WO2005039151A2 - Arrangement for autonomous mobile network nodes to organize a wireless mobile network based on detected physical and logical changes - Google Patents
Arrangement for autonomous mobile network nodes to organize a wireless mobile network based on detected physical and logical changes Download PDFInfo
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- WO2005039151A2 WO2005039151A2 PCT/US2004/032587 US2004032587W WO2005039151A2 WO 2005039151 A2 WO2005039151 A2 WO 2005039151A2 US 2004032587 W US2004032587 W US 2004032587W WO 2005039151 A2 WO2005039151 A2 WO 2005039151A2
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- H04L67/125—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/0088—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
Definitions
- the present invention relates to wireless networking, and techniques for organizing, on an ad hoc basis, mobile networks using unmanned devices or vehicles that are movable over a geographic area.
- IP Internet Protocol
- MANET Mobile Ad-hoc Networks
- NEMO mobile networks
- MIP Mobile IP
- the key component in NEMO is a mobile router that handles MIP on behalf of the mobile networks that it serves.
- the "mobile ad hoc network” is an autonomous system of mobile routers (and associated hosts) connected by wireless links—the union of which form an arbitrary graph.
- the routers are free to move randomly and organize themselves arbitrarily; thus, the network's wireless topology may change rapidly and unpredictably.
- Such a network may operate in a standalone fashion, or may be connected to the larger Internet.
- a “Mobile IPv6” protocol is disclosed in an Internet Draft by Johnson et al., entitled “Mobility Support in IPv6", available on the World Wide Web at the address: http://www.ietf.org/internet-drafts/draft-ietf-mobileip-ipv6-24.txt (the disclosure of which is incorporated in its entirety herein by reference).
- the above-described mobile networking protocols are merely concerned with IP-based connectivity, and rest on the assumption that wireless link establishment and node mobility are uncontrollable factors outside the scope of the mobile networking protocol.
- Remote-controlled devices have been used to provide remote sensoring and remote interaction with respect to hostile (e.g., dangerous) environments or locations that are not practical for human intervention.
- Such remote-controlled devices have included terrestrial robots, aerial drones, satellites, marine or submersible drones, and unmanned spacecraft.
- these remote-controlled devices have relied on a wireless link with a control station that provides direct control over the operations of the remote-controlled devices; as the remote- controlled devices obtain additional processing power and memory storage capabilities, the degree of real-time controller intervention via the control station is reduced.
- the remote-controlled device upon lacking sufficient information to execute an operation, will reach a state where it enters a standby mode while awaiting further instructions from the control station.
- pervasive network refers to a network where every thing, device, and user can be continually connected to a common network fabric.
- a pervasive network would be particularly beneficial in military or rescue operations, where a system (e.g., a mobile network of robotically-controlled mobile nodes) can be quickly deployed (in a manner of hours) without the necessary of manual configuration of each and every mobile node.
- Efforts in attempting to implement and deploy a pervasive network have uncovered numerous problems. Attempts for rapid deployment in a given area may encounter operational difficulties if the area of deployment cannot support continuous coverage of each individual mobile node. In addition, changes in topology and the location of the coverage may change at a rapid and unpredictable pace, risking signal loss between various mobile nodes.
- One attempt to minimize signal loss is to combine satellite communications (offering wide area coverage) and mobile communications.
- Satellites are expensive, fragile, and have a limited bandwidth and a limited time interval of line-of-sight availability in the case of satellites that do not have a geostationary orbit.
- the required power for a mobile base station to transmit to and from a satellite can be both cost prohibitive and dangerous, since the signal transmission can be detected by hostile forces.
- APCO16 and APCO25 systems promulgated by the Association for Public-Safety Communications Officials
- public safety networks public safety networks
- wireless technologies are typically deployed using fixed nodes, namely towers and repeaters stationed over a given area of coverage in a logical fashion to provide robust communications during normal and "planned" conditions.
- those fixed node-based systems may not be able to provide adequate coverage to support rescue or police operations.
- One technology that has been deployed to support ad hoc rescue operations is a "vehicular" repeater. This allows a vehicle, for example a police car, to act as a repeater for the network.
- the officer drives his vehicle to a certain area and the vehicle has a "higher power" repeater in it.
- the officer and others can then use their lower power portable radios to communicate through the repeater within the vehicle thereby extending their range.
- This vehicular repeater has several limitations. First, the vehicle must be driven to a specific point by a human driver and that point might not be reachable or might not be a place where the driver needs (or wants) to go. Second, the vehicle only acts as a repeater back to the fixed infrastructure and cannot support local communications. Third, the repeater has limited bandwidth. Fourth, the repeater cannot account for portable devices having varying power requirements. Yet another common capability is the ability of public safety and military portable radios to enter "talk around mode".
- a wireless network is established between network nodes which can be configured as wireless autonomous robotic mobile access points.
- Each node includes a mobility platform, and an executable routing resource.
- the mobility platform is configured for supplying sensor data from attached physical sensors, and responding to commands such as motor commands.
