CN111586726A - Usability measurement evaluation method for mobile Ad Hoc network fault model - Google Patents

Usability measurement evaluation method for mobile Ad Hoc network fault model Download PDF

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CN111586726A
CN111586726A CN202010309903.3A CN202010309903A CN111586726A CN 111586726 A CN111586726 A CN 111586726A CN 202010309903 A CN202010309903 A CN 202010309903A CN 111586726 A CN111586726 A CN 111586726A
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availability
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CN111586726B (en
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傅妍芳
苏一昶
王赞
戴飞
郭登登
姚海涛
钟联炯
赵明
唐俊勇
田鹏辉
雷翔
李丹
朱宇挺
宋新美
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Xian Technological University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/04—Arrangements for maintaining operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/06—Testing, supervising or monitoring using simulated traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W74/00—Wireless channel access
    • H04W74/08—Non-scheduled access, e.g. ALOHA
    • H04W74/0833—Random access procedures, e.g. with 4-step access
    • H04W74/0841—Random access procedures, e.g. with 4-step access with collision treatment
    • H04W74/085—Random access procedures, e.g. with 4-step access with collision treatment collision avoidance
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract

The invention belongs to the field of network availability, and particularly relates to an availability measurement evaluation method for a mobile Ad Hoc network fault model, which comprises the following steps: the method comprises the following steps: establishing an abstract communication model according to network characteristics; step two: summarizing fault types of end-to-end communication of the network; step three: establishing a network fault model; step four: calculating the service availability based on the time delay index; the method can carry out more accurate availability evaluation on the mobile self-organizing network, and the obtained service availability can be used as one of the evaluation indexes of mobile self-organizing internet design scheme optimization and established mobile self-organizing network.

Description

Usability measurement evaluation method for mobile Ad Hoc network fault model
Technical Field
The invention belongs to the field of network availability, and particularly relates to an availability measurement evaluation method for a mobile Ad Hoc network fault model.
Background
A Mobile Ad Hoc Network (MANET) is a multi-hop, centerless, limited-energy, temporary distributed Network system composed of wireless Mobile nodes, and self-organizes in a Mobile, time-varying wireless communication environment by virtue of mutual cooperation between nodes. Each node in the network has the functions of a host and a router, multi-hop communication is realized through storage and relay forwarding, and each node can dynamically join or leave the network. As a promising wireless communication network technology supporting mobility, high self-organization, fast self-healing, flexible networking and strong system overall survivability, the Ad Hoc network has wide application fields and prospects, such as search and rescue, post-disaster emergency communication, mobile office communication and the like.
The network availability is an important standard for measuring the sustainable communication service capability in the mobile ad hoc network, and is a comprehensive evaluation of factors such as node reliability, link quality reliability, network topology, traffic flow, routing algorithm and the like in the network, and reflects the capability of the network for providing sustainable service between nodes without considering external destructive action. Although the research on the Ad Hoc network at home and abroad is greatly progressed at present, concepts, models and algorithms displayed by the evaluation method are overlapped and disordered and cannot be a system. And the research angle is from the nature of the network, and is independent of faults and user requirements. The invention provides an availability measurement evaluation method for a mobile Ad Hoc network fault model by taking network system faults as a core and performing mathematical analysis and modeling
Disclosure of Invention
In order to solve the above problems in the prior art, the present invention provides a method for evaluating availability metrics of a mobile Ad Hoc network failure model, and the technical problems to be solved by the present invention are realized by the following technical solutions:
a usability measurement evaluation method for a mobile Ad Hoc network fault model comprises the following steps:
the method comprises the following steps: establishing an abstract communication model according to network characteristics;
step two: summarizing fault types of end-to-end communication of the network;
step three: establishing a network fault model;
step four: and calculating the service availability based on the time delay index.
Further, the first step specifically comprises: all mobile terminal nodes are set to have the same limited energy and communication radius; and the network is divided into different areas, the nodes in the same area can directly communicate, and the nodes in different areas communicate through the relay of the nodes in the cross area.
Further, the second step is specifically as follows: a node fault of which the connection is interrupted due to insufficient energy of a relay node or movement of the node is called a type I fault, and the occurrence rate of the type I fault is lambda1Mean time delay of fault transition from class I to no fault is 1/mu1(ii) a Due to the influence of communication link obstruction, fading, noise and the like between nodesThe type of link failure caused by the sound is called class II failure, and the incidence rate of the class II failure is lambda2The mean time delay for transition from class II to no fault is 1/mu2(ii) a The average shift rate of the nodes is λ, and the average shift rate is μ.
