CN113179313B - Distributed space-time query method and system - Google Patents

Distributed space-time query method and system Download PDF

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CN113179313B
CN113179313B CN202110449330.9A CN202110449330A CN113179313B CN 113179313 B CN113179313 B CN 113179313B CN 202110449330 A CN202110449330 A CN 202110449330A CN 113179313 B CN113179313 B CN 113179313B
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CN113179313A (en
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夏东
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Hunan Vision Miracle Intelligent Technology Co ltd
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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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/22—Indexing; Data structures therefor; Storage structures
    • G06F16/2228—Indexing structures
    • G06F16/2246—Trees, e.g. B+trees
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2471—Distributed queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
    • G16Y40/00—IoT characterised by the purpose of the information processing
    • G16Y40/10—Detection; Monitoring
    • 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
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]

Abstract

The invention relates to the technical field of data processing of the Internet of things, and discloses a distributed space-time query method and a distributed space-time query system, which are used for improving the efficiency of data storage and query. The method comprises the following steps: a Hilbert curve is adopted to maintain the two-dimensional space where each station server and each sensor terminal are located in a one-dimensional mode; organizing a peer-to-peer structure of the site servers by Chord, allocating an index space, and corresponding a space divided by a Hilbert curve to the corresponding site server; each site server establishes an FSTI multi-branch tree in a memory, generates an R tree in the FSTI multi-branch tree at intervals of tau time, and packages and encapsulates at least two R trees adjacent in time sequence by carrying time information of each storage segment and pointer information of an R tree storage address indicating a corresponding space range; links are then established to the corresponding predecessor and/or successor nodes for querying overlapping and neighboring region data.

Description

Distributed space-time query method and system
Technical Field
The invention relates to the technical field of data processing of the Internet of things, in particular to a distributed space-time query method and a distributed space-time query system.
Background
As wireless communication technologies, positioning technologies, embedded devices, and geographic information systems are rapidly developed and popularized, more and more sensing devices are used in fire sensing and prediction. In the actual deployment of the sensor, the transmission energy consumption and the transmission distance are considered due to the influence of the region range, and the principle of near is mostly adopted when the sensor information is collected, as shown in fig. 1, the sensing information of the region 1 is transmitted to the server of the near station a for storage, and the sensing information of the region 2 is transmitted to the server of the station B for storage. The physical deployment architecture enables the collection nodes to report the sensing information to the relevant monitoring sites in real time by using local nearby advantages, reduces the time delay of wireless transmission of the collection nodes, and can monitor fire in a relatively wide region range.
However, as global applications are continuously developed, more and more applications need to directly perform global fire real-time query, which needs to deliver query requests to all the site databases, and as there is no goal, the distributed query method not only causes resource waste, but also has very low query efficiency, and cannot assist a director in fire research and judgment in an emergency.
Disclosure of Invention
The invention aims to disclose a distributed space-time query method and a distributed space-time query system, which are applied to scenes such as fire research and judgment and the like, and improve the efficiency of data storage and query.
In order to achieve the above object, the present invention discloses a distributed space-time query method, comprising:
adopting a Hilbert curve to carry out one-dimensional operation on two-dimensional spaces where the servers of all stations and the sensor terminals are located;
organizing a peer-to-peer structure of the site servers by Chord, allocating index spaces, and corresponding spaces divided by Hilbert curves to the corresponding site servers;
each site server establishes an FSTI multi-branch tree in a memory, one R tree is generated in the FSTI multi-branch tree every tau time, and at least two R trees adjacent in time sequence are packaged by carrying storage segment time information and pointer information of an R tree storage address indicating a corresponding space range; and then, judging whether an overlapped and adjacent region of the R tree space range exists or not through interaction with a predecessor node and a successor node of Chord, and if the overlapped and adjacent region exists on the space, establishing a link for inquiring data of the overlapped and adjacent region to the corresponding predecessor node and/or successor node.
Preferably, assuming the Hilbert curve as order D, the entire space with sides of length E is divided into 2 2D And if the set of all points in the whole space is P and the set of Hilbert values is V, the mapping H is formed by P → V, wherein P = { (x, y) |0 ≦ x, y ≦ E },
Figure GDA0003902552860000021
preferably, let the Chord key-value space be [0,2 m -1]M =2D, the key-value space is consistent with the set of Hilbert values V.
Preferably, the method of the present invention further comprises: and each site server utilizes the precursor node, the successor node and the routing table of Chord to define the topological relation among the site servers so as to carry out routing of the query request based on the topological relation and by combining with the distributed space-time index structure information.
