KR20230149704A - Method, apparatus and computer program for finding possible destinations from a plurality of departure nodes - Google Patents

Abstract

A method may be provided in which a computing device obtains a reachable destination using a cost less than a threshold cost from each of N (N is a natural number) starting nodes on a map database including nodes and links. The method includes creating an instance to search a route for each of N starting nodes; Creating a Visit Count List in which the number of instances visited on a node is recorded; recording visit information of instances to nodes in the visit count list, and searching a path until each instance reaches a maximum search range; and obtaining nodes visited by all N instances based on the visit count list, and determining the obtained nodes as destinations. may include.

Description

Method, apparatus, and computer program for finding possible destinations from a plurality of departure nodes {METHOD, APPARATUS AND COMPUTER PROGRAM FOR FINDING POSSIBLE DESTINATIONS FROM A PLURALITY OF DEPARTURE NODES}

This disclosure relates to a method of finding destinations connected from a plurality of starting nodes. Specifically, it is about a method by which a computing device obtains a reachable destination using a cost less than a threshold cost from each of N (N is a natural number) starting nodes on a map database including nodes and links.

When making an appointment, the biggest concern is location. Because users depart from different locations and use different means of transportation, it is difficult to find the optimal meeting place considering time. To solve this problem, map data is being used.

Map data consists of nodes and links. Additionally, the link is provided with information about traffic conditions. Research continues on technology to find the optimal meeting point at each of multiple departure locations, taking into account information about traffic conditions.

Registered Patent No. 1538042 provides a method for searching a route.

The present disclosure has been made in response to the above-described background technology, and is a method in which a computing device can arrive using a cost less than a threshold cost from each of N (N is a natural number) starting nodes on a map database including nodes and links. We want to provide a method to obtain the destination.

In order to solve the above-mentioned problem, a method is provided in which a computing device obtains a reachable destination using a cost less than the threshold cost from each of N (N is a natural number) starting nodes on a map database containing nodes and links. It can be. This method includes creating an instance to search a route for each of N starting nodes; Creating a Visit Count List in which the number of instances visited on a node is recorded; recording visit information of instances to nodes in the visit count list, and searching a path until each instance reaches a maximum search range; and obtaining nodes visited by all N instances based on the visit count list, and determining the obtained nodes as destinations; Includes, the cost is a value calculated by weight information assigned to the link connecting the nodes, and the maximum search range may be the range of nodes where the cost used by the instance to visit the node is less than or equal to the threshold cost.

Alternatively, the method may include obtaining target count information; Further comprising, based on the visit count list, obtaining nodes visited by N instances and determining the obtained nodes as destinations: the number of nodes visited by N instances is target number information determining whether the number is less than the number indicated by; If the determined number of destinations is less than the number indicated by information on the number of destinations, increasing the threshold cost and maximum search range; recording visit information of an instance for a node in the visit count list, and based on the increased maximum search range, searching a path until each instance reaches the increased maximum search range; and acquiring nodes visited by N instances based on the visit count list, and determining the obtained nodes as destinations; It may further include.

Alternatively, the computing device may be configured to search the path until each instance reaches the increased maximum search range, wherein the step of exploring the path is based on the maintained computational information, wherein the computational information includes: Visit flag data indicating whether a node has been reached; Arrival information data indicating which path the instance took to reach the node; and Queue state data, which holds information about the set of nodes and the cost to reach them. It may include at least one of:

Alternatively, the computing device monitors whether the number of nodes visited by all N instances in real time is greater than or equal to the number indicated by the target number information, and when the number of nodes visited by the N instances is greater than or equal to the number indicated by the target number information. , you can end searching the route.

Alternatively, increasing the threshold cost and the maximum search range may increase the degree of increasing the critical cost for at least one of the instances to a different degree than the degree of increasing the critical cost for the other instances. there is.

Alternatively, the computing device may provide an interface for the user to select location group information, and the node that the instance visits may be determined based on information entered in response to the provided interface.

Alternatively, the computing device may obtain information about traffic conditions, and the weight information may be determined based on the obtained information about traffic conditions.

