CN104796793A - Opportunistic multimedia dynamic cloud platform and multi-relay hierarchical coordinated transmission method - Google Patents

Abstract

The invention discloses an opportunistic multimedia dynamic cloud platform and multi-relay hierarchical coordinated transmission method. The method includes: according to different multimedia stream and multimedia cloud states, judging and analyzing change law, to packet loss rate, decodable frame rate and peak value signal-to-noise ratio, of channel quality in realtime, and opportunistically forming an optimal dynamic multimedia cloud platform meeting user's diversity needs; reconstructing the multimedia stream in a wireless sensor network and based on picture group hierarchical coordination; providing a multi-relay and hierarchical coordinated transmission network forming scheme according to user's needs, state of the multimedia cloud platform and sensor node state. The method takes full account of the multimedia stream, the multimedia dynamic cloud platform and state of the wireless sensor network to opportunistically form the multimedia dynamic cloud platform and multi-relay and hierarchical coordinated wireless sensor network, so that needs, on diversity, of a user are met, multimedia stream cloud computing efficiency is improved, multimedia data coding and decoding complexity is optimized, and resource utilization rate of the wireless sensor network is increased.

Description

The transmission method of opportunistic Multimedia Dynamic cloud platform and many relayings classification cooperation

Technical field

The present invention relates to multimedia cloud platform and cooperation transmission method, particularly relate to the transmission method of a kind of opportunistic Multimedia Dynamic cloud platform and many relayings classification cooperation, belong to multimedia communication and field of cloud computer technology.

Background technology

Transmission path between opportunistic network technology Maintenance free transmitting terminal and destination node, takes into full account the dynamic characteristic of network topology, according to the chance of meeting that certain factor inspires, by Nodes Self-organized composition data transmission network.And in wireless sensor network multimedia communication, the large data of multimedia are stored in cloud platform, sensor node receives the media stream from cloud platform.But be subject to when providing multimedia service limiting in own power source, hardware device noise, the interference of extraneous circumstances not known factor etc., be difficult to solve media stream service quality guarantee problem when remote, long-time and big data quantity real time communication.And multimedia streaming data service also has these features: different multimedia flow structure and data are stored, data processing is different with the requirement of transmission; User's request has diversity, and network state is dynamic change.So the media stream computational methods of static cloud platform and single relaying single-stage cooperation transmission method cannot meet the requirements of support of the diversity multimedia application of wireless sensor network in the past.Given this, the applicant has done useful design, and technical scheme described below produces under this background.

Summary of the invention

For above-mentioned the deficiencies in the prior art, the object of this invention is to provide the transmission method of a kind of opportunistic Multimedia Dynamic cloud platform and many relayings classification cooperation, self adaptation opportunistic sets up the optimization active multi-media cloud platform meeting multiplicity of subscriber demand, and sets up many relayings-classification cooperation transmission network according to user's request, multimedia cloud platform status and sensor node state.

Technical scheme of the present invention is such: the transmission method of a kind of opportunistic Multimedia Dynamic cloud platform and many relayings classification cooperation, and comprise and set up opportunistic Multimedia Dynamic cloud platform, described opportunistic Multimedia Dynamic cloud platform of setting up comprises the following steps:

Multimedia streaming data state after MPEG algorithm coding of S01, user side demand is defined as { intracoded frame, forward-predictive-coded frames, bi-directional predicted interpolation coding frame }, each multimedia high in the clouds state is defined as { residual memory space, communication distance between high in the clouds, transmitted power };

Status parameter values after the multimedia streaming data coding obtained in S02, integrating step S01, multimedia streaming data and qualitative parameter SYSTEM OF LINEAR VECTOR calculate, and draw frame of video to be sent;

S03, determine the priority of multimedia streaming data, when multimedia streaming data only comprises intracoded frame, priority is 1, when multimedia streaming data only comprises intracoded frame and forward-predictive-coded frames, priority is 2, and when multimedia streaming data comprises intracoded frame, forward-predictive-coded frames and bi-directional predicted interpolation coding frame, priority is 3;

S04, user side demand are focused on Real-time Ability and are turned S05, focus on play quality guarantee and turn S06, focus on combination property and turn S07;

S05, from the high in the clouds meeting communication distance between high in the clouds and be less than 10% of transmitting terminal and receiving terminal spacing is gathered, 3 high in the clouds are selected to set up cloud platform, calculate the cloud platform error rate, if the error rate is greater than 3%, then from the set of high in the clouds, 1 high in the clouds and aforementioned 3 high in the clouds are selected to rebuild cloud platform, for sending the multimedia streaming data that priority is 1;

