CN110868730A - Mobile sensor coverage enhancement method based on non-cooperative game - Google Patents

Mobile sensor coverage enhancement method based on non-cooperative game Download PDF

Info

Publication number
CN110868730A
CN110868730A CN201911111846.1A CN201911111846A CN110868730A CN 110868730 A CN110868730 A CN 110868730A CN 201911111846 A CN201911111846 A CN 201911111846A CN 110868730 A CN110868730 A CN 110868730A
Authority
CN
China
Prior art keywords
mobile sensor
nodes
sensor node
game
cooperative game
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201911111846.1A
Other languages
Chinese (zh)
Other versions
CN110868730B (en
Inventor
段超凡
冯径
常昊天
张之正
颜超
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
National University of Defense Technology
Original Assignee
National University of Defense Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by National University of Defense Technology filed Critical National University of Defense Technology
Priority to CN201911111846.1A priority Critical patent/CN110868730B/en
Publication of CN110868730A publication Critical patent/CN110868730A/en
Application granted granted Critical
Publication of CN110868730B publication Critical patent/CN110868730B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention discloses a mobile sensor coverage enhancement method based on a non-cooperative game, which comprises the steps of firstly defining a sensor node set and an event set needing to be covered in a region, and expanding the coverage of the whole region to be an optimization target on the basis of covering the event set by a mobile sensor node; secondly, establishing a non-cooperative game model among nodes, constructing a game utility function, carrying out non-cooperative game on the nodes and neighbor nodes thereof, selecting positions with respective maximized benefits to move, and quitting the game when the nodes cannot obtain higher benefits or are exhausted by moving; and finally, deploying the nodes according to the non-cooperative game model. The invention abstracts the sensor nodes, comprehensively defines the motion attributes, communication conditions and individual profits of the nodes, adopts a non-cooperative game theory, constructs a utility function, finally achieves Nash equilibrium, realizes coverage enhancement of the mobile sensor, and is suitable for effectively covering event points by the removability of the sensor under the condition of immediate deployment.