Further, the third step is (1) formally describing elements in the network, making I ∈ I ═ 0,1,2, the., N } represent the number of relay nodes available for normal use in the current intersection region, making J ∈ R ═ 0,1,2} represent a fault type set, 0 is no fault, 1 is a type I fault, 2 is a type ii fault, making a tuple { (I, J) | I ∈ I, J ∈ J } represent a two-hop link connection is valid or faulty, I normal nodes available for relaying are in the intersection region of the current link and the system is in a type J fault, making a state (N,0) represent that the current end-to-end connection is valid, N relay nodes are located in the intersection region and can normally operate, one of the N-1 relay nodes participates in relay forwarding, when any one of the remaining N-1 nodes leaves the intersection region with a probability λ, the network state is transferred to (N-1,0), making a state (N-1,0) represent that the current relay nodes are located outside the intersection region and the relay nodes are not available for relaying, and when the relay nodes are shifted to the network, N-1 node is shifted to the intersection region with a probability λ, and the relay node is shifted to the normal node, and the relay node is shifted to the relay node, and the relay node, wherein the relay node is shifted to the relay node, the relay node1Or λ2Transition to state (N-1,1) or (N-1, 2); for the state (N-1,1) or (N-1,2), the failed node delays 1/mu in passing through the route switching1Or 1/mu2Then, turning to a fault-free state, namely a state (N, 0); (2) calculating the steady-state availability of the end to end; converting the state in the step (1) into a Markov chain with continuous time; solving the Markov state;
for state (N, 0):
-πn,0*((n-1)λ+λ1+λ2)+πn-1,0*μ+πn-1,1*μ1+πn-1,2*μ2＝0
for state (N-1,1) there are: -πn-1,1*μ1+πn,0*λ1＝0
For state (N-1,2) there are: -pin-1,2*μ2+πn,0*λ2＝0
Can obtain the product
Figure BDA0002457291930000031
For state (N-1, 0):
-πn-1,0*((n-1)λμ+λ1+λ2μ)+-πn,0*(n-1)λ+πn-3,0*2μ+πn-3,1*μ1+πn-2,1*μ2＝0
for state (N-2,1) there are: -pin-2,1*μ1+πn-1,0*λ1＝0
For state (N-2,2) there are: -pin-2,2*μ2+πn-1,0*λ2＝0
The following can be obtained:
Figure BDA0002457291930000041
the calculation process for the steady state availability of states (N-2,0), (N-3,0), (2,0) is the same as (N-1, 0);
for state (1, 0):
-π1,0*((n-1)λ+μ+λ1+λ2)+π2,0*λ+π0,0*λμ+π0,1*μ1+π0,2*μ2＝0
-π1,0*((n-1)μ+λ)+π2,0*λ+π0,0*nμ＝0
wherein
Figure BDA0002457291930000042
Figure BDA0002457291930000043
The following can be obtained:
Figure BDA0002457291930000044
and (3) obtaining a universal expression of each state:
Figure BDA0002457291930000045
Figure BDA0002457291930000046
Figure BDA0002457291930000047
then
Figure BDA0002457291930000048
Deriving a two-hop network end-to-end steady state availability of
Figure BDA0002457291930000049
Further, the fourth step specifically includes the following steps: (1) calculating the average steady-state availability of the whole network; (2) analyzing the time delay standard reaching rate; (3) and calculating the availability of the network service.
Further, the step (1) is specifically as follows:
average steady state availability of a multi-hop communication system is
Figure BDA0002457291930000051
Wherein
Figure BDA0002457291930000052
A1Steady state availability, Δ, for a single hop1Is the proportion of one-hop condition in the network system;
A2steady state availability of two hops, Δ2The proportion of the two-hop condition in the network system;
An-1steady state availability of (n-1) hops, Δn-1On-net for (n-1) hop caseThe proportion of complex in the system;
Ansteady state availability of n hops, ΔnIs the proportion of n-hop condition in the network system;
obtaining the end-to-end steady-state availability of the multi-hop communication network as
Figure BDA0002457291930000053
Further, the step (2) is specifically as follows: establishing a Markov chain of discrete time as follows:
Figure BDA0002457291930000054
when the collision probability of each packet transmission is constant at p, where W0Is the minimum contention window, Wi＝2iW0i∈[0,m]M is the maximum avoidance order, i ∈ (0, m) is the transmission failure backoff order;
order to
Figure BDA0002457291930000055
bi,kAnd (3) obtaining the steady state distribution probability of the Markov chain according to the transition probability of the Markov chain:
bi,0＝pib0,0(0＜i＜m)；
bm,0＝pmb0,0/(1-p)；
bi,k＝(wi-k)bi,0/wi；
i∈[0,m],k∈[0,wi-1]；
Figure BDA0002457291930000061
b is formed byi,0＝pib0,0(0 < i < m) indicates that bi,0Obey a geometric distribution and can prove bi,0Is transferred to
Figure BDA0002457291930000063
Is only P/Wi+1(ii) a Since all stations transmit packets only when the back-off counter is 0, the station can transmit packets only when the back-off counter is 0
Figure BDA0002457291930000062
n is the number of subnodes in the combat zone, and the probability that all other n-1 stations do not transmit data packets is (1-tau)n-1(ii) a Tau and p can be obtained through a numerical calculation method;
calculating an average backspacing window of each round;
Wip＝(Wimax+1)/2
Wipis the average backoff window.