As another embodiment for solving the above-described problem, a computer program stored in a computer-readable storage medium may be provided. The computer program includes instructions that cause one or more processors to obtain a reachable destination using a cost less than or equal to a threshold cost from each of N (N is a natural number) starting nodes on a map database containing nodes and links, , the commands include: creating an instance that searches a route for each of N starting nodes; Creating a Visit Count List in which the number of instances visited on a node is recorded; recording visit information of instances to nodes in the visit count list, and searching a path until each instance reaches a maximum search range; and obtaining nodes visited by all N instances based on the visit count list, and determining the obtained nodes as destinations. Includes, the cost is a value calculated by weight information assigned to the link connecting the nodes, and the maximum search range may be the range of nodes where the cost used by the instance to visit the node is less than or equal to the threshold cost.

According to an embodiment of the present disclosure, a reachable destination can be obtained from each of N departure nodes using a cost less than or equal to the threshold cost.

1 is a diagram for explaining a map database according to an embodiment of the present disclosure.
Figures 2A to 2C are schematic diagrams for explaining a method of obtaining a destination according to an embodiment of the present disclosure.
FIG. 3 is a diagram for explaining a computing device 100 according to an embodiment of the present disclosure.
Figure 4 is a diagram for explaining a method of obtaining a destination according to an embodiment of the present disclosure.
FIG. 5 is a diagram illustrating in more detail a method of obtaining nodes visited by all N instances and determining the obtained nodes as destinations, based on a visit count list, according to an embodiment of the present disclosure.
6 is a schematic, general schematic diagram of an example computing environment in which embodiments of the present disclosure may be implemented.

Various embodiments are now described with reference to the drawings. In this specification, various descriptions are presented to provide an understanding of the disclosure. However, it is clear that these embodiments may be practiced without these specific descriptions.

As used herein, the terms “component,” “module,” “system,” and the like refer to a computer-related entity, hardware, firmware, software, a combination of software and hardware, or an implementation of software. For example, a component may be, but is not limited to, a process running on a processor, a processor, an object, a thread of execution, a program, and/or a computer. For example, both an application running on a computing device and the computing device can be a component. One or more components may reside within a processor and/or thread of execution. A component may be localized within one computer. A component may be distributed between two or more computers. Additionally, these components can execute from various computer-readable media having various data structures stored thereon. Components can transmit signals, for example, with one or more data packets (e.g., data and/or signals from one component interacting with other components in a local system, a distributed system, to other systems and over a network such as the Internet). Depending on the data being transmitted, they may communicate through local and/or remote processes.

Additionally, the term “or” is intended to mean an inclusive “or” and not an exclusive “or.” That is, unless otherwise specified or clear from context, “X utilizes A or B” is intended to mean one of the natural implicit substitutions. That is, either X uses A; X uses B; Or, if X uses both A and B, “X uses A or B” can apply to either of these cases. Additionally, the term “and/or” as used herein should be understood to refer to and include all possible combinations of one or more of the related listed items.

Additionally, the terms “comprise” and/or “comprising” should be understood to mean that the corresponding feature and/or element is present. However, the terms “comprise” and/or “comprising” should be understood as not excluding the presence or addition of one or more other features, elements and/or groups thereof. Additionally, unless otherwise specified or the context is clear to indicate a singular form, the singular terms herein and in the claims should generally be construed to mean “one or more.”

And, the term “at least one of A or B” should be interpreted to mean “if it contains only A,” “if it contains only B,” or “if it is a combination of A and B.”

Those skilled in the art will additionally recognize that the various illustrative logical blocks, components, modules, circuits, means, logic, and algorithm steps described in connection with the embodiments disclosed herein may be implemented using electronic hardware, computer software, or a combination of both. It must be recognized that it can be implemented with To clearly illustrate the interchangeability of hardware and software, various illustrative components, blocks, configurations, means, logics, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented in hardware or software will depend on the specific application and design constraints imposed on the overall system. A skilled technician can implement the described functionality in a variety of ways for each specific application. However, such implementation decisions should not be construed as causing a departure from the scope of the present disclosure.