S06, from the high in the clouds meeting communication distance between high in the clouds and be less than 5% of transmitting terminal and receiving terminal spacing is gathered, 4 high in the clouds are selected to set up cloud platform, for sending the multimedia streaming data that priority is 2;

S07, from the high in the clouds meeting communication distance between high in the clouds and be less than 10% of transmitting terminal and receiving terminal spacing is gathered, select 3 high in the clouds to set up cloud platform, calculate the cloud platform error rate, if the error rate is less than 3%, then removes 1 high in the clouds and rebuild cloud platform; If the error rate is more than or equal to 3% and be less than or equal to 4%, then from the high in the clouds meeting communication distance between high in the clouds and be less than 6% of transmitting terminal and receiving terminal spacing is gathered, 2 high in the clouds are selected to set up cloud platform, for sending the multimedia streaming data that priority is 3.

Further, the transmission method of opportunistic Multimedia Dynamic cloud platform and many relayings classification cooperation comprises step S08, selects N _rindividual via node, sets up N _r-N _mclassification cooperation transmission network, described N _mfor the high in the clouds number that the cloud platform set up in described step S05, S06 or S07 comprises.

Further, the transmission method of described opportunistic Multimedia Dynamic cloud platform and many relayings classification cooperation comprises step S09, sender node to N _rindividual candidate relay node and receiving terminal node send multi-medium data, contrast the feedback information from candidate relay node and receiving terminal node, if feedback is consistent, then set up classification cooperation transmission network; If feed back inconsistent, then get rid of the inconsistent candidate relay node of feedback, residue candidate relay node sets up classification cooperation transmission network.

Further, described when setting up the via node fault of classification cooperation transmission network, this via node reconstructs sending failed multimedia streaming data, broadcasts to neighbor node, neighbor node and receiving terminal node receive backward this via node feedback of broadcast, select not at described N from feedback _rthe neighbor node of individual candidate relay node replaces this via node.

Further, described N _rmake channel utilization C _nwith value when decodable code frame per second DFR reaches maximum on receiving terminal node.

Preferably, described in $C_N=\frac{n{N}_M^k}{C_{A}m{(N_R+2)}^{\mathrm{\α}+\mathrm{\β}+\mathrm{\γ}}},$ Described $\begin{array}{c}\mathrm{DFR}={\left\{E\right[e^{\mathrm{\α}}\left]E\right[e^{\mathrm{\β}}\left]E\right[e^{\mathrm{\γ}}\left]\right\}}^{\frac{n}{m}}{e}^{-N_R{N}_M}\frac{d^{-\mathrm{\ρ}}}{\underset{l=1}{\overset{N_R}{\mathrm{\Σ}}}{d}_l^{-\mathrm{\ρ}}}\\ \≤e^{-N_R{N}_M}{d}^{-\mathrm{\α}}\end{array},2\≤\mathrm{\ρ}\≤5,$ Described C _afor the junction network number of channel, described n is frame of video number in multimedia streaming data, described m is picture group number, described k is video frame type number, described α, β, γ are respectively intracoded frame in picture group, forward-predictive-coded frames, bi-directional predicted interpolation coding frame and group of pictures length ratio, described d be sender node to receiving terminal node distance, described d _lfor via node spacing.

Preferably, the received power P of described candidate relay node _lmeet, 2≤ρ≤5, described d be sender node to receiving terminal node distance, described d _{(s, l)}for sender node is to via node distance, described P _rfor receiving terminal node received power.

Preferably, described in described step S05, the residual memory space in high in the clouds is greater than n _is _i/ N _m, described in described step S06, the residual memory space in high in the clouds is greater than (n _is _i+ n _ps _p+ n _bs _b)/N _m, described in described step S07, the residual memory space in high in the clouds is greater than (n _is _i+ n _ps _p)/N _m, described n _iintracoded frame number in multimedia streaming data, described n _pforward-predictive-coded frames number, described n _sbi-directional predicted interpolation coding frame number, described S _iintraframe coding frame sign, described S _pforward-predictive-coded frames size, described S _sit is bi-directional predicted interpolation coding frame sign.

Preferably, the transmitted power P in high in the clouds described in described step S05, S06 and S07 _s≤ P _r(m ^{alpha+beta+γ})/n.

