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DGMA 2008
GRID ACCULTURATION
Zaharin Yusoff (Prof. Dr.)
President, Multimedia University
Eureka Building, USM, Penang
21st October 2008
A
University
Grid Acculturation
Where to begin?
• Parallel computing
• Supercomputing
• …..
• Distributed computing
• High-performance computing
• ….
• Grid computing
• Utility computing
• Cloud computing
(inc. Virtualisation)
• …….
Grid Acculturation – where to begin?
http://linux.sys-con.com/node/587717.... By: Michael Seehan Jul. 25, 2008 10:15 AM
We all know that the term “Cloud Computing” is relatively new to the Technology
buzz. But just how new is it? For starters, I ran a quick comparison of “Cloud
Computing,” “Grid Computing” and “Utility Computing”.
The term Grid Computing has been around for a while (even before Google Trends
tracking shows it). But as you can see from the graphic above, it is trending
downwards. Utility Computing has pretty much remained below the radar in
comparison. But, the newcomer Cloud Computing, which made its full entrance into
this trend analysis around 2007 is rapidly gaining momentum. 2008 seems to be a
pivotal time where it surpassed Grid Computing (and continues to grow).
Grid Acculturation – where to begin?
http://hothardware.com/News/Cloud_Computing_The_Future_Takes_Nebulous_Shape/
Monday, June 30, 2008 – by Dave Altavilla
…. In the final analysis, there's no question that Cloud Computing,
Grid Computing, Utility Computing or whatever else you'd like to
call it, is definitely the wave of the future for many applications
and usage models. Granted, the average power user or
enthusiast will likely still have a powerful desktop or notebook
system for many years to come….
http://blogs.wsj.com/biztech/2008/09/25/larry-ellisons-brilliant-anti-cloud-computing-rant/
September 25, 2008, 7:53 pm – Larry Ellison’s Brilliant Anti-Cloud Computing Rant
“The interesting thing about cloud computing is that we’ve redefined
cloud computing to include everything that we already do. I can’t
think of anything that isn’t cloud computing with all of these
announcements. The computer industry is the only industry that is
more fashion-driven than women’s fashion. Maybe I’m an idiot, but I
have no idea what anyone is talking about. What is it? It’s complete
gibberish. It’s insane. When is this idiocy going to stop? …”
Table of Contents
 Introduction
• Generalities (… naive…)
• At the School of Computer Sciences, USM
 Some Attempts at National Initiatives
• Centre for Computational Sciences
• 8th Malaysia Plan – 20012005
• 9th Malaysia Plan – 20062010
 Some Pertinent Questions
• Some Input & Questions
• Grid Acculturation
Introduction
Generalities
Some Terminologies
http://en.wikipedia.org/wiki/Grid_computing
Parallel computing is a form of computation in which many instructions are carried
out simultaneously, operating on the principle that large problems can often be
divided into smaller ones, which are then solved concurrently (‘in parallel’). There
are several different forms of parallel computing: bit-level parallelism, instructionlevel parallelism, data parallelism, and task parallelism ...
‘Distributed’ or ‘grid’ computing in general is a special type of parallel computing
which relies on complete computers (with onboard CPU, storage, power supply,
network interface, etc.) connected to a network (private, public or the Internet) by
a conventional network interface, such as ethernet. This is in contrast to the
traditional notion of a supercomputer, which has many processors connected by a
local high-speed computerbus …
What distinguishes grid computing from typical cluster computing systems is that
grids tend to be more loosely coupled, heterogeneous, and geographically
dispersed. Also, while a computing grid may be dedicated to a specialized
application, it is often constructed with the aid of general purpose grid software
libraries and middleware.
Grid Computing – Historical Perspective
The term Grid Computing originated in the early 1990s
as a metaphor for making computer power as easy to
access as an electric power grid in Ian Foster and Carl
Kesselmans seminal work, "The Grid: Blueprint for a
new computing infrastructure".
In Malaysia, grid computing also evolved from parallel
computing and distributed computing in the early nineties.