- Each sensor datum is converted into a corresponding sensor object according to a vector space relative to the attribute measured by the corresponding sensor.
- the received movement directives also are converted into respective mobility commands (e.g., robotic commands, packet routing commands, etc.).
- he executable routing resource is configured for maintaining a database of world objects representing attributes within an infosphere established by the wireless network based on the sensor objects and network objects received by the executable routing resource.
- the executable routing resource also is configured for generating the received movement directives and executing network decisions based on periodic evaluation of the world object database, and exchanging the world objects with other network nodes for synchronization of the respective databases of world objects.
- the nodes nodes can operate autonomously to execute coordinated decisions for optimized operations with respect to both physical operations and wireless network operations.
- the exchanging of world objects enables the network nodes to establish a self-adapting, autonomous wireless network that can adjust to detected changes in physical space, geographic space, network topology space, or wireless link space.
- One aspect of the present invention provides a method in a network node. The method includes establishing within the network node a world object database that stores world objects.
- the world objects represent respective attributes of an infosphere of a network that includes the network node.
- the world object database also includes smart world objects as a subclass of the world objects and that are configured for generating decisions based on evaluation of selected world objects.
- the method also includes adding, as world objects to the world object database, sensor objects from sensor data generated in response to detected attributes within the infosphere.
- the sensor objects include network node objects associated with the network node.
- the method also includes forming the network.
- the network is formed based on: (1) discovery of other network nodes, (2) adding second network node objects as world objects to the world object database and representing attributes of the other network nodes, and (3) sharing the world objects with the other network nodes.
- the method also includes performing a change in at least one of position, velocity, orientation, and wireless communication characteristics of the network node based on detecting a world object specifying a directive based on at least one of the decisions.
- Figure 1 is a diagram illustrating an autonomous wireless mobile network comprising mobile nodes configured as wireless autonomous robotic mobile access points, according to an embodiment of the present invention.
- Figure 2 is a diagram illustrating one of the mobile nodes of Figure 1 according to an embodiment of the present invention.
- Figure 3 is a object relationship diagram illustrating relationships between different objects from the world object database of Figure 2.
- Figure 4 is a diagram illustrating an object-based world from the world object database of Figure 3 containing multiple objects.
- Figure 5 is a diagram illustrating exemplary reaction objects that may be used in the world object database illustrated in Figures 2 and 6.
- Figure 6 is a diagram illustrating exemplary brain objects that may be used in the world object database illustrated in Figures 2 and 3.
- Figure 7 is a diagram illustrating a software-based architecture of the executable processes portion of the mobile node of Figure 2.
- Figure 8 is a diagram illustrating the executable application-layer resources of Figure 3.
- Figure 9 is a diagram illustrating interactions between different objects from the world object database of Figure 2 during execution of a decision.
- Figure 10 is a diagram illustrating steps performed by the mobile nodes in establishing and maintaining the autonomous wireless mobile network, according to an embodiment of the present invention.
- the disclosed embodiment is directed to establishment of a routing protocol that implements an autonomous solution for deployment of a mobile network having movable network nodes configured for independently moving to an optimum position, relative to the other network nodes (movable and fixed).
- the routing protocol provides a wireless and autonomous robotic mobile access point.
- the routing protocol of the disclosed embodiment considers movement of its physical platform as an option to optimize routing metrics, were each movable network node includes routing resources, a mobile platform, and a standardized interface between its routing resources and its mobile platform.
- FIG. 1 is a diagram illustrating mobile nodes having various implementations of mobile platforms that may be used for deployment of the mobile network 10: the mobile network 10 may include an airborne drones 12a, 12b, a marine or submersible drone 12c, a terrestrial drone 12d and 12e, and/or a spacecraft drone 12f.
- a mobile platform may include a robotic system 14 configured for moving a transmit/receive antenna 16 to a selected orientation, for example in the case of a ground station antenna mounted on the terrestrial drone 12e.
- the disclosed mobile network may be used for applications including robotic-based rescue support communications, military deployments, remote exploration, intelligent sensor arrays, mobile control of cameras for security systems or sporting events, etc..
- the mobile network 10 relies upon the establishment of communication links 18 between the different mobile nodes; as known in mobile networking technologies , the communication links 18 are established dynamically between respective network nodes 12 depending on the relative signal strength and propagation characteristics, as well as resistance to interference (e.g., geographic, atmospheric, RF-induced includingjamming).
- agiven network node e.g., 12a
- Each of the network nodes 12 includes at least one (preferably multiple) LAN/WAN wireless interface for IP-based communication with other network nodes.
- each network node 12 preferably has multiple wireless interfaces that can be utilized depending on proximity of other network nodes and relative signal strength; for example, if a network node 12 travels a substantial distance from other network nodes, the traveling network node 12 may switch from using a low-power LAN interface to a higher-power WAN interface.
- Each of the network nodes 12 also include IP-based routing resources that enable the network nodes 12 to establish the mobile network 10 between themselves, for example on an ad hoc basis, based on mutual discovery operations, and sharing of information associated with the discovery operations, including identifying network topology, etc., in the form of IP-based packets.