To achieve the above object, the present invention also discloses a distributed spatiotemporal query system, which includes a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the above method when executing the computer program.
The invention has the following beneficial effects:
a brand-new distributed space-time query method and a system are defined, and efficient, rapid and accurate data storage and query results are ensured through the mapping relation between Hilbert curves and subspaces, a Chord network peer-to-peer organization structure and a corresponding distributed space-time index structure. Meanwhile, based on the space-time index structure, each server node can store and index a part of global data without storing and indexing global fire data, so that the pressure of each server is reduced, and the cost is saved. And the failure of a single server can not cause global paralysis, and the rest other server nodes can be conveniently organized to provide space-time index service.
The present invention will be described in further detail below with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic diagram of a prior art distributed fire monitoring environment.
Fig. 2 (a) is a schematic diagram of a 1-order Hilbert curve versus spatial partitioning for the embodiment of the present invention, fig. 2 (b) is a schematic diagram of a 2-order Hilbert curve versus spatial partitioning for the embodiment of the present invention, fig. 2 (c) is a schematic diagram of a 3-order Hilbert curve versus spatial partitioning for the embodiment of the present invention, fig. 2 (d) is a schematic diagram of a 4-order Hilbert curve versus spatial partitioning for the embodiment of the present invention, and fig. 2 (e) is a schematic diagram of a 5-order Hilbert curve versus spatial partitioning for the embodiment of the present invention.
Fig. 3 is a schematic structural diagram of a site server key value space and a responsible subspace according to an embodiment of the present invention.
FIG. 4 is a Chord peer-to-peer organizational structure and a routing representation of a site server according to an embodiment of the present invention.
FIG. 5 is a schematic diagram of an FSTI multi-way tree structure according to an embodiment of the invention.
Fig. 6 is a schematic diagram of the spatial neighbors that exist between the site server N8 and the predecessor node N1 and successor node N14 in the embodiment of the present invention.
Fig. 7 is a network diagram of the site server N8 establishing links of neighborhood region data with the predecessor node N1 and successor node N14.
FIG. 8 is a schematic flow chart of a distributed spatiotemporal query method for fire research and judgment according to an embodiment of the present invention.
FIG. 9 is a flow chart of a distributed spatio-temporal query method according to an embodiment of the present invention.
Detailed Description
The embodiments of the invention will be described in detail below with reference to the drawings, but the invention can be implemented in many different ways as defined and covered by the claims.
Example 1
The embodiment discloses a distributed space-time query method. As shown in fig. 9, the method specifically includes:
and step A, adopting Hilbert curves to carry out one-dimensional operation on the two-dimensional space where each station server and each sensor terminal are located.
And step B, organizing a peer-to-peer structure of the site servers by Chord, distributing an index space, and corresponding the space divided by the Hilbert curve to the corresponding site servers.
Step C, each site server establishes an FSTI multi-branch tree in a memory, one R tree is generated in the FSTI multi-branch tree every tau time, and at least two R trees adjacent in time sequence are packaged and encapsulated by pointer information carrying each piece of storage segment time information and an R tree storage address indicating a corresponding space range; and then, judging whether an overlapped and adjacent region of the R tree space range exists or not through interaction with a predecessor node and a successor node of Chord, and if the overlapped and adjacent region exists on the space, establishing a link for inquiring data of the overlapped and adjacent region to the corresponding predecessor node and/or successor node.
To facilitate the detailed understanding of the present invention, the detailed description is as follows:
fig. 2 shows Hilbert curves of order 1 to 5. Specifically, in this embodiment, a Hilbert (Hilbert) curve in the space filling curves is used to maintain the two-dimensional space in a one-dimensional manner, so that the purpose of organizing the site servers in a one-dimensional peer-to-peer structure is achieved. The Hilbert curve has good local retentivity, and is coded by entering and exiting subspaces one by one, so that one-dimensional operation is completed.
After the space is one-dimensional, the embodiment organizes the overlay network topology between site servers by using a classic P2P network model Chord. The method specifically comprises the following steps:
1) And adopting a Hilbert curve to maintain the whole space. Let the Hilbert curve be of order D, and the whole space (with side length E) be divided into 2 2D A subspace (lattice) of the same size. If the set of all points in the whole space is P and the set of Hilbert values is V, the mapping H is P → V, wherein P = (x, y) |0 ≦ x, y ≦ E },
Figure GDA0003902552860000031
2) And organizing the site server peer-to-peer structure and allocating index space using Chord. Let the Chord key value space be [0,2 m -1]M =2D, i.e. the key-value space is consistent with the set of Hilbert values V. Therefore, the space taking the subspace divided by the Hilbert curve as a unit can correspond to a certain site server. For example, as shown in FIG. 3, site server N8 is responsible for indexing on Chord (1, 8)]The data in the interval, whose corresponding subspace is the subspace with Hilbert numbers 2-8 (i.e. the hatched area in the figure), i.e. all fire spatio-temporal data intersecting the subspace 2-8, are indexed by the site server N8.
