Upload
trankhanh
View
222
Download
0
Embed Size (px)
Citation preview
HIRP OPEN 2016 Future Networks
2
Copyright © Huawei Technologies Co., Ltd. 2015-2016. All rights reserved.
No part of this document may be reproduced or transmitted in any form or by any means without prior written consent of Huawei Technologies Co., Ltd.
Trademarks and Permissions
and other Huawei trademarks are trademarks of Huawei Technologies Co., Ltd.
All other trademarks and trade names mentioned in this document are the property of their respective holders.
Confidentiality
All information in this document (including, but not limited to interface protocols, parameters, flowchart and formula) is the confidential information of Huawei Technologies Co., Ltd and its affiliates. Any and all recipient shall keep this document in confidence with the same degree of care as used for its own confidential information and shall not publish or disclose wholly or in part to any other party without Huawei Technologies Co., Ltd’s prior written consent.
Notice
Unless otherwise agreed by Huawei Technologies Co., Ltd, all the information in this document is subject to change without notice. Every effort has been made in the preparation of this document to ensure accuracy of the contents, but all statements, information, and recommendations in this document do not constitute the warranty of any kind, express or implied.
Distribution
Without the written consent of Huawei Technologies Co., Ltd, this document cannot be distributed except for the purpose of Huawei Innovation R&D Projects and within those who have participated in Huawei Innovation R&D Projects.
Application Deadline: 09:00 A.M., 18th July, 2016 (Beijing Standard Time, GMT+8).
If you have any questions or suggestions about HIRP OPEN 2016, please send Email
([email protected]). We will reply as soon as possible.
HIRP OPEN 2016 Future Networks
3
Catalog
HIRPO20160201: Mobility Research for High-Frequency Network .......................................... 5
HIRPO20160202: Wireless Power Supply for Low Power Consumption Equipment by Base
Station ........................................................................................................................................ 8
HIRPO20160203: Research on Key Technology of Transmission of High Definition Video for
UAV ......................................................................................................................................... 12
HIRPO20160204: Research on Key Technology of Virtual Reality using Wireless
Communication ........................................................................................................................ 15
HIRPO20160205: Research on Wireless Communication Network for Robotic Applications 17
HIRPO20160206: Research on Ambient Backscatter Wireless Communication Technology 19
HIRPO20160207: Research on Haze Suppression Using Electromagnetic Wave
Agglomeration .......................................................................................................................... 22
HIRPO20160208: Auto-Scaling and Resource Coordination of Network Slices ..................... 25
HIRPO20160209: Carrier Grade Cloud Resource Management based on Deep Learning
Technology .............................................................................................................................. 28
HIRPO20160210: Game Theory based Network Slicing Management .................................. 30
HIRPO20160211: Resource Allocation and Mapping for Network Slices ............................... 33
HIRP OPEN 2016 Future Networks
4
HIRPO20160212: Trajectory Modeling and Generation for Mobile Users .............................. 36
HIRP OPEN 2016 Future Networks
5
HIRPO20160201: Mobility Research for
High-Frequency Network
1 Theme: Future Networks
2 Subject: architecture and resource management
List of Abbreviations
NR: New RAT
RLF: Radio Link Failure
RRM: Radio Resource Management
BRS: Beam Reference Signal
3 Background
The new RAT (NR) will consider frequency ranges up to 100 GHz. The radio
characteristics of NR may include large path loss, enlarged noise power (due
to large bandwidth), small cell coverage and large signal variation. To
overcome high frequency channel condition, the beamforming technology may
be used in some scenarios. However in general one beam has relatively
narrow coverage. Also the UE may be receiving more than one beam in a cell.
This brings huge challenges to mobility management, e.g. beam acquisition,
beam tracking, beam-based RRM measurement, RLF detection.
Moreover, this small coverage and fragile channel characteristic of NR lead to
frequent handovers and handover failures which UE experiences. Ping-pong
also happens more frequently in NR. As a result, mobility performance will be
HIRP OPEN 2016 Future Networks
6
degraded unless mobility mechanism is improved in NR compared to the
current LTE.
So, it is a valuable research direction to investigate the measurement and
mobility mechanism in high frequency to ensure good mobility performance in
NR.