- a particular feature of the network nodes 12 is that they understand not only the connectivity of each of the nodes 12 relative to each other, but the network nodes 12 also understand metrics about the connectivity, including packet error rate, bandwidth delay, latency, etc., that are typically recognized on an OSI layer 2 (link layer) connection, as well as OSI layer 1 (physical layer) factors such as signal strength.
- the mobile nodes 12 are configured to recognize that numerous constraints may limit the physical positioning of the mobile nodes 12, both in terms of maintaining a communication link 18 and maintaining the viability of the network node itself. Such constraints may include geography, building integrity, presence of interference or obstructions, geopolitical constraints (e.g., airspace avoidance or marine navigation constraints), threat avoidance, etc..
- the routing protocol of the disclosed embodiment considers movement of its physical platform as an option to optimize routing metrics.
- the routing resources of each mobile node include movement of its physical platform, and all factors and consequences associated with executing decisions related to movement, as part of the decision-making process to determine how to respond to inputs, including how to route data packets.
- Each of these factors are also shared among the mobile nodes 12 to provide a level of understanding between all the mobile nodes 12 as to the state of the network 10 from the perspective of each of the individual nodes 12.
- each of the mobile nodes 12 decide how to route packets, and move their respective mobility platforms, based on the available information from local sensors and information shared between the other mobile nodes.
- the mobile network 10 becomes a dynamic entity where the individual mobile nodes 12 interact to route packets, establish connections among each other, and move at selected velocities as needed, based on shared information and detected information.
- the mobile network 10 can be deployed within a geographic area without actually programming the geographic topology or network topology within the mobile nodes.
- the mobile nodes 12 in the case of an emergency where a building has collapsed, the mobile nodes 12 (implemented as movable robots) could follow each other (e.g., led by a robot having proximity sensors, controlled by a rescue worker, or following a human rescue worker) to provide an RF chain despite poor RF characteristics within the collapsed building.
- FIG. 2 is a diagram illustrating in further detail an exemplary mobile node 12.
- the mobile node 12 includes IP router-based routing resources 20, a mobility platform 22, and an interface 24.
- the routing resources 20 are configured for execution of the routing protocol for the corresponding mobile node 12.
- the mobility platform 22 is configured for supplying physical sensor data associated with physical attributes of the mobile node 12, and data received from other wireless devices, and implementing the movement directives generated by the routing resources 20.
- the mobility platform 22 includes a location element 23 (e.g., a GPS receiver), configured for identifying the location of the mobility platform.
- the routing resources 20 include a routing table 100, also referred to as a "World Object Database", and executable resources and protocols 30.
- the executable resources and protocols 30 implement all decisions related to operation of the mobile node 12, including routing of packets, movement of the mobile node 12 by the mobility platform 22, selecting wireless interfaces for transmission and reception of wireless data, and adjusting gain for wireless transmission and reception.
- the executable resources and protocols 30 implement the operational decisions based on accessing relevant data objects from the world object database 100, and generating directives in the form of data objects for storage in the world object database 100.
- Figure 3 is a diagram illustrating the world object database 100 according to an embodiment of the present invention.
- the world object database 100 represents a model of the "world” as perceived by the mobile node 12, including inheritance of objects from the other mobile nodes 12 within the mobile network 10.
- the world object database 100 encompasses all attributes associated with the mobile network 10 (i.e., the "infosphere”).
- infosphere i.e., the attributes associated with the mobile network 10
- infosphere including for example network topology, geographic and physical parameters of the region encompassed by the mobile network 10, routing of data packets by a mobile node 12, etc.
- infosphere are represented using data objects represented according to multiple n-dimensional vectors that can be transformed based on transformational matrices.
- IP Internet Protocol
- a router's forwarding table can be considered an example of a three-dimensional vector space; however, since IP networks tend to be hierarchal in nature due to their addressing schemes (i.e., a subnetwork is identified as within a network based on using subnet prefixes), the forwarding tables can be simplified by to a two-dimensional mapping (network prefix: next hop) by following the implied hierarchical structure of the network while searching the forwarding tables.
- a forwarding table in a router can be represented as a three-dimensional vector space (i.e., a "World") that includes a coordinate system: each coordinate system is based on a prescribed reference point (e.g., an origin, waypoint, etc), and a coordinate system for identifying a second position (e.g., a waypoint) relative to the prescribed reference point in prescribed units (Cartesian coordinates, Geodesic coordinates, polar coordinates, etc.).
- a prescribed reference point e.g., an origin, waypoint, etc
- a coordinate system for identifying a second position e.g., a waypoint
- a given World may include a native coordinate system, and a coordinate transform (i.e., transformation of vector space) that enables the waypoint to be transformed to a second coordinate system for use in a second vector space for identification by another world object.
- coordinate transform i.e., transformation of vector space
- Examples of traditional vector spaces include network masks having various lengths (i.e., bits), hop count, bandwidth, network address, etc..