3) And the topological relation among the site servers can be defined by using the predecessor node and successor node of Chord and a routing table FingerTable (fast routing). A FingerTable route where the predecessor node is N1 and the successor node is N14, 1 to 32 hops, as in site server N8, is shown in fig. 4. Therefore, after the topological relation between the site servers is established, the query request can be routed based on the topology.
Preferably, the construction of the distributed spatio-temporal index of this embodiment includes:
for fire real-time query and future-oriented fire research and judgment query, the constructed spatio-temporal index of the embodiment must support rapid retrieval in a distributed environment, so that the constructed index can support the requirement of geographical dispersion and can also support index update during data insertion and real-time-oriented spatio-temporal query in time. By comprehensively considering the current research situation of the Spatio-Temporal Index, a Spatio-Temporal Index FSTI (Fast Spatio-Temporal Index) which supports quick update and faces to real-time query based on a memory is designed. The specific structure is described as follows:
1) And each server establishes an independent FSTI in the memory. FSTI is a multi-way tree structure whose root node is an array of storage times, and an R-tree is generated every τ times, as shown in FIG. 5, and the spatio-temporal object index in the [ t, t + τ) time period is the R-tree under the array of root nodes t. Each grid at the top layer in fig. 5 is regarded as a root node of an R tree, and includes storage segment time information and pointer information indicating an R tree storage address of a corresponding spatial range; the specific storage structure of the R tree corresponding to the root node for the spatial data is similar to the existing one, and is not described in detail.
2) As described in 1), the FSTI structure will generate redundancy of spatio-temporal objects, and therefore, the server will move the root node and the corresponding R-tree cluster in the delta time period from the left side of the FSTI to the external memory for storage by using a timely persistence mechanism, i.e., at intervals of delta, delta = n x τ. The method not only ensures the effective storage rate of the memory, but also can meet the requirement of efficient and quick query, and also meets the requirement of the user on current or recent query on the fire. Corresponding to fig. 5, that is, at intervals of δ, n R trees adjacent in time sequence are packed and then are moved into an external memory for storage, and specific package information carries storage segment time information and pointer information indicating an R tree storage address of a corresponding space range.
3) The above description is of FSTI structure within a single server node, and since the environment is distributed, a distributed FSTI structure needs to be designed. Comprehensively considering, in order to aim at the query facing the real-time fire trend, after the FSTI is established by each server node, the corresponding R tree root node is connected with the adjacent R tree root nodes or the R tree root nodes which are overlapped in the space range and belong to other server nodes aiming at each time period, so that the time-space query efficiency aiming at a certain time period can be accelerated according to the principle of proximity. In other words, namely: and judging whether the overlapped and adjacent region of the R tree space range exists or not through interaction with the predecessor node and the successor node of Chord, and if the overlapped and adjacent region exists on the space, establishing a link for inquiring the data of the overlapped and adjacent region to the corresponding predecessor node and/or successor node.
As shown in fig. 6, the adjacent region corresponding to the region in which the N8 site server in fig. 3 is responsible also includes a left N1 dashed-line frame region and an upper N14 dashed-line frame region, so that the internal region in which the N8 site server itself is responsible is correspondingly linked with the two adjacent regions, and the related connection diagram corresponds to the diagram of the Chord peer-to-peer network structure, specifically refer to fig. 7, which connects the server nodes N1, N8 and N14 at the root node of the R tree in the t1 period. Generally, the steps of link establishment are:
a: a server A is set, and the server A actively contacts a precursor server node B and a subsequent server node C of the server A.
b: b and C send the node range of the root of the R tree to A according to the time array sequence.
c: and after receiving each R root node, the A establishes connection for adjacent or overlapped areas compared with each R tree root node of the A.
d: b and C each perform the operation of node a.
Based on the above index structure, the corresponding spatio-temporal query method, as shown in fig. 8, includes:
step S100, a space-time query request is obtained, wherein the space-time query request comprises space coordinate information and time information of a queried data object.
And S200, calculating a central point of the inquired data object according to the space coordinate information, and mapping the central point to a corresponding one-dimensional space according to a Hilbert curve.