The description of the presented embodiments is provided to enable anyone skilled in the art to use or practice the present invention. Various modifications to these embodiments will be apparent to those skilled in the art. The general principles defined herein may be applied to other embodiments without departing from the scope of the disclosure. Therefore, the present invention is not limited to the embodiments presented herein. The present invention is to be interpreted in the broadest scope consistent with the principles and novel features presented herein.

1 is a diagram for explaining a map database according to an embodiment of the present disclosure.

According to one embodiment of the present disclosure, a map database may be composed of nodes and links.

Here, the node may represent a place where a change in speed occurs as the vehicle drives on the road. Specifically, a node may represent an intersection, an overpass start and end point, a road start and end point, an underpass start and end point, a tunnel start and end point, an administrative boundary, etc., but is not limited thereto.

Additionally, a link may mean a line connecting a node, which is a point at which a speed change occurs, and may represent a road in reality. Specifically, the link may represent a road, bridge, overpass, underpass, tunnel, etc., but is not limited thereto.

According to an embodiment of the present disclosure, weight information may be assigned to a link. Weight information represents the cost used in the link, and the computing device 100 may assign weight information to the link in advance. Additionally, the computing device 100 may obtain information on traffic conditions and determine weight information based on the obtained information on traffic conditions. Specifically, the computing device 100 may assign a high weight value to a link that matches a road with high traffic congestion. In this case, the computing device 100 may update the weight value in predetermined time units (eg, 5 minutes, etc.). As another embodiment, the computing device 100 may update weight values according to traffic conditions in response to user input.

According to one embodiment of the present disclosure, the cost for a path from node to node can be calculated. For example, referring to Figure 1, the path from node a1 to node a3 must pass through link 1 and link 2. If the weight value of link 1 is (Wo) and the weight value of link 2 is (W1), the cost used in the path from node (a1) to node (a3) is the weight value assigned to link 1 (Wo) and It may be the sum of the weight values (W1) assigned to Link 2. In addition, according to another embodiment, the cost used in the path from node (a1) to node (a3) is determined by calculating the weight value (Wo) assigned to link 1 and the weight value (W1) assigned to link 2 using a predetermined calculation formula. It may be an output value output after input, but is not limited to this.

Figures 2A to 2C are schematic diagrams for explaining a method of obtaining a destination according to an embodiment of the present disclosure.

Referring to FIG. 2A according to an embodiment of the present disclosure, the computing device 100 may acquire a plurality of starting nodes. For example, when a plurality of users use the computing device 100 to make an appointment, the computing device 100 may obtain the current locations of the plurality of users as departure nodes. Additionally, the computing device 100 may provide an interface through which a user can select a location, and may determine starting nodes based on location information input by the user in response to the provided interface.

Referring to FIG. 2B according to an embodiment of the present disclosure, the computing device 100 may search for a destination while performing a predetermined algorithm for each of the starting nodes within the maximum search range. Additionally, the computing device 100 may record nodes commonly visited by instances of each starting node while searching for a destination.

Additionally, if there is no predetermined number of destinations within the maximum search range, the computing device 100 may increase the maximum search range and then continue searching for the destination. In this case, the resources of the computing device 100 can be reduced by maintaining existing search process data.

Referring to FIG. 2C according to an embodiment of the present disclosure, the computing device 100 may end the search activity when a predetermined number of destinations are obtained. By searching for a destination (eg, a meeting place) through these processes, the computing device 100 can provide an optimal meeting place to a plurality of users.

Hereinafter, a method for obtaining a destination according to an embodiment of the present disclosure will be described in more detail.

FIG. 3 is a diagram for explaining a computing device 100 according to an embodiment of the present disclosure.

In one embodiment of the present disclosure, the computing device 100 may include different configurations for performing the computing environment of the computing device 100, and only some of the disclosed configurations may configure the computing device 100.

The computing device 100 may include a processor 110, a memory 130, and a network unit 150.