- a top-level object represented in Figure 3 below as a top-level container 104, would contain a /0 prefix of IP addresses; the top- level container would contain four (4) containers for Class A, B, C and D networks, respectively; each container for one of the Class A, B, C or D networks in turn contain additional containers for respective networks.
- This hierarchal model can be converted into a tuple space (i.e., a vector space), that has transformation matrices for transforming a vector space into another vector space; hence, a "distance" can be computed from one vector space for use in another vector space.
- the routing resources 20 manages data by modeling all data, including network parameters, into three-dimensional vector spaces; in addition, the creation of new vector spaces for physical parameters such as signal strength, Cartesian and Geodesic physical space, etc., enables generation of different tuple-space models such as an RF model that measures distance by signal power (dBm), a network topology model that measures distance by hop count, etc..
- Each node includes a database of world objects having a hereditary tree: a world object is a basic object, where all objects are world objects, including the world (i.e., world domain), the waypoints, and the smart world objects.
- Figure 3 is a diagram illustrating a portion of the world object database 100, namely a class of objects known as "data containers".
- the world object database 100 provides an object-oriented model for all objects in the world.
- the world object database 100 includes a world factory 102 which owns a container 104 of world objects.
- world objects 104 There are three types of world objects 104: worlds stored in a world container (i.e., world domain) 106, waypoints stored in a waypoint container 108, and smart world objects stored in a smart world container 110.
- world objects 104 contain a "Shape 3D" container 116 that includes any set of polyhedrons (i.e., prescribed three-dimensional shapes). Note that Figure 3 is written in accordance with the Uniform Modeling Language (UML) Specification Ver.
- UML Uniform Modeling Language
- the solid arrows on solid lines 120 point in the direction of inheritance; hence, the world 106 is a kind of (i.e., a subclass of) world object 104; a "dot" 122 on a dashed line implies ownership, such that the world 106 owns world objects 104; in other words, the world 106 is a container that contains one or more world objects 104. Similarly, the world object 104 owns the shape objects 116.
- a "world” from the world container (i.e., world domain)106 is a kind of world object 104 that can contain world objects 104, which can contain other worlds (i.e., world domains), and has a coordinate transform 130.
- Each world i.e., world domain
- world objects 104 have a hereditary tree, such that a world 106 may contain more world objects, enabling a hierarchy of a vector space to be developed.
- Figure 4 illustrates a "world" (i.e., world domain) 106a that encompasses a city and has a certain shape (i.e., the shape of the city) from the shape objects 116, a location 105a specified in a native coordinate space (e.g., GPS coordinates), and a coordinate transform 130a for mapping the native coordinate space into other vector spaces in the world object database 100.
- a native coordinate space e.g., GPS coordinates
- Each world 106 typically will encompass (i.e, contain or own) multiple objects that certain attributes within the domain of that world (also referred to as an infosphere), including a specified geographic area space based on position and shape, as well as physical space, RF space (e.g., signal characteristics relative to each node), network topology relative to each node, and physical parameters for each network node (including position, velocity, orientation).
- an infosphere e.g., a specified geographic area space based on position and shape, as well as physical space, RF space (e.g., signal characteristics relative to each node), network topology relative to each node, and physical parameters for each network node (including position, velocity, orientation).
- the "parent" city 106a encloses "child" world domains 106b and 106c; as illustrated in Figure 4, the world 106b encompassing (e.g., representing) a building within the city 106a and having a certain shape 116 and location 105b and having a corresponding coordinate transform 130b, and inside the building 106b are world objects 104a, 104b, and 104c for objects inside the building (e.g., floors) and having their own respective coordinate transforms 130c, 130d, 130e.
- Figure 4 illustrates the example where the universe is modeled as the world 106a, and the world 106a has a transformation 130a that serves as a universal transformation: the world objects 104a, 104b, and 104c that share the same types coordinates can "talk to each other" without any transformation; if, for example, the world objects 104a and 104b use different types of coordinates, the world object 104a could send a request to its "parent" object 106b to transform its native coordinates to the coordinate system used by the world object 104b; the world 106b would use its transformation 130b to perform the transformation.
- the world objects 104a and 104b inherit the transformation capabilities of their parent object 106b; similarly, the worlds 106b and 106c inherit the transformation capabilities of their parent world 103 a.
- the arrangement of Figure 4 illustrates that worlds can be nested with additional worlds within worlds, etc., each with another layer of transformation 130, where vectors in one space can be transformed to another space.
- a waypoint object 108 is a kind of world object that represents a "place" or attribute in the world: the term "waypoints" is not limited to geographic waypoints as used by GPS systems, but also may specify a host computer or a certain router in a vector space utilizing hop count, GPS coordinates in a Geodesic vector space, dBm levels in an RF vector space, etc.. Since the waypoint 108 is a world object, it has a shape since all world objects 104 own a shape from the shape container 116. Note that unlike worlds 106, waypoints 108 do not own world objects 104, hence a world object 104 cannot be added into a waypoint, but a world object 104 can be added into a world 106.
- each world 106 includes a transform 130 that is a matrix transformation for vectors representing the different vector spaces.
