CN112887785B - Time delay optimization method based on remote video superposition interactive calculation - Google Patents
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Abstract
The invention discloses a time delay optimization method based on remote video superposition interactive calculation, which comprises the following steps: the mobile device and the intelligent television acquire independent and complete computing resource data link based on a data multicast form in a home video service environment, on the computing control, the computing tasks born by all computing nodes are set through a cooperative computing control module among the computing nodes, data communication is carried out through a WiFiDirect connection channel established among the nodes, and the following computation is carried out in the home network environment: s10, a calculation scheduling step, namely, carrying out calculation unloading and scheduling aiming at the calculation equipment in the application family video environment; s20, unloading step of multi-order interactive operation, namely unloading calculation is carried out aiming at multi-order complex calculation; s30, a critical condition analysis step; and S40, an algorithm design step, namely determining the overall unloading schedule by taking the minimum value of the time delay as an optimization target.
Description
Technical Field
The invention belongs to the technical field of videos, and particularly relates to a time delay optimization method based on remote video superposition interactive calculation.
Background
There are many influencing factors for smart televisions, including the following: (1) impact of high picture quality video content. The service of the intelligent television core is the playing bearing of high-quality video content. In the video data service using the public ethernet network represented by the OTT service mode as a transmission medium, high-quality video data occupies a large amount of downlink channel network bandwidth for a long time in the public network transmission process. When the public cloud server is used as a calculation unloading server, the influence of network blocking caused by the transmission of high-picture-quality video data of a public network can be caused in the process of transmitting calculation unloading data from the server to the intelligent television, so that the interactive calculation response time delay is improved. The influence of service diversity is interactively calculated. In the intelligent television interactive computing service, the user demands are diversified. The video service using the CDN private network represented by the IPTV service mode as a transmission medium, due to lack of enough computing nodes in the network, particularly lack of near-end computing nodes, cannot meet the interactive requirements of user diversification through a near-end caching mechanism. Synchronization of interactive presentation data and video content can only be synchronously overlapped at a remote central server, and diversified interactive demand response data can lead a downlink channel of a special network to bear higher data transmission pressure, so that higher calculation response delay is further generated. (3) impact of video traffic presentation characteristics. The intelligent television presents close relativity with the video content based on the interactive service of the video content. Video programs based on intelligent televisions, especially video services of live broadcast type and regional type, show high time-intensive characteristics and geographic relevance. Server-based video interaction computing offload policies may result in a large number of high-density interaction computations being undertaken by a particular server in a short period of time. The high density and multiple concurrent computation affects the computation offload response delay.
The higher delay brought by the challenges causes the problems of slow response of user interaction, poor fluency of video and the like under the influence of the characteristic of high coupling of video and interaction, and influences the interaction experience quality of users.
Disclosure of Invention
In view of the problems existing above, the invention provides a time delay optimization method based on remote video superposition interactive calculation.
In order to solve the technical problems, the invention adopts the following technical scheme:
a time delay optimization method based on remote video superposition interactive calculation comprises the following steps: the mobile device and the intelligent television acquire independent and complete computing resource data link based on a data multicast form in a home video service environment, on the computing control, the computing tasks born by all computing nodes are set through a cooperative computing control module among the computing nodes, data communication is carried out through a WiFi Direct connection path established among the nodes, and the following computation is carried out in the home network environment:
s10, a calculation scheduling method focuses on how to apply computing equipment in a home video environment to carry out calculation unloading scheduling;
s20, an unloading method of multi-order interaction operation is performed aiming at how to perform effective unloading calculation of multi-order complex calculation;
s30, analyzing critical conditions, wherein the time delay of the hierarchical collaborative calculation of different orders of calculation on different nodes is smaller than that of the collaborative unloading calculation of the nodes;
s40, algorithm design, and the same-order unloading calculation of the proving sub-nodes has shorter time delay compared with the same-order collaborative unloading calculation.