Description

Mobile sensor coverage enhancement method based on non-cooperative game
Technical Field
The invention discloses a mobile sensor network coverage enhancement method based on a non-cooperative game, belongs to the technical field of wireless sensor networks, and is particularly suitable for mobile sensor coverage enhancement under the condition of dynamic topology change.
Background
The sensor network has been widely applied to the aspects of ecological environment monitoring and the like due to the characteristics of low cost, adaptability and the like, the data acquisition mode in the traditional sense is changed by collecting data through the sensor, and the gap between the physical world and the information world is broken through. Particularly, when the monitoring environment is unknown and an autonomous controllable deployment mode is difficult to adopt, the sensor equipment is randomly scattered through the aircraft, the mobile platform is carried, so that the sensor can autonomously move to a proper position, and the coverage rate is increased by adopting the mobile nodes instead of more sensors, so that the network coverage effect can be effectively enhanced. The mobile node is provided with a positioning and navigation device which can move after initial deployment, thereby avoiding the situation that a large amount of sensors need to be spread if tasks such as coverage, point detection and the like need to be completed, greatly reducing the deployment cost of a cost system, and effectively achieving coverage optimization of the mobile node is the key of the problems.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the prior art, a non-cooperative game-based mobile sensor network coverage enhancement method is provided, the coverage rate is increased while the coverage effect of the mobile sensor node on an event is enhanced, and the moving distance of the node and the energy cost are reduced as much as possible.
The technical scheme is as follows: a non-cooperative game-based mobile sensor coverage enhancement method is characterized by comprising the following steps: firstly, defining a sensor node set and an event set needing to be covered in an area, and expanding the coverage of the whole area on the basis of covering the event set by a mobile sensor node to serve as an optimization target; secondly, establishing a non-cooperative game model among the mobile sensor nodes, constructing a game utility function, carrying out non-cooperative game on the sensor nodes and the neighbor nodes, selecting positions with respective maximized benefits to move, and quitting the game when the sensor nodes cannot obtain higher benefits or are exhausted by moving; and finally, deploying the nodes according to a non-cooperative game model.
Further, if m event monitoring points E exist in the region Z, the event set E ═ E is defined1,e2,...,em}，eiE.z, i 1,21,s2,...,sn}，sjE, Z, j is 1,2, n, and the sensing radius of the mobile sensor node is rjThe current position of the mobile sensor node is PjThe communication radius of the mobile sensor node is rc，rc＝2rj；
Within the monitoring area, for
Figure BDA0002272938860000021
Mobile sensor node sjTo eiCoverage probability p (e)i,sj) The following formula is satisfied:
Figure BDA0002272938860000022
wherein d (e)i,sj) Representing a mobile sensor node sjAnd event eiEuclidean distance of rsRadius of confidence circle, r, for a mobile sensor nodejIs the maximum detection radius of the mobile sensor; λ is a perceptual attenuation factor;
when the Euclidean distance between the mobile sensor nodes is smaller than the communication radius r of the sensorcThen they are the other side's neighbor nodes, then the mobile sensor node siSet of neighbor nodes
Figure BDA0002272938860000023
Expressed as:
Figure BDA0002272938860000024
the establishment of the non-cooperative game model among the mobile sensor nodes comprises the following steps:
non-cooperative playThe playing model is expressed as
Figure BDA0002272938860000025
Wherein the participant of the game is a mobile sensor node S ═ S in the monitoring area1,s2,...,sn}，sj∈Z,j＝1,2,...,n，
Figure BDA0002272938860000026
Is a mobile sensor node siThe set of optional actions of (a) is,
Figure BDA0002272938860000027
is a utility function; note the book
Figure BDA0002272938860000028
For moving sensor nodes siThe selected action is
Figure BDA0002272938860000029
Represents a combination of all mobile sensor node selection actions; in a game, the mobile sensor node changes the decision behavior of the mobile sensor node by acquiring local network information, and the selectable position of the mobile sensor node is a region gridding position with the radius rcInner grid point positions;
after the initial deployment is completed, the mobile sensor nodes monitor more events by changing positions, and the value of a single mobile sensor node is inspected by constructing a cost function
Figure BDA00022729388600000210
Figure BDA00022729388600000211
Wherein the content of the first and second substances,
Figure BDA00022729388600000212
for moving sensor nodes siBy taking actions
Figure BDA00022729388600000213
Then, sense the event ekThe probability of (d);
meanwhile, in order to reduce the overlapping area between the mobile sensor nodes and avoid the situation that the mobile sensor nodes in partial areas are too dense, an equilibrium function is constructed to improve the equilibrium of deployment, and the equilibrium function is shown as the following formula:
Figure BDA00022729388600000214
wherein the content of the first and second substances,
Figure BDA0002272938860000031
denotes siThe actions taken by the neighboring nodes of (c),
Figure BDA0002272938860000032
representing a mobile sensor node siAnd sjThe distance between the positions is determined by the distance between the positions,
Figure BDA0002272938860000033
representing a mobile sensor node sjThe position of (a);
constructing utility functions for a game
Figure BDA0002272938860000034
Figure BDA0002272938860000035
In the non-cooperative game stage, the nodes select the positions with maximized benefits to move, and the neighbor node sets are recalculated.
Has the advantages that: (1) a non-cooperative game model among sensor nodes is established, the positions of the nodes are selected as a strategy set of the nodes, the sensor nodes interact with the information of the neighbor nodes, and as the sensor nodes always make decisions according to the 'good sense', a balance function is introduced to construct a utility function of a game so as to achieve global optimization.
(2) The method is a distributed autonomous deployment sensor deployment method in a dynamic environment, effective coverage of events is achieved through autonomous movement of sensors, centralized control of a central node is not needed, nodes can autonomously move to proper positions, the utilization rate of the nodes is effectively improved, and the coverage rate of a network is increased.