And step S300, routing the query condition and the address of the client c to a server node in charge of the one-dimensional space according to a Chord routing protocol.
And S400, the server node in charge of the one-dimensional space performs data query and integration processing according to the space coordinate information and the time information in combination with a distributed space-time index structure.
Further, a specific query process of the preferred query method includes:
s0, a server node A receives a query request of a client c; the query request carries spatiotemporal information (qx) l ,qx u , qy l ,qy u ,t s ,t e ) (ii) a Wherein, (qx) l ,qy l ) The lower left corner coordinate representing the spatial range, (qx) u ,qy u ) Representing the coordinates of the upper right hand corner of the spatial range.
Step S1, A, calculating a spatial range (qx) l ,qx u ,qy l ,qy u ) Central point (qx) of (c) c ,qy c ) Then, the center point (qx) is divided according to Hilbert curve c ,qy c ) Mapping to a one-dimensional space h q 。
S2, routing the query condition and the address of the client c to a responsible index value h according to a Chord routing protocol q Of the server node R.
Step S3, according to Hilbert curve mapping, the space range (qx) is mapped by the R l ,qx u ,qy l ,qy u ) Conversion into a one-dimensional interval list LH q Wherein LH q ＝{[hs i ,he i ]|0<i<= n }; wherein hs represents the starting point of the one-dimensional interval, he represents the ending point of the one-dimensional interval, and n represents the number of intervals.
Step S4, R is to the time range (t) s ,t e ) The judgment is carried out as follows:
(4.1) if t e Is that at present:
(4.1.1) judging if t s Starting point t of root node time array of FSTI earlier than R 0 Adjust the query time range to (t) 0 ,t e ) Otherwise, the time range is still (t) s ,t e )。
(4.1.2) R according to (t) 0 ,t e ) Or (t) s ,t e ) Filtering the FSTI root node time array, and inquiring a time period list LT { seg meeting a time condition j |0<j<= m }. Wherein seg j Indicating the jth time period.
(4.1.3) R for each seg in LT j According to spatial extent (qx) l ,qx u ,qy l ,qy u ) Finding corresponding seg in FSTI j R tree of (1), return result list ret R And simultaneously, the R also sends the time-space query to the corresponding server node through the searched R tree and the root node link of the R tree, and the server node list is set as LFS.
(4.1.4) each server node in the LFS searches through the local FSTI when receiving the query condition, and returns the result to R.
(4.1.5) R receives the result returned from LFS and ret R And combining and removing the duplicate to form a final result ret which is returned to the client c.
(4.2) if t e Not currently.
(4.2.1) R queries the condition (qx) according to Chord routing protocol l ,qx u ,qy l ,qy u ,t s ,t e ) Route to responsible LH q The list of server nodes is set as LCS.
(4.2.2) each server node in R and LCS judges if t s Starting point t of root node time array earlier than self FSTI 0 。
(4.2.2.1) Each Server node in R and LCS adjusts the query time horizon to (t) s ,t 0 ) And (t) 0 ,t e )。
(4.2.2.2) R targeting query conditions (qx) with local FSTI l ,qx u ,qy l ,qy u ,t 0 ,t e ) Searching is carried out, and the fire object in the external memory is aimed at the query condition (qx) l ,qx u ,qy l ,qy u ,t s ,t 0 ) Searching is carried out, and the two results are combined into a result ret R 。
(4.2.2.3) Each Server node in LCS aims at query condition (qx) with local FSTI l ,qx u ,qy l ,qy u ,t 0 , t e ) Searching is carried out, and the fire object in the external memory is aimed at the query condition (qx) l ,qx u ,qy l ,qy u ,t s ,t 0 ) And searching is carried out, and each server node in the LCS combines the results of the two and returns the result to the R.
(4.2.2.4) R receives the result returned from LCS and ret R And combining and removing the duplicate to form a final result ret which is returned to the client c.
(4.2.3) if t s Starting point t of root node time array not earlier than own FSTI 0 。
(4.2.3.1) R targeting query conditions (qx) with local FSTI l ,qx u ,qy l ,qy u ,t s ,t e ) Perform the lookup with the result ret R 。
(4.2.3.2) Each Server node in LCS uses local FSTI for query condition ((qx) l ,qx u ,qy l ,qy u ,t s , t e ) And (4) searching is carried out, and each server node in the LCS returns the result to the R.
(4.2.3.3) R receives the result returned from LCS and ret R And combining and removing the duplicate to form a final result ret which is returned to the client c.