4 Scope
Beam-based RRM measurement and RLF detection mechanisms
Investigate the beam-based RRM measurement and RLF detection
mechanisms, including beam acquisition, beam tracking, beam-based RRM
measurement (e.g. BRS design, how to measure, how to be averaged and
how to trigger measurement report), RLF detection, avoid and/or quickly react
to sudden SINR drops due to beamforming, and so on;
Mobility mechanisms in high frequency
Investigate the mobility mechanisms in high frequency, including how to
decrease the handover failure and Ping-Pong rate, ensuring 0ms handover
interruption time, and so on;
5 Expected Outcome and Deliverables
Technical reports of beam-based RRM measurement and RLF detection
mechanisms;
Technical reports of mobility mechanisms in high frequency;
Related simulation platform with source codes and description;
1~2 Invention/patents.
HIRP OPEN 2016 Future Networks
7
6 Acceptance Criteria
Design competitive measurement and mobility mechanisms in high frequency
and ensure good mobility performance at least not worse than LTE.
7 Phased Project Plan
Phase1 (~3 months): Survey the state of the art of measurement and mobility
solutions in high frequency especially with beamforming technology, analyze
and provide the related technical report;
Phase2 (~6 months): Research on schemes of measurement and mobility,
including beam-based RRM measurement, RLF detection and handover, and
provide the related technical report;
Phase3 (~3 months): Research and provide related algorithms, simulation
results and patents.
Click here to back to the Top Page
HIRP OPEN 2016 Future Networks
8
HIRPO20160202: Wireless Power Supply for Low
Power Consumption Equipment by Base Station
1 Theme: Future Networks
2 Subject: IRF
List of Abbreviations
RFID: Radio Frequency IDentification
3 Background
Limited device battery life has always been a key consideration in the design of
modern mobile wireless technologies. Frequent battery
replacement/recharging is often costly due to the large number of wireless
devices in use, and even infeasible in many critical applications (e.g., sensors
embedded in structures and implanted medical devices).
Categories and Applications
RF-enabled wireless energy transfer (WET) technology provides an attractive
solution by powering wireless devices with continuous and stable energy over
the air. By leveraging the far-field radiative properties of electromagnetic (EM)
waves, wireless receivers could harvest energy remotely from RF signals
radiated by an energy transmitter. RF-enabled WET enjoys many practical
advantages, such as wide operating range, low production cost, small receiver
form factor, and efficient energy multicasting thanks to the broadcast nature of
EM waves.
One important application of RF-enabled WET is wireless powered
communication (WPC), where wireless devices use harvested RF energy to
HIRP OPEN 2016 Future Networks
9
transmit/decode information to/from other devices. Without being interrupted
by energy depletion due to communication usage, WPC is expected to
improve user experience and convenience, with higher and more sustainable
throughput performance than conventional battery-powered communication.
WPC can also be applied in sensors with much lower maintenance cost and
enhanced flexibility in practical deployment.
Due to the high attenuation of microwave energy over distance, RF-enabled
WET is commonly used for supporting low power devices, such as RFID tags
and sensors. However, recent advances in antenna technologies and RF
energy harvesting circuits have enabled much higher microwave power to be
efficiently transferred and harvested by wireless devices. Therefore, WPC will
be an important building block of many popular commercial and industrial
systems in the future, including the upcoming Internet of Things/Everything
(IoT/IoE) systems consisting of billions of sensing/RFID devices as well as
large-scale wireless sensor networks (WSNs).
Model of (Power + Communication) vs. Model of Energy Harvesting
We also envision RF-enabled WET as a key component of the “last-mile”
power delivery system, with the smart electrical power gird forming the
backbone or core power network. Before proceeding to the discussion of
RFenabled WET/WPC, it is worth pointing out its relation to another green
communication technique, energy harvesting (EH), where wireless devices
harness energy from energy sources in the environment not dedicated to
powering wireless devices, such as solar power, wind power, and ambient EM
radiation.
