CN102946629A - Online optimal scheduling solution for tail energy consumption of 3-G communication of mobile intelligent terminal - Google Patents

Online optimal scheduling solution for tail energy consumption of 3-G communication of mobile intelligent terminal Download PDF

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CN102946629A
CN102946629A CN2012104113743A CN201210411374A CN102946629A CN 102946629 A CN102946629 A CN 102946629A CN 2012104113743 A CN2012104113743 A CN 2012104113743A CN 201210411374 A CN201210411374 A CN 201210411374A CN 102946629 A CN102946629 A CN 102946629A
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崔勇
肖诗汉
王弘毅
杨扬
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Tsinghua University
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Abstract

The invention provides an online optimal scheduling scheme for tail energy consumption of 3-G (third-generation) communication of a mobile intelligent terminal. The scheme comprises the following steps: analyzing three energy consumption states of IDLE, FACH (Forward Access Channel) and DCH (Dedicated Channel) and the relationship between the state delay and the state conversion; using a fine grit description model of the energy consumption states, the state delay and the state conversion based on time slot to estimate the energy consumption in a scheduling process; establishing a flow forecasting model within the scheduling time domain; and using historical flow data to calculate and forecast probabilities of packed probabilities. By adopting the scheme, the capability of the scheduling solution for regulating strategies for dense flow may be brought in future is enhanced.