PS＝nτ(1-τ)n-1
PN＝(1-τ)n
PC＝1-PS-PN
Wherein P isSIs the probability of successful transmission of the data packet; pNIs the probability that the data packet is not transmitted; pCIs the probability of a data packet transmission but a collision occurs;
TS＝DIFS+H+ED++SIFS+ACK+
TC＝DIFS+H+ED+
wherein T isSDue to the channel busy time averaged for successful packet transmission; t isCChannel busy time averaged due to packet transmission collisions; h is the total length of the physical layer and MAC layer packet header fields; sIFSShort inter-frame intervals; let the propagation delay be; ED is the average transmission delay of the message; dIFSIs a distributed coordination function interval; average back-off time E of each round of message sendingBi＝Wip*σ+EFi(PSTS+PCTC)；WipAveraging the size of a backoff window for each round of message transmission; σ one slot duration; pSThe probability of successful transmission of each round of data packets; pCIs the probability of a data packet transmission but a collision occurs;TSdue to the channel busy time averaged for successful packet transmission; t isCIs the average channel busy time due to packet transmission collisions.
EFi＝Wip/Eldle-1
Eldle＝PN/(1-PN)
EFiAnd averaging the frequency of freeze in each round of message rollback process. EldleThe number of slots that are free before each transmission is expected.
The delay should be calculated by the following equation
Figure BDA0002457291930000071
Wherein L isj＝EBj+TC+T0，i∈(0,6)；
The average transmission delay probability distribution rate of the message is Pi＝P·(1-P)iI ∈ (0,6) when the collision is not successful in transmitting 6 times, the upper layer of the transmission report is terminated, correspondingly, when the collision is performed for i-1 times, the message is successfully transmitted, and the transmission delay time of the message is Edi。
Further, the step (3) is specifically as follows: when the network delay index is TB, calculating the standard rate of network delay
Figure BDA0002457291930000072
When the network delay index is TB, the network delay standard rate is calculated to be
Figure BDA0002457291930000073
Wherein for all edi≤TB。
Figure BDA0002457291930000081
Wherein i represents the number of hops, F1The delay achievement rate of one hop is represented, and the average delay achievement rate of the multiple hops is as follows:
Figure BDA0002457291930000082
according to the statistical principle, the service availability formula based on time delay is established as follows:
Figure BDA0002457291930000083
compared with the prior art, the invention has the beneficial effects that:
the Ad Hoc network service availability evaluation method based on the fault can obtain the service availability which can be used as one of the evaluation indexes of the design scheme optimization and the built vehicle-mounted mobile Ad Hoc network of the vehicle-mounted mobile Ad Hoc network; according to the method, the network fault is analyzed, a multi-state transition theory is introduced, and the reliable evaluation of the steady-state availability of the network system is obtained by solving the Markov process of each state. In the modeling process, the characteristics of easy interference of a vehicle-mounted mobile network, frequent node movement, high node movement speed and the like are closely combined, and system faults are induced and classified, so that the model is closer to the actual communication situation. The invention can carry out more accurate availability evaluation on the vehicle-mounted mobile self-organizing network under the support of the simulation environment.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is an abstract network communication model.
FIG. 3 is a state transition diagram of state transitions of the network under failure.
FIG. 4 is a state transition diagram of a CSMA \ CA protocol backoff window
Fig. 5 shows the situation that the network steady-state availability varies with the interference strength during the simulation process.
Fig. 6 is a graph of the impact of interference time interval on traffic availability.
Fig. 7 is the effect of the number of nodes on the availability of traffic.
Fig. 8 is a graph of the effect of channel transmission rate on availability.
Fig. 9 is a graph of the effect of message length on availability.
Detailed Description
The present invention will be described in further detail with reference to specific examples, but the embodiments of the present invention are not limited thereto.
As shown in fig. 1, a method for evaluating availability metrics of a mobile Ad Hoc network failure model includes the following steps:
the method comprises the following steps: establishing an abstract communication model according to network characteristics;
step two: summarizing fault types of end-to-end communication of the network;
step three: establishing a network fault model;
step four: and calculating the service availability based on the time delay index.