Unlike RF-based EH from ambient transmitters, the energy source of WET is
stable and, more importantly, fully controllable in its transmit power, waveforms,
and occupied time/frequency dimensions to power the energy receivers. With
HIRP OPEN 2016 Future Networks
10
a controllable energy source, a WPC network (WPCN) could be efficiently built
to power multiple communication devices with different physical conditions and
service requirements. Besides, with RF enabled WET, information could also
be jointly transmitted with energy using the same waveform. Such a design
paradigm is referred to as simultaneous wireless information and power
transfer (SWIPT), which has proved to be more efficient in spectrum usage
than transmitting information and energy in orthogonal time or frequency
channels.
4 Scope
Investigate wireless charging technology;
Research on marco base station based wireless charging technology,
which aims to provide power for low cost devices.
5 Expected Outcome and Deliverables
1 survey reports on key technology;
Research on marco base station based wireless charging technology,
which aims to provide power for low cost devices at the power level of
0.001w;
1-2 patents and 1 publication submission;
1 prototype of technical identification.
6 Acceptance Criteria
Survey Report: Comprehensive study of the subject;
HIRP OPEN 2016 Future Networks
11
Research Report/Design Report: Technical solution can be implemented.
Clear technological advancement can be proved. Clear advancement can be
proved;
Patent Proposal: Patent proposals are evaluated and accepted by the internal
Huawei patent evaluation;
Publication: Paper written and submitted to a prestigious conference.
7 Phased Project Plan
Phase1 (~3 months): Survey on technology of the wireless power supply;
Phase2 (~6months): Explore the technology of the wireless power supply for
low power consumption equipment by base station;
Phase3 (~3 months): Use case study and solution study.
Click here to back to the Top Page
HIRP OPEN 2016 Future Networks
12
HIRPO20160203: Research on Key Technology of
Transmission of High Definition Video for UAV
1 Theme: Future Networks
2 Subject: radio transmission technology
3 Background
Now Unmanned Aerial Vehicle (UAV) is a very hot topic, and there are already
many UAV both in the consumer market and civilian market. One typical use
case of UAV is remote monitor, which will send back the real-time HD video to
the monitor center. How to use the existing wireless communication
technology or new to transfer the VR contents is an interesting problem.
4 Scope
Identify the typical requirements for the HD video transmission for UAV;
Survey on the transmission technology of high definition video for UAV
when using wireless communication;
Impact on wireless communication when using HD video;
Research on a new network architecture to fit for high definition video
transmission for UAV;
Research on coverage enhancement/experience improvement solution
design: based on the typical UAV HD video transmission use cases, and
identified requirements, design the solutions to effectively enhance the HD
video coverage and transmission reliability, within the latency and energy
limitation.
HIRP OPEN 2016 Future Networks
13
5 Expected Outcome and Deliverables
1 survey reports on key technology of transmission of high definition video
for UAV;
1-2 research reports on key technology, including license/un-license
spectrum,candidate schemes of optimal technology used in wireless
communication;
1 design/analysis reports and verification about key technology and
system architecture;
1-2 patents and 1 publication submission;
1 prototype of technical identification.
6 Acceptance Criteria
Survey Report: Comprehensive study of the subject;
Research Report/Design Report: Technical solution can be implemented.
Clear technological advancement can be proved. Clear advancement can
be proved;
Patent Proposal: Patent proposals are evaluated and accepted by the
internal Huawei patent evaluation;
Publication: Paper written and submitted to a prestigious conference.
7 Phased Project Plan
Phase 1 (~2 months): Survey on key technology of transmission of high
definition video for UAV, including industry and academia area;
HIRP OPEN 2016 Future Networks
14
Phase 2 (~7 months): Research on key technology of transmission of high
definition video for UAV, including architecture design, model selection,
algorithm design and so on;
Phase 3 (~3 months): Verification of the proposed architecture and technology.
Click here to back to the Top Page
HIRP OPEN 2016 Future Networks
15
HIRPO20160204: Research on Key Technology of
Virtual Reality using Wireless Communication
1 Theme: Future Networks
2 Subject: others
3 Background
Now virtual reality or augmented reality is a very hot topic, and there are many
VR devices in the commercial market. Because of the inherent character of VR
contents, the amount of transport is very large, so now the connection between
VR server and display headset is all fixed, which will restrict the mobility when
playing VR game or using other VR services. How to use the wireless
communication to transfer the VR contents is an interesting problem.