Description

Mobile intelligent terminal 3G communication tail energy consumption on-line optimizing scheduling scheme
Technical field
The invention belongs to 3G mobile communication Energy Saving Control field, particularly a kind of mobile intelligent terminal 3G communication tail energy consumption on-line optimizing scheduling scheme.
Background technology
In actual life, along with the gradually enhancing of embedded chip storage, calculating and display performance, when the cellphone subscriber who grows with each passing day was enjoying abundant service, the energy consumption problem of its terminal was also outstanding day by day.Under the more and more thinner trend of mobile intelligent terminal, say that technically the raising of existing battery electric quantity has arrived a bottleneck at present, be difficult within the short cycle, have the raising of matter.In today that mobile cloud computing day by day develops, for faster, better, more effectively improve the flying power of battery of mobile phone, how to make the more energy-conservation focus that has become current mobile Internet research of Internet Transmission of portable terminal.
In 3G communication, the tail energy consumption problem is the large key problem of one in the network transmission process, namely in the 3G network transmission course, only have the sub-fraction energy consumption to spend in the actual data transfer process, be wasted in up to the energy consumption more than 60% in the wait time-delay of high energy consumption state, in unactual transfer of data of time period corresponding to tail energy consumption.For this key issue, the researcher has proposed numerous analysis and solve schemes, wherein mainly comprises the dynamic-configuration scheme of the RRC state machine parameter of the bottom that J.Yeh proposes, and operator can dynamically arrange suitable tail delay parameter according to traffic characteristic; What the people such as F.Qi an proposed reduces the quick dormancy scheme of tail energy consumption duration in terminal; The people such as N.Balasubramanian propose for the online optimal scheduling that minimizes tail time-delay target; The people such as H.A.Lagar-Cavilla have designed a kind of scheme of carrying out traffic transport at the OS layer with certain probability; The people such as A.Schulman have further introduced signal strength signal intensity transmission optimization tail energy consumption have been carried out in the impact of through-put power; The people such as F.Qian have proposed a kind ofly to describe cross-layer interaction problems between Radio Resource and the application layer based on tail energy consumption energy model.
Summary of the invention
In order to overcome above-mentioned the deficiencies in the prior art, the object of the present invention is to provide a kind of mobile intelligent terminal 3G communication tail energy consumption on-line optimizing scheduling scheme, by introducing historical data on flows information, improve scheduling process to pre-perception and the adaptability of following traffic characteristic, and take discrete time slot as unit, transmit the fine granularity assessment of energy consumption, improve energy consumption and the energy increment assessment accuracy of scheduling process, finally realize a large amount of minimizings of tail energy consumption in the 3G communication by suitable transmission request scheduling, reach the target of the energy-conservation communication of 3G.
To achieve these goals, the technical solution used in the present invention is:
Mobile intelligent terminal 3G communication tail energy consumption on-line optimizing scheduling scheme,
At first, set up the volume forecasting model in the cover scheduling time domain, carry out probability statistics and prediction with historical data on flows to wrapping probability, specifically realize according to the following steps:
Step (11) historical record is defined as: in a nearest history cycle T, whether its each time slot t that comprises is marked as has request to arrive at this time slot, is designated as c (t), and codomain is [0,1];
Step (12) is according to historical record c (t), and maximum adjacent request arrival interval is designated as J chronomere, and calculating adjacent Inter-arrival Time is t AProbability during the individual unit interval, namely Wherein the adjacent request parlor of Count (t) expression is divided into the historical number of times of the situation appearance of t, and the number that is spaced apart t among the statistics c (t) between adjacent 1 can obtain;
Step (13) is calculated the time slot t with current bag accumulative total 0Be starting point, following duration is T 0Period in have new transmission request to arrive probability, namely
Secondly, the fine granularity descriptive model that utilizes timeslot-based power consumption state, state delay and state to change carries out the energy consumption assessment in the scheduling process, specifically realizes according to the following steps:
Step (21) obtains energy consumption calculation function under the RRC model according to the mobile phone hardware parameter, is defined as follows: Wherein ST (t) is the power consumption state of time slot t, the state value be IDLE, CELL_DCH, CELL_FACH}, corresponding state performance number when P (ST) is ST for the state value is determined by the mobile phone hardware parameter;
Step (22) calculating is transmitted request when certain and is arranged at time slot t eDuring transmission, the desired value of the energy increment that it can obtain, namely
E u ( t e , t l ) = ( 1 - σ ) × ( E RRC ( ST s ( t 0 , t l ) ⊗ { t e } ) + σ × ( E RRC ( ST s ( t 0 , t l ) ⊗ { t e , } t l ) ) , Wherein ST s ( t 1 , t 2 ) ⊗ I : ST s(t 1, t 2) be illustrated in time period [t 1, t 2] in former energy consumption state,
Figure BDA00002303884300031
The time point set I effect of expression and transmission request, its value is with STs (t 1, t 2) as former energy consumption state, I sends the new power consumption state that produces after the request in the time point set;
At last, in carrying out the process of data communication by 3G network, realizes according to the following steps portable terminal energy optimization:
Step (31) adds a deadline label for the all-network transmission request that arrives, and indicates its tolerable time-delay;
Step (32) is to current time slots t 0, the Internet Transmission request that accumulative total does not send is maintained as a formation Q, checks each Internet Transmission request among the formation Q, if this request u has been assigned with time slot scheduling t sAnd satisfy t s〉=t 0The time, u is carried out the actual request sending action; Otherwise, carry out following steps:
Step (33) is by t remaining time rCarry out ascending sort, wherein t r=t u+ deadline u-t 0, current scheduling scope is designated as
Figure BDA00002303884300032
T wherein uTime slot for request u generation;
Step (34) is sequentially taken out each Internet Transmission request u, and the scheduling time domain scope of u is: I u=[t 0, t u+ deadline u], at I uWithin it is carried out the arrangement of actual schedule time slot:
Step (34a) is from t 0Beginning, traversal I uInterior next time slot t e
Step (34b) is if time slot t eCorresponding time slot capacity C (t e) greater than the current data transmission rate, namely greater than current unit interval during volume of transmitted data, then forward step (34a) to; Otherwise, continue following steps;
Step (34c) is calculated from arranging time slot t according to the probabilistic model of first eMay come the probability of new transmission request to the period of cut-off time slot tl:
Figure BDA00002303884300033
T wherein l=t u+ deadline u
Step (34d) is according to the energy increment expectation computational methods of second portion, and calculating is worked as this request and is arranged at time slot t eThe time energy increment that brings expectation: E u(t e, t l);