- the "location" 105 of any given world object may be relative to different frames of references (i.e., coordinate spaces); in the case of a building, the building object 106b of Figure 4 could be located using a street address relative to the city object 106a, or GPS coordinates, in which case the transform 130b and/or the transform 130a would be able to convert between the street address and GPS coordinates.
- vector mapping between different vector spaces is performed automatically using the transforms in each world, enabling the three- dimensional location and position vectors from different vector spaces to be compared and manipulated.
- a smart world object 110 is a type of world object 104 and as such include all the properties of world objects 104, including having a shape 116.
- Each smart world object 110 also owns an object called a brain 112, and each brain 112 owns a set of reactions 114.
- Brains 112 are responsible for "thinking" (in a heuristic manner) about the advice of each reaction 114, and then suggesting and forming a behavior (in the form of force vectors), also referred to as an "opinion", of what should be done.
- a reaction 114 is an object that "behaves" by reacting to various stimuli (e.g., objects identifying current system conditions and/or state) by suggesting a change, in the form of a recommendation or "advice” element (which also may be a world object 104), to a brain 112 (which is a designated smart world object).
- stimuli e.g., objects identifying current system conditions and/or state
- a brain 112 which is a designated smart world object.
- reactions have an "influence factor" that the brain 112 might consider (e.g., a minimum and maximum radius that might be considered). In some cases the reactions are sensitive to a given target or group of targets.
- Figure 5 is a diagram illustrating the different kinds of reactions 114. Reactions provide advice to the brain 112 in the form of a three-dimensional advice element.
- Reactions 114 work independently, and each reaction 114 may have an associated influence factor that the brain may use to reason with (i.e., use to reach an "opinion"). Reactions 114 use input factors such as space, signal strength, frequency, hop count, orientation, reasoning and other factors as their stimulus. Reactions also may consider various factors, including: position of itself; position of a target or a group of target world objects; nearness of other world objects; orientation of other world objections; predicted position of other world objects; Leaders and Groups; signal strength between world objects; distance to world objects; hop count to world objects; other link metrics between world objects.
- the alignment reaction 114a seeks to align the mobile node 12 with some other group of mobile nodes 12.
- the alignment reaction 114a is effective within some minimum radius and out to some maximum radius.
- the arrive reaction 114b sets a condition for arrival. This reaction 114b can qualify arrive as being within a certain radius of a physical location, being within a certain signal strength range or being within a certain packet hop count to a given destination.
- the cohesion reaction 114c attempts to cause the mobile node 12 to stay within a certain "distance" to a group of other network mobile nodes 12. Cohesion can be physical, signal strength or hop count driven.
- the evade reaction 114d attempts to keep the mobile node 12 away from (evade) a given kind of object.
- the flocking reaction 114e combines the effects of "cohesion" and "separation" with a group of world objects 104.
- the leader following reaction 114f attempts to cause the mobile node 12 to maintain cohesion with a given "leader" world object.
- the obstacle avoidance reaction 114g attempts to cause the mobile node 12 to avoid other world objects by maintaining a given separation from them.
- the offset seek reaction 114h is a modified version of the leader following reaction 114f in which the goal is to cause the mobile node 12 to seek to an offset from the given leader.
- the pursuit reaction 114i is a kind of reaction 114 that attempts to cause the mobile node 12 to get near a given world object. Nearness can be physical, signal strength or hop count.
- the seek reaction 114j is a kind of reaction 114 that attempts to cause the mobile node 12 to seek a given world object (i.e., a "target") given its current position, signal strength and hop count. Using only the target's current position (as opposed to estimating the next position) is the main difference between seek and pursuit. Note that "cmrent" position can be characterized in terms of physical position, signal strength, or hop count.
- the separation reaction 114k is a kind of reaction 114 that attempts to maintain a minimum separation between the mobile node 12 and other world objects.
- the simple path following reaction 114m is a kind of reaction 114 that moves the mobile node 12 through a set of given waypoints 108.
- the wander reaction 114n is a kind of reaction 114 that "randomly" changes the mobile node 12. It can randomly change the power output, position, frequency or route to other world objects. The randomness can be cryptographically random or simple random behavior. Note that the reactions 114 of Figure 5 are merely illustrative of mobility-based reactions; similar reactions would be implemented for routing packets, selecting wireless communication links, adjusting RF link power, etc.
- the executable algorithms of the brain objects 112 and the reactions objects 114 of Figure 3 operate on all of the vector spaces modeled in the world object database 100 transparently, such that the container of world objects 104 is an abstract set of objects, and the brain objects 112 and the reactions objects 114 formulate reactions and behavior on top of a set of world objects 104; those world objects 104 provide a uniform set of transformations.
- the world object database 100 provides a model for executing decisions based on physical movement and logical movement: one aspect is modeling the data in a manner as illustrated by the world object database 100 such that differences in data types are inconsequential; another aspect is implementing iterative decision-making processes in view of the objects in the world object database 100.
- the brain 112 and the reactions 114 manage the decision making in the mobile node 12.