4 Scope
Survey on the AR/VR technology when using wireless communication;
Impact on wireless communication when using VR services;
Analysis of the requirement for wireless network for different AR
experience;
Research on a new network architecture to fit for VR transport.
5 Expected Outcome and Deliverables
1 survey reports on key technology of virtual reality using wireless
communication;
HIRP OPEN 2016 Future Networks
16
1-2 research reports on key technology of virtual reality, including
candidate schemes of optimal technology used in wireless communication;
1 design/analysis reports and verification about key technology of virtual
reality using wireless communication, such as system architecture;
1-2 patents and 1 publication submission.
6 Acceptance Criteria
Survey Report: Comprehensive study of the subject;
Research Report/Design Report: Technical solution can be implemented.
Clear technological advancement can be proved. Clear advancement can
be proved;
Patent Proposal: Patent proposals are evaluated and accepted by the
internal Huawei patent evaluation;
Publication: Paper written and submitted to a prestigious conference.
7 Phased Project Plan
Phase1 (~2 months): Survey on key technology of virtual reality using wireless
communication, including industry and academia area;
Phase2 (~7 months): Research on key technology of virtual reality using
wireless communication, including architecture design, model selection,
algorithm design and so on;
Phase 3 (~3 months): Verification of the proposed architecture and technology.
Click here to back to the Top Page
HIRP OPEN 2016 Future Networks
17
HIRPO20160205: Research on Wireless
Communication Network for Robotic Applications
1 Theme: Future Networks
2 Subject: architecture and resource management
3 Background
Robotic application has been an emerging area in both enterprise and
consumer business. There is also ongoing standardization work in 3GPP for
related scenarios, e.g. NB-IoT and/or mMTC. However there may be more
specific verticals that require different user experience and functionalities, such
as cooperative robotics in a Multi Agent System. How to use wireless
technologies to enable more exciting applications would be a promising area.
4 Scope
Survey on the robotic technology when using wireless communication;
Impact on wireless communication when implementing robotic services;
Analysis of the requirement for wireless network for different robotic
applications;
Research on a new network architecture to fit for robotics traffic.
5 Expected Outcome and Deliverables
1 survey reports on key technology of robotics using wireless
communication;
1-2 research reports on key technology of robotics, including candidate
schemes of optimal technology used in wireless communication;
HIRP OPEN 2016 Future Networks
18
1 design/analysis reports and verification about key technology of robotics
using wireless communication, such as system architecture;
1-2 patents and 1 publication submission.
6 Acceptance Criteria
Survey Report: Comprehensive study of the subject;
Research Report/Design Report: Technical solution can be implemented.
Clear technological advancement can be proved. Clear advancement can
be proved;
Patent Proposal: Patent proposals are evaluated and accepted by the
internal Huawei patent evaluation;
Publication: Paper written and submitted to a prestigious conference.
7 Phased Project Plan
Phase 1 (~2 months): Survey on key technology of robotics using wireless
communication, including industry and academia area;
Phase 2 (~7 months): Research on key technology of robotics using wireless
communication, including architecture design, model selection, algorithm
design and so on.
Phase 3 (~3 months): Verification of the proposed architecture and technology.
Click here to back to the Top Page
HIRP OPEN 2016 Future Networks
19
HIRPO20160206: Research on Ambient Backscatter
Wireless Communication Technology
1 Theme: Future Networks
2 Subject: radio transmission technology
3 Background
In traditional backscatter communication (e.g., RFID), a device communicates
by modulating its reflections of an incident RF signal (and not by generating
radio waves). Hence, it is orders of magnitude more energy-efficient than
conventional radio communication.
Ambient backscatter differs from RFID-style backscatter in three key respects.
Firstly, it takes advantage of existing RF signals so it does not require the
deployment of a special-purpose power infrastructure—like an RFID
reader—to transmit a high-power (1W) signal to nearby devices. This
avoids installation and maintenance costs that may make such a system
impractical, especially if the environment is outdoors or spans a large area;
Second, and related, it has a very small environmental footprint because
no additional energy is consumed beyond that which is already in the air;
Finally, ambient backscatter provides device-to-device communication.