The beneficial effect of technical scheme provided by the present invention is, adopt Multimedia Dynamic high in the clouds, according to different media streams and multimedia high in the clouds state, real-time judge analyzes channel quality to the Changing Pattern of packet loss, decodable code frame per second and Y-PSNR, self adaptation opportunistic sets up the optimization active multi-media cloud platform meeting multiplicity of subscriber demand, thus has reliable, real-time and healthy and strong multimedia streaming service for wireless sensor network provides.In wireless sensor network, based on picture group GOP classification cooperation, the media stream from cloud platform is reconstructed; Received power in conjunction with via node and receiving terminal node sets up the set of optimum many relayings classification collaboration relay node; Many relayings-classification cooperation transmission network set up the scheme is given according to user's request, multimedia cloud platform status and sensor node state.Meet the diversity requirement of user, promote media stream cloud computing efficiency, optimize multi-medium data Code And Decode complexity, and improve wireless sensor network resource utilization.

Accompanying drawing explanation

Fig. 1 is the transmission schematic diagram based on opportunistic Multimedia Dynamic cloud platform and many relayings-classification cooperation wireless sensor network.

Fig. 2 is that the error rate affects Changing Pattern schematic diagram to packet loss.

Fig. 3 is that the error rate affects Changing Pattern schematic diagram to decodable code frame per second.

Fig. 4 is that the error rate affects Changing Pattern schematic diagram to Y-PSNR PSNR.

Fig. 5 is multimedia cloud platform architecture schematic diagram.

Fig. 6 is 6*5 network design schematic diagram.

Fig. 7 is multi-relay cooperation communication topology schematic diagram.

Fig. 8 is many relayings classification cooperation transmission cyclic process schematic diagram.

Fig. 9 is multimedia application hierarchical mode schematic diagram.

Embodiment

Below in conjunction with embodiment, the invention will be further described, but not as a limitation of the invention.

In wireless sensor network multimedia communication, suppose that M is that multi-medium data is quantitatively gathered, T is the qualitative parameter set of media stream on M, if quantitatively multi-medium data x belongs to M and is the Random Maps of T, degree of certainty f (x) of x to T belongs to interval [0,1], and have the random number of stable tendency, then the distribution of x on multimedia domain, MMD M is called that multimedia high in the clouds is denoted as M (x).

On M (x), store t frame of video, F=F ₁, F ₂..., F _t.Each frame of video belongs to intracoded frame I respectively, one of forward-predictive-coded frames P and bi-directional predicted interpolation coding frame category-B type.In conjunction with user's request U _rparameter vector T qualitative with media stream, calculates frame of video F to be sent _i, calculate according to formula (1).

Wherein, function h (F _i, T) and be that calculating object frame of video is analyzed in conjunction with qualitative parameter, function that user's request is analyzed conclusion combine, particularly by the degree of certainty f (F of frame of video with above-mentioned 2 _i) and qualitative analysis h (F _i, T) combine, be user's mapped streams data exactly.

In addition, T _p(F _i) be judge its priority according to video frame type, determine the frame type comprised in media stream according to result of calculation simultaneously:

(1) T _p(F _i)=1 shows only to comprise I frame in media stream, and now defining this media stream is elementary media stream S ₀, priority is 1;

(2) T _p(F _i)=2 show only to comprise I frame and P frame in media stream, and now defining this media stream is secondary multimedia stream S _l, priority is 2;

(3) T _p(F _i)=3 show only to comprise I frame in media stream, P frame and B frame, and now defining this media stream is high-level multimedia stream S _h, priority is 3, and the media stream of degree of certainty and 3 kinds of different stages has relation as Suo Shi formula (2) simultaneously.

$f\left(F\right)=T_p\left(F_i\right)\exp (-\frac{L\left(S_0\right)}{L\left(S_L\right)+L\left(S_H\right)})---\left(2\right)$

Wherein, L (S ₀) L (S _l) and L (S _h), represent the length of three kinds of rank media streams respectively, in units of packet, there is following features:

(1) passive type mark (up): wireless sensor network WSNs uploading data, self adaptation marks a high in the clouds and sets up through type service conversation with it;

(2) active on-demand service (descending): according to the active transmission of wireless sensor network WSNs user's request or repeating multimedia data;

(3) heterogeneous network is compatible: can wired, WLAN (wireless local area network), WSNs, and the heterogeneous networks such as Internet of Things IOT realize compatible communication, will set up transparent processing module between itself and upper layer cloud service;

(4) streaming cloud computing resources is shared: adaptively selected high in the clouds multi-medium data provides the streaming data devices of long-time stable for user;

(5) cloud service reliability: for user provides the multimedia streaming service with highly reliable, real-time and robustness.

In multimedia communication process, definition multimedia cloud platform status is { multimedia high in the clouds number N _m, signal to noise ratio snr, decodable code frame number N _dec, number-of-packet N _packet, error rate P _b.When each multimedia high in the clouds is separate and when meeting Gaussian Profile, the signal to noise ratio of receiving terminal can be calculated by formula (3).