As shown in fig. 2, the communication model is abstracted according to the actual characteristics of the combat network:
and in the vehicle-mounted network building process, the terminals of each vehicle-mounted network system realize interconnection through the self-built network. To simplify the analysis, it is assumed that each mobile terminal node has the same limited energy and communication radius. According to the characteristics of the random mobile model algorithm, the nodes in the network are uniformly distributed and the motion of all the nodes is independent. The network can be divided into different areas by considering the networking characteristics of the network and the influence of the actual communication environment, nodes in the same area can directly communicate, and the nodes in different areas cannot directly communicate due to the limitation of communication radius or terrain and the like, and can communicate only through the relay of the nodes in the crossed area.
Generalizing the fault types of network end-to-end communication:
the failure reasons of the end-to-end communication of the mobile Ad Hoc network are mainly a node failure type caused by insufficient energy of a relay node or connection interruption caused by node movement and a link failure type caused by the influence of communication link obstacles, fading, noise and the like among nodes. Other failures (e.g., node hardware failures) are ignored because of their low probability of occurring and their long recovery time. The failure type research and analysis of the network obtains the main reason types on two levels. To simplify the analysis in the modeling, the following assumptions were made:
a node fault of which the connection is interrupted due to insufficient energy of a relay node or movement of the node is called a type I fault, and the occurrence rate of the type I fault is lambda1Mean time delay of fault transition from class I to no fault is 1/mu1。
The type of link failure caused by communication link failure between nodes, fading, noise, etc. is called as class II failure, and the incidence rate of the class II failure is lambda2The mean time delay for transition from class II to no fault is 1/mu2。
Considering the mobility of the nodes, the average mobility rate of the nodes is λ, and the average mobility rate is μ.
Establishing a network fault model:
as shown in fig. 3, elements in a network are formally described in order to evaluate network end-to-end communication availability.
Let I ∈ I ═ {0,1, 2., N } denote the number of relay nodes available for normal use in the current intersection region, let j ∈ R ═ {0,1,2} denote a set of fault types, 0 is no fault, 1 is a type I fault, and 2 is a type ii fault. When the two-tuple { (I, J) | I ∈ I, J ∈ J } represents that one two-hop link connection is valid (or fails), I (including the node providing the relay work) normal nodes available for relaying exist in the crossing area of the current link, and the system is in J-type failure.
The current end-to-end connection is effective by using a state (N,0), N relay nodes are positioned in a cross region and can work normally, and one of the relay nodes participates in relay forwarding. When any of the remaining N-1 nodes moves out of the intersection region with a probability λ, the network state transitions to (N-1, 0). For the state (N-1,0), the current end-to-end connection is effective, N-1 relay nodes are positioned in a cross region and can work normally, and one relay node participates in relay forwarding. The network state transitions to (N,0) when 1 node outside the area moves into the intersection area with probability μ. For the state (N,0), if the node currently in relay has I-type fault or II-type fault, the end-to-end connection is interrupted, the number of relay nodes available in the cross area is changed into N-1, and the network uses lambda as the network1Or λ2Transition to state (N-1,1) or (N-1, 2). For the state (N-1,1) or (N-1,2), the failed node delays 1/mu in passing through the route switching1Or 1/mu2And then to a no fault state, state (N, 0). Need to emphasizeIn the model assumption, the moving-in and moving-out of the nodes are dynamically balanced, the system is restored to the original state after the route switching delay, and similarly, the nodes are moved out of the cross area due to the link failure caused by interference or shielding, can only temporarily not work normally, and still return to the original state after being repaired. For state (1,0), if the last available relay node moves out with probability λ, there will be no more nodes available for relay forwarding and the network transitions to state (0, 0). At this time, the communication nodes at both ends must search for a new relay node again through the routing protocol, in this state, N backup relay nodes can all move in with probability μ, if a node is found to enter the cross region, the connection will be reestablished, and the network returns to the state (1, 0). After assigning transition probabilities to each state, the states can be converted into a continuous-time Markov chain.
By solving for the Markov state, for state (N,0) there is:
-πn,0*((n-1)λ+λ1+λ2)+πn-1,0*μ+πn-1,1*μ1+πn-1,2*μ2＝0
for state (N-1,1) there are: -pin-1,1*μ1+πn,0*λ1＝0
For state (N-1,2) there are: -pin-1,2*μ2+πn,0*λ2＝0
The following can be obtained:
Figure BDA0002457291930000111
for state (N-1, 0):
-πn-1,0*((n-1)λμ+λ1+λ2μ)+-πn,0*(n-1)λ+πn-3,0*2μ+πn-3,1*μ1+πn-2,1*μ2＝0
for state (N-2,1) there are: -pin-2,1*μ1+πn-1,0*λ1＝0
To the state (N-2,2) has-pin-2,2*μ2+πn-1,0*λ2＝0
The method is simplified and can be obtained:
Figure BDA0002457291930000121
the process of calculating the steady state availability for states (N-2,0), (N-3,0), (2,0) is similar to (N-1, 0).