Drawings
FIG. 1 is a schematic diagram of the network model description steps of the present invention;
FIG. 2 is an initial network layout of a sensor network in a random deployment scenario;
fig. 3 is a network layout completed after the sensors have moved on the basis of fig. 2.
Detailed Description
The invention is further explained below with reference to the drawings.
As shown in fig. 1, a method for enhancing the coverage of a mobile sensor based on a non-cooperative game, which fully considers the dynamic change characteristics of a network topology and the information interaction between nodes, comprises the following steps: firstly, defining a sensor node set and an event set needing to be covered in an area, and expanding the coverage of the whole area on the basis of covering the event set by moving the sensor node to serve as an optimization target. Secondly, establishing a non-cooperative game model among the mobile sensor nodes, constructing a game utility function, carrying out non-cooperative game on the sensor nodes and the neighbor nodes, selecting positions with respective maximized benefits to move, and quitting the game when the sensor nodes cannot obtain higher benefits or are exhausted by moving. And finally, deploying the nodes according to a non-cooperative game model. The method comprises the following specific steps:
defined in the area Z, if there are m event monitoring points E, the event set E ═ E1,e2,...,em}，eiE.z, i 1,21,s2,...,sn}，sjE.g., Z, j ═ 1, 2. According to the physical characteristics of the sensor, the sensing radius of the mobile sensor node is determined to be rjThe communication radius of the mobile sensor node is rc，rc＝2rjAnd get whenLocation P of a front moving sensor nodej。
Since the sensor is disturbed by a series of environmental factors in the monitoring area, the sensor is not influenced by the environmental factors in the monitoring area
Figure BDA0002272938860000041
Mobile sensor node sjTo eiCoverage probability p (e)i,sj) The following formula is satisfied:
Figure BDA0002272938860000042
wherein d (e)i,sj) Representing a mobile sensor node sjAnd event eiEuclidean distance of rsRadius of confidence circle, r, for a mobile sensor nodejIs the maximum detection radius of the mobile sensor; λ is a perceptual attenuation factor, which is a physical characteristic of the node. And if the distance between the event node and the mobile sensor node is smaller than the radius of the confidence circle of the mobile sensor node, the event is considered to be certainly sensed by the mobile sensor node.
When the Euclidean distance between the mobile sensor nodes is smaller than the communication radius r of the sensorcThen they are the other side's neighbor nodes, then the mobile sensor node siSet of neighbor nodes
Figure BDA0002272938860000043
Expressed as:
Figure BDA0002272938860000044
the non-cooperative game model consists of three parts, namely a game participant, a game strategy set and a game utility function, and the establishment of the non-cooperative game model among the mobile sensor nodes comprises the following steps:
the non-cooperative game model is expressed as
Figure BDA0002272938860000045
Wherein the participants of the game areMobile sensor node S ═ S in monitoring area1,s2,...,sn}，sj∈Z,j＝1,2,...,n；
Figure BDA0002272938860000046
Is a mobile sensor node siThe game, the next selectable location of the mobile sensor node constitutes a selectable policy set for the single node,
Figure BDA0002272938860000047
is a utility function. Note the book
Figure BDA0002272938860000048
For moving sensor nodes siThe selected action is
Figure BDA0002272938860000049
Representing the combination of all mobile sensor node selection actions. In a game, the mobile sensor node changes the decision behavior of the mobile sensor node by acquiring local network information, and the selectable position of the mobile sensor node is a region gridding position with the radius rcInner grid point position.
After the initial deployment is finished, the positions of the mobile sensor nodes and the monitoring event points are randomly distributed, and the mobile sensor nodes have a certain coverage radius, so that after the initial deployment is finished, the mobile sensor nodes monitor more events by changing the positions, and the value of a single mobile sensor node is inspected by constructing a cost function
Figure BDA00022729388600000410
Figure BDA0002272938860000051
Wherein the content of the first and second substances,
Figure BDA0002272938860000052
for moving sensor nodes siBy taking actions
Figure BDA0002272938860000053
Then, sense the event ekThe probability of (c).
Meanwhile, in order to reduce the overlapping area between the mobile sensor nodes and avoid the situation that the mobile sensor nodes in partial areas are too dense, an equilibrium function is constructed to improve the equilibrium of deployment, and the equilibrium function is shown as the following formula:
Figure BDA0002272938860000054
wherein the content of the first and second substances,
Figure BDA0002272938860000055
denotes siThe actions taken by the neighboring nodes of (c),
Figure BDA0002272938860000056
representing a mobile sensor node siAnd sjThe distance between the positions is determined by the distance between the positions,
Figure BDA0002272938860000057
representing a mobile sensor node sjThe position of (a).
The balance function mainly considers two indexes of the distance between the sensor nodes and the standard deviation, the method can adjust the distance between the sensor nodes to realize the large-range coverage of a target area as far as possible, and simultaneously, the distance between the mobile sensor nodes is as small as possible to avoid the imbalance of the density of the area.
Because the equilibrium function of the neighbor nodes is only changed in the strategy selection process of the decision maker in the game, the utility function of the game is constructed
Figure BDA0002272938860000058
Figure BDA0002272938860000059
Based on effectsUsing functions
Figure BDA00022729388600000510
The non-cooperative game model among the mobile sensor nodes can be finally expressed as:
Figure BDA00022729388600000511
in the non-cooperative game stage, the node selects the position with the maximized benefit to move, and the neighbor node set is recalculated, and when the node energy cannot support the movement or the node movement cannot obtain higher benefit, the node exits the game.
As shown in fig. 2, the dot nodes are sensor nodes, and the fork nodes are event set nodes, and initially, the sensor nodes cannot achieve effective coverage on the time nodes. After the non-cooperative game-based mobile sensor coverage enhancement algorithm is utilized, the effect is shown in fig. 3, and it can be seen that the event coverage can be effectively increased by utilizing the method.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims (2)