$\left\{\begin{array}{c}\mathrm{SNR}=g\left(F_i\right)\\ f\left(x\right)=\frac{E_N}{d}\underset{i=1}{\overset{N_M}{\mathrm{\Σ}}}\left[({2N}_{\mathrm{packet}}-1)p_b\right]x\end{array}\right.---\left(3\right)$

Wherein, E _nfor Gaussian Profile desired value, d is the spacing of sender node and receiving terminal node.

Decodable code frame per second N _deccan be calculated by formula (4).

$N_{\mathrm{dec}}=T_p\left(F_i\right)N_{\mathrm{packet}}[{(1-P_b)}^{N_I}+P_b^{N_I}\underset{j=1}{\overset{N_P}{\mathrm{\Σ}}}(1-P_b)+P_b^{N_I+N_P}\underset{j=1}{\overset{N_B}{\mathrm{\Σ}}}(1-P_b)]---\left(4\right)$

Wherein, N _i, N _pand N _bbe respectively I frame, the number of P frame and B frame.

Packet loss can be calculated by formula (5).

$\left\{\begin{array}{c}{P}_M=r(N_{\mathrm{packet}},N_M)\\ r(x,y)=1-{(1-\frac{1}{2}{e}^{f\left(F_i\right)})}^{x/y}\frac{N_{\mathrm{dec}}}{x}\end{array}\right.---\left(5\right)$

PSNR (English full name is: Peak Signal to Noise Ratio, and Chinese is: Y-PSNR) can be calculated by formula (6).

$\mathrm{PSNR}=20\ln \left[\frac{N_{\mathrm{dec}}}{N_{\mathrm{packet}}}\frac{1}{\sqrt{\underset{i=1}{\overset{N_I}{\mathrm{\Σ}}}\underset{j=1}{\overset{N_P}{\mathrm{\Σ}}}\underset{k=1}{\overset{N_B}{\mathrm{\Σ}}}[C_R(I,P,B)-C_S(I,P,B)}}\right]---\left(6\right)$

According to formula (4), (5) and (6), the assay error rate is on the impact of packet loss, decodable code frame per second and PSNR, and result is as shown in Fig. 2,3 and 4.Consult Fig. 2, when the error rate increases, packet loss increases thereupon.When multimedia high in the clouds scale or communication distance increase, packet loss increases thereupon.As the good and N of channel quality _mwhen being 3, packet loss is close to 0.Show, increase multimedia high in the clouds quantity and significantly can not improve multimedia communication quality.Consult Fig. 3 to find, the error rate larger decodable code frame per second is lower.When multimedia high in the clouds scale or communication distance increase, packet loss also increases.When the error rate is greater than 3% and is less than 4%, N _mless to SNR (English full name is: Signal to Noise Ratio, and Chinese is: signal to noise ratio) impact with d.Consult Fig. 4 to find, if the error rate is greater than 4%, shakes by the level and smooth PSNR of increase multimedia high in the clouds number thus provide effective guarantee for telecommunication quality.

In sum, based on the performance aware such as packet loss, decodable code frame per second and PSNR chance active multi-media cloud platform as shown in Figure 5, implementation step is specific as follows:

(English full name is: Moving Picture Experts Group through MPEG for S01, multimedia streaming data, Chinese is: dynamic image expert group) be defined as { intracoded frame I after algorithm coding, forward-predictive-coded frames P, bi-directional predicted interpolation coding frame B}, multimedia high in the clouds state is defined as { residual memory space SR _i, communication distance d _c, transmitted power P _s.Wherein media stream status parameter values can obtain after system initialization, and multimedia high in the clouds status parameter values can obtain according to cloud device build-in attribute.

Status parameter values after the multimedia streaming data coding obtained in S02, integrating step S01, multimedia streaming data and qualitative parameter vector T linearly calculate, and draw frame of video F to be sent _i.

S03, determine the frame type T that comprises in media stream according to result of calculation _p(F _i) determine priority.T _p(F _i)=1 shows that only comprising I frame assignment in media stream is 1, and namely priority is 1; I frame is only comprised and P frame assignment is 2 in media stream, namely priority is 2; Comprise I frame in media stream, P frame and B frame assignment are 3, namely priority is 3.

