CN109981194B - Energy efficiency optimization system based on software defined network in smart home - Google Patents

Energy efficiency optimization system based on software defined network in smart home Download PDF

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CN109981194B
CN109981194B CN201711465519.7A CN201711465519A CN109981194B CN 109981194 B CN109981194 B CN 109981194B CN 201711465519 A CN201711465519 A CN 201711465519A CN 109981194 B CN109981194 B CN 109981194B
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module
link
limitation
network
software
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CN109981194A (en
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汪莹
施展
亢中苗
刘紫健
李溢杰
陈辉煌
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Electric Power Dispatch Control Center of Guangdong Power Grid Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/02—Traffic management, e.g. flow control or congestion control
    • H04W28/0231—Traffic management, e.g. flow control or congestion control based on communication conditions
    • H04W28/0236—Traffic management, e.g. flow control or congestion control based on communication conditions radio quality, e.g. interference, losses or delay
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/02—Traffic management, e.g. flow control or congestion control
    • H04W28/10—Flow control between communication endpoints
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/02—Power saving arrangements
    • H04W52/0203—Power saving arrangements in the radio access network or backbone network of wireless communication networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Quality & Reliability (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention discloses an energy efficiency optimization system based on a software defined network in smart home, which comprises the following steps: the system comprises an intelligent household equipment system downlink module, a node and link limiting module and a combined traffic engineering and interference management module. And the downlink module of the intelligent household equipment system is connected with the node and the link limiting module in order to aggregate the wireless links. The node and link limiting module is connected with the joint flow engineering and interference management module in order to solve the problems of non-convexity caused by flow rate limitation of the wireless link and the coupling mode of flow in flow conservation limitation. According to the invention, the software-defined network and the intelligent home system are linked through the research on the joint flow control and physical layer interference management problems of the large-scale software-defined wireless network in the heterogeneous network scene, so that the energy efficiency optimization system based on the software-defined network is realized, and the energy efficiency of the system in the intelligent home scene is improved to the maximum extent.