Thus, the above query process takes into account the following two cases:
in case 1, namely, (4.1) above, when the user is performing query facing the current time, the system defaults to that the user has a higher requirement for the query efficiency, so that the query condition is directly delivered to the relevant server node for query by using the root node link of the R tree of the FSTI, namely, (4.1.2) and (4.1.3), thus the method improves the concurrency of simultaneous query of a plurality of server nodes and improves the query efficiency; however, since the node hit by the link delivery query condition of the root node of the R tree may not be completely covered, the recall ratio may not reach 100% by using this method, but the requirement for the efficiency is slightly higher in consideration of the emergency of fire.
Case 2, namely (4.2) above, when the user does not perform the query for the current time, the server initiated by the query will forward all the involved spaces to the respective server nodes responsible for corresponding using Chord routing mechanism, namely (4.2.1), so that the recall rate of the query result is guaranteed to be 100%; however, since the Chord protocol is used for forwarding one by one, the query efficiency is not as fast as direct delivery by using the root node of the R tree. Therefore, the query mode is suitable for the condition that the query efficiency is not high.
As a variation, a person skilled in the art may also make other variations of the query method based on the index structure of this embodiment, which is not described in detail in this embodiment.
In summary, the technique disclosed in this embodiment has the following advantages:
(1) And each server node does not need to store and index global fire data but stores and indexes partial data of the whole situation, so that the pressure of each server is reduced, and the cost is saved.
(2) The failure of a single server can not cause global paralysis, and the rest server nodes can be organized to provide space-time index service.
(3) And the inquiry is not delivered to all servers, but is accurately delivered to the server nodes related to the inquiry, so that the inquiry efficiency is greatly improved, and the requirement of real-time fire research and judgment is met.
Example 2
Corresponding to the above embodiments, the present embodiment further discloses a distributed space-time query system, which is applied to scenes such as a fire research and judgment internet of things, and includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor implements the steps corresponding to the above method embodiments when executing the computer program.
To sum up, the distributed spatio-temporal query method and system disclosed by the embodiment of the invention have the following advantages:
a brand-new space-time index structure is defined, and efficient, fast and accurate data storage and query results are guaranteed through the mapping relation between Hilbert curves and subspaces, the Chord network peer-to-peer organization structure and the corresponding distributed space-time index structure. Meanwhile, based on the space-time index structure, each server node can store and index a part of global data without storing and indexing global fire data, so that the pressure of each server is reduced, and the cost is saved. And the failure of a single server can not cause global paralysis, and the rest other server nodes can be conveniently organized to provide space-time index service.
The above embodiments and the background art of the present invention are only examples of fire research data, and based on the common general knowledge of those skilled in the art, the spatio-temporal index structure disclosed in the present invention can be easily transplanted into other application scenarios, so the above scenarios based on fire research and the specific query method are not intended to limit the maximum protection scope of the present invention, and those skilled in the art may make various modifications and changes. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (2)

1. A distributed spatio-temporal query method, comprising:
a Hilbert curve is adopted to maintain the two-dimensional space where each station server and each sensor terminal are located in a one-dimensional mode; the method comprises the following steps: let the Hilbert curve be of order D and the entire space with side length E be divided into 2 2D And if the set of all points in the whole space is P and the set of Hilbert values is V, the mapping H is formed by P → V, wherein P = { (x, y) |0 ≦ x, y ≦ E },
Figure FDA0003915401550000011
organizing a peer-to-peer structure of the site servers by Chord, allocating an index space, and corresponding a space divided by a Hilbert curve to the corresponding site server; the method comprises the following steps: let Chord key value space be [0, 2% m -1]M =2D, the key value space is consistent with the Hilbert value set V;
each site server establishes an FSTI multi-branch tree in a memory, one R tree is generated in the FSTI multi-branch tree every tau time, and at least two R trees adjacent in time sequence are packaged by carrying storage segment time information and pointer information of an R tree storage address indicating a corresponding space range; then, whether an overlapping and adjacent region of the R tree space range exists or not is judged through interaction with a predecessor node and a successor node of Chord, and if the overlapping and adjacent region on the space exists, a link used for inquiring data of the overlapping and adjacent region from the corresponding predecessor node and/or successor node is established; the method comprises the steps that a precursor node, a site server and a subsequent node are connected at the root node of an R tree of a corresponding time period, each site server utilizes the precursor node, the subsequent node and a routing table of Chord to define the topological relation among the site servers, and the routing of query requests is carried out based on the topological relation and by combining distributed space-time index structure information.
2. A distributed spatiotemporal query system comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the steps of the method of claim 1 are performed when the computer program is executed by the processor.
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