Preferably, S10 further comprises:
firstly, taking simple interaction calculation as a research object, and carrying out calculation delay analysis in a collaborative interaction calculation environment, wherein the total delay of collaborative interaction calculation is as follows:
in the collaborative computing mode, when the computing time delay of the intelligent television is the same as the time delay of the mobile device, the total collaborative computing time delay is minimum. In the server task scheduling mode, when the total time delay of the mobile device for carrying out the interactive calculation task and transmitting the calculation result to the intelligent television is equal to the total time delay of the intelligent television for completing the interactive calculation task, the total time delay of the cooperative interactive calculation is minimum, and the relationship shown by the following formula is obtained:
from this condition, the calculation task allocation policy in the synchronous acquisition data mode is deduced as shown in the following formula:
for the case that the same calculation is performed in different home video service environments, since the calculation is the same, k and t remain unchanged in the calculation process, and in different home video service environments, the calculation resources allocated by the calculation nodes such as the intelligent television and the mobile device for collaborative calculation will change. The effect of its variation is as follows:
(1) Mobile device computing power: under the condition that the computing capacity of the computing and the intelligent television is certain, the computing capacity of the mobile equipment is increased, and the computing amount born by the mobile equipment is larger;
(2) Intelligent television computing power: under the condition that the operation and the operation capability of the mobile equipment are certain, the calculation amount born by the intelligent television gradually increases along with the increase of the calculation capability of the intelligent television;
for the total time delay under the cooperative computing method, the formula (3) is brought into the formula (2), and the formula (4) is obtained:
in the same video service environment, the parameters fmobile, fclie and wwifirect are relatively unchanged, and k and t corresponding to different interactive calculations show changes, wherein for convenience of research, the computing resource capacity ratio p of the mobile device and the edge server is introduced respectively, as shown in a formula (5), the computing resource capacity ratio q of the mobile device and the WiFi direct is shown in a formula (6):
then equations (3), (4) can be further expressed as:
from the analysis of the above formula, it can be seen that k, t has the following effect on the total computation delay:
(1) Variation of the coefficient of expansion of the interactive calculation, τ, with increasing of the coefficient of expansion of the interactive calculation, given a certain computational complexity and computing environment col Gradually increasing and approaching to the delay value of the calculation task independently born by the mobile device;
(2) The variation of the calculation complexity is not only smaller but also smaller along with the increase of the calculation complexity, and under the condition of a certain calculation environment and a certain calculation expansion coefficient, tau col Will also gradually increase.
Preferably, for a single mobile edge server that cannot be effectively solved, introducing multiple mobile edge servers together provides an interactive computing service for a mobile terminal, on the construction of the mobile edge servers, the connection between the mobile edge servers presents a relatively stable state, the power of the connection is constant, according to Shannon equation, it is deduced that the connection bandwidth of each connection point shares the total bandwidth of Wi-Fi direct connection within a certain time, meanwhile, since multiple computing nodes can independently perform computing tasks, the computing power is equivalent to superposition of the computing power of each device, and the computing power of the new computing device is approximately:
the connection bandwidth is about:
B sum ＝W WD (8)
therefore, on the premise that a plurality of mobile edge server accesses are subjected to interactive computation offload, an equivalent virtual mobile edge server can be introduced into the computation offload schedule of S10, and the computation characteristic parameter of the new edge server is f sum 、B sum 。
The invention has the following beneficial effects: the method solves the problems of data blocking of the public network, insufficient concurrent computing resources and the like, and on an unloading target node of video interactive computing, the method is required to be closer to mobile equipment, and meanwhile more privately-owned equipment serves the interactive computing of the mobile equipment. And further determining a calculation scheduling method and a collaborative calculation implementation method under the condition of determining a collaborative calculation mode in the video service environment. And determining an overall unloading scheduling method by taking the minimum value of the time delay as an optimization target.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely, and it is apparent that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The time delay optimization method based on remote video superposition interactive calculation provided by the embodiment of the invention comprises the following steps: the mobile device and the intelligent television acquire independent and complete computing resource data link based on a data multicast form in a home video service environment, on the computing control, the computing tasks born by all computing nodes are set through a cooperative computing control module among the computing nodes, data communication is carried out through a WiFi Direct connection path established among the nodes, and the following computation is carried out in the home network environment:
s10, a calculation scheduling method focuses on how to apply computing equipment in a home video environment to carry out calculation unloading scheduling;
s20, an unloading method of multi-order interaction operation is performed aiming at how to perform effective unloading calculation of multi-order complex calculation;
s30, analyzing critical conditions, wherein the time delay of the hierarchical collaborative calculation of different orders of calculation on different nodes is smaller than that of the collaborative unloading calculation of the nodes;
s40, algorithm design, and the same-order unloading calculation of the proving sub-nodes has shorter time delay compared with the same-order collaborative unloading calculation.