Description

Energy efficiency optimization system based on software defined network in smart home
Technical Field
The invention relates to the technical field of communication, in particular to an energy efficiency optimization system based on a software defined network in smart home.
Background
The intelligent home is embodied in an internet of things under the influence of the internet of things. The intelligent home is characterized in that various devices (such as audio and video devices, lighting systems, curtain control, air conditioner control, security systems, digital cinema systems, network home appliances, three-meter reading and the like) in the home are connected together through the Internet of things technology, and multiple functions and means such as home appliance control, lighting control, curtain control, telephone remote control, indoor and outdoor remote control, anti-theft alarm, environment monitoring, heating and ventilation control, infrared forwarding, programmable timing control and the like are provided.
However, any technology implementation requires energy support, and energy is generally provided by way of electrical energy. At present, the electric energy consumed by information and communication technology can reach 5% of the world, and nearly 2% of greenhouse gases around the world are discharged, which is equivalent to the total discharge amount of the aviation industry. With the current growth trend, the carbon emissions of the information and communication technology industry will be doubled in 2020 if not controlled. Therefore, the research on the energy efficiency in the smart home system becomes especially important, and the problems of low energy efficiency, high energy consumption of a network and the like exist in the prior art.
Disclosure of Invention
The invention aims to solve the problem of low energy utilization efficiency in an intelligent home system, and provides an energy efficiency optimization system based on a software defined network in intelligent home.
In order to solve the technical problems, the technical scheme of the invention is as follows:
an energy efficiency optimization system based on a software defined network in smart home comprises: a first module, a second module and a third module;
the first module is an intelligent household equipment system downlink module;
the second module is a node and link limiting module;
the third module is a combined traffic engineering and interference management module;
the first module is connected with the second module and used for gathering wireless links;
the second module is connected with a third module, and the third module is used for solving the problems of non-convexity caused by the flow rate limitation of the wireless link and the coupling mode of flow in the flow conservation limitation.
Preferably, the first module is a downlink module of an intelligent home device system of a software-defined wireless network, and data streams of the first module flow to the intelligent home terminal through the software-defined wireless network.
Preferably, the software defined wireless network is a directed link combination;
the directed link combination comprises a wired link and a wireless link;
the wired link provides a connection between a route and a base station;
the wireless link provides single-hop connection between the base station and the intelligent home terminal.
Preferably, the second module feeds back the channel state information of the uplink to the first module.
Preferably, when the second module feeds back the channel state information of the uplink to the first module, the limitation on link feedback and network access includes: link capacity limitation, node traffic conservation limitation, transmit power limitation, heterogeneous Qos guarantee limitation, cross-layer interference limitation, and virtual resource user modulation limitation.
Preferably, when the link feedback and the limitation constraint on accessing the network occur, the following steps need to be performed:
s1, routing from a node s (N) to N intelligent household terminals of a node d (N), wherein N is 1-N;
and S2, designing a linear precoder at each base station.
Preferably, in order to solve the non-convex problem caused by the wireless link flow rate limitation, the third module adopts the following formula:
Figure GDA0003207593160000021
wherein u isl(v) For preliminary additional optimization variables, assume that each base station uses a linear precoder vlWherein
Figure GDA0003207593160000022
Figure GDA0003207593160000023
R represents a real number set, plRepresenting the allocated power for the directed link,
Figure GDA0003207593160000024
pmallocated power, h, representing network routeslmRepresenting the passage of a subchannel klBy base stations smTo end user dlOf the channel tap coefficient hllRepresenting the passage of a subchannel klBy base stations slTo end user dlThe channel tap coefficients of (a) are,
Figure GDA0003207593160000025
is a user dlThe variance of additive white gaussian noise, m represents network routing, l represents a directional link, I (l) represents a wireless link set containing a link l, and v represents a node.
Preferably, in order to solve the problem of the coupling mode of the flow in the flow conservation limitation, the third module adopts the following formula:
wl(v)＝(1-|hll|vlul(v))-1
wherein wl(v) Represents an advanced additional optimization variable, hllRepresenting channel tap coefficients; in addition, the allocated power is pl＝vl 2。
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
according to the energy efficiency optimization system based on the software defined network in the smart home, the downlink module, the node and link limiting module and the joint flow engineering and interference management module of the smart home equipment system are mutually matched, and the joint flow engineering and interference management module adopts a distributed algorithm to realize rate optimization and solve the problem of large-scale distributed convex optimization.
The invention can optimize the energy efficiency of the network, reduce the energy consumption of the network and improve the energy efficiency of the intelligent home system to the maximum extent.
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Fig. 1 is a schematic diagram of an energy efficiency optimization system based on a software defined network in smart home.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent;
for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product;
it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Example 1
An energy efficiency optimization system based on a software defined network in smart home, as shown in fig. 1, includes: a first module, a second module and a third module;
the first module is an intelligent household equipment system downlink module;
the second module is a node and link limiting module;
the third module is a combined traffic engineering and interference management module;
the first module is connected with the second module and used for gathering wireless links;
the second module is connected with a third module, and the third module is used for solving the problems of non-convexity caused by the flow rate limitation of the wireless link and the coupling mode of flow in the flow conservation limitation.
Preferably, the first module is a downlink module of an intelligent home device system of a software-defined wireless network, and data streams of the first module flow to the intelligent home terminal through the software-defined wireless network.
Preferably, the software defined wireless network is a directed link combination;
the directed link combination comprises a wired link and a wireless link;
the wired link provides a connection between a route and a base station;
the wireless link provides single-hop connection between the base station and the intelligent home terminal;
and according to the wireless link and the distributed power, the rate of the wireless link can be obtained based on a Shannon capacity formula.
Preferably, the second module feeds back the channel state information of the uplink to the first module.
Preferably, when the second module feeds back the channel state information of the uplink to the first module, the limitation on link feedback and network access includes: link capacity limitation, node traffic conservation limitation, transmission power limitation, heterogeneous Qos guarantee limitation, cross-layer interference limitation and virtual resource user modulation limitation;
for each wireless link of the software-defined wireless network, given a linear precoder, when estimating channel state information for an uplink through a home base station in a smart home scenario and feeding back the channel state information from femto users to a downlink, a variety of system-level constraints are considered in a backhaul link and an access network, wherein for any one wired link, the sum of flow rates of all data transmitted thereon must be smaller than the total capacity of the link, for any node V ∈ V, the total input traffic is equal to the total output traffic, for the transmission power of a base station s, the sum should be smaller than a given budget power, and any user is ensured to obtain a service with QoS (user quality of service) guarantee at any time and any place in the use of the smart home, while cross-layer interference constraints must be taken into account to reduce communication interference between smart home users, for the problem of scheduling limitation of virtual resource users, each sub-channel in a cell can be occupied by at most one home user using smart home.
Under the constraint of the above restriction, the present invention also simultaneously implements the routing from the node s (N) to the node d (N), where N is 1 to N; and designing a linear precoder at the base station in each intelligent home scene, so that the network energy efficiency in the intelligent home scene can be used
Figure GDA0003207593160000041
To indicate.
Preferably, in order to solve the non-convex problem caused by the wireless link flow rate limitation, the third module adopts a weighted minimum mean square error algorithm defined as WMMSE:
Figure GDA0003207593160000042
wherein u isl(v) For preliminary additional optimization variables, assume that each base station uses a linear precoder vlWherein
Figure GDA0003207593160000043
Figure GDA0003207593160000044
R represents a real number set, plRepresenting the allocated power for the directed link,
Figure GDA0003207593160000045
pmallocated power, h, representing network routeslmRepresenting the passage of a subchannel klBy base stations smTo end user dlOf the channel tap coefficient hllRepresenting the passage of a subchannel klBy base stations slTo end user dlThe channel tap coefficients of (a) are,
Figure GDA0003207593160000051
is a user dlThe variance of additive white gaussian noise, m represents network routing, l represents a directional link, I (l) represents a wireless link set containing a link l, and v represents a node.
Preferably, in order to solve the problem of the coupling manner of the flow in the flow conservation limit, the third module adopts an alternating direction multiplier algorithm defined as ADMM:
wl(v)＝(1-|hll|vlul(v))-1
wherein wl(v) Represents an advanced additional optimization variable, hllRepresenting channel tap coefficients; in addition, the allocated power is pl＝vl 2。
In some embodiments, the joint traffic engineering and interference management module deals with the problems of non-convexity caused by wireless link flow rate limitation and the way of coupling the flow in the flow conservation limitation, and the like, and is not limited to the introduction of one additional variable.
The terms describing positional relationships in the drawings are for illustrative purposes only and are not to be construed as limiting the patent;
it should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.