This is unlike traditional RFID systems in which tags must talk exclusively
to an RFID reader and are unable to even sense the transmissions of other
nearby tags.
Designing an ambient backscatter system is challenging for at least three
reasons.
HIRP OPEN 2016 Future Networks
20
Since backscattered signals are weak, traditional backscatter uses a
constant signal to facilitate the detection of small level changes. Ambient
backscatter uses uncontrollable RF signals that already have information
encoded in them. Hence it requires a different mechanism to extract the
backscattered information;
Traditional backscatter receivers rely on power-hungry components such
as oscillators and ADCs and decode the signal with relatively complex
digital signal processing techniques. These techniques are not practical for
use in a battery-free receiver;
Ambient backscatter lacks a centralized controller such as an RFID reader
to coordinate all communications. Thus, it must operate a distributed
multiple access protocol and develop functionalities like carrier sense that
are not available in traditional backscattering devices.
4 Scope
Survey on the Ambient Backscatter wireless communication technology;
Explore the maximum transmission distance and transmission rate via
Ambient Backscatter technology;
Use case study and solution study using Ambient Backscatter technology.
5 Expected Outcome and Deliverables
One survey reports on key technology of Ambient Backscatter wireless
communication;
One or two research reports on key technology of Ambient Backscatter
wireless communication technology;
HIRP OPEN 2016 Future Networks
21
One design/analysis reports and verification about key technology of
Ambient Backscatter wireless communication technology, such as system
architecture;
One or two patents and 1 publication submission.
6 Acceptance Criteria
Survey Report: Comprehensive study of the subject;
Research Report/Design Report: Technical solution can be implemented.
Clear technological advancement can be proved. Clear advancement can
be proved;
Patent Proposal: Patent proposals are evaluated and accepted by the
internal Huawei patent evaluation;
Publication: Paper written and submitted to a prestigious conference.
7 Phased Project Plan
Phase1 (~3 months): Survey on the Ambient Backscatter wireless
communication technology;
Phase2 (~6 months): Explore the maximum transmission distance and
transmission rate via Ambient Backscatter technology;
Phase3 (~3 months): Use case study and solution study using Ambient
Backscatter technology.
Click here to back to the Top Page
HIRP OPEN 2016 Future Networks
22
HIRPO20160207: Research on Haze Suppression
Using Electromagnetic Wave Agglomeration
1 Theme: Future Networks
2 Subject: IRF
List of Abbreviations
PM 2.5: Particulate Matter with diameter smaller than 2.5μm
EMW: Electromagnetic Wave
3 Background
Haze weather is growing to be a global issue, which not only decreases the
traffic visibility, but also causes disease among a large number of individuals,
especially in urban area. Traditional methods of suppressing haze can merely
be used in a confined space, usually connected to a stove, which is widely
applied in coal fields. With respect to urban area, however, the haze created by
plenty of sources including automobile exhaust as well as the residues of dust
and powder from surrounding factories, is everywhere in the open space. Even
though the indoor air cleaner can exert some function, the expensive price for
an average family is a financial burden; and furthermore, the majority of people
should go outside in daily life. Therefore, a haze suppression approach for
open space is significant and emergency for protecting the environment
particularly in a heavy haze day.
Electromagnetic wave (EMW), widely used in wireless communication,
broadcasting, radar, etc., is nearly the only technology that propagates freely in
the open space and tends to be safe by controlling the transmit power. The
HIRP OPEN 2016 Future Networks
23
implement of approaching EMW to haze suppression could make great
benefits for both public health and commercial profit. Research on this
possibility is, in a word, valuable.
4 Scope
1) Valid parameters of the EMW for haze suppression: the parameter scope of
the EMW which is valid for suppressing the concentration of PM2.5, especially
the power and frequency instigating more than 20% of the PM2.5 particles
agglomerated to PM10, should be obtained with experiment and/or theoretic
proof;
2) Charging scheme on the base station: for the outdoor haze weather, the
particles should be charged sufficient for electrical agglomeration;
3) Device design: minimizing the size and power of the device for the particle
agglomeration, for being settled on base station.
