CN107567067A - A kind of improved method of MPR algorithms - Google Patents
A kind of improved method of MPR algorithms Download PDFInfo
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- CN107567067A CN107567067A CN201710594925.7A CN201710594925A CN107567067A CN 107567067 A CN107567067 A CN 107567067A CN 201710594925 A CN201710594925 A CN 201710594925A CN 107567067 A CN107567067 A CN 107567067A
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Abstract
The invention discloses a kind of improved method of MPR algorithms, in the method, the selection of multiple spot relaying (MPR) node is on having multiple maximal cover degree nodal basis, increase Link State and node state as the foundation judged, select coverage maximum and the node of state optimization is as MPR nodes；The Link State can be weighed with link bandwidth, chain-circuit time delay and link packet drop rate；The node state can be weighed with a kind of index in the computing capability, dump energy, node load of neighbor node or many indexes.Using this method, on the basis of maximal cover degree is ensured, MPR selects the node of state optimization so that network performance is more excellent.
Description
Technical field
The present invention relates to technical field of communication network, more particularly to the selection process of MPR nodes in wireless network.
Background technology
Multiple spot relays (MultiPoint Relay：MPR) it is the redundant transmission that broadcast the message in a kind of reduction wireless network
Mechanism.Node selects MPR collection in a hop neighbor node, and the standard of selection is to ensure that by MPR sets of node, can reach section
All two hop neighbors nodes of point.For broadcast message in flooding, the MPR rallies of only node forward the broadcast message received, from
And have the function that to reduce the flooding number to broadcast the message in wireless network.
According to the neighbor node collection and two-hop neighbor node collection of node, each node can be selected certainly independently of other nodes
Oneself MPR collection.In general selection principle is in the case where that can reach all two hop neighbors nodes of node so that MPR collection
It is small as far as possible.MPR collection is smaller, and the routing cost of saving is more.But minimum MPR collection problem has proven to one
Np complete problem, optimal solution solve difficulty, some heuritic approaches can only be utilized to find near-optimum solution.At present, heuritic approach
The coverage of node is considered, does not account for the robustness of Radio Link and radio node.
The content of the invention
The shortcomings that it is a primary object of the present invention to overcome prior art and deficiency, propose a kind of improvement side of MPR algorithms
Method, on the basis of maximal cover degree is ensured, MPR selects the node of state optimization so that network performance is more excellent.
To realize object above, the present invention adopts the following technical scheme that：
The invention discloses a kind of improved method of MPR algorithms, comprise the steps：
Step 1：If node i is performs the node of MPR election algorithms, MPR (i) is the MPR collection of node i, initializes MPR
(i) collection is sky, and reads the hop neighbor set of node N1 (i) and two hop neighbor set of node N2 (i) of node；
Step 2：By in a hop neighbor set of node N1 (i), some nodes in two hop neighbor set of node N2 (i) can be uniquely reached
Node be added to MPR (i) collection, and remove these nodes from N1 (i)；
Step 3：To arbitrary y ∈ N1 (i), y coverage C (y) is calculated；The coverage refers to what is reached by y
N2 (i) nodes subtract the node number after N2 (i) nodes reached by MPR (i) collection nodes；
Step 4：JudgeThen election algorithm terminates, and otherwise chooses the maximum node of C (y) value and adds temporarily
Set of node Temp；
Step 5：Judge transient node centralized node number | Temp |, if | Temp |==1 directly select the node
As MPR nodes, a node of state optimization in transient node collection Temp is otherwise selected as MPR nodes；
Step 6：MPR nodes are added into MPR (i) collection, and remove the node from a hop neighbor set of node N1 (i)；Then,
Temp collection is emptied, continues executing with step 3.
As preferable technical scheme, state optimization described in step 5, weighed with following formula：
V=α × vnode+(1-α)×vlink
Wherein, 0≤α≤1；V represents state value；vnodeRepresent the node state value after normalization；vlinkAfter representing normalization
Link State value.
As preferable technical scheme, in the calculation formula of the state of measurement, the node state value vnodeSaved with neighbours
Computing capability, dump energy and the node load of point are weighed, the computing capability of neighbor node is better, dump energy is more and
Node load is lighter, and node state value is bigger；The Link State value vlinkWeighed with the bandwidth, time delay and packet loss of link
Amount, the bandwidth of link is bigger, time delay is smaller and packet loss is smaller, and Link State value is bigger.
As preferable technical scheme, the node state value vnode, calculated with following formula：
vnode=βa×A+βb×B+βc×C-1
Wherein, A represents the computing capability of node；B represent dump energy, with battery institute more than electricity percentage weigh；C is represented
Node load, with node receiving queue length, accounting is weighed in the total queue length；βa、βb、βcRepresent weight coefficient.