Step (34e) repeats (34a)-(34d) until I uTravel through complete;
Step (35) is assigned to the time slot scheduling of u the time slot of the desired value minimum of energy increment If a plurality of minimization expected values are arranged, then select maximum t s
Step (36) repeated execution of steps (34) is until all transmission requests all are assigned with time slot scheduling in the current queue;
Step (37) is along with time slot t 0Increase, the time slot scheduling t that arbitrary network transmission request u is arranged in formation Q sDuring arrival, will carry out the actual request sending action; When having new arbitrarily transmission request to arrive, the scheduling of a new round will be excited, execution in step (31)-(36).
Compared with prior art, the present invention effectively reduces the tail energy consumption of 3G communication, has realized the energy-conservation purpose of mobile terminal network transmission.
Description of drawings
Fig. 1 is process chart of the present invention.
Fig. 2 is the accumulated probability figure that the present invention comes inter-packet gap.
Fig. 3 is the power consumption state hard ware measure figure that the present invention once sends generation.
Embodiment
Below in conjunction with embodiment the present invention is carried out more detailed explanation.
Mobile intelligent terminal 3G communication tail energy consumption on-line optimizing scheduling scheme of the present invention,
At first, set up the volume forecasting model in the cover scheduling time domain, carry out probability statistics and prediction with historical data on flows to wrapping probability, specifically realize according to the following steps:
Step (11) historical record is defined as: in a nearest history cycle T, whether its each time slot t that comprises is marked as has request to arrive at this time slot, is designated as c (t), and codomain is [0,1];
Step (12) is according to historical record c (t), and maximum adjacent request arrival interval is designated as J chronomere, and calculating adjacent Inter-arrival Time is t AProbability during the individual unit interval, namely
Figure BDA00002303884300041
Wherein the adjacent request parlor of Count (t) expression is divided into the historical number of times of the situation appearance of t, and the number that is spaced apart t among the statistics c (t) between adjacent 1 can obtain;
Step (13) is calculated the time slot t with current bag accumulative total 0Be starting point, following duration is T 0Period in have new transmission request to arrive probability, namely
Figure BDA00002303884300042
, the interval accumulated probability of certain section actual flow distributes and sees accompanying drawing 2.
Secondly, the fine granularity descriptive model that utilizes timeslot-based power consumption state, state delay and state to change carries out the energy consumption assessment in the scheduling process, specifically realizes according to the following steps:
Step (21) obtains energy consumption calculation function under the RRC model according to the mobile phone hardware parameter, is defined as follows:
Figure BDA00002303884300051
Wherein ST (t) is the power consumption state of time slot t, and the state value is { IDLE, CELL_DCH, CELL_FACH}, corresponding state performance number when P (ST) is ST for the state value is determined by the mobile phone hardware parameter, as shown in Figure 3, can obtain by hard ware measure.
Step (22) calculating is transmitted request when certain and is arranged at time slot t eDuring transmission, the desired value of the energy increment that it can obtain, namely
E u ( t e , t l ) = ( 1 - σ ) × ( E RRC ( ST s ( t 0 , t l ) ⊗ { t e } ) + σ × ( E RRC ( ST s ( t 0 , t l ) ⊗ { t e , } t l ) ) , Wherein ST s ( t 1 , t 2 ) ⊗ I : ST s(t 1, t 2) be illustrated in time period [t 1, t 2] in former energy consumption state, The time point set I effect of expression and transmission request, its value is with ST (t 1, t 2) as former energy consumption state, I sends the new power consumption state that produces after the request in the time point set;
At last, as shown in Figure 1, realize according to the following steps energy optimization in portable terminal carries out the process of data communication by 3G network: at first the transmission request to each arrival adds a tolerable time-delay label, the value of this label shows the urgency of this Internet Transmission request, when certain Internet Transmission request time delay exceeds its corresponding label value, show that this request loses former valuable and effect; Otherwise, think that this request keeps former valuable and effect.For the transmission request of current accumulative total, remember that from current time the time domain in its residue tolerable time-delay is its scheduling time domain.In this time domain, corresponding energy increment expectation when calculating is arranged in each time slot with this request selects the minimum time slot of increment expectation as time slot scheduling, if a plurality of minimum values are arranged, then get the time slot after the time leans on most, the probability that augmented flow converges, thus reduce as much as possible the tail energy consumption.
The concrete execution in step of energy optimization is as follows:
Step (31) adds a deadline label for the all-network transmission request that arrives, and indicates its tolerable time-delay;
Step (32) is to current time slots t 0, the Internet Transmission request that accumulative total does not send is maintained as a formation Q, checks each Internet Transmission request among the formation Q, if this request u has been assigned with time slot scheduling t sAnd satisfy t s〉=t 0The time, u is carried out the actual request sending action; Otherwise, carry out following steps:
Step (33) by remaining time tr carry out ascending sort, wherein t r=t u+ deadline u-t 0, current scheduling scope is designated as
Figure BDA00002303884300055
T wherein uTime slot for request u generation;
Step (34) is sequentially taken out each Internet Transmission request u, and the scheduling time domain scope of u is: I u=[t 0, t u+ deadline u], at I uWithin it is carried out the arrangement of actual schedule time slot:
Step (34a) is from t 0Beginning, traversal I uInterior next time slot t e
Step (34b) is if time slot t eCorresponding time slot capacity C (t e) greater than the current data transmission rate, namely greater than current unit interval during volume of transmitted data, then forward step (34a) to; Otherwise, continue following steps;
Step (34c) is calculated from arranging time slot t according to the probabilistic model of first eMay come the probability of new transmission request to the period of cut-off time slot tl:
Figure BDA00002303884300061
T wherein l=t u+ deadline u
Step (34d) is according to the energy increment expectation computational methods of second portion, and calculating is worked as this request and is arranged at time slot t eThe time energy increment that brings expectation: E u(t e, t l);
Step (34e) repeats (34a)-(34d) until I uTravel through complete;
Step (35) is assigned to the time slot scheduling of u the time slot of the desired value minimum of energy increment
Figure BDA00002303884300062
If a plurality of minimization expected values are arranged, then select maximum t s
Step (36) repeated execution of steps (34) is until all transmission requests all are assigned with time slot scheduling in the current queue;
Step (37) is along with time slot t 0Increase, the time slot scheduling t that arbitrary network transmission request u is arranged in formation Q sDuring arrival, will carry out the actual request sending action; When having new arbitrarily transmission request to arrive, the scheduling of a new round will be excited, execution in step (31)-(36).