1. A non-cooperative game-based mobile sensor coverage enhancement method is characterized by comprising the following steps: firstly, defining a sensor node set and an event set needing to be covered in an area, and expanding the coverage of the whole area on the basis of covering the event set by a mobile sensor node to serve as an optimization target; secondly, establishing a non-cooperative game model among the mobile sensor nodes, constructing a game utility function, carrying out non-cooperative game on the sensor nodes and the neighbor nodes, selecting positions with respective maximized benefits to move, and quitting the game when the sensor nodes cannot obtain higher benefits or are exhausted by moving; and finally, deploying the nodes according to a non-cooperative game model.
2. The method of claim 1, wherein m event monitoring points E are defined to exist in zone Z, and the event set E ═ E is determined1,e2,...,em}，eiE.z, i 1,21,s2,...,sn}，sjE, Z, j is 1,2, n, and the sensing radius of the mobile sensor node is rjThe current position of the mobile sensor node is PjThe communication radius of the mobile sensor node is rc，rc＝2rj；
Within the monitoring area, for
Figure FDA0002272938850000011
Mobile sensor node sjTo eiCoverage probability p (e)i,sj) The following formula is satisfied:
Figure FDA0002272938850000012
wherein d (e)i,sj) Representing a mobile sensor node sjAnd event eiEuclidean distance of rsRadius of confidence circle, r, for a mobile sensor nodejIs the maximum detection radius of the mobile sensor; λ is a perceptual attenuation factor;
when the Euclidean distance between the mobile sensor nodes is smaller than the communication radius r of the sensorcThen they are the other side's neighbor nodes, then the mobile sensor node siSet of neighbor nodes
Figure FDA0002272938850000013
Expressed as:
Figure FDA0002272938850000014
the establishment of the non-cooperative game model among the mobile sensor nodes comprises the following steps:
the non-cooperative game model is expressed as
Figure FDA0002272938850000015
Wherein the participant of the game is a mobile sensor node S ═ S in the monitoring area1,s2,...,sn}，sj∈Z,j＝1,2,...,n，
Figure FDA0002272938850000016
Is a mobile sensor node siThe set of optional actions of (a) is,
Figure FDA0002272938850000017
is a utility function; note the book
Figure FDA0002272938850000018
For moving sensor nodes siThe selected action is
Figure FDA0002272938850000019
Represents a combination of all mobile sensor node selection actions; in a game, the mobile sensor node changes the decision behavior of the mobile sensor node by acquiring local network information, and the selectable position of the mobile sensor node is a region gridding position with the radius rcInner grid point positions;
after the initial deployment is completed, the mobile sensor nodes monitor more events by changing positions, and the value of a single mobile sensor node is inspected by constructing a cost function
Figure FDA0002272938850000021
Figure FDA0002272938850000022
Wherein the content of the first and second substances,
Figure FDA0002272938850000023
for moving sensor nodes siBy taking actions
Figure FDA0002272938850000024
Then, sense the event ekThe probability of (d);
meanwhile, in order to reduce the overlapping area between the mobile sensor nodes and avoid the situation that the mobile sensor nodes in partial areas are too dense, an equilibrium function is constructed to improve the equilibrium of deployment, and the equilibrium function is shown as the following formula:
Figure FDA0002272938850000025
wherein the content of the first and second substances,
Figure FDA0002272938850000026
denotes siThe actions taken by the neighboring nodes of (c),
Figure FDA0002272938850000027
representing a mobile sensor node siAnd sjThe distance between the positions is determined by the distance between the positions,
Figure FDA0002272938850000028
representing a mobile sensor node sjThe position of (a);
constructing utility functions for a game
Figure FDA0002272938850000029
Figure FDA00022729388500000210
In the non-cooperative game stage, the nodes select the positions with maximized benefits to move, and the neighbor node sets are recalculated.
CN201911111846.1A 2019-11-14 2019-11-14 Mobile sensor coverage enhancement method based on non-cooperative game Active CN110868730B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201911111846.1A CN110868730B (en) 2019-11-14 2019-11-14 Mobile sensor coverage enhancement method based on non-cooperative game