In a specific application example, S10 further includes:
firstly, taking simple interaction calculation as a research object, and carrying out calculation delay analysis in a collaborative interaction calculation environment, wherein the total delay of collaborative interaction calculation is as follows:
in the collaborative computing mode, when the computing time delay of the intelligent television is the same as the time delay of the mobile device, the total collaborative computing time delay is minimum. In the server task scheduling mode, when the total time delay of the mobile device for carrying out the interactive calculation task and transmitting the calculation result to the intelligent television is equal to the total time delay of the intelligent television for completing the interactive calculation task, the total time delay of the cooperative interactive calculation is minimum, and the relationship shown by the following formula is obtained:
from this condition, the calculation task allocation policy in the synchronous acquisition data mode is deduced as shown in the following formula:
for the case that the same calculation is performed in different home video service environments, since the calculation is the same, k and t remain unchanged in the calculation process, and in different home video service environments, the calculation resources allocated by the calculation nodes such as the intelligent television and the mobile device for collaborative calculation will change. The effect of its variation is as follows:
(1) Mobile device computing power: under the condition that the computing capacity of the computing and the intelligent television is certain, the computing capacity of the mobile equipment is increased, and the computing amount born by the mobile equipment is larger;
(2) Intelligent television computing power: under the condition that the operation and the operation capability of the mobile equipment are certain, the calculation amount born by the intelligent television gradually increases along with the increase of the calculation capability of the intelligent television;
for the total time delay under the cooperative computing method, the formula (3) is brought into the formula (2), and the formula (4) is obtained:
in the same video service environment, the parameters fmobile, fclie and wwifirect are relatively unchanged, and k and t corresponding to different interactive calculations show changes, wherein for convenience of research, the computing resource capacity ratio p of the mobile device and the edge server is introduced respectively, as shown in a formula (5), the computing resource capacity ratio q of the mobile device and the WiFi direct is shown in a formula (6):
then equations (3), (4) can be further expressed as:
from the analysis of the above formula, it can be seen that k, t has the following effect on the total computation delay:
(1) Variation of the coefficient of expansion of the interactive calculation, τ, with increasing of the coefficient of expansion of the interactive calculation, given a certain computational complexity and computing environment col Gradually increasing and approaching to the delay value of the calculation task independently born by the mobile device;
(2) The variation in the computational complexity is dependent on the computational complexityWith less increase of t, under the conditions of a certain computing environment and a certain computing expansion coefficient, tau col Will also gradually increase.
Further, for a single mobile edge server that cannot be effectively solved, a plurality of mobile edge servers are introduced to jointly provide an interactive computing service for a mobile terminal, on the construction of the mobile edge servers, the connection between the mobile edge servers presents a relatively stable state, the power of the connection is constant, according to the Shannon equation, the connection bandwidth of each connection point is deduced to share the total bandwidth of Wi-Fi direct connection within a certain time, meanwhile, as a plurality of computing nodes can independently execute computing tasks, the computing power is equivalent to superposition of the computing power of each device, and the computing power of the new computing device is approximately as follows without considering additional loss of connection switching and starting delay computation:
the connection bandwidth is about:
B sum ＝W WD (8)
therefore, on the premise that a plurality of mobile edge server accesses are subjected to interactive computation offload, an equivalent virtual mobile edge server can be introduced into the computation offload schedule of S10, and the computation characteristic parameter of the new edge server is f sum 、B sum 。
Specifically, S20, the method for offloading multi-level interactive operation, above, proposes a method for offloading computing nodes in a home video service environment for single-level interactive computation. In the actual interactive calculation process, the calculation is composed of complex multi-order calculation. How to perform efficient offload calculations for multi-order complex calculations would be the focus of this section of research.
Here, it is assumed that the interaction computation can be decomposed into a plurality of independent single-order interaction computations, as shown in equation (9 d):
t(n)＝t s (n)+t s -1(n)......t 3 (n)+t 2 (n)+t 1 (n) (9d)
in formula (9 d), t i (n) (i is more than or equal to 0 and less than or equal to s) respectively represents an independent interaction calculating unit capable of calculating the complexity and the interaction calculating expansion coefficient in advance. The calculation complexity and the calculation expansion coefficient are respectively t i ，k i 。
Thus, applying the collaborative offload settlement method, the total interaction computation latency can be expressed as:
the calculation complexity and the interactive calculation expansion coefficient have different influence trends on calculation time delay, and the characteristics of mutual independence between k and t, so that the calculation complexity and the interactive calculation expansion coefficient have different influence on different single-order interactive operations.