Claims (1)

1. mobile intelligent terminal 3G communication tail energy consumption on-line optimizing scheduling scheme is characterized in that,
At first, set up the volume forecasting model in the cover scheduling time domain, carry out probability statistics and prediction with historical data on flows to wrapping probability, specifically realize according to the following steps:
Step (11) historical record is defined as: in a nearest history cycle T, whether its each time slot t that comprises is marked as has request to arrive at this time slot, is designated as c (t), and codomain is [0,1];
Step (12) is according to historical record c (t), and maximum adjacent request arrival interval is designated as J chronomere, and calculating adjacent Inter-arrival Time is t AProbability during the individual unit interval, namely Wherein the adjacent request parlor of Count (t) expression is divided into the historical number of times of the situation appearance of t, and the number that is spaced apart t among the statistics c (t) between adjacent 1 can obtain;
Step (13) is calculated the time slot t with current bag accumulative total 0Be starting point, following duration is T 0Period in have new transmission request to arrive probability, namely
Figure FDA00002303884200012
Secondly, the fine granularity descriptive model that utilizes timeslot-based power consumption state, state delay and state to change carries out the energy consumption assessment in the scheduling process, specifically realizes according to the following steps:
Step (21) obtains energy consumption calculation function under the RRC model according to the mobile phone hardware parameter, is defined as follows: Wherein ST (t) is the power consumption state of time slot t, the state value be IDLE, CELL_DCH, CELL_FACH}, corresponding state performance number when P (ST) is ST for the state value is determined by the mobile phone hardware parameter;
Step (22) calculating is transmitted request when certain and is arranged at time slot t eDuring transmission, the desired value of the energy increment that it can obtain, namely E u ( t e , t l ) = ( 1 - σ ) × ( E RRC ( ST s ( t 0 , t l ) ⊗ { t e } ) + σ × ( E RRC ( ST s ( t 0 , t l ) ⊗ { t e , } t l ) ) , Wherein ST s ( t 1 , t 2 ) ⊗ I : ST s(t 1, t 2) be illustrated in time period [t 1, t 2] in former energy consumption state, The time point set I effect of expression and transmission request, its value is with ST s(t 1, t 2) as former energy consumption state, I sends the new power consumption state that produces after the request in the time point set;
At last, in carrying out the process of data communication by 3G network, realizes according to the following steps portable terminal energy optimization:
Step (31) adds a deadline label for the all-network transmission request that arrives, and indicates its tolerable time-delay;
Step (32) is to current time slots t 0, the Internet Transmission request that accumulative total does not send is maintained as a formation Q, checks each Internet Transmission request among the formation Q, if this request u has been assigned with time slot scheduling t sAnd satisfy t s〉=t 0The time, u is carried out the actual request sending action; Otherwise, carry out following steps:
Step (33) is by t remaining time rCarry out ascending sort, wherein t r=t u+ deadline u-t 0, current scheduling scope is designated as
Figure FDA00002303884200021
T wherein uTime slot for request u generation;
Step (34) is sequentially taken out each Internet Transmission request u, and the scheduling time domain scope of u is: I u=[t 0, t u+ deadline u], at I uWithin it is carried out the arrangement of actual schedule time slot:
Step (34a) is from t 0Beginning, traversal I uInterior next time slot t e
Step (34b) is if time slot t eCorresponding time slot capacity C (t e) greater than the current data transmission rate, namely greater than current unit interval during volume of transmitted data, then forward step (34a) to; Otherwise, continue following steps;
Step (34c) is calculated from arranging time slot t according to the probabilistic model of first eTo cut-off time slot t lPeriod may come the probability of new transmission request:
Figure FDA00002303884200022
T wherein l=t u+ deadline u
Step (34d) is according to the energy increment expectation computational methods of second portion, and calculating is worked as this request and is arranged at time slot t eThe time energy increment that brings expectation: E u(t e, t l);
Step (34e) repeats (34a)-(34d) until I uTravel through complete;
Step (35) is assigned to the time slot scheduling of u the time slot of the desired value minimum of energy increment
Figure FDA00002303884200023
If a plurality of minimization expected values are arranged, then select maximum t s
Step (36) repeated execution of steps (34) is until all transmission requests all are assigned with time slot scheduling in the current queue;
Step (37) is along with time slot t 0Increase, the time slot scheduling t that arbitrary network transmission request u is arranged in formation Q sDuring arrival, will carry out the actual request sending action; When having new arbitrarily transmission request to arrive, the scheduling of a new round will be excited, execution in step (31)-(36).
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Cited By (3)