5 Expected Outcome and Deliverables
1 survey reports on key technology of the EMW for haze suppression;
1-2 research reports on key technology of the EMW for haze suppression;
1 design/analysis reports and verification about key technology of the EMW for
haze suppression;
1-2 patents and 1 publication submission.
6 Acceptance Criteria
Survey Report: Comprehensive study of the subject;
HIRP OPEN 2016 Future Networks
24
Research Report/Design Report: Technical solution can be implemented.
Clear technological advancement can be proved. Clear advancement can be
proved;
Patent Proposal: Patent proposals are evaluated and accepted by the internal
Huawei patent evaluation;
Publication: Paper written and submitted to a prestigious conference.
7 Phased Project Plan
Phase1 (~3 months): Researching and preparing for the experiments;
Phase2 (~6 months): Testing and searching for the valid parameter scopes of
the EMW;
Phase3 (~3 months): Compiling the reports and intellectual property material.
Click here to back to the Top Page
HIRP OPEN 2016 Future Networks
25
HIRPO20160208: Auto-Scaling and Resource
Coordination of Network Slices
1 Theme: Future Networks
2 Subject: architecture and resource management
List of Abbreviations
NFV: Network Function Virtualization
SDN: Software Defined Network
3 Background
A digital transformation, brought by the power of connectivity, is taking place in
almost every industry. New Communication types like Vehicle-to-Vehicle and
Machine-to-Machine will emerge with different network requirements. Network
slicing will enable operators to provide networks on an xyz-as-a-service basis.
By leveraging SDN and NFV, dedicated network slices will be created on the
same physical infrastructure. Network operators should make proper decisions
based on algorithms about the lifecycle management to meet the service
requirements and enhance resource utilization.
4 Scope
Survey on characteristics of different network slices and topics of network
slice resource management, resource allocation and coordination
algorithms;
Research on service requirement of different network slices. Feature
extraction and trend prediction of service workload and resource workload;
HIRP OPEN 2016 Future Networks
26
Definition of network attributes in network slice and setup mathematical
models;
Design auto-scaling algorithms and resource coordination algorithms
between network slices to satisfy carrier-grade reliability requirement and
enhance physical resource utilization.
5 Expected Outcome and Deliverables
1 survey reports on auto-scaling and network resource coordination;
1-2 research reports on auto-scaling architecture design, including
candidate schemes of optimal resource coordination for network slices;
2 algorithms analysis reports about auto-scaling and resource
coordination;
1-2 patents and 1 publication submission.
6 Acceptance Criteria
Survey Report: Comprehensive study of the subject;
Research Report/Algorithm Report: Technical solution can be implemented.
Clear technology and algorithm advancement can be proved;
Patent Proposal: Patent proposals are evaluated and accepted by the internal
Huawei patent evaluation;
Publication: Paper written and submitted to a prestigious conference.
HIRP OPEN 2016 Future Networks
27
7 Phased Project Plan
Phase 1 (~2 months): Characteristics of different network slices and topics of
network slice resource management, resource allocation or resource
coordination algorithms;
Phase 2 (~3 months): Research on service requirement of different network
slices. Feature extraction and trend prediction of service workload and
resource workload;
Phase 3 (~7 months): Definition of network attributions in network slice and
setup mathematical models. Design auto-scaling algorithms and resource
coordination algorithms between network slices in network slice to satisfy
carrier-grade reliability requirement and enhance physical resource utilization.
Click here to back to the Top Page
HIRP OPEN 2016 Future Networks
28
HIRPO20160209: Carrier Grade Cloud Resource
Management based on Deep Learning Technology
1 Theme: Future Networks
2 Subject: architecture and resource management
List of Abbreviations
DL: Deep Learning
3 Background
Deep learning (DL) is widely used in natural language processing, image
recognition, text recognition and other fields currently. While operating the
Telco networks, there are many system performance data and log information
that can be collected. The expert system will run resource management and
failure analysis from these data. But this method is inefficient and difficult to
adapt the revolution of complex telecommunication networks. It is a major
research topic of how to use machine learning algorithms or deep learning
algorithms to identify potential risks in telecommunications networks.