Because different single-order interactive calculations are subject to node communication time delay cost caused by calculation node calculation capability and calculation expansion coefficient, calculation with lower calculation complexity coefficient and calculation expansion coefficient is unloaded to a mobile equipment node end, calculation with higher calculation complexity coefficient and calculation expansion coefficient is reserved at an intelligent television end, a hierarchical collaborative unloading calculation method is constructed, and interactive calculation time delay can be effectively reduced under certain conditions. Further analysis of the collaborative calculations will be described below, with latency as the objective of optimization, to determine the execution strategy of the collaborative offload calculations.
And researching calculation delay information generated on different calculation nodes respectively aiming at different orders of calculation. First we assume that the computation delays generated by the x-order computation at the mobile device and the y-order computation at the smart tv end are the same. x and y correspond to different orders of interactive computation in t (n), respectively. The computational decomposition includes the following:
in the above three cases, in the case of Con_I and Con_II, a single node may incur additional computation delay relative to another node
Or->
Under the condition of hierarchical collaborative offload computing hybrid application, the additional computation delay of a single node can be converted into:
wherein m_i, m_j are respectively:
here, the additional computation of a single node is approximately equivalent to the original computation material interaction computation of l_inter ', where l_inter ' =m_i×l_inter or l_inter ' =m_j×l_inter.
In the process of the step calculation of different steps of interaction calculation, the step calculation time delay born by each calculation node is as follows:
wherein equation 18a represents calculation condition I,18b represents calculation condition II, and 18c represents calculation condition III. Under three conditions, the corresponding calculation complexity coefficient and calculation expansion coefficient are equivalent to:
calculation conditions I, t χ ＝t i /(1-m i )，k χ ＝(1-m i )k i ；
Calculation of conditions II, t y ＝t j /(1-m j )，k y ＝k χ ；
S30, analyzing critical conditions, specifically including: in an environment adopting multi-order collaborative unloading calculation, analysis is required to be carried out on each critical point, and an overall calculation strategy is determined so as to ensure optimization of calculation time delay. According to the analysis, the time delay of the hierarchical collaborative calculation of different orders of calculation on different nodes is smaller than that of the hierarchical node collaborative unloading calculation under the following conditions.
(1) The calculation time delay of the mobile device is the same as the calculation time delay of the intelligent television, namely:
(2) The hierarchical cooperative computing time delay is smaller than the node cooperative computing time delay, namely:
τ sig ＜τ col
the derivation from the condition (1) can result in:
not only k x When the formula is satisfied, the calculation time delay generated by the x-order operation at the mobile equipment and the y-order calculation at the intelligent television end is the same, and the time delay is as follows:
the condition (2) can deduce that the time delay difference between the x-stage and y-stage interactive calculation and the calculation of the node according to the steps is as follows:
when Deltaτ c-s >0, it means that the adoption of the stepwise node calculation has shorter calculation delay compared with the cooperative calculation unloading method.
S40, algorithm design, specifically comprising: it can be seen on the basis of the analysis of critical conditions that when Δτ c-s The larger the time, the shorter the delay of the representative hierarchical cooperative offload operation relative to the node-wise same-order offload computation. While when Deltaτ c-s <At 0, the hierarchical peer offload computation has a shorter latency than the hierarchical collaborative offload computation.
It should be understood that the exemplary embodiments described herein are illustrative and not limiting. Although one or more embodiments of the present invention have been described, it will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present invention as defined by the following claims.