Claims (3)

1. The utility model provides an energy efficiency optimizing system based on software defined network in intelligent house which characterized in that includes: a first module, a second module and a third module;
the first module is an intelligent household equipment system downlink module;
the second module is a node and link limiting module;
the third module is a combined traffic engineering and interference management module;
the first module is connected with the second module and used for gathering wireless links;
the second module is connected with a third module, and the third module is used for solving the problems of non-convexity caused by flow rate limitation of a wireless link and the coupling mode of flow in flow conservation limitation;
the second module feeds back the channel state information of the uplink to the first module;
when the second module feeds back the channel state information of the uplink to the first module, the limitation on the link feedback and the network access comprises: link capacity limitation, node traffic conservation limitation, transmission power limitation, heterogeneous Qos guarantee limitation, cross-layer interference limitation and virtual resource user modulation limitation;
when the limit constraint occurs, the following steps are required to be executed:
s1, routing from a node s (N) to N intelligent household terminals of a node d (N), wherein N is 1-N;
s2, designing a linear precoder at each base station;
the third module adopts the following formula in order to solve the non-convex problem caused by the wireless link flow rate limitation:
Figure FDA0003207593150000011
wherein u isl(v) For preliminary additional optimization variables, assume that each base station uses a linear precoder vlWherein
Figure FDA0003207593150000012
Figure FDA0003207593150000013
R represents a real number set, plRepresenting the allocated power for the directed link,
Figure FDA0003207593150000014
pmallocated power, h, representing network routeslmRepresenting the passage of a subchannel klBy base stations smTo end user dlOf the channel tap coefficient hllRepresenting the passage of a subchannel klBy base stations slTo end user dlThe channel tap coefficients of (a) are,
Figure FDA0003207593150000015
is a user dlThe variance of additive white Gaussian noise is measured, m represents network routing, l represents a directional link, I (l) represents a wireless link set containing a link l, and v represents a node;
the third module adopts the following formula in order to solve the problem of the flow coupling mode in the flow conservation limitation:
wl(v)＝(1-|hll|vlul(v))-1
wherein wl(v) Represents an advanced additional optimization variable, hllRepresenting the passage of a subchannel klBy base stations slTo end user dlThe channel tap coefficients of (a); in addition, the allocated power is pl＝vl 2。
2. The system for optimizing energy efficiency based on the software-defined network in the smart home according to claim 1, wherein the first module is a downlink module of a system of smart home devices of the software-defined wireless network, and a data stream of the first module flows to the smart home terminal through the software-defined wireless network.
3. The system for optimizing energy efficiency based on the software-defined network in the smart home according to claim 2, wherein the software-defined wireless network is a directed link combination;
the directed link combination comprises a wired link and a wireless link;
the wired link provides a connection between a route and a base station;
the wireless link provides single-hop connection between the base station and the intelligent home terminal.
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CN104468410A (en) * 2014-11-28 2015-03-25 广东电网有限责任公司电力调度控制中心 Communication node flow scheduling method and system for smart home
CN105007583A (en) * 2015-07-28 2015-10-28 华中科技大学 Energy efficiency improving method based on game playing in heterogeneous cellular network
CN106209336A (en) * 2016-07-14 2016-12-07 东南大学 A kind of resource allocation methods in software definition mobile network

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JP2002245077A (en) * 2001-02-14 2002-08-30 Hitachi Ltd Information distribution service system and mobile data transmitter-receiver

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CN104468410A (en) * 2014-11-28 2015-03-25 广东电网有限责任公司电力调度控制中心 Communication node flow scheduling method and system for smart home
CN105007583A (en) * 2015-07-28 2015-10-28 华中科技大学 Energy efficiency improving method based on game playing in heterogeneous cellular network
CN106209336A (en) * 2016-07-14 2016-12-07 东南大学 A kind of resource allocation methods in software definition mobile network

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