Research and Publications: A Personal Perspective
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Transcript of Research and Publications: A Personal Perspective
23/4/19 p. 1
Research and Publications:A Personal Perspective
Bo Li
Hong Kong University of Science and Technology
Microsoft Research Asia
23/4/19 p. 2
Outline
What about research? How much does one have to learn? PhD research What is procedure of publications? How to write technical papers?
23/4/19 p. 3
Research is easy!
You have done this many times in course projects
Take a known problem, and apply a known technique
Obtain results, and write a report
23/4/19 p. 4
Research is difficult!
Is it technically correct? Does it make intuitively sense? Is it publishable, where and why? Does it offer some insights beyond
what we have known? Does it have any impact? …
23/4/19 p. 5
Research
There are basically four types of research works:
New problem and new solution New problem and old solution Old problem and new solution Old problem and old solution
23/4/19 p. 6
Research
Case I comes rarely, perhaps something you could only wish, once a life-time experience
Shannon theory Cases II and III are the ones that you
should target for Packet scheduling: weighted fair queuing Geographical routing in ad hoc networks
Case IV is where you can start Plenty of out there under the category of
“Yet another paper on … “
23/4/19 p. 7
Where do ideas come from?
Drink a beer, relax, ideas will come to you
The ideas fall from the sky!
Understanding the existing works, build upon that incrementally
23/4/19 p. 8
Where do ideas come from?
Ideas in most cases come from the deep understanding of a subject, and possess of broad knowledge
This is not a technical training, i.e., this is not about solving a bipartite graph, or differential equations
This is about relating them to real world problems This is about providing new insight beyond known This is about your creativity!
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Research: What is it?
Research = Re (repeat) + search Much of the research has been built upon
existing works, therefore a thorough understanding of those is the basis
Too many smart people in each area, so if an idea seems to be too good to be true, it likely is -> rethink that again
Each idea needs iterations: what is it? why has it not been done? what is the logical connection with the existing approaches?
23/4/19 p. 10
Research: Engineering Problem Each solution to an engineering problem is
only a trade-off; it is not a cure for all, it definitely has side-effect.
Networking coding Potential capacity gain under loaded system Is it really? Is there any alternative? What is the
penalty for doing so? Can we handle that in system design?
P2P Facilitate the voluntary file sharing Can this be extended beyond that?
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Case I: Adaptive Video Multicast
The need for multicast - efficiency
Multiple-unicast Multicast
Fundamental problem: users’ heterogeneity and network dynamics
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Case I: Adaptive Video Multicast
Layered video encoding and transmission Cumulative layered coding (Scalable coding)
Base layer: most important feature, low rate, low quality
Enhancement layers: progressively refine quality
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Case I: Adaptive Video Multicast
Existing solutions Multiple multicast tree, each for a layer Receiver adaptation: user’s joining and
leaving groups (receiver) Adaptation is performed at receivers only:
fixed layer rates and limited num of layers
Fundamental Problem The mismatch between the fixed sending
rate and the dynamic and heterogeneous rate requirement from receivers
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Case I: Adaptive Video Multicast
Layered Bit-stream
Bandwidth Report
Sender
A Recei ver
Layered VideoCoder
RateController
FeedbackCollector
LayeredRate
Calculator
LayeredDecoder
LayerAdapter
BandwidthEstimator
Multicast Network
Receiver 1
Receiver 2
Receiver N
Layered Bit-stream
......
BandwidthReport
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Case I: Adaptive Video Multicast
End-to-end adaptive video multicast Optimal rate allocation for each layer:
formulation and solution End-to-end transmission protocol and
whether TCP friendly Complexity analysis Practical issues: feedback explosion
(sampling), RTT estimation (open and closed loop)
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Sample References
B. Li and J. Liu, “Multi-Rate Video Multicast over the Internet: An Overview,” IEEE Network, (17)1: 24-29, January-February 2003.
J.-C. Liu, B. Li and Y.-Q. Zhang, “Adaptive Video Multicast Over the Internet,” IEEE Multimedia, (10)1: 22-33, January-March 2003.