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WO2015061940A1 (en) * 2013-10-28 2015-05-07 华为技术有限公司 Rrc state control method, device and apparatus
CN105245919A (en) * 2015-10-08 2016-01-13 清华大学 Energy-consumption-optimization adaptive streaming media distribution method for intelligent terminal
CN111179252A (en) * 2019-12-30 2020-05-19 山东大学齐鲁医院 Cloud platform-based digestive tract disease focus auxiliary identification and positive feedback system

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CN101110618A (en) * 2007-06-21 2008-01-23 上海交通大学 Distributed associating power control method
CN101431467A (en) * 2008-12-18 2009-05-13 中国人民解放军国防科学技术大学 Real-time task admission control method of shared resource network
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Publication number Priority date Publication date Assignee Title
WO2015061940A1 (en) * 2013-10-28 2015-05-07 华为技术有限公司 Rrc state control method, device and apparatus
CN105245919A (en) * 2015-10-08 2016-01-13 清华大学 Energy-consumption-optimization adaptive streaming media distribution method for intelligent terminal
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CN111179252A (en) * 2019-12-30 2020-05-19 山东大学齐鲁医院 Cloud platform-based digestive tract disease focus auxiliary identification and positive feedback system
CN111179252B (en) * 2019-12-30 2021-02-05 山东大学齐鲁医院 Cloud platform-based digestive tract disease focus auxiliary identification and positive feedback system

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