For state (1, 0):
-π1,0*((n-1)λ+μ+λ1+λ2)+π2,0*λ+π0,0*λμ+π0,1*μ1+π0,2*μ2＝0
-π1,0*((n-1)μ+λ)+π2,0*λ+π0,0*nμ＝0
wherein
Figure BDA0002457291930000122
Figure BDA0002457291930000123
The method is simplified and can be obtained:
Figure BDA0002457291930000124
generalizing we through the above process we get a general expression for each state:
Figure BDA0002457291930000125
Figure BDA0002457291930000126
Figure BDA0002457291930000127
in the process of programming calculation, pi0,0Very small, can be ignored, then
Figure BDA0002457291930000128
Thus the end-to-end steady state availability of a two-hop network is
Figure BDA0002457291930000129
Calculating the service availability based on the time delay index:
and calculating the average steady-state availability of the whole network, wherein the calculation process of the multi-hop steady-state availability can be used for reference of the analysis process of the two-hop steady-state availability calculation, and a data packet starts from a source node, is transferred through a first cross area node, is forwarded to a second cross area, and so on until the data packet is finally transferred to a destination node. In the process, the data packet passes through the transit process of n-1 crossing areas. Thus, it is possible to provide
Figure BDA0002457291930000131
An average steady state availability of a multi-hop communication system is
Figure BDA0002457291930000132
Wherein:
A1steady state availability, Δ, for a single hop1Is the proportion of one-hop condition in the network system;
A2steady state availability of two hops, Δ2The proportion of the two-hop condition in the network system;
An-1steady state availability of (n-1) hops, Δn-1Is the proportion of (n-1) hop condition in the network system;
Ansteady state availability of n hops, ΔnIs the proportion of the n-hop case in the network system.
Thus, the end-to-end steady state availability of a multi-hop communication network is
Figure BDA0002457291930000133
Analyzing the time delay standard reaching rate:
a Markov model is established according to a CSMA/CA communication mechanism to research the behavior of a single node, so that the steady-state probability tau of sending a data packet by the node in a random time gap and the probability p of collision of transmission are deduced. Consider that there are n competing nodes. In the saturated state, each node has a data packet ready for transmission after each successful transmission. In addition, all packets are consecutive, and each packet needs to wait for a random back-off time before being transmitted. Let b (t) be a random process of the back-off time timer for a given node. The discrete time back-off mechanism employed by the DCF is an exponential back-off mechanism. The back-off time is chosen uniformly within the range (0, W-1) at each data packet transmission. Where W is the contention window and the size of the contention window depends on the number of failed transmissions of the packet. Each packet collides with a constant and independent probability p at each attempt to transmit, regardless of the number of retransmissions experienced. p is the conditional collision probability, which indicates the probability that this is the expected collision of a packet being transmitted on the channel. Let s (t) be a random process representing the back-off order (0...., m) at time t, and b (t) be a random process of the back-off time timer of a given node. According to the above conditions, a discrete-time back-off window size markov chain can be established, as shown in fig. 4, and the following formula is obtained by solving:
Figure BDA0002457291930000141
when the collision probability of each packet transmission is constant at p, where W0Is the minimum contention window, Wi＝2iW0i∈[0,m]M is the maximum avoidance order, i ∈ (0, m) is called the transmission failure backoff order.
Order to
Figure BDA0002457291930000142
bi,kFor the steady state distribution probability of the Markov chain, the following equation can be obtained from the transition probability of the Markov chain:
bi,0＝pib0,0(0＜i＜m)；
bm,0＝pmb0,0/(1-p)；
bi,k＝(wi-k)bi,0/wi；
i∈[0,m],k∈[0,wi-1]；
Figure BDA0002457291930000143
b is formed byi,0＝pib0,0(0 < i < m) indicates that bi,0Obey a geometric distribution and can prove bi,0Is transferred to
Figure BDA0002457291930000152
Is only P/Wi+1. Since all stations transmit packets only when the back-off counter is 0, the station can transmit packets only when the back-off counter is 0
Figure BDA0002457291930000151
n is the number of subnodes in the combat zone, and the probability that all other n-1 stations do not transmit data packets is (1-tau)n-1. It can be proved that the system has unique solution, and tau and p can be obtained by a numerical calculation method.
