CN102724731B - Epidemic routing algorithm with adaptive capacity - Google Patents
Epidemic routing algorithm with adaptive capacity Download PDFInfo
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- CN102724731B CN102724731B CN201210239801.4A CN201210239801A CN102724731B CN 102724731 B CN102724731 B CN 102724731B CN 201210239801 A CN201210239801 A CN 201210239801A CN 102724731 B CN102724731 B CN 102724731B
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Abstract
The invention relates to an opportunistic network routing algorithm, which can improve an Epidemic routing algorithm, so that nodes in an opportunistic network efficiently forward data packets, and simultaneously, the consumption of network resources is reduced as much as possible. According to the Epidemic routing algorithm, high delivery ratio and low delivery delay can be obtained in some scenes, but the adaptability of the algorithm is relatively poor; and in some other scenes, the algorithm performance drops dramatically. The invention provides an adaptive mechanism, by which the Epidemic routing algorithm is improved. With the adoption of the adaptive mechanism, the number of invalid data packet copies is effectively reduced, the consumption of network resources is reduced, and the performance of the routing algorithm is improved, thus the scalability of the Epidemic routing algorithm is improved.
Description
Technical field
The present invention relates to opportunistic network routing algorithm, effect makes the efficient forwarding data bag of opportunistic network interior joint, reduces the transfer amount of node as far as possible simultaneously, thus reduce network resource consumption.
Background technology
Opportunistic network is that one does not need to there is fullpath between a source node and a destination node, the chance of meeting utilizing node motion to bring realize network service, time delay and the tolerable self-organizing network of division.Opportunistic network is different from traditional multi-hop wireless network, and its node is not by unified plan, and network size and node initial position pre-set, and the path between source node and destination node can not determine whether exist in advance.Opportunistic network realizes inter-node communication with " storing-carry-forwarding " pattern hop-by-hop transmission information, and its architecture is different from multi-hop wireless network, and it inserts the new protocol layer that is called as bundle layer between application layer and transport layer.
The insoluble problems of conventional wireless network technology such as network division, time delay can be processed due to opportunistic network, can meet the network service needs under mal-condition, it is mainly used in, and to lack the communications infrastructure, network environment severe and tackle the occasion of urgent accident.
1. contrast routing algorithm
For contrasting with routing algorithm of the present invention, have chosen 2 kinds of typical routing algorithms as comparator algorithm.Epidemic algorithm is the Typical Representative based on the policybased routing algorithm that floods, and the routing algorithm much based on the strategy that floods all can be considered it is derived by this algorithm.Spray and Wait algorithm floods according to certain strategy, and be based on the limited strategy that floods, the main performance index of this algorithm all has significant advantage under most scene.
(1) Epidemic algorithm
The basic thought of Epidemic algorithm exchanges the packet that the other side do not have, and after enough exchanges, each non-isolated node will receive all packets in theory, thus realize the transmission of packet.
In Epidemic algorithm, each data are surrounded by the unique mark of an overall situation, preserve a summary vector and be used for recording the packet carried in node in each node.When 2 nodes meet, first both sides exchange summary vector, and after knowing that the other side carries packet situation, both sides only transmit the packet that the other side does not have.
Epidemic algorithm is that one floods algorithm in essence, and the success rate of this algorithm energy maximum data bag transmission theoretically, minimizes transmission delay, but also can make to there is a large amount of packet copies in network, consume a large amount of Internet resources.
Epidemic algorithm has 3 targets, is maximum transmission success rate, minimum transmission delay and minimum network resource consumption respectively.Realize above-mentioned target and need specific scene, under most scene, cause the performance of routing algorithm significantly to decline owing to excessively flooding.
(2) Spray And Wait algorithm
Spray and Wait algorithm is divided into 2 stages.First be the Spray stage, the partial data bag in source node is diffused into neighbor node; Then enter into the Wait stage, if the Spray stage does not find destination node, the node comprising packet in Direct Delivery mode by data packets to destination node, namely only when running into destination node, send packet.This algorithm transmission quantity is less than Epidemic algorithm significantly, and transmission success rate is high, and transmission delay is less, and algorithm applicability is strong.
(3) Prophet algorithm
Prophet algorithm is based on probability strategy, and this routing algorithm is estimated the successful probability of message transmissions, optionally duplicate packet, avoids the copy generating low transmission efficiency as possible.This algorithm defines the probability that a communicating predicted value carrys out Successful transmissions between description node.When 2 nodes meet, node updates communicating predicted value separately, and utilize this value to determine whether forwarding data bag.
2. metric
The metric evaluating opportunistic network routing algorithm performance index mainly contains:
(1) transmission success rate
Transmission success rate (Delivery Ratio) is within the regular hour, successfully arrive the ratio that destination node packet sum and the need that send of source node transmit packet sum, this index features the ability of the correct forwarding data bag of routing algorithm to destination node, is most important index.