S04, user side demand are focused on Real-time Ability and are turned S05, focus on play quality guarantee and turn S06, focus on combination property and turn S07;

S05, from the high in the clouds meeting communication distance between high in the clouds and be less than 10% of sender node and receiving terminal node spacing is gathered, 3 high in the clouds are selected to set up cloud platform, calculate the cloud platform error rate, if the error rate is greater than 3%, then from the set of high in the clouds, 1 high in the clouds and aforementioned 3 high in the clouds are selected to rebuild cloud platform, for sending the multimedia streaming data that priority is 1;

S06, from the high in the clouds meeting communication distance between high in the clouds and be less than 5% of sender node and receiving terminal node spacing is gathered, 4 high in the clouds are selected to set up cloud platform, for sending the multimedia streaming data that priority is 2;

S07, from the high in the clouds meeting communication distance between high in the clouds and be less than 10% of sender node and receiving terminal node spacing is gathered, select 3 high in the clouds to set up cloud platform, calculate the cloud platform error rate, if the error rate is less than 3%, then removes 1 high in the clouds and rebuild cloud platform; If the error rate is more than or equal to 3% and be less than or equal to 4%, then from the high in the clouds meeting communication distance between high in the clouds and be less than 6% of sender node and receiving terminal node spacing is gathered, 2 high in the clouds are selected to set up cloud platform, for sending the multimedia streaming data that priority is 3.

Suppose in media stream containing n frame of video, (English full name is m GOP: Group of Pictures, Chinese is: picture group), k video frame type, the goodput that WSNs transmits can be calculated by formula (7).

Wherein, N _rfor cooperative node scale, i.e. via node number, represent that receiving terminal is correctly decoded.

As can be seen from formula (7), T (n) is directly proportional to the via node scale participating in cooperation transmission in WSNs, is inversely proportional to the video frame type in media stream, and is directly proportional to GOP number.Therefore, adopt many relayings-classification cooperation scheme transmitting multimedia stream, there is following several advantage:

(1) space diversity gain is obtained by many relay transmission;

(2) by optimizing video frame structure in media stream, compressing multimedia stream scale can obtain energy gain, ensures real-time;

(3) many relayings-classification cooperation transmission can obtain at a distance, long-time transmission reliability guarantee.

Therefore, the cooperation media stream based on chance multimedia cloud platform is defined as, and { n, m, k}, frame of video characterizing definition is { α, beta, gamma }.Sender node, from after multimedia cloud platform obtains media stream, reconstructs by above-mentioned definition and sends to N _rindividual via node, { S, N _r, D} forms classification cooperation transmission network jointly.

After each via node and receiving terminal node D receive media stream, to its reconstruct and to sender node S feedback acknowledgment information.When designing many relayings-classification cooperation transmission network, for the detection of nodes break down and collaborative network restorative procedure as follows:

(1) by contrasting from N _rfeedback and the feedback of D, if unanimously, show correct reception;

(2) otherwise, inconsistent via node must exit many relayings-classification collaborative network;

(3) malfunctioning node is by sending failed multimedia streaming data by definition reconstruct, and to neighbor node broadcast, neighbor node and D node receive this malfunctioning node backward feedback, select not at N from feedback _rin neighbor node replace this node;

(4) by once retransmitting, ensureing that flow data correctly arrives D node, selecting substitute node, reconstruct classification collaborative network.

In sum, specifically set up relaying-classification cooperation transmission network process and be divided into three phases:

First stage: set up N _r-N _mthe set of classification cooperative node

The received power P of D node can be obtained by formula (8) _r.Wherein, the received power P of via node _lcan be obtained by formula (9).

$P_r=\underset{l=1}{\overset{N_R}{\mathrm{\Σ}}}{P}_l{\left(\frac{d}{d_{(S,l)}}\right)}^{-\mathrm{\ρ}},2\≤\mathrm{\ρ}\≤5---\left(8\right)$

$P_r\left(N_R^l\right)=P{\left(\frac{d}{d_{(S,l)}}\right)}^{-\mathrm{\ρ}}-10\mathrm{\βlg}\left(d\right),2\≤\mathrm{\ρ}\≤5---\left(9\right)$

Wherein, β represents path loss parameter and β=3.

In order to support parallel communications, this method requires transmitted power P _s≤ P _r(m ^{alpha+beta+γ})/n, wherein, α β γ is respectively in GOP, I, P and B frame and GOP length ratio.

Many relayings under extreme conditions-classification collaborative network signal to noise ratio is as shown in formula (10).

$S_{N_R}=\frac{\underset{l=1}{\overset{N_R+1}{\mathrm{\Σ}}}{P}_r\frac{m^{\mathrm{\α}+\mathrm{\β}+\mathrm{\γ}}}{n}}{\underset{l=1}{\overset{N_R+1}{\mathrm{\Σ}}}{P}_l\left(\frac{d}{d_{(S,l)}}\right)P_r{\left(N_R\right)}^l}=\frac{d^{-\mathrm{\ρ}}}{\underset{l=1}{\overset{N_R+1}{\mathrm{\Σ}}}{d_{(S,l)}}^{-\mathrm{\ρ}}}---\left(10\right)$

Whole transmission channel utilization used can be obtained by formula (11).