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201911111846.1A CN110868730B (en) 2019-11-14 2019-11-14 Mobile sensor coverage enhancement method based on non-cooperative game

Publications (2)

Publication Number Publication Date
CN110868730A true CN110868730A (en) 2020-03-06
CN110868730B CN110868730B (en) 2022-07-26

Family

ID=69654760

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201911111846.1A Active CN110868730B (en) 2019-11-14 2019-11-14 Mobile sensor coverage enhancement method based on non-cooperative game

Country Status (1)

Country Link
CN (1) CN110868730B (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112243281A (en) * 2020-10-15 2021-01-19 广州大学 Bayesian game routing design method based on rechargeable wireless sensor network
CN114707814A (en) * 2022-03-15 2022-07-05 燕山大学 Underwater event coverage-oriented underwater robot deployment method

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103916912A (en) * 2014-03-25 2014-07-09 南京邮电大学 Node cooperation motivational method of wireless heterogeneous network on basis of non-cooperative game
EP3206425A1 (en) * 2014-11-27 2017-08-16 Shenyang Institute of Automation of the Chinese Academy of Sciences Robust coverage method for relay nodes in double-layer structure wireless sensor network
CN107094060A (en) * 2017-04-24 2017-08-25 东南大学 Distributed super-intensive heterogeneous network disturbance coordination method based on non-cooperative game
CN108322938A (en) * 2018-01-23 2018-07-24 南京邮电大学 Super-intensive group power distribution method and its modeling method off the net based on double-deck non-cooperative game theory
CN110401958A (en) * 2019-08-05 2019-11-01 重庆邮电大学 A kind of node dynamic coverage Enhancement Method based on fictitious force