(2) transmission delay
Transmission delay (Delivery Delay) is that packet arrives the time needed for destination node from source node, usually adopts average transfer delay to evaluate.Transmission delay little meaning routing algorithm transmittability is strong, efficiency of transmission is high, also means will take less Internet resources in transmitting procedure.
(3) routing cost
Routing cost (Overhead) refers to the sum of node for data forwarding bag within a certain period of time, and the ratio of the packet sum usually forwarded with all nodes by all number-of-packet successfully arriving destination node is evaluated.Routing cost is high, means node forwarding data bag in large quantities, can make to be full of a large amount of packet copies in network, increases the probability that packet collides, also can consume node energy in large quantities.
3.Epidemic algorithm performance is analyzed
Based on table 1 scene, respectively to packet add up to 50 and every node generate 10 packets, 2 kinds of situations and emulate, obtain result shown in Fig. 1, Fig. 2.
With Spray And Wait algorithm in contrast in Fig. 1, Fig. 2, this algorithm can obtain close to optimum transmission success rate and routing cost under most scene, and no matter the scale of network can keep good performance, has good extensibility.
Can obtain as drawn a conclusion by Fig. 1, Fig. 2:
(1) the very high transmission success rate of Epidemic algorithm and low-down transmission delay under some specific scenes, this two indices is better than contrast algorithm greatly;
(2) in data packet number one timing, the increase of nodes quantity can improve the performance of routing algorithm;
(3) in some scenarios, there is the factor that some and network application environment be closely related can cause the performance of Epidemic algorithm significantly to decline.
Fig. 3 based on table 1 scene, describe node total number certain when, the relation between data packet number and transmission success rate.When packet increases as shown in Figure 3, transmission success rate declines thereupon.The reason producing this phenomenon is referred to as crowding-out effect by the present invention, namely when needing transmission packet sum to exceed the storable packet total amount of node in network, nodal cache saturated phenomenon can be there is, when now node receives new data packets, have to abandon old packet according to certain rule, the existence of this effect causes Epidemic algorithm performance significantly to decline.
Summary of the invention
The present invention relates to a kind of new opportunistic network routing algorithm, this algorithm introduces adaptation mechanism on Epidemic routing algorithm basis.This algorithm can reduce the transfer amount of invalid packets copy, obtains higher transmission success rate and lower network resource consumption.
In Epidemic algorithm, crowding-out effect is the core reasons causing algorithm performance to decline, and reduces packet copy amount in network, can suppress the generation of crowding-out effect, if but the very few algorithm performance that also can make of copy amount decline.If situation determination data bag copy quantity forwarded that can be current according to nodes buffer memory, obtain better compromise, obviously can improve algorithm performance, the applicability of expandable algorithm.
Present invention improves over Epidemic algorithm, target is when nodes buffer memory is tending towards full, initiatively reduces the quantity of the packet copy of injection network, suppresses the generation of crowding-out effect, even if algorithm has adaptive ability.Concrete scheme is mechanism below increasing on Epidemic algorithm basis, and the present invention is referred to as adaptation mechanism, and this machine-processed algorithm of employing is called Adaptive Epidemic algorithm.
(1) each node maintenance field is used for depositing threshold values λ, λ ∈ [0,1].If the percentage in occupied space exceedes threshold values λ in nodal cache, then think that nodal cache district is saturated;
(2) when node i and any node j meet, first node i obtains j and surroundings nodes cache condition, adds up the node number N contacted with node i
ai, cushion saturated node number N
ei;
(3) p is calculated
i=N
ei/ N
ai, define known p by it
i∈ [0,1];
(4) node i is according to p
ivalue, random reproduction packet is also sent to the node contacted with it.
Under adaptation mechanism, p value can reflect the saturated situation of surroundings nodes buffer memory, obviously can suppress the generally generation of buffer memory saturated conditions according to p value to injecting data bag copy in network, suppresses the generation of crowding-out effect, thus the performance of improved routing algorithm.
Accompanying drawing explanation
Fig. 1 transmission success rate compares
Fig. 2 transmission delay compares
Fig. 3 data packet number affects transmission success rate
Fig. 4 threshold values is on the impact of transmission success rate
The transmission success rate of innovatory algorithm under the different scene of Fig. 5
The transmission delay of innovatory algorithm under the different scene of Fig. 6
The routing cost of innovatory algorithm under the different scene of Fig. 7
Embodiment
Be described principle of the present invention and feature below, example, only for explaining the present invention, is not intended to limit scope of the present invention.
ONE (the Opportunistic Networking Environment) emulation platform is used to implement the routing algorithm that the present invention relates to.Simulate in emulation below carry smart bluetooth equipment pedestrian's walking in real City scenarios, and implement, analyze the performance of routing algorithm with this.Concrete scene setting is as shown in table 1.