J. Liu, B. Li, and Y.-Q. Zhang, “An End-to-End Adaptation Protocol for Layered Video Multicast Using Optimal Rate Allocation, IEEE Transactions on Multimedia, (6)7: 87-102, February 2004.
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Summary
Identify a general category of problems
The idea should be intuitively simple Publications can be “easier”
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Outline
What about research? How much does one have to learn? PhD research What is procedure of publications? How to write technical papers?
23/4/19 p. 19
How much does one have to learn?
I have learnt all the mathematics, and I am loaded Discrete algorithms, partial differential
equations, dynamic control, probabilistic modeling, information theory and etc.
I still don’t have a clue what to do in research.
Where in the world is research topic?
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How much does one have to learn?
I have read all papers out there from journals and conferences
Can I do research now? There is no way you can cope with all of
them Majority of the published works are junks,
and can cause brain damage and can be misleading
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The minimum needed for research
Logical thinking, after all we are in engineering world
Basic skills You have to know the Dijstra algorithm in order
to understand the OSFP (?) the ability to learn
Life long learning process, esp. in CS
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The minimum needed for research
Abstraction. Take a problem, you have to know What is/are the fundamental problem(s) You have to see both “forest and trees” What have been done, why? What are seemingly undoable?
Understand your strength and weakness
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The minimum needed for research
Open mind We are not dealing with math problem in that there
exists perfect solutions Engineering solutions are subject to argument and
debate, i.e., each solution is a trade-off, and it only works in a constrained environment
Critical mind When you read others, it is equally important to
understand what circumstance that it does not work as in which it works
If you can not identify such scenario, you are not understanding the problem
23/4/19 p. 24
Case II: Proxy Placement
How to place the proxy (mirror sites) in the internet
B. Li et al., “On the Optimal Placement of Web Proxies in the Internet,” Proc. IEEE Infocom'99
ACM Communications Review (2001) cited as the 1st ever work on this topic
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Case II: Proxy Placement
Formulation: graph theory problem, k-median problem: given N nodes, how to select K nodes to place the content so certain optimal criterion can be met
For general graph, this is NP-hard For tree, we solved this using a known dynamic
programming technique This turns out to be the fundamental problem
for object replication in DB, which has been cited over 300 times since then
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Sample References
J.-L. Xu, B. Li and D. Lee, “Placement Problems for Transparent Data Replication Proxy Services,” IEEE Journal Selected Areas in Communications, 20(7): 1383-1398, 2002
A. Vigneron, L. Gao, M. Golin, G. Italiano and B. Li, “An Algorithm for Finding a k-Median in a Directed Tree,” Information Processing Letter, 74(1-2): 81-88, 2000
B. Li, “Content Replication in a Distributed and Controlled Environment,” Journal of Parallel and Distributed Computing, 59(2), pp. 1-21, Nov. 1999
23/4/19 p. 27
Summary
Finding a problem is more important, and difficult than solving a problem
You need out-of-box thinking
23/4/19 p. 28
Outline
What about research? How much does one have to learn? PhD research What is procedure of publications? How to write technical papers?
23/4/19 p. 29
PhD Research
Make a plan earlier, for 3-4 years The research topics must be of current
interest, and state-of-the-art Don’t work on packet scheduling, and IEEE 802.11
MAC protocol Beating the performance of Ethernet is like kicking a
dead horse! It has to be something that within your
capability You need to understand your strength and
weakness, and be realistic (don’t shoot stars) You should know your interest, self-motivation is one
of the single most important factors
23/4/19 p. 30
PhD Research
Read top 10 or 20 papers in the area Understand the basics, fundamental
problems, and open issues Think and read
Put all papers into perspective Start from a small yet concrete problem
Build you skill and confidence Discussions generates ideas
23/4/19 p. 31
Reading
Top conference or workshop first ACM Sigcomm, ACM Mobicom, IEEE Infocom IEEE ICNP, IWQoS, MobiHoc
Second tier conference only for reference IEEE Globecom, ICC
Avoid bad conferences Regional, and less reputable ones
Read journal papers only it has not been published else where, or when it contains more detailed and complete treatment
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PhD Research
Focus! Don’t over-estimate your ability Don’t diversify too much
Start with small idea(s), publish in an easy conference in the 2nd year
Working plan: target at 2 conferences (20 or less acceptance rate) and one journal paper per year (in 2-3 years)
The thesis is a collection of the papers So you need to have a focus!