Along with these came application domains that need high
performance computing, such as computational sciences
(e.g. crystallography) and bioinformatics …
GRID COMPUTING
Using the resources of many computers in a network at the same
time, to solve a single problem (http://www.netnw.net.uk/Jargon_Explained/jargon.htm)
…. is a form of distributed computing whereby a
"super and virtual computer" is composed of a
cluster of networked, loosely-coupled computers,
acting in concert to perform very large tasks.
http://en.wikipedia.org/wiki/Grid_computing
The technology has been applied to computationally-intensive
scientific, mathematical, and academic problems through
volunteer computing, and it is used in commercial enterprises
for such diverse applications as drug discovery, economic
forecasting, seismic analysis, and back-office data processing
in support of e-commerce and web-services.
At the School of Computer Sciences,
USM
School of Computer Sciences, USM
1993: Parallel & Distributed Processing Research Group
 Parallel Computing (1992  1994)
• Parallel constructs,
• Parallelisation of sequential programs
 Distributed Computing (1993  1996)
1980s 
(UM, UKM, UTM, USM, …)
 Parallel computing
 Computational Science
 ……
• Distributed databases
• Distributed processing
 Grid Computing (1997  ..)
• Parallel numerical algorithms for message-passing
•
•
•
•
•
•
architectures
Cost Effective High Performance PC Cluster with Virtual
Shared Memory
Meta-computing Environment for Computational Sciences
e-Science Grid (back-end engine and grid infrastructure)
Knowledge Grid
Seeding Bioinformatics
….
Grid Intrusion &
Detection System
- AS
Resource Allocation
- CHY, FH & GCS
Resource Monitoring
- CHY, FH & GCS
Fault Tolerance (algorithm
level & grid level - RA, CHY
Parallel Iterative &
direct solvers
- RKS, NMA
Fast Cryptography
Protocols - AS
Parallelization,
Dependency, Aliases
- RKS, GCS
Distributed shared
Memory (replication
& consistency)
- RKS & MAO
Parallelising Access to Large
Databases (matching, indexing
R&D&(C) Workshop 28-30July 2003
and clustering) – NAR, RA, ZZ
E-Science Grid Framework
Applications
e-Science
Portal
Replica
Management
Service
User
Replica
Catalog
File
Transfer
Job Manager
Intrusion Detection
Service
Bill
Scheduler Specific
plug-in
Mobile
Agent
Resources
Account
Manager
Resource
Usage
Tracking
Agent
Directory Service
5/25/2017
R&D&(C) Workshop 28-30July 2003
14
Overall Architecture
User
Access
Visualization
Iterative Solver
Agent
e-Sciences Grid Portal
(Dynamic Information Services)
Processed Data
Resource
Allocation
Resource
Monitoring)
Authorized
Prediction
Resource Monitor
Event Publication
Information
Dispatch Agent
Mobile Agents
Facility
Invitation/Correction
Resources
Directory Service
Event Publication
Information
Platform
Type,
Operating
System,
CPU,
Memory,
Network,
File System,
Job Status
… Knowledge Grid
Current Scenario at USM
Math Tsunami
Modelling Group
School of
Computer
Sciences, USM
MBBS
CLUSTER
OTHER RESEARCH IN USM
Digital Content at
School of Arts
Geographical
Information
System at
School of Humanities
stealth
School of
Computer
Sciences,
USM
CEDEC
Aurora
CEDEC
Some Attempts at
National Initiatives
Proposal for a
National Centre for Computational Sciences
National Centre for Computational Sciences
2000: …. Quality Hotel
 Inter-university & interdisciplinary Collaboration
• About 80 researchers (UM, USM, UKM, UTM, …..)
• Computer Science, Chemistry, Biology, …
• ….
 Ministry of Science
• KSU
• Science Advisor
• ….