As preferable technical scheme, the Link State value vlink, calculated with following formula：
vlink=βd×D+βe×E-1+βf×F-1
Wherein, D represents link bandwidth；E represents link packet drop rate；F represents chain-circuit time delay；βd、βe、βfRepresent weight coefficient.
The present invention is had the following advantages relative to prior art and effect：
Classical MPR Algorithms of Selecting does not differentiate between random choosing when there is a hop neighbor node of multiple coverages maximums
Take a hop neighbor node to add MPR collection, ensure that the coverage of maximum.The present invention is run into using the MPR algorithms after improving
During same case, select an optimal hop neighbor node to add MPR collection according to state value, ensure that the coverage of maximum
Meanwhile the robustness of node and link is also ensure that, so that the performance of MPR algorithms more optimizes.
Brief description of the drawings
Fig. 1 is MPR algorithm improvement method flow diagrams；
Fig. 2 is the example of MPR algorithm improvements method election.
Embodiment
With reference to embodiment and accompanying drawing, the present invention is described in further detail, but embodiments of the present invention are unlimited
In this.
Embodiment
Fig. 1 is the MPR algorithm improvement method flow diagrams of the present invention, and each mathematic sign is explained as follows：
i：Perform the node calculated；
MPR(i)：The MPR collection of node i, is initialized as sky；
N1(i)：One hop neighbor set of node of node i；
N2(i)：Two hop neighbor sets of node of node i, not including the node in node i and N1 (i), also do not include by
Elect MPR node as；
O(i)：Quasi- MPR collection, certain in two hop neighbor set of node N2 (i) can uniquely be reached by referring in a hop neighbor set of node N1 (i)
The node of a little nodes；
C(y)：Y coverage, y ∈ N1 (i), i.e., N2 (i) nodes that can be reached by y, which subtract, to be saved by MPR (i)
The node number for N2 (i) nodes that point reaches；
Temp collection：One transient node collection, because the possibility of the coverage of N1 (i) interior joints and degree of communication top ranked is not
An only node, with Temp collection come interim storage, when Temp centralized nodes number is 1, MPR (i) concentrations are added directly into, such as
Fruit Temp is concentrated, and node number is more than 1, then therefrom optimal one addition MPR collection of picking link-quality.Wherein, | Temp | table
Show the node number that Temp is concentrated.
The MPR algorithm improvement methods of the present invention specifically include following steps：
1. initializing MPR (i) as sky, and read the hop neighbor set of node N1 (i) and two hop neighbor set of node N2 of node
(i)；
2. the node that in N1 (i), can uniquely reach some nodes in N2 (i) is added into MPR (i) collection, and collect from N1 (i)
In remove these nodes；
3. couple arbitrary y ∈ N1 (i), calculate y coverage C (y)；
4. judgeThen election algorithm terminates, and otherwise chooses the maximum node of C (y) value and adds transient node
Collect Temp；
5. judge transient node centralized node number | Temp |, if | Temp |==1 to directly select the node be MPR
Node, otherwise compare | Temp | concentrate, a node of selection wherein state optimization is as MPR nodes；
6. MPR nodes are added into MPR (i) collection, and remove the node from N1 (i).Then, Temp collection is emptied, continues to hold
Row step 3.
The state optimization, it can be weighed with following formula：
V=α × vnode+(1-α)×vlink
Wherein, 0≤α≤1；V is state value；vnodeFor the node state value after normalization；vlinkFor the link after normalization
State value.
The node state value vnodeOne kind in the computing capability, dump energy, node load of neighbor node can be used
Index or many indexes are weighed, and neighbor node computing capability is better, dump energy is more, load lighter, node state value
It is bigger.Node state value vnodeCalculated with below equation：
vnode=βa×A+βb×B+βc×C-1
Wherein, A represents the computing capability of node；B represent dump energy, with battery institute more than electricity percentage weigh；C is represented
Node load, with node receiving queue length, accounting is weighed in the total queue length；βa、βb、βcFor weight coefficient.
The Link State value vlinkIt can be weighed with the bandwidth, time delay and packet loss of link, bandwidth is bigger, and time delay is got over
It is small, packet loss is smaller, Link State value is bigger.Link State value vlinkCalculated with below equation：
vlink=βd×D+βe×E-1+βf×F-1
Wherein, D is link bandwidth；E is link packet drop rate；F is chain-circuit time delay；βd、βe、βfFor weight coefficient.
Fig. 2 is the example of MPR algorithm improvements method election.Under the topology situation, node a first and node d are selected into
MPR collection.Calculate node b and node c coverage are all 1, the selection that classical heuritic approach can not distinguish between the two
One node adds MPR collection.Assuming that α=0.5, the state value of b nodes and c nodes is calculated the inventive method：vb
=0.8, vc=0.6, so as to choose the MPR collection that the preferable node b of state adds node, finally obtain MPR collection { a, b, d }.