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103916912A (en) * 2014-03-25 2014-07-09 南京邮电大学 Node cooperation motivational method of wireless heterogeneous network on basis of non-cooperative game
EP3206425A1 (en) * 2014-11-27 2017-08-16 Shenyang Institute of Automation of the Chinese Academy of Sciences Robust coverage method for relay nodes in double-layer structure wireless sensor network
CN107094060A (en) * 2017-04-24 2017-08-25 东南大学 Distributed super-intensive heterogeneous network disturbance coordination method based on non-cooperative game
CN108322938A (en) * 2018-01-23 2018-07-24 南京邮电大学 Super-intensive group power distribution method and its modeling method off the net based on double-deck non-cooperative game theory
CN110401958A (en) * 2019-08-05 2019-11-01 重庆邮电大学 A kind of node dynamic coverage Enhancement Method based on fictitious force

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
包学才等: "能量获取型传感网络技术在水利监测中的应用探讨", 《水利信息化》 *
段鸿轩等: "基于博弈理论无线传感网覆盖空洞修复算法", 《计算机工程与设计》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112243281A (en) * 2020-10-15 2021-01-19 广州大学 Bayesian game routing design method based on rechargeable wireless sensor network
CN112243281B (en) * 2020-10-15 2022-06-21 广州大学 Bayesian game routing design method based on rechargeable wireless sensor network
CN114707814A (en) * 2022-03-15 2022-07-05 燕山大学 Underwater event coverage-oriented underwater robot deployment method
CN114707814B (en) * 2022-03-15 2024-02-02 燕山大学 Underwater robot deployment method for underwater event coverage

Also Published As

Publication number Publication date
CN110868730B (en) 2022-07-26

Similar Documents

Publication Publication Date Title
Liu A deployment strategy for multiple types of requirements in wireless sensor networks
CN103354642B (en) A kind of method improving mobile sensor network coverage rate
CN110868730B (en) Mobile sensor coverage enhancement method based on non-cooperative game
CN103401922B (en) Distributed localization apparatus and method based on game method in wireless sensor network
CN103997747B (en) A kind of uniform dispositions method of spatial network node based on fictitious force
CN108632831A (en) A kind of unmanned aerial vehicle group frequency spectrum resource allocation method based on dynamic flight path
WO2018130135A1 (en) Method and device for controlling way-finding of simulation object, and server
Jain A coherent approach for dynamic cluster-based routing and coverage hole detection and recovery in bi-layered WSN-IoT
CN110062432A (en) A kind of Wireless sensor network clustering routing algorithm based on least energy consumption
CN108683468A (en) AUV mobile data collection algorithms in underwater sensing network based on data prediction
CN110225569A (en) A method of based on the WSNs clustering and multi-hop Routing Protocol for improving particle swarm algorithm
CN104219704A (en) Toxic gas boundary monitoring and tracking method based on double-layer mesh model in wireless sensor network
Chen et al. Artificial intelligence-empowered path selection: A survey of ant colony optimization for static and mobile sensor networks
CN113242562B (en) WSNs coverage enhancement method and system
CN103249110A (en) Dynamic-tree-based wireless sensor network target tracking method
CN107222900A (en) A kind of wireless sensor network node collaboration method based on dynamic chain
CN104883676A (en) Cooperative safety communication method in multi-UAV environment
CN110049448A (en) A kind of wireless sense network method of data capture based on unmanned aerial vehicle group
Vinodhini et al. Fuzzy based unequal clustering and context-aware routing based on glow-worm swarm optimization in wireless sensor networks: forest fire detection
Zhang et al. New computing tasks offloading method for MEC based on prospect theory framework
Huo et al. A UAV mobile strategy in mobile ad hoc networks
Li et al. Multi-Objective Optimization for UAV Swarm-Assisted IoT with Virtual Antenna Arrays
Lin et al. Fast node clustering based on an improved birch algorithm for data collection towards software-defined underwater acoustic sensor networks
CN104606886B (en) A kind of method of distributed collisionless movement planning
CN108271168B (en) Wireless sensor network coverage optimization method based on Dijkstra algorithm

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant