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### Research and Publications:A Personal Perspective

OutlineOutline

Bo Li

Hong Kong University of Science and Technology

Microsoft Research Asia

Outline

- What about research?
- How much does one have to learn?
- PhD research
- What is procedure of publications?
- How to write technical papers?

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

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?
- …

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

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 … “

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

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!

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?

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?

Case I: Adaptive Video Multicast

- The need for multicast - efficiency
- Multiple-unicast Multicast
- Fundamental problem: users’ heterogeneity and network dynamics

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

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 mismatchbetween the fixed sending rate and the dynamic and heterogeneous rate requirement from receivers

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)

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.

Summary

- Identify a general category of problems
- The idea should be intuitively simple
- Publications can be “easier”

Outline

- What about research?
- How much does one have to learn?
- PhD research
- What is procedure of publications?
- How to write technical papers?

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?

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

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

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

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

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

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

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

Summary

- Finding a problem is more important, and difficult than solving a problem
- You need out-of-box thinking

Outline

- What about research?
- How much does one have to learn?
- PhD research
- What is procedure of publications?
- How to write technical papers?

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

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

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

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!

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

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

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

You really need an Advisor/Mentor

- Can a rabbit eat a dog, fox and wolf?

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

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 within the 5 years’ after one’s PhD

Example II: My student

- Jiangchuan Liu
- Who has written close to 20 top journal papers since 1999, largely on video multicast
- Assistant Professor at Simon Fraser Univ., former with Chinese Univ. of Hong Kong.
- Won the prestigious Hong Kong Young Scientist award in 2003, given to one individual annually by Hong Kong Institute of Science (HKIS)
- Sometime direction is all a student needs

Collaborations leads to Productivity

- Working with the right people
- Skill complementary
- Same interests
- Working with smart people

Case III: Cellular Networks

7

3

1

6

4

1

4

5

5

2

7

7

3

1

3

1

6

6

4

1

4

5

2

2

7

1

3

1

6

4

Frequency Reuse Pattern for N=7

Number of cells per cluster:

Frequency Reuse Factor,

If total of S channels available,

Each cell can be assigned k channel

If M clusters within the system, the total system capacity:

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 exponential sojourn time and exponential call duration time) fails due to data traffic
- Gaussian approximation for a cell capacity fails given the cell is small …

Case III: Cellular Network

- Relaxing Erlang, by considering heavy tail long range dependency LRD) distribution, i.e., Pareto distribution
- Failed since 1997

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.

Summary

- Working on hard and open problems
- Persistence pays off

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

- What about research?
- How much does one have to learn?
- PhD research
- What is procedure of publications?
- How to write technical papers?

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

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

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?
- …

- What about research?
- How much does one have to learn?
- PhD research
- What is procedure of publications?
- How to write technical papers?

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

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

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!

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

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

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 … “

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

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

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

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

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!”

Closing Thoughts

- Don’t believe anything you read, esp., those obviously correct ones!
- Challenge the fundamental!

Acknowledgement

- Students, collaborators, and MSRA
- Charles X. Ling (Univ. of Western Ontario), Qiang Yang (HKUST), Jim Kurose (UMass at Amherst)

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