Embodiment described above only expresses the several embodiments of the present invention, and its description is more specific and detailed, but simultaneously
Therefore the limitation to the scope of the claims of the present invention can not be interpreted as.It should be pointed out that for one of ordinary skill in the art
For, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to the guarantor of the present invention
Protect scope.Therefore, the protection domain of patent of the present invention should be to be defined described in claim.
Claims (5)
1. a kind of improved method of MPR algorithms, it is characterised in that comprise the steps：
Step 1：If node i is performs the node of MPR election algorithms, MPR (i) is the MPR collection of node i, and initialization MPR (i) collects
For sky, and read the hop neighbor set of node N1 (i) and two hop neighbor set of node N2 (i) of node；
Step 2：By in a hop neighbor set of node N1 (i), the section of some nodes in two hop neighbor set of node N2 (i) can be uniquely reached
Point is added to MPR (i) collection, and removes these nodes from N1 (i)；
Step 3：To arbitrary y ∈ N1 (i), y coverage C (y) is calculated；The coverage refers to the N2 (i) reached by y
Node subtracts the node number after N2 (i) nodes reached by MPR (i) collection nodes；
Step 4：JudgeThen election algorithm terminates, and otherwise chooses the maximum node of C (y) value and adds transient node
Collect Temp；
Step 5：Judge transient node centralized node number | Temp |, if | Temp |==1 directly select the node conduct
MPR nodes, a node of state optimization in transient node collection Temp is otherwise selected as MPR nodes；
Step 6：MPR nodes are added into MPR (i) collection, and remove the node from a hop neighbor set of node N1 (i)；Then, empty
Temp collection, continues executing with step 3.
2. the improved method of MPR algorithms according to claim 1, it is characterised in that state optimization described in step 5, use
Following formula is weighed：
V=α × vnode+(1-α)×vlink
Wherein, 0≤α≤1；V represents state value；vnodeRepresent the node state value after normalization；vlinkRepresent the chain after normalization
Line state value.
3. the improved method of MPR algorithms according to claim 2, it is characterised in that in the calculation formula of the state of measurement,
The node state value vnodeWeighed with the computing capability, dump energy and node load of neighbor node, the meter of neighbor node
Calculation ability is better, dump energy is more and node load is lighter, and node state value is bigger；The Link State value vlinkUse chain
Bandwidth, time delay and the packet loss on road are weighed, and the bandwidth of link is bigger, time delay is smaller and packet loss is smaller, Link State value
It is bigger.
4. the improved method of MPR algorithms according to claim 3, it is characterised in that the node state value vnode, to
Under formula calculate：
vnode=βa×A+βb×B+βc×C-1
Wherein, A represents the computing capability of node；B represent dump energy, with battery institute more than electricity percentage weigh；C represents node
Load, with node receiving queue length, accounting is weighed in the total queue length；βa、βb、βcRepresent weight coefficient.
5. the improved method of MPR algorithms according to claim 3, it is characterised in that the Link State value vlink, to
Under formula calculate：
vlink=βd×D+βe×E-1+βf×F-1
Wherein, D represents link bandwidth；E represents link packet drop rate；F represents chain-circuit time delay；βd、βe、βfRepresent weight coefficient.
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Cited By (5)
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| CN109104366A (en) * | 2018-08-29 | 2018-12-28 | 重庆大学 | A kind of link duration calculation method, MPR node selecting method and Routing Protocol |
| CN109787898A (en) * | 2019-03-07 | 2019-05-21 | 杭州电子科技大学 | A method of the wireless sensor network downstream message energy conservation flooding based on sleep scheduling |
| CN109787897A (en) * | 2019-03-07 | 2019-05-21 | 杭州电子科技大学 | A kind of energy-efficient sensor network MPR node selection and downlink broadcast implementation method |
| CN111132236A (en) * | 2019-12-31 | 2020-05-08 | 南京航空航天大学 | Multi-unmanned aerial vehicle self-organizing network MPR node selection method based on improved OLSR protocol |
| CN114520960A (en) * | 2022-01-25 | 2022-05-20 | 中国船舶重工集团公司第七二四研究所 | MPR set selection method of multi-subnet wireless network |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109787897A (en) * | 2019-03-07 | 2019-05-21 | 杭州电子科技大学 | A kind of energy-efficient sensor network MPR node selection and downlink broadcast implementation method |
| CN111132236A (en) * | 2019-12-31 | 2020-05-08 | 南京航空航天大学 | Multi-unmanned aerial vehicle self-organizing network MPR node selection method based on improved OLSR protocol |
| CN114520960A (en) * | 2022-01-25 | 2022-05-20 | 中国船舶重工集团公司第七二四研究所 | MPR set selection method of multi-subnet wireless network |
| CN114520960B (en) * | 2022-01-25 | 2024-03-19 | 中国船舶集团有限公司第七二四研究所 | MPR set selection method for multi-subnet wireless network |
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