The processor 110 may be composed of one or more cores, and may include a central processing unit (CPU), a general purpose graphics processing unit (GPGPU), and a tensor processing unit (TPU) of a computing device. unit) may include a processor for data analysis and deep learning. The processor 110 may read a computer program stored in the memory 130 and perform data processing for machine learning according to an embodiment of the present disclosure. According to an embodiment of the present disclosure, the processor 110 may perform an operation for learning a neural network. The processor 110 is used for learning neural networks, such as processing input data for learning in deep learning (DL), extracting features from input data, calculating errors, and updating the weights of the neural network using backpropagation. Calculations can be performed. At least one of the CPU, GPGPU, and TPU of the processor 110 may process learning of the network function. For example, CPU and GPGPU can work together to process learning of network functions and data classification using network functions. Additionally, in one embodiment of the present disclosure, the processors of a plurality of computing devices can be used together to process learning of network functions and data classification using network functions. Additionally, a computer program executed in a computing device according to an embodiment of the present disclosure may be a CPU, GPGPU, or TPU executable program.

According to an embodiment of the present disclosure, the memory 130 may store any type of information generated or determined by the processor 110 and any type of information received by the network unit 150.

According to an embodiment of the present disclosure, the memory 130 is a flash memory type, hard disk type, multimedia card micro type, or card type memory (e.g. (e.g. SD or -Only Memory), and may include at least one type of storage medium among magnetic memory, magnetic disk, and optical disk. The computing device 100 may operate in connection with web storage that performs a storage function of the memory 130 on the Internet. The description of the memory described above is merely an example, and the present disclosure is not limited thereto.

The network unit 150 according to an embodiment of the present disclosure includes Public Switched Telephone Network (PSTN), x Digital Subscriber Line (xDSL), Rate Adaptive DSL (RADSL), Multi Rate DSL (MDSL), and VDSL ( A variety of wired communication systems can be used, such as Very High Speed DSL), Universal Asymmetric DSL (UADSL), High Bit Rate DSL (HDSL), and Local Area Network (LAN).

In addition, the network unit 150 presented in this specification includes Code Division Multi Access (CDMA), Time Division Multi Access (TDMA), Frequency Division Multi Access (FDMA), Orthogonal Frequency Division Multi Access (OFDMA), and SC-FDMA ( A variety of wireless communication systems can be used, such as Single Carrier-FDMA) and other systems.

In the present disclosure, the network unit 150 may be configured regardless of the communication mode, such as wired or wireless, and may be composed of various communication networks such as a personal area network (PAN) and a wide area network (WAN). You can. Additionally, the network may be the well-known World Wide Web (WWW), or may use wireless transmission technology used for short-distance communication, such as Infrared Data Association (IrDA) or Bluetooth.

The computing device 100 of the present disclosure can obtain a reachable destination using a cost less than or equal to the threshold cost from each of N starting nodes on a map database including nodes and links. Hereinafter, it will be described in detail with reference to FIGS. 4 and 5.

Figure 4 is a diagram for explaining a method of obtaining a destination according to an embodiment of the present disclosure.

In step S410, the computing device 100 may create an instance that searches a route for each of the N starting nodes.

According to an embodiment of the present disclosure, the computing device 100 may create an instance to search a route for each of N starting nodes. An instance may refer to an object in an object-oriented program, but is not limited to this.

For example, when there are N departure nodes, the computing device 100 may search for an instance of a destination for a first departure node, an instance of searching a destination for a second departure node, and an instance of searching a destination for a third departure node. Instances that do... ., an instance searching for a destination for the N-1th starting node and an instance searching for a destination for the Nth starting node can be created.

In step S420, the computing device 100 may generate a visit count list in which the number of instances that visit the node is recorded.

According to an embodiment of the present disclosure, the Visit Count List may hold information about the number of instances that have visited a node. For example, when N instances are created for N starting nodes, the Visit Count List may hold information about how many of the N instances visited the node.

In step S430, the computing device 100 records visit information of instances to nodes in the visit count list, and may search a path until each instance reaches the maximum search range.

According to one embodiment of the present disclosure, computing device 100 may have a threshold cost. The threshold cost is the upper limit of the predetermined cost. Computing device 100 may hold the critical cost in the form of a specific value, and may hold the critical cost in the form of time, but is not limited thereto.

Additionally, the maximum search range refers to the range of nodes where the cost used by an instance to visit a node is less than or equal to the threshold cost.

For example, if the critical cost is 10, the maximum search range refers to nodes that can be arrived at by consuming a cost of less than 10 starting from the starting node. For another example, if the critical cost is 10 seconds, the maximum search range refers to nodes that can be reached by spending less than 10 seconds starting from the starting node.

According to an embodiment of the present disclosure, the computing device 100 records visit information of instances of nodes in a visit count list, and may search a path until each instance reaches the maximum search range.

Specifically, if the critical cost is 10, the computing device 100 can sequentially visit nodes that can be reached by consuming a cost of less than 10 from the starting node. For example, if there is a first node that can be reached by consuming a cost of 1, a second node that can be reached by consuming a cost of 5, and a third node that can be reached by consuming a cost of 7, the instance is the first node and the third node that can be reached by consuming a cost of 7. We will visit node 2 and node 3 sequentially. In this case, when the instance visits the first node, second node, and third node, the computing device 100 may record information that the instance visited the node in the visit count list. In this case, if a plurality of instances are created, the computing device 100 may record all information about nodes visited by the plurality of instances in the visit count list.

In step S440, the computing device 100 may obtain nodes visited by all N instances based on the visit count list and determine the obtained nodes as destinations.

According to an embodiment of the present disclosure, the visit count list may hold information about how many instances have visited a specific node.

Based on the information recorded in the visit count list, the computing device 100 can obtain nodes that have been visited by all N instances created for each of the N starting nodes, and determine the obtained nodes as destinations.

FIG. 5 is a diagram illustrating in more detail a method of obtaining nodes visited by all N instances and determining the obtained nodes as destinations, based on a visit count list, according to an embodiment of the present disclosure.

According to an embodiment of the present disclosure, the computing device 100 may obtain target number information. The target number information is information about the number of destinations to be searched, and the computing device 100 can obtain the target number information based on information input from the user, and can hold the target number information in advance, and is limited to this. It doesn't work.

In step S441, the computing device 100 may determine whether the number of nodes visited by the N instances is less than the number indicated by the target number information.

For example, if the target number information indicates 3 and the number of nodes visited by all N instances is 2, the computing device 100 may determine that the number of nodes visited by the N instances is less than the target number information. .

In step S443, the computing device 100 may increase the threshold cost and maximum search range when the determined number of destinations is less than the number indicated by information on the number of destinations.

For example, if the target number information indicates 3, the threshold cost is 10, and there are 2 nodes in the maximum search range that are visited by all N instances, computing device 100 increases the threshold cost to 20, and the increased The maximum search range can be increased depending on the critical cost.

Additionally, if the target number information indicates 3 and the threshold cost is 10 seconds, and there are 2 nodes visited by all N instances in the based maximum search range, computing device 100 increases the threshold cost to 20 seconds and the increased threshold The maximum search range can be increased depending on the cost. In this case, the degree of increased critical cost may be predetermined and may be selected by the user, but is not limited thereto.

According to another embodiment of the present disclosure, the degree of increased critical cost may be determined differently for each instance.

Specifically, the degree to which the critical cost is increased for at least one of the instances may be different from the degree to which the critical cost is increased for other instances.

For example, if a first user, a second user, and a third user wish to meet and have a meeting location relatively close to the first user, computing device 100 may determine an increasing threshold cost of matching the first user. By setting the degree (the degree of the critical cost increased for an instance of the first user's starting node) to be smaller than the degree of the critical cost increased for other instances, it is possible to obtain a destination close to the first user. .

In this case, the computing device 100 may provide an interface for selecting at least one user who wants a relatively nearby location, and may determine the degree of increase in the critical cost based on selection information input in response to the provided interface. there is.

Specifically, the computing device 100 may select a user based on selection information input in response to an interface provided to the user (hereinafter, at least one user may be selected, hereinafter referred to as A). The computing device 100 can obtain a destination close to the selected users by setting the degree of the increased critical cost for the instance created for A to be smaller than the degree of the increased critical cost for other instances. .

In step S445, computing device 100 records the visit information of the instance for the node in the visit count list and, based on the increased maximum search range, routes each instance until it reaches the increased maximum search range. You can explore.

According to one embodiment of the present disclosure, the computing device 100 records visit information of instances to nodes in a visit count list, and may search a path until each instance reaches an increased maximum search range. .