- all of the world objects 104, brains 112, shapes 116 and reactions 1 14 are owned by (i.e., controlled by) the world factory 102 and are constructed from Extensible Markup Language (XML) tags.
- Figure 6 illustrates two types of brains 112: a basic brain and a reactive brain.
- the basic brain 132 is configured for scaling the respective reactions 114 (i.e., the advice elements supplied from the reactions 114) by an influence factor and then summing the scaled reactions to obtain a total reaction; the total reaction is then scaled to fit within a maximum reaction.
- the reactive brain 134 sorts the reactions 114 based on the influence factor and adds the influence of each reaction until a maximum reaction is reached.
- the influence factor may be a simple scalar for all reactions, or may be a specific value for each corresponding reaction 114.
- the architecture illustrated in Figures 3-6 are implemented by storing the objects as data structures in a tangible nonvolatile memory that is readable by a processor.
- the memory includes a memory that stores a table representing the world factory 102; the world factory 102 has entries for the world objects 104.
- the world 106, waypoint 108, and smart world objects 110 are tables stored within the memory storing the world objects 104.
- FIG 7 is a diagram illustrating in further detail one implementation of the executable resources 30, the interface 24, and the mobility platform 22 of Figure 2 according to an embodiment of the present invention. Different implementations using different interfaces, capabilities, and operating systems can be constructed according to the disclosed embodiment.
- the executable resources 30, illustrated as a software stack includes an application software layer 32, a collection of Java-based executable routines 34, and a network operating system layer 36 such as the commercially-available Cisco IOS from Cisco Systems, Inc.
- the IOS layer 36 interfaces with the physical interface device layer 24.
- the physical interface device layer 24 includes three I 2 C ports (I2C0, 12C1, 12C2), two Fast Ethernet Ports (FEO/1, FEO/1), an auxiliary serial port (Aux), and a Console port (CON) for interfacing with selected porti ons of the mobility platform 22.
- the physical interface device layer 24 is coupled to radio devices 38 enabling wireless LAN/WAN connectivity to other platforms.
- Exemplary radio devices include a cellular packet data (CDPD) radio 38a, or other wireless radio technology, including a location service such as GPS.
- the I2C2 port is configured for interfacing with robotic components 40, including for example an ultrasonic sonar 40a, a magnetic (fluxgate) compass 40b, a light detector 40c, and motor controllers 40d and 40e.
- the I2C0 port is configured for configuring (and reading/writing) a DRAM 40f
- the I2C1 port is configured for monitoring a router thermal sensor 40g.
- the executable resources and protocols 30 continually execute operations to maintain the mobility platform 22 (including auto-piloting the mobile node 12), and performing IP packet routing. These operations are implemented based on the following interactions: between the mobility platform 22 and the world object database 100; between brains 112, reactions 114, and the world object database 100; and between the mobile nodes 12 via the wireless interfaces. These interactions each involve the world object database 100, which serves as the "glue" between the mobile nodes 12 and the real world.
- the brains 112 and reactions 114 interact with the world 106, and the mobile nodes 12 interact with each other through a world object exchange protocol.
- Figure 8 is a diagram illustrating in further detail the executable processes 30 executed in a runtime environment by the routing resources 20 of Figure 2.
- the executable processes 30 that implement the wireless and autonomous robotic mobile access point include an adjacency or neighbor discovery protocol process 50 (in the application layer 32) used to find potential neighbors in the mobile network 10.
- the adjacency or neighbor discovery protocol process 50 similar to existing router discovery protocols in an IP network, is configured for finding reachable neighbors and creating an adjacency list of neighbors.
- the executable processes 30 also include a world distribution protocol process 52 (in the application layer 32) configured for distributing the objects of the world object database 100 to the neighbors discovered by the adjacency or neighbor discovery protocol resource 50.
- the world distribution protocol process 52 independently attempts to synchronize and distribute its view of the "world” (i.e., its perspective) as reflected in its world object database 100.
- Both the adjacency protocol process 50 and the world distribution protocol process 52 are instantiated by a protocol factory process 53 , and communicate with the other mobile nodes 12 using a mobile IPv6 protocol resource 55.
- the executable processes 30 also include a robot factory process 54 (in the application layer 32) configured for instantiating a Java-based robot object 56 (in the Java layer 34) for each smart world object 110 in the world object database 100; hence, each smart world object 110 has a corresponding robot object 56.
- Each robot object 56 includes a motor complex 58, a locator process 60, and a sensor process 62.
- the robot object 56 is not associated with the processes 50 or 52, and is not involved with the brain 112; rather, the robot object 56 is a smart world object 110 that is populated into the database 100 by the robot factory 54 when the system starts, and which interacts with the brain object 112 via force vectors, velocity vectors and/or position vectors.
- Figure 9 is a diagram illustrating operations by the robot object 56 and the brain 112 in deciding and implementing decisions and directives.
- the robot object 56 retrieves a three- dimensional velocity vector 64 from its smart world object 110; if the velocity vector 64 has a nonzero value, the robot object 56 reacts to the velocity vector 64 by attempting to repositioning itself to minimize the velocity vector.