Next, an average backoff window for each round is calculated.
Wip＝(Wimax+1)/2
WipIs the average backoff window.
PS＝nτ(1-τ)n-1
PN＝(1-τ)n
PC＝1-PS-PN
Wherein P isSIs the probability of successful transmission of the data packet; pNIs the probability that the data packet is not transmitted; pCIs the probability of a packet transmission but a collision.
TS＝DIFS+H+ED++SIFS+ACK+
TC＝DIFS+H+ED+
Wherein T isSDue to the channel busy time averaged for successful packet transmission; t isCChannel busy time averaged due to packet transmission collisions; h is the total length of the physical layer and MAC layer packet header fields; sIFSShort interframe space (Short interframe space); let the propagation delay be; ED is the average transmission delay of the message. DIFSDistributed coordination function interval (distributeddireframe Space). To avoid channel acquisition, a station must wait a random back-off time between two successive new packet transmissions, even if it senses that the channel is idle at DIFS.
Calculating the average back-off time E of each round of message sendingBi＝Wip*σ+EFi(PSTS+PCTC)。WipAveraging the size of a backoff window for each round of message transmission; σ one slot duration; pSThe probability of successful transmission of each round of data packets; pCIs the probability of a data packet transmission but a collision occurs; t isSDue to the channel busy time averaged for successful packet transmission; t isCIs the average channel busy time due to packet transmission collisions.
EFi＝Wip/Eldle-1
Eldle＝PN/(1-PN)
EFiAnd averaging the frequency of freeze in each round of message rollback process. EldleThe number of slots that are free before each transmission is expected.
The delay should be calculated by the following equation
Figure BDA0002457291930000161
Wherein L isj＝EBj+TC+T0，i∈(0,6)。
The average transmission delay probability distribution rate of the message is Pi＝P·(1-P)iI ∈ (0,6) collision does not occur when sending 6 timesWhen successful, the message is successfully sent after the upper layer of the transmission report is stopped to send corresponding i-1 times of conflicts, and the transmission delay time of the message is Edi。
Calculating the service availability:
when the delay index of the vehicle-mounted network is TB, the network delay standard rate is calculated to be TB
Figure BDA0002457291930000162
When the delay index of the vehicle-mounted network is TB, the network delay standard rate is calculated to be TB
Figure BDA0002457291930000163
Wherein for all edi≤TB。
Figure BDA0002457291930000164
Wherein i represents the number of hops, F1The delay achievement rate of one hop is represented, and the average delay achievement rate of the multiple hops is as follows:
Figure BDA0002457291930000165
by applying the statistical principle, a service availability formula based on time delay is established as follows:
Figure BDA0002457291930000171
example 2:
by comparing the simulation experiment result with the theoretical calculation result, the method for quantifying the network availability under the premise of considering the factors of node mobility, faults, communication protocols and the like of the AdHoc network is verified. For guiding the performance evaluation and network planning of mobile ad hoc networks. In the simulation, the network scenario is: 20 nodes of a vehicle-mounted squad are uniformly distributed in a plane area of 20km multiplied by 20km, the communication radius of a radio station is 2km, the combat radius is 4km, and the maximum relay value is 4 hops. And all the nodes are simulated according to the Brownian motion model. The actual meaning of the parameters in the network model is shown in table 1.
TABLE 1 availability parameter Table
Figure BDA0002457291930000172
By examining the relevant indexes, a basic parameter value table as shown in table 2 was established. The network availability under the CSMA/CA communication mechanism and according to partial variation combination of variable parameters is researched, and compared with theoretical calculation results, the performances under different actual network environments are compared.
Table 2 service availability parameter table
Figure BDA0002457291930000181
The above parameters are important factors affecting the performance of the mobile ad hoc network, and a large number of simulation experiments are performed on the parameters.
When the network is simulated to have 1 hop, 2 hop and 4 hop under different interference strengths by shortening the interference interval, the network steady-state availability is shown in fig. 5.
Then, the service availability based on the transmission delay can be calculated according to the steady-state availability and the delay reaching rate, and the result is shown in table 3. It can be seen from the calculation results that the steady-state availability of the network drops sharply when the interference frequency exceeds a limit. And the influence of interference becomes greater as the number of nodes increases.
TABLE 3 simulation results
Figure BDA0002457291930000182
Under the same conditions, the results are compared with the calculation results through multiple simulation experiments, and the results are shown in fig. 6. The service availability values are counted by changing the number of nodes, the message length and the channel transmission rate respectively, and the results are shown in the following fig. 7-9. The average error between the result of the calculation model and the simulation result is less than 9%, which shows that the usability calculation model established by the method can accurately reflect the usability of part of the connection network.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.