$C_N=\frac{n{N}_M^k}{C_{A}m{(N_R+2)}^{\mathrm{\α}+\mathrm{\β}+\mathrm{\γ}}}---\left(11\right)$

It is wherein the number of channel in junction network.

Decodable code frame per second DFR can be obtained by formula (12).

$\begin{array}{c}\mathrm{DFR}={\left\{E\right[e^{\mathrm{\α}}\left]E\right[e^{\mathrm{\β}}\left]E\right[e^{\mathrm{\γ}}\left]\right\}}^{\frac{n}{m}}{e}^{-N_R{N}_M}\frac{d^{-\mathrm{\ρ}}}{\underset{l=1}{\overset{N_R}{\mathrm{\Σ}}}{d}_l^{-\mathrm{\ρ}}}\\ \≤e^{-N_R{N}_M}{d}^{-\mathrm{\α}}\end{array}---\left(12\right)$

In order to obtain optimum N _rn _mvalue, provides following constraints:

(1) channel usage number reaches maximum;

(2) on node D, decodable code frame per second reaches maximum.

Fig. 6 gives a 6*5 two-dimensional network topology, wherein deploys 4 multimedia high in the clouds and 3 via nodes.

Second stage: multi-relay cooperation transmits.

Each via node by the multimedia high in the clouds from sender node S and correspondence, receive n, m, k} reconstruct cooperation media stream, reconstruct absolute coding after transmitted in parallel to node D.During parallel communications, average transmit power must be less than or equal to after the media stream that via node receives, do not decode, not decoding is only reconstructed, need the frame number of transmission to be all via nodes all complete classification cooperation transmission and need 2N altogether _rn _msecondary.

Fig. 7 gives multi-relay cooperation transmission topology.Consult Fig. 7 to find, chance active multi-media cloud platform can build according to user's request and network channel real-time status self adaptation.Sender node S and via node can select optimum multimedia high in the clouds scale to improve media stream from cloud platform to the down transmission efficiency of WSNs and quality.

Phase III: classification cooperation decoding.

Node D receives from sender node S and N _rindividual via node individual packet.Fig. 8 gives many relayings N _r-N _ma structure of classification collaborative network and the concrete example of dynamic conditioning.

Refer to Fig. 1 and 9, the multimedia application based on opportunistic Multimedia Dynamic cloud platform and many relayings-classification cooperation wireless sensor network is divided into three-tier architecture: (1) multimedia application layer; (2) cloud podium level; (3) infrastructure layer.The cloud computing method of multimedia service and the implementation step of system specific as follows:

(English full name is: Moving Picture Experts Group through MPEG for S01, multimedia streaming data, Chinese is: dynamic image expert group) be defined as { intracoded frame I after algorithm coding, forward-predictive-coded frames P, bi-directional predicted interpolation coding frame B}, multimedia high in the clouds state is defined as { residual memory space SR _i, communication distance d _c, transmitted power P _s.Wherein media stream status parameter values can obtain after system initialization, and multimedia high in the clouds status parameter values can obtain according to cloud device build-in attribute.

Status parameter values after the multimedia streaming data coding obtained in S02, integrating step S01, multimedia streaming data and qualitative parameter vector T linearly calculate, and draw frame of video F to be sent _i.

S03, determine the frame type T that comprises in media stream according to result of calculation _p(F _i) determine priority.T _p(F _i)=1 shows that only comprising I frame assignment in media stream is 1, and namely priority is 1; I frame is only comprised and P frame assignment is 2 in media stream, namely priority is 2; Comprise I frame in media stream, P frame and B frame assignment are 3, namely priority is 3.