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Research Topics
Theoretical vs. practical Can this be related to a real world
problem Engineering approach
It should have a clear boundary Focus on what can or/and can not be done
Don’t lose the bigger picture Tree and the forest How does it help to solve one or more
pieces in the bigger problem
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PhD Research System works
System work usually involves team efforts Building from scratch is a dangerous thing The prototype has to demonstrate significance in
that either this is a proof of a concept, or demonstrate the feasibility
Less than 5% chance being useful, yet worth the investment for technical break through
Theoretical works Theoretical work usually provides an elegant solution
to a generalized problem The significance can be greatly enhanced if practical
insight can be drawn
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Advisor/Mentor
Choosing an advisor could be the single most important factor for your research Understanding the general problem, the ability to
identify the significance and yet another
Personal and professional relationship Junior vs. senior, hands-on or hands-off Regular guidance vs. direction Independent and close collaboration Group or individual effort Time, efforts and experience
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You really need an Advisor/Mentor
Can a rabbit eat a dog, fox and wolf?
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You really need an Advisor/Mentor
Punch line
It really does not matter what the topic is, and what you are doing, all it matters is
who your advisor is
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Example I: My PhD research What you need is a jump start for confidence building
A. Ganz and B. Li “Performance of Packet Networks in Satellite Clusters,” IEEE Journal on Selected Areas in Communications, (10)6: 1012-1019, August 1992
Be objective, don’t lose the bigger picture The research topics are both important and not so important The research works in PhD study is simply a training process,
be realistic. Usually the most productive period for one’s career is withi
n the 5 years’ after one’s PhD
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Example II: My student
Jiangchuan Liu Who has written close to 20 top journal papers since 1999, la
rgely on video multicast Assistant Professor at Simon Fraser Univ., former with Chine
se Univ. of Hong Kong. Won the prestigious Hong Kong Young Scientist award in 200
3, given to one individual annually by Hong Kong Institute of Science (HKIS)
Sometime direction is all a student needs
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Collaborations leads to Productivity
Working with the right people Skill complementary Same interests
Working with smart people
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Frequency Reuse Factor,
If total of S channels available,
Each cell can be assigned k channel
Case III: Cellular Networks
NSk /
22 jijiN
N/1
1
2
4
5
6
7
Frequency Reuse Pattern for N=7
3
2
5
6
7
3
4
3
7
7
4
4
4
3
2
5
6
6
1
1
1
1
1
1
Number of cells per cluster:
If M clusters within the system, the total system capacity: MSMkNC
23/4/19 p. 42
Case III: Cellular Network
There were several fundamental problems in cellular network when moving to multi-service environment Bandwidth within a cell have to be shared Erlang assumption (Poisson arrival and exponentia
l sojourn time and exponential call duration time) fails due to data traffic
Gaussian approximation for a cell capacity fails given the cell is small …
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Case III: Cellular Network
Relaxing Erlang, by considering heavy tail long range dependency LRD) distribution, i.e., Pareto distribution Failed since 1997
23/4/19 p. 44
Case III: Cellular Network
Gaussian approximation Particle movement and diffusion equation S. Wu, K. Y. M. Wong and B. Li, “A Dynamic Call
Admission Policy with Precision QoS Guarantee Using Stochastic Control for Mobile Wireless Networks,” IEEE/ACM Transactions on Networking, (10)2: 257-271, April 2002.
23/4/19 p. 45
Summary
Working on hard and open problems Persistence pays off
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Summary
The idea has to be simple, this is a hard lessen we have learn
10 years of research on ATM are pretty much a waste
Internet POTS or PSTN
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Outline
What about research? How much does one have to learn? PhD research What is procedure of publications? How to write technical papers?
23/4/19 p. 48
Conference Paper
Start earlier for a conference submission Deadline is the best drive for making progress What make a good paper: content and writing! Clear, convincing, simple and good English
This is a never-ending optimization process, do this within the time and page limits
Review process 5/30 rule 5 minutes - Abstract, introduction, figure and
conclusion 30 minutes – understand 90% of the paper
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Journal Paper
A good conference paper (10%-25% acceptance rate) can be submitted to a journal, with 30% new results
Report more complete and focused results Give yourself a deadline Be patient with the long review and re-review At the earlier stage of one’s career, don’t quit
if asked for major revision But don’t do seemingly impossible
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What does a reviewer look for
New problem or new solution? Are the main results significant? Is the paper technically correct? Does the paper provide a fair assessment of its
strength and limitation? Is the paper clearly written, thus accessible to
general readers? Are the references adequate? Is the paper appropriate for conference/journal? …
23/4/19 p. 51
Outline
What about research? How much does one have to learn? PhD research What is procedure of publications? How to write technical papers?
23/4/19 p. 52
Writing
Writing is a process of self-clarification Habit of writing, notes, random thoughts
There are plenty of books teaching you how to write Imitation might be the best way to start
Writing is part of the work Writing can be difficult and painful for
all of us, there is no short cut, it improves along the process
23/4/19 p. 53
Writing
Iterative refinement, outlines – 3-5 times Start with existing work, introduction, your
own work, experiment Abstract and summary (many hours’ work) Revise many times, ask others to read
Lots of efforts for small improvement Is there a better way to say, a better word to use? Is the paper logically connected? What are the questions reviewers might have?
Never ending optimization subject to time and page limit
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Review Process
Low acceptance rate Reviewers are potential competitors
Convincing but less critical Reviewers are very busy
Try to make their job easier English is not our strength Don’t try your luck, it won’t work!
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Problem I
Reviewers have to understand me Only you know your work well, not
reviewers Make it easier to understand
Motivation and rationales Control the level of details Make connection throughout the paper Use examples, graph, flow chat whenever
needed Pose questions, and answer them
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Problem II
Formality leads to elegance I am good at math, formal is high class, I
have 20 definitions and 15 theorems Keep it simple, perhaps stupid Start with motivations and rationales Avoid unnecessary formality
23/4/19 p. 57
Problem III
I have 10 contributions Reviewers should see this is a masterpiece
Focus in the key One problem, one solution in a conference paper One problem, more complete solutions in a journal
paper Thorough and deep
Emphasize but not exaggerate your contributions Say it is “significant” only if it is, and justify it If it is the first time, say “This is, to the best of our
knowledge, the first time … “
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Problem IV
It is ok to be informal as long as understandable Technical writing is formal Avoid casual writing
“believe me, this is really a good work” Don’t use long sentences, break them
Flow and logic is much more important, proof reading does not help you with that
Top-down organization and outlining Use good papers as sample – imitate! Write down your mistakes and eliminate them
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Problem V
Reviewers are evil They reject paper so their papers can be accepted They reject my paper, so to steal my ideas
Reviewers are critical You have to be a good salesman to convince
them
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Closing Thoughts
Research needs creativity, patience, hard working, persistence
Writing is a self-improving process Understanding the process of publication, in
particular review process helps
KEYS Balance the search and re-development and
out-of-box thinking Working with smart people
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Closing Thoughts
We have done so much for networking! 10 years ago: IP vs. ATM Since then
QoS, network Calculi, intServ, diffServ, CNDs, DDoS, VoIP, SIP, multicast TPC, closed-loop control, measurement, LRD traffic, power laws, Streaming, WWW protocols, caching
23/4/19 p. 62
Closing Thoughts
Yet this conversation happened in a major research lab (NJ)
Q: given the traffic and network topology, how do we optimize the routes?
A1: “Uh ….”A2: “We don’t really think it that way … “A3: “We don’t know the traffic, we don’t know
the topology, the routers do not automatically adapt to traffic, and we don’t know how to optimize the route configuration. BUT, other than that, we are all set!”
23/4/19 p. 63
Closing Thoughts
Don’t believe anything you read, esp., those obviously correct ones!
Challenge the fundamental!
23/4/19 p. 64
Acknowledgement
Students, collaborators, and MSRA Charles X. Ling (Univ. of Western Ontario), Qiang Ya
ng (HKUST), Jim Kurose (UMass at Amherst)