Claims (8)

1. A usability measurement evaluation method for a mobile Ad Hoc network fault model is characterized in that: the method comprises the following steps:
the method comprises the following steps: establishing an abstract communication model according to network characteristics;
step two: summarizing fault types of end-to-end communication of the network;
step three: establishing a network fault model;
step four: and calculating the service availability based on the time delay index.
2. The method of claim 1 for assessing availability metrics of a mobile Ad Hoc network failure model, wherein: the first step is specifically as follows: all mobile terminal nodes are set to have the same limited energy and communication radius; and the network is divided into different areas, the nodes in the same area can directly communicate, and the nodes in different areas communicate through the relay of the nodes in the cross area.
3. The method of claim 1 for assessing availability metrics of a mobile Ad Hoc network failure model, wherein: the second step is specifically as follows: a node fault of which the connection is interrupted due to insufficient energy of a relay node or movement of the node is called a type I fault, and the occurrence rate of the type I fault is lambda1Mean time delay of fault transition from class I to no fault is 1/mu1(ii) a The type of link failure caused by communication link failure between nodes, fading, noise, etc. is called as class II failure, and the incidence rate of the class II failure is lambda2From class II to no faultHas an average fault transition delay of 1/mu2(ii) a The average shift rate of the nodes is λ, and the average shift rate is μ.
4. The method as claimed in claim 1, wherein the third step is (1) formally describing elements in the network, I ∈ I ═ 0,1, 2.. the.n } represents the number of relay nodes available for normal use in the current intersection region, J ∈ R ═ 0,1,2} represents a fault type set, 0 is no fault, 1 is a type I fault, 2 is a type ii fault, a dyad { (I, J) | I ∈ I, J ∈ J } represents a two-hop link connection valid or a fault, I normal nodes available for relay are in the intersection region of the current link, and the system is in a type J fault, a state (N,0) represents that the current end-to-end connection is valid, N relay nodes are in the intersection region and can operate normally, the rest of the relay nodes participate in relay forwarding, any one of N-1 nodes moves out of the intersection region with a probability, N-1 node moves into the intersection region with a probability, N-1 node moves out of the intersection region with a probability, N-1 node moves into the relay node, N-N nodes are in the intersection region with a probability, N-1 state, N-1-N nodes are in the relay nodes are in the intersection region, and the relay nodes are in the relay nodes, N-1 state, N-1Or λ2Transition to state (N-1,1) or (N-1, 2); for the state (N-1,1) or (N-1,2), the failed node delays 1/mu in passing through the route switching1Or 1/mu2Then, turning to a fault-free state, namely a state (N, 0); (2) calculating the steady-state availability of the end to end; converting the state in the step (1) into a Markov chain with continuous time; solving the Markov state;
for state (N, 0):
-πn,0*((n-1)λ+λ1+λ2)+πn-1,0*μ+πn-1,1*μ1+πn-1,2*μ2＝0
for state (N-1,1) there are: -pin-1,1*μ1+πn,0*λ1＝0
For state (N-1,2) there are: -pin-1,2*μ2+πn,0*λ2＝0
Can obtain the product
Figure FDA0002457291920000021
For state (N-1, 0):
-πn-1,0*((n-1)λμ+λ1+λ2μ)+-πn,0*(n-1)λ+πn-3,0*2μ+πn-3,1*μ1+πn-2,1*μ2＝0
for state (N-2,1) there are: -pin-2,1*μ1+πn-1,0*λ1＝0
To the state (N-2,2) has-pin-2,2*μ2+πn-1,0*λ2＝0
The following can be obtained:
Figure FDA0002457291920000031
the calculation process for the steady state availability of states (N-2,0), (N-3,0), (2,0) is the same as (N-1, 0);
for state (1, 0):
-π1,0*((n-1)λ+μ+λ1+λ2)+π2,0*λ+π0,0*λμ+π0,1*μ1+π0,2*μ2＝0
-π1,0*((n-1)μ+λ)+π2,0*λ+π0,0*nμ＝0
wherein
Figure FDA0002457291920000032
Figure FDA0002457291920000033
The following can be obtained:
Figure FDA0002457291920000034
and (3) obtaining a universal expression of each state:
Figure FDA0002457291920000035
Figure FDA0002457291920000036
Figure FDA0002457291920000037
then
Figure FDA0002457291920000038
Deriving a two-hop network end-to-end steady state availability of
Figure FDA0002457291920000041
5. The method of claim 1 for assessing availability metrics of a mobile Ad Hoc network failure model, wherein: the fourth step specifically comprises the following steps: (1) calculating the average steady-state availability of the whole network; (2) analyzing the time delay standard reaching rate; (3) and calculating the availability of the network service.
