, the node may determine a local smoothed path cost from itself to the root node, and in step520, may also determine a local VGF for each link of the node (for the path as a whole including the particular link) based on all of the received advertisements and VGFs, as well as corresponding actual link costs (e.g., based on selecting alternative parents or actual link costs being smoothed within a dual threshold). In Step525, the node computes a resulting smoothed path cost to the root node along with an associated (cumulative) VGF. Thereafter, in step530, the node may advertise the resulting smoothed path cost along with the associated (cumulative) VGF on each link to other nodes of the network such that, in step535, any node receiving a resulting smoothed path cost and/or associated VGF that surpasses a threshold may request a rebuild of the DAG (e.g., a portion or in its entirety). The procedure500ends in step540.

The novel techniques described herein manage smoothed metric value error accumulation for DAGs in a computer network. In particular, as described above, by reporting the cumulative gain/loss (e.g., the VGF), along with providing a mechanism that allows for signaling that cumulative effect to trigger a routing topology change, the novel techniques alleviate the fairly common situation where paths within a DAG become very sub-optimal and even unacceptable for nodes deep in the network. In addition, the techniques above utilize only lightweight additional traffic control for a potential significant gain in terms of path quality.

While there have been shown and described illustrative embodiments that manage DAGs in a computer network, it is to be understood that various other adaptations and modifications may be made within the spirit and scope of the embodiments herein. For example, the embodiments have been shown and described herein with relation to LLNs, and more particular, to the RPL protocol. However, the embodiments in their broader sense are not so limited, and may, in fact, be used with other types of networks and/or protocols utilizing DAG routing (e.g., distance vector protocols).