In this case, computing device 100 may maintain existing calculation information. The calculation information includes visit flag data that indicates whether the instance reached a node during navigation, arrival information data that indicates which path the instance took to reach the node, and the node and the cost to reach the node. It may include at least one of queue state data holding information about the set, but is not limited thereto.

According to an embodiment of the present disclosure, the computing device 100 can improve the efficiency of an algorithm for finding a destination by searching by expanding the maximum search range while maintaining existing calculation information.

In step S447, the computing device 100 may acquire nodes visited by N instances based on the visit count list and determine the obtained nodes as destinations.

According to an embodiment of the present disclosure, the visit count list may hold information about how many instances have visited a specific node.

Based on the information recorded in the visit count list, the computing device 100 can obtain nodes that have been visited by all N instances created for each of the N starting nodes, and determine the obtained nodes as destinations.

According to another embodiment of the present disclosure, despite searching based on the increased maximum search range, nodes (here, nodes refer to nodes visited by N instances) exceeding the number indicated by the target number information are not obtained. If not, the critical cost and maximum search range can be increased again according to step S443, and the path can be searched according to step S445 based on the increased maximum search range again. In this case, the computing device 100 may repeat steps S443 and S445 until it obtains more nodes than the number indicated by the target number information (here, nodes mean nodes visited by N instances). there is.

According to another embodiment of the present disclosure, the computing device 100 monitors in real time whether the number of nodes visited by all N instances is greater than or equal to the number indicated by the target number information, and the number of nodes visited by the N instances is set to the target number. If the number is greater than the number indicated by the number information, the path search can be terminated. Specifically, the computing device 100 searches the path if it determines that the number of nodes visited by all N instances is greater than or equal to the number indicated by the target number information, even before the search range of the instance reaches the maximum search range. You can terminate the process and determine the obtained nodes as destinations.

Additionally, the computing device 100 may provide the determined destinations to the user.

According to another embodiment of the present disclosure, when providing the method according to FIGS. 4 and 5, the computing device 100 provides the user with an interface for selecting place group information, and information input in response to the provided interface. Based on this, the node that the instance visits can be determined.

Specifically, the computing device 100 may provide the user with an interface to select a location such as a cafe, restaurant, entertainment facility, or movie theater, and obtain selection information selected by the user in response to the provided interface. Based on the selection information, the computing device 100 may determine nodes to be searched.

Specifically, assuming that the user selects a cafe, the computing device 100 may perform the method of obtaining a destination according to the above description by targeting only nodes that match the cafe.

6 is a schematic, general schematic diagram of an example computing environment in which embodiments of the present disclosure may be implemented.

Although the present disclosure has generally been described above as being capable of being implemented by a computing device, those skilled in the art will understand that the present disclosure can be implemented in combination with computer-executable instructions and/or other program modules that can be executed on one or more computers and/or in hardware and software. It will be well known that it can be implemented as a combination.

Typically, program modules include routines, programs, components, data structures, etc. that perform specific tasks or implement specific abstract data types. Additionally, those skilled in the art will understand that the methods of the present disclosure are applicable to single-processor or multiprocessor computer systems, minicomputers, mainframe computers, as well as personal computers, handheld computing devices, microprocessor-based or programmable consumer electronics, etc. It will be appreciated that each of these may be implemented in other computer system configurations, including those capable of operating in conjunction with one or more associated devices.

The described embodiments of the disclosure can also be practiced in distributed computing environments where certain tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

Computers typically include a variety of computer-readable media. Computer-readable media can be any medium that can be accessed by a computer, and such computer-readable media includes volatile and non-volatile media, transitory and non-transitory media, removable and non-transitory media. Includes removable media. By way of example, and not limitation, computer-readable media may include computer-readable storage media and computer-readable transmission media. Computer-readable storage media refers to volatile and non-volatile media, transient and non-transitory media, removable and non-removable, implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Includes media. Computer readable storage media may include RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital video disk (DVD) or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage. This includes, but is not limited to, a device, or any other medium that can be accessed by a computer and used to store desired information.