Claims (2)
1. A time delay optimization method based on remote video superposition interactive calculation is characterized by comprising the following steps: the mobile device and the intelligent television acquire independent and complete computing resource data link based on a data multicast form in a home video service environment, on the computing control, the computing tasks born by all computing nodes are set through a cooperative computing control module among the computing nodes, data communication is carried out through a WiFi Direct connection path established among the nodes, and the following computation is carried out in the home network environment:
s10, a calculation scheduling step, namely, carrying out calculation unloading and scheduling aiming at the calculation equipment in the application family video environment;
s20, unloading step of multi-order interactive operation, namely unloading calculation is carried out aiming at multi-order complex calculation;
s30, a critical condition analysis step, wherein each critical point is analyzed under the environment of multi-order collaborative offload computation, and an overall computation strategy is determined, so that the overall computation strategy meets the requirement that the time delay of the hierarchical collaborative computation of different orders of computation on different nodes is smaller than the time delay of the hierarchical collaborative offload computation of the nodes;
s40, algorithm design step, taking the minimum value of time delay as the optimization target, determining the overall unloading schedule,
s10 further comprises:
firstly, taking simple interaction calculation as a research object, and carrying out calculation delay analysis in a collaborative interaction calculation environment, wherein the total delay of collaborative interaction calculation is as follows:
in the cooperative computing mode, when the computing time delay of the intelligent television is the same as the time delay of the mobile equipment, the total cooperative computing time delay is minimum; in the server task scheduling mode, when the total time delay of the mobile device for carrying out the interactive calculation task and transmitting the calculation result to the intelligent television is equal to the total time delay of the intelligent television for completing the interactive calculation task, the total time delay of the cooperative interactive calculation is minimum, and the relationship shown by the following formula is obtained:
from this condition, the calculation task allocation policy in the synchronous acquisition data mode is deduced as shown in the following formula:
substituting the formula (3) into the formula (2) for the total time delay under the cooperative computing method to obtain the formula (4):
under the same video service environment, the parameters fmobile, fclie and wwifidirect are relatively unchanged, and k and t corresponding to different interactive calculations show changes, and the computing resource capacity ratio p of the mobile equipment and the edge server is introduced, as shown in a formula (5), the computing resource capacity ratio q of the mobile equipment and the WiFi direct is introduced, as shown in a formula (6):
then equations (3), (4) can be further expressed as:
s30 specifically comprises the following steps: in an environment adopting multi-order collaborative offload computation, analyzing each critical point to determine an overall computation strategy so as to ensure optimization of computation time delay, wherein the time delay of the hierarchical collaborative computation of different orders of computation on different nodes is smaller than that of the hierarchical collaborative offload computation, and the conditions are as follows:
(1) The calculation time delay of the mobile device is the same as the calculation time delay of the intelligent television, namely:
(2) The hierarchical cooperative computing time delay is smaller than the node cooperative computing time delay, namely:
τ sig ＜τ col derived from the condition (1):
i.e. k x When the formula is satisfied, the calculation time delay generated by the x-order operation at the mobile equipment and the y-order calculation at the intelligent television end is the same, and the time delay is as follows:
deducing from the condition (2), adopting a cooperative computing mode for the interactive computation of the x-order and the y-order and computing the time delay difference between the node according to the order as follows:
when Deltaτ c-s >0, it means that the adoption of the stepwise node calculation has shorter calculation delay compared with the cooperative calculation unloading method.
2. The method for optimizing time delay based on remote video overlay interactive computation according to claim 1, wherein a plurality of mobile edge servers are introduced to provide interactive computation services for mobile terminals together, connections between mobile edge servers are in a relatively stable state in terms of construction of the mobile edge servers, power of the connections is constant, and it is deduced from Shannon's equation that connection bandwidth of each connection point shares total bandwidth of Wi-Fi direct connection for a certain period of time, and at the same time, the computation power of the new computation device is as follows without considering additional loss of connection switching and starting time delay computation:
the connection bandwidth is about:
B sum ＝W WD (8)
on the premise of performing interactive calculation unloading on the access of a plurality of mobile edge servers, introducing an equivalent virtual mobile edge server into the calculation unloading scheduling of S10, wherein the calculation characteristic parameter of the new edge server is f sum 、B sum 。
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| CN110401871A (en) * | 2019-08-13 | 2019-11-01 | 浙江传媒学院 | The smart television interactive service arithmetic system and method shared based on calculation resources |
| CN111585916A (en) * | 2019-12-26 | 2020-08-25 | 国网辽宁省电力有限公司电力科学研究院 | LTE electric power wireless private network task unloading and resource allocation method based on cloud edge cooperation |
| CN111459670A (en) * | 2020-03-30 | 2020-07-28 | 中科边缘智慧信息科技（苏州）有限公司 | Method for performing cooperative processing at different levels of edge calculation |
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