S04, user side demand are focused on Real-time Ability and are turned S05, focus on play quality guarantee and turn S06, focus on combination property and turn S07;

S05, from the high in the clouds meeting communication distance between high in the clouds and be less than 10% of sender node and receiving terminal node spacing is gathered, 3 high in the clouds are selected to set up cloud platform, calculate the cloud platform error rate, if the error rate is greater than 3%, then from the set of high in the clouds, 1 high in the clouds and aforementioned 3 high in the clouds are selected to rebuild cloud platform, for sending the multimedia streaming data that priority is 1;

S06, from the high in the clouds meeting communication distance between high in the clouds and be less than 5% of sender node and receiving terminal node spacing is gathered, 4 high in the clouds are selected to set up cloud platform, for sending the multimedia streaming data that priority is 2;

S07, from the high in the clouds meeting communication distance between high in the clouds and be less than 10% of sender node and receiving terminal node spacing is gathered, select 3 high in the clouds to set up cloud platform, calculate the cloud platform error rate, if the error rate is less than 3%, then removes 1 high in the clouds and rebuild cloud platform; If the error rate is more than or equal to 3% and be less than or equal to 4%, then from the high in the clouds meeting communication distance between high in the clouds and be less than 6% of sender node and receiving terminal node spacing is gathered, 2 high in the clouds are selected to set up cloud platform, for sending the multimedia streaming data that priority is 3;

S08, selection N _rindividual via node, sets up N _r-N _mclassification cooperation transmission network;

S09, sender node are to N _rindividual candidate relay node and receiving terminal node send multi-medium data, contrast the feedback information from candidate relay node and receiving terminal node, if feedback is consistent, then set up classification cooperation transmission network; If feed back inconsistent, then get rid of the inconsistent candidate relay node of feedback, residue candidate relay node sets up classification cooperation transmission network.

S10, when setting up the via node fault of classification cooperation transmission network, this via node will send failed multimedia streaming data reconstruct, to neighbor node broadcast, neighbor node and receiving terminal node receive backward this via node feedback of broadcast, select not at described N from feedback _rthe neighbor node of individual candidate relay node replaces this via node.

S11, by once retransmitting, ensure that flow data correctly arrives receiving terminal node D, select substitute node, reconstruct classification collaborative network.

S12, many relayings N _r-N _mclassification cooperation decoding.Receiving terminal node D receives from sender node S and N _rindividual via node individual packet, play multimedia stream after demodulation, decoding, mpeg decode.

The present invention is by real-time perception channel quality, wireless sensor network state, multimedia high in the clouds and sensor node state, opportunistic builds Multimedia Dynamic cloud platform, Adaptive Planning many relayings-classification cooperation transmission network, thus the comprehensive coverage of the aspects such as robustness, robustness, real-time, energy efficiency and computational efficiency is provided for the multimedia application under different network environments.

Claims (9)

1. a transmission method for opportunistic Multimedia Dynamic cloud platform and many relayings classification cooperation, it is characterized in that, comprise and set up opportunistic Multimedia Dynamic cloud platform, described opportunistic Multimedia Dynamic cloud platform of setting up comprises the following steps:

Multimedia streaming data state after MPEG algorithm coding of S01, user side demand is defined as { intracoded frame, forward-predictive-coded frames, bi-directional predicted interpolation coding frame }, each multimedia high in the clouds state is defined as { residual memory space, communication distance between high in the clouds, transmitted power };

Status parameter values after the multimedia streaming data coding obtained in S02, integrating step S01, multimedia streaming data and qualitative parameter SYSTEM OF LINEAR VECTOR calculate, and draw frame of video to be sent;

S03, determine the priority of multimedia streaming data, when multimedia streaming data only comprises intracoded frame, priority is 1, when multimedia streaming data only comprises intracoded frame and forward-predictive-coded frames, priority is 2, and when multimedia streaming data comprises intracoded frame, forward-predictive-coded frames and bi-directional predicted interpolation coding frame, priority is 3;

S04, user side demand are focused on Real-time Ability and are turned S05, focus on play quality guarantee and turn S06, focus on combination property and turn S07;

S05, from the high in the clouds meeting communication distance between high in the clouds and be less than 10% of transmitting terminal and receiving terminal spacing is gathered, 3 high in the clouds are selected to set up cloud platform, calculate the cloud platform error rate, if the error rate is greater than 3%, then from the set of high in the clouds, 1 high in the clouds and aforementioned 3 high in the clouds are selected to rebuild cloud platform, for sending the multimedia streaming data that priority is 1;

S06, from the high in the clouds meeting communication distance between high in the clouds and be less than 5% of transmitting terminal and receiving terminal spacing is gathered, 4 high in the clouds are selected to set up cloud platform, for sending the multimedia streaming data that priority is 2;

S07, from the high in the clouds meeting communication distance between high in the clouds and be less than 10% of transmitting terminal and receiving terminal spacing is gathered, select 3 high in the clouds to set up cloud platform, calculate the cloud platform error rate, if the error rate is less than 3%, then removes 1 high in the clouds and rebuild cloud platform; If the error rate is more than or equal to 3% and be less than or equal to 4%, then from the high in the clouds meeting communication distance between high in the clouds and be less than 6% of transmitting terminal and receiving terminal spacing is gathered, 2 high in the clouds are selected to set up cloud platform, for sending the multimedia streaming data that priority is 3.