A computer-readable transmission medium typically implements computer-readable instructions, data structures, program modules, or other data on a modulated data signal, such as a carrier wave or other transport mechanism. Includes all information delivery media. The term modulated data signal refers to a signal in which one or more of the characteristics of the signal have been set or changed to encode information within the signal. By way of example, and not limitation, computer-readable transmission media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared, and other wireless media. Combinations of any of the above are also intended to be included within the scope of computer-readable transmission media.

An example environment 1100 is shown that implements various aspects of the present disclosure, including a computer 1102, which includes a processing unit 1104, a system memory 1106, and a system bus 1108. do. System bus 1108 couples system components, including but not limited to system memory 1106, to processing unit 1104. Processing unit 1104 may be any of a variety of commercially available processors. Dual processors and other multiprocessor architectures may also be used as processing unit 1104.

System bus 1108 may be any of several types of bus structures that may further be interconnected to a memory bus, peripheral bus, and local bus using any of a variety of commercial bus architectures. System memory 1106 includes read only memory (ROM) 1110 and random access memory (RAM) 1112. The basic input/output system (BIOS) is stored in non-volatile memory 1110, such as ROM, EPROM, and EEPROM, and is a basic input/output system that helps transfer information between components within the computer 1102, such as during startup. Contains routines. RAM 1112 may also include high-speed RAM, such as static RAM, for caching data.

Computer 1102 may also include an internal hard disk drive (HDD) 1114 (e.g., EIDE, SATA)—the internal hard disk drive 1114 may also be configured for external use within a suitable chassis (not shown). Yes - a magnetic floppy disk drive (FDD) 1116 (e.g., for reading from or writing to a removable diskette 1118), and an optical disk drive 1120 (e.g., a CD-ROM for reading the disk 1122 or reading from or writing to other high-capacity optical media such as DVDs). Hard disk drive 1114, magnetic disk drive 1116, and optical disk drive 1120 are connected to system bus 1108 by hard disk drive interface 1124, magnetic disk drive interface 1126, and optical drive interface 1128, respectively. ) can be connected to. The interface 1124 for implementing an external drive includes at least one or both of Universal Serial Bus (USB) and IEEE 1394 interface technologies.

These drives and their associated computer-readable media provide non-volatile storage of data, data structures, computer-executable instructions, and the like. For computer 1102, drive and media correspond to storing any data in a suitable digital format. Although the description of computer-readable media above refers to removable optical media such as HDDs, removable magnetic disks, and CDs or DVDs, those skilled in the art will also recognize removable optical media such as zip drives, magnetic cassettes, flash memory cards, cartridges, etc. It will be appreciated that other types of computer-readable media, such as the like, may also be used in the example operating environment and that any such media may contain computer-executable instructions for performing the methods of the present disclosure.

A number of program modules may be stored in drives and RAM 1112, including an operating system 1130, one or more application programs 1132, other program modules 1134, and program data 1136. All or portions of the operating system, applications, modules and/or data may also be cached in RAM 1112. It will be appreciated that the present disclosure may be implemented on various commercially available operating systems or combinations of operating systems.

A user may enter commands and information into computer 1102 through one or more wired/wireless input devices, such as a keyboard 1138 and a pointing device such as mouse 1140. Other input devices (not shown) may include microphones, IR remote controls, joysticks, game pads, stylus pens, touch screens, etc. These and other input devices are connected to the processing unit 1104 through an input device interface 1142, which is often connected to the system bus 1108, but may also include a parallel port, an IEEE 1394 serial port, a game port, a USB port, an IR interface, It can be connected by other interfaces, etc.

A monitor 1144 or other type of display device is also connected to system bus 1108 through an interface, such as a video adapter 1146. In addition to monitor 1144, computers typically include other peripheral output devices (not shown) such as speakers, printers, etc.

Computer 1102 may operate in a networked environment using logical connections to one or more remote computers, such as remote computer(s) 1148, via wired and/or wireless communications. Remote computer(s) 1148 may be a workstation, computing device computer, router, personal computer, portable computer, microprocessor-based entertainment device, peer device, or other conventional network node, and is generally connected to computer 1102. For simplicity, only memory storage device 1150 is shown, although it includes many or all of the components described. The logical connections depicted include wired/wireless connections to a local area network (LAN) 1152 and/or a larger network, such as a wide area network (WAN) 1154. These LAN and WAN networking environments are common in offices and companies and facilitate enterprise-wide computer networks, such as intranets, all of which can be connected to a worldwide computer network, such as the Internet.