Table 1 simulating scenes is arranged
(1) impact of threshold values
Based on table 1 scene, with 100 nodes, 800 packets are example, and analyze the impact of threshold values on algorithm transmission success rate, result as shown in Figure 4.In Fig. 4, data are by (d
ae-d
e)/d
ecalculate and obtain, wherein d
aeand d
ethe transmission success rate of AdaptiveEpidemic and Epidemic algorithm respectively.
According to Adaptive Epidemic algorithm mechanism, when threshold values is 0, this algorithm deteriorates to Epidemic algorithm, and in Fig. 4, result also verifies this conclusion.As seen from Figure 4 when threshold values arranges appropriate, the transmission success rate of algorithm can improve by a relatively large margin, and as when threshold values is 90%, improvement amplitude reaches 38.9%.
(2) different pieces of information bag quantity impact
Based on table 1 scene, adopt 100 nodes, 30-3600 packet, packet life cycle is 3 hours, carrys out the performance of evaluation algorithms.
With Epidemic, Prophet, Spray And Wait algorithm in contrast in Fig. 5-Fig. 7.Prophet and AdaptiveEpidemic belongs to analogous algorithms, all can be considered to improve algorithm performance by restricting data bag copy amount on Epidemic algorithm basis, and 2 kinds of algorithms have higher comparativity.Be that to should be this algorithm adaptability comparatively strong with the reason of Spray And Wait method comparison, good performance can be obtained under various network environment.
When data packet number is 30, because the saturated situation of nodal cache can not occur data packet number less, Adaptive Epidemic algorithm deteriorates to Epidemic algorithm at this moment.Fig. 5-Fig. 7 simulation result shows, and all indexs of 2 algorithms are identical, and this is consistent with theoretical analysis result.
Fig. 5 result shows, under different pieces of information bag quantity, the transmission success rate of Adaptive Epidemic algorithm is all better than Epidemic and Prophet.As when 1600 packet, improvement degree reaches 39.3% and 25.6% respectively.
Fig. 5 result shows, comparing when data packet number is less Adaptive Epidemic with Spray And Wait algorithm can abundant Epidemic advantage, and transmission success rate is significantly leading.And when packet is a lot, inhibit the transmission of packet copy because adaptation mechanism plays a role, Adaptive Epidemic also can obtain and to be better than or close to the performance of Spray And Wait algorithm.
Fig. 6 result shows, comparatively Epidemic algorithm is poor for Adaptive Epidemic algorithm transmission delay index, when maximum gap occurs in 800 packets, now transmission delay adds 17.6%, this result meets algorithm mechanism, when nodal cache district occurs saturated, packets need is waited in source node, thus adds transmission delay.
Fig. 7 result shows, Adaptive Epidemic algorithm is compared with Epidemic and reduced routing cost all sidedly, when node is more, especially significantly, as when 3600 node, have dropped 87.1%; Compare with Spray And Wait algorithm and also reduced 79.2%
Consistent with each index trend height of Prophet algorithm as can be seen from Fig. 5-Fig. 7, Adaptive Epidemic, Epidemic, reflect the contact of 3 kinds of algorithm inherences; Also show that Self-adaptive mechanism can't change the core mechanism of Epidemic algorithm.
Fig. 5-Fig. 7 simulation result supports theory analysis above, shows in some scenarios, and adaptation mechanism can suppress crowding-out effect to a certain extent, improves algorithm performance, widens the applicability of algorithm.
Claims (1)
1. an opportunistic network routing algorithm, it is characterized in that: this routing algorithm comprises the principle of Epidemic routing algorithm, parameter and the course of work, that the one of Epidemic routing algorithm is improved, introduce adaptation mechanism on the basis of Epidemic routing algorithm, in opportunistic network, each node maintenance field is used for depositing threshold values λ, λ ∈ [0,1], if the percentage in occupied space exceedes threshold values λ in nodal cache, then think that nodal cache district is saturated; When node i and any node j meet, first node i obtains node j and surroundings nodes cache condition, adds up the node number N contacted with node i
ai, cushion saturated node number N
ei; Calculate p
i=N
ei/ N
ai, define known p by it
i∈ [0,1]; Node i is according to p
ivalue, random reproduction packet is also sent to the node contacted with it.
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| CN101267400A (en) * | 2008-04-25 | 2008-09-17 | 北京航空航天大学 | A self-adapted local routing method in Scale-Free network |
| CN102209029A (en) * | 2011-05-19 | 2011-10-05 | 北京工商大学 | Grouping strategy based opportunistic network routing algorithm |
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| CN101267400A (en) * | 2008-04-25 | 2008-09-17 | 北京航空航天大学 | A self-adapted local routing method in Scale-Free network |
| CN102209029A (en) * | 2011-05-19 | 2011-10-05 | 北京工商大学 | Grouping strategy based opportunistic network routing algorithm |
Non-Patent Citations (1)
| Title |
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| Yunfeng Lin et al.Performance Modeling of Network Coding in Epidemic Routing.《MobiOpp "07 Proceedings of the 1st international MobiSys workshop on Mobile opportunistic networking》.2007,67-74. * |
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