2. the transmission method of opportunistic Multimedia Dynamic cloud platform according to claim 1 and many relayings classification cooperation, is characterized in that, comprise step:

S08, selection N _rindividual via node, sets up N _r-N _mclassification cooperation transmission network, described N _mfor the high in the clouds number that the cloud platform set up in described step S05, S06 or S07 comprises.

3. the transmission method of opportunistic Multimedia Dynamic cloud platform according to claim 2 and many relayings classification cooperation, is characterized in that, comprise step:

S09, sender node are to N _rindividual candidate relay node and receiving terminal node send multi-medium data, contrast the feedback information from candidate relay node and receiving terminal node, if feedback is consistent, then set up classification cooperation transmission network; If feed back inconsistent, then get rid of the inconsistent candidate relay node of feedback, residue candidate relay node sets up classification cooperation transmission network.

4. the transmission method of the opportunistic Multimedia Dynamic cloud platform according to Claims 2 or 3 and many relayings classification cooperation, it is characterized in that: described when setting up the via node fault of classification cooperation transmission network, this via node will send failed multimedia streaming data reconstruct, broadcast to neighbor node, neighbor node and receiving terminal node receive backward this via node feedback of broadcast, select not at described N from feedback _rthe neighbor node of individual candidate relay node replaces this via node.

5. the transmission method of the opportunistic Multimedia Dynamic cloud platform according to Claims 2 or 3 and many relayings classification cooperation, is characterized in that: described N _rmake channel utilization C _nwith value when decodable code frame per second DFR reaches maximum on receiving terminal node.

6. the transmission method of opportunistic Multimedia Dynamic cloud platform according to claim 5 and many relayings classification cooperation, is characterized in that: described in $C_N=\frac{{\mathrm{nN}}_M^k}{C_{A}m{(N_R+2)}^{\mathrm{\α\β\γ}}},$ Described $\begin{array}{c}\mathrm{DFR}={\left\{E\right[e^{\mathrm{\α}}\left]E\right[e^{\mathrm{\β}}\left]E\right[e^{\mathrm{\γ}}\left]\right\}}^{\frac{n}{m}}{e}^{{-N}_R{N}_M}\frac{d^{-\mathrm{\ρ}}}{\underset{l=1}{\overset{N_R}{\mathrm{\Σ}}}{d_l}^{-\mathrm{\ρ}}},2\≤\mathrm{\ρ}\≤5,\\ \≤e^{N_R{N}_M}{d}^{-\mathrm{\α}}\end{array}$ Described C _afor the junction network number of channel, described n is frame of video number in multimedia streaming data, described m is picture group number, described k is video frame type number, described α, β, γ are respectively intracoded frame in picture group, forward-predictive-coded frames, bi-directional predicted interpolation coding frame and group of pictures length ratio, described d be sender node to receiving terminal node distance, described d _lfor via node spacing.

7. the transmission method of opportunistic Multimedia Dynamic cloud platform according to claim 3 and many relayings classification cooperation, is characterized in that: the received power P of described candidate relay node _lmeet, $P_r\left(N_R^l\right)=P{\left(\frac{d}{d_{(S,l)}}\right)}^{-\mathrm{\ρ}}-10\mathrm{\β}1g\left(d\right),2\≤\mathrm{\ρ}\≤5,$ Described d be sender node to receiving terminal node distance, described d _{(s, l)}for sender node is to via node distance, described P _rfor receiving terminal node received power.

8. the transmission method of opportunistic Multimedia Dynamic cloud platform according to claim 1 and many relayings classification cooperation, is characterized in that: described in described step S05, the residual memory space in high in the clouds is greater than n _is _i/ N _m, described in described step S06, the residual memory space in high in the clouds is greater than (n _is _i+ n _ps _p+ n _bs _b)/N _m, described in described step S07, the residual memory space in high in the clouds is greater than (n _is _i+ n _ps _p)/N _m, described n _iintracoded frame number in multimedia streaming data, described n _pforward-predictive-coded frames number, described n _sbi-directional predicted interpolation coding frame number, described S _iintraframe coding frame sign, described S _pforward-predictive-coded frames size, described S _sit is bi-directional predicted interpolation coding frame sign.

9. the transmission method of opportunistic Multimedia Dynamic cloud platform according to claim 1 and many relayings classification cooperation, is characterized in that: the transmitted power P in high in the clouds described in described step S05, S06 and S07 _s≤ P _r(m ^{alpha+beta+γ})/n.