- the robot object 56 retrieves from its smart world object 110 a location object 66 that specifies the location of the robot object 56 and an orientation object 68 that specifies the orientation of the robot object: the robot object 56 updates the location object 66 and the orientation object 68 in the smart world object 100.
- the robot object 56 interacts with its smart world object 110 by obtaining a vector for velocity, attempting to move in the direction and speed specified by the velocity vector by outputting movement directives to the mobility platform 22, and updating its resulting location and orientation in the smart world object 110.
- the robot object 56 does not interact directly with the brain 112, and is not otherwise aware of the world 106 or world objects 104.
- the motor complex 58 interacts with its associated control systems in the mobility platform by outputting movement directives to effect the changes specified by the corcesponding velocity vector; the locator process 60 and sensors process 62 interact with the mobility platform via the interface 24 to determine the resulting effect of the motor complex 58 in implementing the velocity vector.
- the locator process 60 interacts with the location element 23 to identify the location of the mobile node 12.
- the brain 112 is a Java-based executable in the Java layer34 and is configured for operating within a prescribed time cycle (i.e., a "thought interval"), for example every ten (10) seconds.
- the brain 112 considers the advice of all its reactions; as illustrated in Figure 9, the brain 112 solicits advice from each of its reactions 114a, 114b, 114c, 114d, etc.. Based on the set of reactions 114a, 114b, and 114c configured for the brain 114 for the given robot 56, each of the reactions 114a, 114b, and 114c supply corresponding advice elements (Al , A2, and A3) to the brain 112 as far as the corresponding action that should be earned out.
- corresponding advice elements Al , A2, and A3
- the brain 112 applies any necessary influence factor (S 1 , S2, S3) to the respective advice elements (Al , A2, A3), and forms a "decision" (i.e., behavior) in the form of a new force vector (Fv) in the smart world object 110.
- the brain 112 may have a constraint such as a maximum length of a vector that can be effected during any thought interval. Hence, the brain 112 needs to determine how to logically divide the maximum length among all the reactions 1 14 using their respective influence factors.
- the reactive brain 134 first sorts the reactions by their influence, and then scales the reactions by their influence; the scaled reactions are then accumulated, in their sorting order (highest influence summed first), until the maximum vector constraint is reached.
- each reaction 114 e.g., 114a
- the cohesion reaction 114c may look at the current location object 66 (updated by the locator process 60) and/or the orientation object 68, plus signal strength or hop count objects to determine whether the robot 56 should move closer to (or further from) any one of the other mobile nodes 12.
- the world object database 100 provides an object oriented model of all information necessary for the brain 112 (e.g., as illustrated in Figure 9) to reach decisions in the time domain, and for the robot 56 to implement the decisions. Within certain thought intervals, the brain 112 decides what decision needs to be made based on the received opinions (Al, A2, A3) from the associated reactions 114.
- the brain 112 would reconcile between conflicting opinions (e.g., avoiding a location to prevent destruction versus turning toward the location to improve signal reception).
- the brain 112 communicates its decision in the form of a force vector (Fv) which is stored in its smart world object 110 for use by another smart world object 110 (not shown) in modifying the velocity vector 64; alternately, the force vector (Fv) may be applied (e.g., added) directly to the stored velocity vector 64, resulting in an updated velocity vector 64.
- the force vector may directly applied, for example in the case of a robot 56 having a motor complex 58 configured for controlling a mechanical device configured for exerting a specified force.
- the force vector is applied as needed based on the relevant transformation matrix (e.g., 130a) for a given world object.
- a world factory 70 in the application layer 32 boots the system 30 into an initial state containing at least one smart world object 110, its brain 112 and associated reactions 114.
- the reactions 1 14 are abstract and universal, and world objects have transformations and vector maps.
- the reaction "obstacle avoidance” in the physical world a physical wall or other structure may be detected by a sonar or other sensor at a distance of 100 meters at a bearing of 350 degrees relative to the front of the moving node 12; the "obstacle avoidance" reaction would likely issue an opinion to move away from the structure.
- the obstacle avoidance reaction may detect the structure as a null point in the RF field.
- the obstacle avoidance reaction is concerned, whether the sensor is detecting physical space or RF space is irrelevant; rather, the obstacle avoidance reaction is issuing an opinion to avoid an "obstacle" in the world, where the obstacle may map to different manifestations depending on the world (e.g, structure in physical space or RF null point in RF space).
- Another feature of the reactions 114 is that they are general-purpose processes for performing low-level decisions that are evaluated by the brain 112.
- a world in RF space can be transformed between any of the other worlds 106 (physical space, hop count space, RF space, bandwidth, network address, etc.).
- multiple layers of transformations may exist including a basic transformation level that is contained within each world object 104.
- the world 106 is a kind of world object 104 that can contain world objects and has a vector transformation (e.g., coordinate transformation).
- routing objects 140 are a type of brain 112 that update a next-hop routing table within the world object database 100 for a received packet.