8th Malaysia Plan (ICT Sector)
– 20012005
RM8 – LAYERS
DELIVERY
SERVICES
PROCESSORS
KB
SERVICES
SERVICES
PROCESSORS
PROCESSORS
KB
KB
INFRASTRUCTURE
PROCESSORS
KB
RM8 – SERVICES
(inc. Processors & KBs)
ESTABLISHMENT
OFSERVICES
ENHANCEMENT OF
MSC FLAGSHIP
APPLICATIONS
SCIENCE,
ENGINEERING &
TECHNOLOGY (SET)
SERVICES
SERVICE
STANDARDS &
PROTOCOLS
SET
SERVICES
SMART
E-BUSINESS
• Architecture &
E-HEALTHCARE
EDUCATION
Software
Infrastructure
• Business
• Knowledge & Data
• Wellness Maintenance • System Software
Engineering
Acquisition
• Healthcare
& Tools
• Enablers for
• Computer-Assisted
Practitioner Portal
• Applications
E-Business
Education & Training • Healthcare Enterprise
• Sophisticated • Teaching-Learning
Modelling
Processors
Materials
• Socio• Business Process
Economic
• Networking of Educators
Engineering
Studies
• Student-Educator Consultation
• Personalised
• HCI Tools for
Information on • Personalised Lifetime Education Plan
E-Business
• Online Education and Open Learning
Education
9th Malaysia Plan (Grid Computing)
– 20062010
Grid Computing Domains
APPLICATIONS
SERVICE MANAGEMENT
•Managing Users & Applications
•Managing lower level technical components
•Utility grid management modules
•….
RESOURCE MONITORING
•Detecting faults
•Managing faults
•….
GRID DATA WAREHOUSE
•Grid Database
•Data Replication
•….
GRID SECURITY
•Component security
•Data security
•….
•Compute-Intensive
•Data Intensive
•On-Demand
•Collaborative
•…
RESOURCE ALLOCATION
•Service Aggregation
•Resource Aggregation
•Scheduler (load balancing)
•…
TOOLS & ENABLERS
•Tools for specific applications
•Tools for grid construction
•Data warehousing
•Grid Algorithms
•Mobile Agents & Software agents
•Grid Protocols
•…
GRID INFOSTRUCTURE
GRID INFRASTRUCTURE (incl. Networks)
Grid Computing Architecture
SET Services  compute intensive
(bioinformatics, pharmaceuticals, …)
Middleware Engineering
(e.g. aggregator)
…..
Knowledge Grid
(e.g. e-Science)
National Grid Utilities
(c.f. TNB, Jaring/TMNet )
Knowledge
Dissemination
Support
Computational
Resources
……
Users
Grid
Resources
Software
Industry  data intensive
(financial, administrative, …)
Human
Data
☺Scientists
☺Engineers
☺Researchers
Hardware
e.g. High
Performance
Cluster and etc.
Data Source
Molecular Health Care
Database Information
etc
Grid Computing Architecture
Individual
User
Company
Commercialisation
or
Service to Public
A Cluster Centre
is inevitable
Satellite
Center
others
Government
Main Center
for Grid Computing
Research Cluster
Satellite
Center
USM
MIMOS
Satellite
Center
Satellite
Satellite
Satellite
Center
Center
UTM
Center
UKM
UPM
UM
Grid Computing Projects
Technology Development
SERVICE MANAGEMENT
•Tokens & Metering – 2008
•Negotiator (Agent, AI, etc.) – 2008 – 2009
•Search & Optimization Data Set – 2007
•Service Resource Discovery/Retrieval – 2007 – 2008
•Service Resource Management – 2005 - 2006
•Accounting/Billing/Service Level Agreement – 2005- 2006
•Generic Gateway (Portal) – 2006 – 2007