6. An availability metric evaluation method for a mobile Ad Hoc network failure model according to claim 5, characterized in that: the step (1) is specifically as follows:
average steady state availability of a multi-hop communication system is
Figure FDA0002457291920000042
Wherein
Figure FDA0002457291920000043
A1Steady state availability, Δ, for a single hop1Is the proportion of one-hop condition in the network system;
A2steady state availability of two hops, Δ2The proportion of the two-hop condition in the network system;
An-1steady state availability of (n-1) hops, Δn-1Is the proportion of (n-1) hop condition in the network system;
Ansteady state availability of n hops, ΔnIs the proportion of n-hop condition in the network system;
obtaining the end-to-end steady-state availability of the multi-hop communication network as
Figure FDA0002457291920000044
7. The method of claim 5, wherein the method comprises the following steps: the step (2) is specifically as follows: establishing a Markov chain of discrete time according to the communication mechanism characteristics of the CSMA/CA protocol as follows:
Figure FDA0002457291920000051
when the collision probability of each packet transmission is constant at p, where W0Is the minimum contention window, Wi＝2iW0i∈[0,m]M is the maximum avoidance order, i ∈ (0, m) is the transmission failure backoff order;
Figure FDA0002457291920000052
bi,kand (3) obtaining the steady state distribution probability of the Markov chain according to the transition probability of the Markov chain:
bi,0＝pib0,0(0＜i＜m)；
bm,0＝pmb0,0/(1-p)；
bi,k＝(wi-k)bi,0/wi；
i∈[0,m],k∈[0,wi-1]；
Figure FDA0002457291920000053
b is formed byi,0＝pib0,0(0 < i < m) indicates that bi,0Obey a geometric distribution and can prove bi,0Is transferred to
Figure FDA0002457291920000054
Is only P/Wi+1(ii) a Since all stations transmit packets only when the back-off counter is 0, the station can transmit packets only when the back-off counter is 0
Figure FDA0002457291920000055
p＝1-(1-τ)n-1
n is the number of subnodes in the combat zone, and the probability that all other n-1 stations do not transmit data packets is (1-tau)n-1(ii) a Tau and p can be obtained through a numerical calculation method;
calculating an average backspacing window of each round;
Wip＝(Wi max+1)/2
Wipis the average backoff window;
PS＝nτ(1-τ)n-1
PN＝(1-τ)n
PC＝1-PS-PN
wherein P isSIs the probability of successful transmission of the data packet; pNIs the probability that the data packet is not transmitted; pCIs the probability of a data packet transmission but a collision occurs;
TS＝DIFS+H+ED++SIFS+ACK+
TC＝DIFS+H+ED+
wherein T isSDue to the channel busy time averaged for successful packet transmission; t isCChannel busy time averaged due to packet transmission collisions; h is the total length of the physical layer and MAC layer packet header fields; sIFSShort inter-frame intervals; let the propagation delay be; ED is the average transmission delay of the message; dIFSIs a distributed coordination function interval; average back-off time E of each round of message sendingBi＝Wip*σ+EFi(PSTS+PCTC)；WipAveraging the size of a backoff window for each round of message transmission; σ one slot duration; pSThe probability of successful transmission of each round of data packets; pCIs the probability of a data packet transmission but a collision occurs; t isSDue to the channel busy time averaged for successful packet transmission; t isCChannel busy time averaged due to packet transmission collisions;
EFi＝Wip/Eldle-1
Eldle＝PN/(1-PN)
EFiaveraging the frequency of freeze in each round of message rollback process; eldleThe number of idle time slots is expected before each transmission;
the delay should be calculated by the following equation
Figure FDA0002457291920000071
Wherein L isj＝EBj+TC+T0，i∈(0,6)；
The average transmission delay probability distribution rate of the message is Pi＝P·(1-P)iI ∈ (0,6) when the collision is not successful in transmitting 6 times, the upper layer of the transmission report is terminated, correspondingly, when the collision is performed for i-1 times, the message is successfully transmitted, and the transmission delay time of the message is Edi。
8. The method of claim 5, wherein the method comprises the following steps: the step (3) is specifically performedComprises the following steps: when the network delay index is TB, calculating the standard rate of network delay
Figure FDA0002457291920000072
When the network delay index is TB, the network delay standard rate is calculated to be
Figure FDA0002457291920000073
Wherein for all edi≤TB；
Fi＝F1 i,i＞1，
Wherein i represents the number of hops, F1The delay achievement rate of one hop is represented, and the average delay achievement rate of the multiple hops is as follows:
Figure FDA0002457291920000074
according to the statistical principle, the service availability formula based on time delay is established as follows:
Figure FDA0002457291920000075
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