- a received packet is routed based on the routing object 140 looking within the world object database 100 for a given objective (e.g., minimum latency); the routing object 140 would look in the latency space to identify the shortest distance to determine the next hop.
- the opinion Fv generated by the brain 112 is distributed to the appropriate object based on its association within the world object database.
- FIG. 10 is a diagram illustrating steps performed by the mobile node 12 in implementing autonomous organization of the mobile network 10, according to an embodiment of the present invention.
- the steps and operations described herein with respect to Figures 1-10 can be implemented as executable code stored on a computer readable medium (e.g., floppy disk, hard disk, NVRAM, EEPROM, CD-ROM, etc.), or propagated via a computer readable transmission medium (e.g., fiber optic cable, electrically-conductive transmission line medium, wireless electromagnetic medium, etc.).
- a computer readable medium e.g., floppy disk, hard disk, NVRAM, EEPROM, CD-ROM, etc.
- a computer readable transmission medium e.g., fiber optic cable, electrically-conductive transmission line medium, wireless electromagnetic medium, etc.
- the world factory 70 initializes the world object database 100 in step 200.
- the protocol factory 53 starts in step 202 an adjacency/neighbor discovery protocol process 50 and the world distribution protocol (i.e., world object exchange protocol) process 52.
- the robot factory 54 constructs in step 204 the robot process 56, and associates the robot process 56 with itself (i.e
- each of the processes operate independently 50, 52, and 56 of each other.
- the adjacency protocol process 50 monitors for new neighboring network nodes using prescribed discovery operations (e.g., via Mobile IPv6 protocol): if in step 206 the adjacency protocol process 50 detects a new neighbor, the adjacency protocol process 50 adds in step 208 world objects that describe the neighboring network node 12; the world objects describing the neighboring network node are added to a neighbor database 210.
- the neighbor database 210 is part of the world object database 100.
- the adjacency protocol process 50 detects in step 212 that an existing neighbor is lost (e.g., an identifying wireless signal cannot be detected by any network node for a neighbor identified in the neighbor database 210 after a prescribed interval)
- the adjacency protocol process 50 removes the neighbor from the neighbor database 210 in step 214, and sends a request for the world factory 70 to remove the world objects 104 associated with the lost neighbor.
- the adjacency protocol process 50 establishes a network topology based on populating and maintaining the neighbor database 210 with world objects 104 associated with the neighboring network nodes.
- the world object exchange protocol process 52 monitors for changes detected in the world object database 100.
- the world object exchange protocol process 52 In response to detecting in step 220 a change in the world object database 100, the world object exchange protocol process 52 sends in step 222 the changed object to the neighbors specified in the neighbor database 210. If in step 224 a new neighbor is detected in the neighbor database 210, the world object exchange protocol process 52 sends the world object database 100 in step 226 to the new neighbor. If in step 228 the world object exchange protocol process 52 detects reception of a new world object from a neighboring network node 12 (i.e., a remote world object), the world object exchange protocol process 52 sends a request in step 230 for the world factory 70 to add the remote world object to the world object database 100.
- a neighboring network node 12 i.e., a remote world object
- the robot factory 54 initializes robot objects 56 in step 204, and the brain objects 112 begin periodic generation of behaviors based on received advice from reactions 114. For example, if in step 240 the robot object 56 detects a change in the velocity vector object 64 (see, e.g., Figure 9), the robot object 56 may attempt to move in step 242 using its motor complex 58; if in step 244 the robot object 56 detects a change in the location of the mobile node 12 relative to the location object 66, the robot object 56 updates in step 246 the location object 66 stored in the world object database 100.
- step 248 the sensors process 62 of the robot process 56 detect an obstacle (e.g., based on prescribed signals from proximity sensors or radar signals exceeding a prescribed threshold)
- the robot object 56 sends a request in step 250 for the world factory 70 to insert an obstacle object in the world object database.
- various reactions e.g., evade 114d, avoidance 114g, etc.
- mobile nodes as mobile access points can autonomously move about a given area (i.e., an infosphere) based on identifying an optimal location relative to topological information, network topology information, and link layer information.
- each network node is a non-mobile node (i.e., fixed node), where a change implemented by a network node according to the disclosed embodiment may involve changing from using a local area network (LAN) interface to a wide area network (WAN) interface, or changing a logical operation such as changing a next-hop route in order to change hop count attributes.
- LAN local area network
- WAN wide area network
Abstract
Description
Claims
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CN2004800258751A CN1902623B (en) | 2003-10-07 | 2004-10-04 | Arrangement for autonomous mobile network nodes to organize a wireless mobile network based on detected physical and logical changes |
CA002537946A CA2537946A1 (en) | 2003-10-07 | 2004-10-04 | Arrangement for autonomous mobile network nodes to organize a wireless mobile network based on detected physical and logical changes |
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CN1902623A (en) | 2007-01-24 |
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WO2005039151A3 (en) | 2006-09-14 |
AU2004306838A1 (en) | 2005-04-28 |
EP1673928A2 (en) | 2006-06-28 |
US8527457B2 (en) | 2013-09-03 |
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