•Grid Human Computer Interface – 2008 – 2009
•Policy Service Management – 2008 – 2009
•Provisioning (license management, etc) – 2008 – 2009
GRID SECURITY
•Intrusion & Prevention Detection – 2005 – 2006
•Fast Cryptography – 2006 - 2007
•Data Security – 2006 - 2007
•Identification & Authentication – 2005 -2006
•Authorisation & Policy – 2006 - 2007
GRID INFOSTRUCTURE
RESOURCE ALLOCATION
•Resource Aggregation – 2006 – 2007
•Service Aggregation – 2007 - 2008
•Scheduler, Meta-Scheduler, Load Balancer – 2006 - 2007
•Resource Reservation – 2007 - 2008
•Trader/Broker – 2007 - 2008
•National Data Centres – 2005
•Grid Database – 2006 - 2007
Data Replication – 2006 – 2007
•Grid Storage – 2006 - 2007
•Transaction Management – 2007 - 2008
•Dist. Backup & Recovery – 2005 - 2006
•Parallel Access to Databases – 2007 - 2008
•Content-Based Info Retrieval – 2007 - 2008
•Parallel Data Mining – 2008 - 2009
•Knowledge Engineering – 2008 - 2009
RESOURCE MONITORING
TOOLS & ENABLERS
•Fault Management/Tolerance – 2007 – 2008
•Discovery Protocol – 2008 - 2009
•Grid Monitoring Kit – 2006 - 2007
•Grid Sensor – 2005 – 2006
GRID INFRASTRUCTURE (incl. Networks)
•High Speed Grid (MYREN, IPv6) – 2005
•Mobile/Wireless Grid – 2006 – 2007
•Distributed Shared Memory – 2006 – 2007
•Parallel Dependencies, Aliases – 2006 – 2007
•Parallel Iterative &Direct Solvers – 2005 – 2006
•Mobile Agents & Software agents – 2006 – 2007
•Grid Protocols – 2009 – 2010
•Interconnection of Clusters – 2006 – 2007
•Algorithm Analysis – 2006 - 2007
•Search Algorithms (Drug Design) – 2006 – 2007
•Grid S’ware Dev Lib (Numerical, Graphics) – 2006 - 2007
•Connectivity/Comms (Master/Slave, P2P) – 2005 - 2006
•Cluster Node Management – 2006 – 2007
•Grid Simulator – 2005 – 2006
Roadmap – Technology Development
Generic Grid Portal
2010
2009
2008
2007
• ADVANCE
DISTRIBUTED
KNOWLEDGE BASE
• COLLABORATIVE
MULTIPLE
INTELLIGENT
SCHEDULER
• SCHEDULER WITH
MULTI-DIMENSION
PREDICTION
• AGGREGRATED
MACHINE’S BEHAVIOR
PREDICTOR
• HIGH
TRANSPARENCY
DISTRIBUTED
DATABASE
• HETEROGENOUS
DISTRIBUTED
DATABASE
• ADVANCE
INTRUSION
DETECTOR
• FAST
CRYPTOGRAPHY
2006
Middleware
Engineering Toolkits
• CRYPTOGRAPHY
• INTRUSION DETECTOR
• CLUSTER MACHINE
USAGE CLASSIFIER
• SINGLE MACHINE‘S
BEHAVIOR PREDICTOR
• SCHEDULER WITH
SINGLE DIMENSION
PREDICTION
• COMPUTE POWER
MARKET ii
• MULTI-MACHINE
USAGE CLASSIFIER
• HETEROGENOUS MULTI ALGORITHM SCHEDULER
National Grid Utility
• NON-DOMAIN SPECIFIC
INTELLIGENT NEGOTIATOR
• OPTIMIZED SERVICE
MATCHER WITH
CONTENT AWARENESS
• DOMAIN
ADMINISTRATOR
• Global Grid
• KNOWLEDGE FILTER
• SERVICE MATCHER
• COMPUTATIONAL ECONOMY
SCHEDULER
• Bioinformatics Grid
• SERVICE BROWSER
2008
• Financial Grid
• POLICY ENFORCER
• GRID VISUALISATOR
• GRID SERVICE TEMPLATE
• HIGH THROUGHPUT SCHEDULER
2009
• MULTI-PLATFORM
ONTOLOGIES AND DESCRIPTOR
• HETEROGENOUS
MONITORING SYSTEM
• HOMOGENEOUS MONITORING
SYSTEM
• National Grid
• INTELLIGENT
COORDINATOR AND
COLLABORATOR
• DOMAIN SPECIFIC MULTIISSUE INTELLIGENT
NEGOTIATOR.