4 Scope
Survey on deep learning technology, especially in telecommunication
management;
Describe and design the architecture, model and key technology of
telecommunication management with deep learning;
Research on the Telco cloud resource management, failure prediction (not
limited) assisted by deep learning.
HIRP OPEN 2016 Future Networks
29
5 Expected Outcome and Deliverables
1 survey reports on carrier grade cloud resource management based on
deep learning technology;
1-2 research reports on deep learning based resource management
architecture design, including candidate schemes of optimal carrier grade
resource management;
2 algorithms analysis reports and verification about carrier grade cloud
resource management based on deep learning, such as failure prediction;
1-2 patents and 1 publication submission.
6 Acceptance Criteria
Survey Report: Comprehensive study of the subject;
Research Report/Algorithm Report: Technical solution can be implemented.
Clear technology and algorithm advancement can be proved;
Patent Proposal: Patent proposals are evaluated and accepted by the internal
Huawei patent evaluation;
Publication: Paper written and submitted to a prestigious conference.
7 Phased Project Plan
Phase 1 (~2 months): Survey on the carrier grade cloud resource
management based on deep learning technology, including industry and
academia area;
Phase 2 (~7 months): Research on carrier grade cloud resource management
based on deep learning, including architecture design, model selection,
algorithm design and so on;
Phase 3 (~3 months): verification of the proposed algorithms.
Click here to back to the Top Page
HIRP OPEN 2016 Future Networks
30
HIRPO20160210: Game Theory based Network Slicing
Management
1 Theme: Future Networks
2 Subject: architecture and resource management
3 Background
NFV change the way how carrier networks are architected by separating
software and hardware and leveraging virtualization technology. It brings great
flexibility, reduces service deployment complexity and speeds up service
deployment. To obtain these benefits, however, network operators have to
spend huge amount of money on carrier grade servers and operation &
maintenance. To further reduce expenses, their network could be constructed
on the public cloud. Therefore, a slice resource management mechanism that
take advantage of the public cloud service should be established to guarantee
a carrier grade service.
4 Scope
1). VM auction and pricing modeling: VM pricing based on demand and
supply in the market, take customized VM and resources in geo-distributed DC
into consideration; game theory based auction mechanism, maximize revenue
of both provider and users, support VM auction on demand, combinatorial
auction of customized VMs and online auction;
2). Deployment algorithm in public cloud: analyze the number of users and
cloud resource consumption model, determine the required VM template and
HIRP OPEN 2016 Future Networks
31
combinatorial VM templates for a service based on traffic model; optimal
service deployment cross-DC with low latency;
3). Modeling of elastic scaling scenarios in public cloud: consider VM cost,
auto-scaling overheads, SLA violation penalty, minimize the expenses and
maximize the resource utilization;
4). According to the analysis above, validating the algorithm and solution in
public cloud.
5 Expected Outcome and Deliverables
1 survey reports on game theory based network slicing management;
1-2 research reports on network slicing management architecture design,
including candidate schemes of optimal network slicing management;
2 algorithms analysis reports and verification for proposed algorithms;
1-2 patents and 1 publication submission.
6 Acceptance Criteria
Survey Report: Comprehensive study of the subject;
Research Report/Algorithm Report: Technical solution can be implemented.
Clear technology and algorithm advancement can be proved;
Patent Proposal: Patent proposals are evaluated and accepted by the internal
Huawei patent evaluation;
Publication: Paper written and submitted to a prestigious conference.
HIRP OPEN 2016 Future Networks
32
7 Phased Project Plan
Phase 1 (~2 months): Survey on game theory based network slicing
management, including industry and academia area;
Phase 2 (~7 months): Research on game theory based network slicing
management, including architecture design, model selection, algorithm design
and so on;
Phase 3 (~3 months): verification of the proposed algorithms.
Click here to back to the Top Page
HIRP OPEN 2016 Future Networks
33
HIRPO20160211: Resource Allocation and Mapping for
Network Slices
1 Theme: Future Networks
2 Subject: architecture and resource management
3 Background
The integration of vertical markets (e.g. smart car, e-health, smart city, Internet
of Things, etc.) and the ability to support real-time critical services (e.g. virtual
reality office, real-time remote computing for mobile terminal, traffic safety and
efficiency etc.) are needed in 5G network era. Network slices as an end-to-end
virtual resource for connection will satisfy these diverse service requirements.