When used in a LAN networking environment, computer 1102 is connected to local network 1152 through wired and/or wireless communication network interfaces or adapters 1156. Adapter 1156 may facilitate wired or wireless communication to LAN 1152, which also includes a wireless access point installed thereon for communicating with wireless adapter 1156. When used in a WAN networking environment, the computer 1102 may include a modem 1158 or be connected to a communicating computing device on the WAN 1154 or to establish communications over the WAN 1154, such as via the Internet. Have other means. Modem 1158, which may be internal or external and a wired or wireless device, is coupled to system bus 1108 via serial port interface 1142. In a networked environment, program modules described for computer 1102, or portions thereof, may be stored in remote memory/storage device 1150. It will be appreciated that the network connections shown are exemplary and that other means of establishing a communications link between computers may be used.

Computer 1102 may be associated with any wireless device or object deployed and operating in wireless communications, such as a printer, scanner, desktop and/or portable computer, portable data assistant (PDA), communications satellite, wirelessly detectable tag. Performs actions to communicate with any device or location and telephone. This includes at least Wi-Fi and Bluetooth wireless technologies. Accordingly, communication may be a predefined structure as in a conventional network or may simply be ad hoc communication between at least two devices.

Wi-Fi (Wireless Fidelity) allows connection to the Internet, etc. without wires. Wi-Fi is a wireless technology, like cell phones, that allows these devices, such as computers, to send and receive data indoors and outdoors, anywhere within the coverage area of a base station. Wi-Fi networks use wireless technology called IEEE 802.11 (a, b, g, etc.) to provide secure, reliable, and high-speed wireless connections. Wi-Fi can be used to connect computers to each other, the Internet, and wired networks (using IEEE 802.3 or Ethernet). Wi-Fi networks can operate in the unlicensed 2.4 and 5 GHz wireless bands, for example, at data rates of 11 Mbps (802.11a) or 54 Mbps (802.11b), or in products that include both bands (dual band). .

Those skilled in the art will understand that information and signals may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols and chips that may be referenced in the above description include voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields. It can be expressed by particles or particles, or any combination thereof.

Those skilled in the art will understand that the various illustrative logical blocks, modules, processors, means, circuits and algorithm steps described in connection with the embodiments disclosed herein may be used in electronic hardware, (for convenience) It will be understood that it may be implemented by various forms of program or design code (referred to herein as software) or a combination of both. To clearly illustrate this interoperability of hardware and software, various illustrative components, blocks, modules, circuits and steps have been described above generally with respect to their functionality. Whether this functionality is implemented as hardware or software depends on the specific application and design constraints imposed on the overall system. A person skilled in the art of this disclosure may implement the described functionality in various ways for each specific application, but such implementation decisions should not be construed as departing from the scope of this disclosure.

The various embodiments presented herein may be implemented as a method, apparatus, or article of manufacture using standard programming and/or engineering techniques. The term article of manufacture includes a computer program, carrier, or media accessible from any computer-readable storage device. For example, computer-readable storage media include magnetic storage devices (e.g., hard disks, floppy disks, magnetic strips, etc.), optical disks (e.g., CDs, DVDs, etc.), smart cards, and flash. Includes, but is not limited to, memory devices (e.g., EEPROM, cards, sticks, key drives, etc.). Additionally, various storage media presented herein include one or more devices and/or other machine-readable media for storing information.

It is to be understood that the specific order or hierarchy of steps in the processes presented is an example of illustrative approaches. It is to be understood that the specific order or hierarchy of steps in processes may be rearranged within the scope of the present disclosure, based on design priorities. The appended method claims present elements of the various steps in a sample order but are not meant to be limited to the particular order or hierarchy presented.

The description of the presented embodiments is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments without departing from the scope of the disclosure. Thus, the present disclosure is not limited to the embodiments presented herein but is to be interpreted in the broadest scope consistent with the principles and novel features presented herein.

Claims (1)

A method for a computing device to obtain a reachable destination using a cost less than or equal to a threshold cost from each of a plurality of departure nodes.