Virtual resources allocation and mapping for carrier grade network calls for
higher reliability. Virtual resource allocation and mapping management for
network slices serve as a key component in 5G network operation. Therefore
designing an optimal virtual resource allocation and mapping management
algorithm for network slices are of vital significance.
4 Scope
A. Survey and analysis of resource allocation and mapping management
algorithm, as well as research of the industry’s trend to implement virtual
resource allocation and mapping management;
B. Detailed definition of the environment and constraints for network slice
resource allocation and mapping, plus analysis of resource modeling;
C. Design the resource allocation and mapping management algorithms for
network slices, which meet the following requirements: fulfills
HIRP OPEN 2016 Future Networks
34
telecommunications reliability requirement, effectively utilizes existing physical
resources and reduces resource fragments. The objectives considered include
resource utilization, load balance, reliability and energy efficiency, etc.
5 Expected Outcome and Deliverables
1 survey and report on resource allocation and mapping for network
slices;1-2 research reports on resource allocation and mapping for
network slices, including different algorithms for optimal resource
allocation and mapping. In addition, explain how the proposed algorithm
can be adapted and verified on the dynamic industry with flexibility;
1-2 patents and 1 publication submission.
6 Acceptance Criteria
Survey Report: Comprehensive study of the subject;
Research Report/Algorithm Report: Technical solution can be implemented.
Clear technology and algorithm advancement can be proved;
Patent Proposal: Patent proposals are evaluated and accepted by the internal
Huawei patent evaluation;
Publication: Paper written and submitted to a prestigious conference.
7 Phased Project Plan
Phase 1 (~2 months): Survey on resource allocation and mapping for network
slices, including industry and academia area;
Phase 2 (~7 months): Research on resource allocation and mapping for
network slices, including architecture design, model selection, algorithm
design and so on;
HIRP OPEN 2016 Future Networks
35
Phase 3 (~3 months): verification of the proposed algorithms.
Click here to back to the Top Page
HIRP OPEN 2016 Future Networks
36
HIRPO20160212: Trajectory Modeling and Generation
for Mobile Users
1 Theme: Future Networks
2 Subject: others
3 Background
Location is a unique asset for mobile operators, with wide coverage,
all-weather, high frequency, etc. Open location ability through open API can
create new revenue model. However the accuracy of user position acquired
from network is not high, that is why we need the trajectory recovery algorithm.
It requires a lot of location data of multi users to refine relative algorithm, but it
is hard to get those data. Obtain large quantities of user location data through
simulation has a positive impact on the trajectory recovery algorithm.
4 Scope
Investigation and analysis of the current mobile user tracking information,
include accuracy, sampling rate, magnitude, cost, as well as the content
and sampling rate of MR (measurement report);
Analysis of Integrated map data in simulation platform, and generate user
trajectory automatically by map data;
Modeling trajectory in simulation platform, and build large-scale scenarios,
output a large number of user trajectory, align with trajectory recovery
algorithm.
HIRP OPEN 2016 Future Networks
37
5 Expected Outcome and Deliverables
1 survey reports on trajectory modeling and generation for mobile users;
1-2 research reports on architecture design of trajectory modeling and
generation for mobile users, including candidate schemes of optimal
trajectory generation;
2 algorithms analysis reports and verification about proposed algorithms;
1-2 patents and 1 publication submission.
6 Acceptance Criteria
Survey Report: Comprehensive study of the subject;
Research Report/Algorithm Report: Technical solution can be implemented.
Clear technology and algorithm advancement can be proved;
Patent Proposal: Patent proposals are evaluated and accepted by the internal
Huawei patent evaluation;
Publication: Paper written and submitted to a prestigious conference.
7 Phased Project Plan
Phase 1 (~2 months): Survey on trajectory modeling and generation for mobile
users, including industry and academia area;
Phase 2 (~7 months): Research on trajectory modeling and generation for
mobile users, including architecture design, model selection, and algorithm
design and so on;
Phase 3 (~3 months): Verification of the proposed algorithms.
Click here to back to the Top Page