• ONE STEP AHEAD PREDICTOR
2010
• Knowledge Grid
• MULTIPLE STEP
AHEAD PREDICTOR
• MULTI-CRITERIA SCHEDULER
• SINGLE MACHINE
USAGE CLASSIFIER
SET / Industry
Applications
2007
• DATASET FILTER &
OPTIMISER
• TOKEN MANAGER
• COMMUNICATION PROTOCOL
• DOMAIN SPECIFIC NEGOTIATOR
• Campus Grid
2006
Grid Computing Projects
Applications Development
•
•
•
•
•
•
•
Life Science Grid
– Bioinformatics
– Biotechnology
– Medical Grid (e.g. Virtual Anatomy, Virtual Surgery)
– Pharmaceuticals (e.g. Genetically Modified Gamat / Tongkat Ali)
– Agriculture Grid
– Environment
Computational Science Grid
– Physics (e.g. Nuclear Applications)
– Biology
– Chemistry (e.g. Liquid Crystals, Molecular Dynamics)
– Mathematics (e.g. Modeling)
Computational Engineering Grid
– Volumetric Rendering
Social Science Grid
– Culture, Heritage & Civilisation Grid
Commercial Grid
– Financial (e.g. Forecasting, Banking)
– Multimedia
– Oil & Gas
Education
– E-Learning
– Language
Disaster Mitigation
TARGETS
•Clustering
•Campus Grid
•National Grid
•Global Grid
•Grid Services Provider
•National Grid Utility
Grid Computing Projects
Capacity Development
Years
Human Resources Development
2005 Formation of Core Teams
- Management Team
- Technical Team
- Marketing Team
- Content Team
2007 Developing Curriculum for Grid Computing
2006 Developing Programmes for Post Graduate
2006 Strategic distribution of projects (hands on)
2006 Training/Certification
- Capacity Building of Users
- Training of Trainers
Years
Policy & Governance
Years
2005-2006 Central Governance Body
2005-2006 Formulation of Policies
- Grid
- Users
- Application
- Security
- Operation
- Database
- Collaboration
- IP
- Funding
- Metering/Billing
2006
Cluster Centre
Years
2005
2005
2005
2006
Type of Programmes
2005
a) Programme to Inculcate Culture of Sharing & Collaboration
b) Awareness Programme
2007
- seminar & Workshop (Twice a year)
- Conference
2008
- website
- Campaign/Roadshow
2007-2008
2005
2006
2006
2006
Marketing
- Market Survey
- Market Research
- Market Creation Programme
- International Benchmarking
2006
2006-2007 Competency Centre
2006
Awareness & Market Creation
Industrial Participation
- Technology
- Industry End Users
- Service Providers
Advisory Panel
2007
International Collaboration
2006
2006
2007
2007
2007
2007
Priority Application (Inter Agenda)
- BioInformatics
- Agriculture
- BioMedical
- BioTechnology
- Modelling
- Culture & Heritage
Towards National Utility Grid
National Agenda
Help Desk
Inspectorate (License)
Grid Service Providers
2008-2009 Application Service Providers
2006-2007 Grid of Grids
2007-2008 Computing Power Transmitting (metering)
2009
National Grid
2010
MyGrid
2010
International Grid
Some Pertinent Questions
Some Input & Questions
Main Points
Grid computing is much more than the deployment of hardware and
software resulting in a higher performing network. It also includes a
culture of sharing, of content as well as computational resources
Another point to look at is whether or not we are asking the
appropriate questions of the domain. The goals should not only be of
the operational type (such as on efficiency and performance), but
also of the functional type. Can there be:




a universal grid operating system,
a grid computing language,
formal criteria for usability, and
grid computing as a utility.
Such questions (or goals) would not only lead to the corresponding
R&D aspirations but will also open up discussions on very pertinent
issues that need to be resolved before any implementation.
Some Input (1/2)
There are a number of R&D areas and questions asked
in grid computing:
1) Traditionally, many researchers conduct investigation
on resource management, namely on the issues of
scalability, heterogeneity, efficiency, availability and
transparency.
 For high availability and adaptability, IBM would
term these as autonomic computing (for selfhealing or for auto-configuration).
 For transparency, the term cloud computing is
used when viewing resources as services.
2) Grid is viewed as a body or brawn, while an agent is
viewed as a brain. Researchers attempt to meet the
brain with the brawn, and many are talking about
multi-agent systems on the grid.
Some Input (2/2)
3) Grid computing can be viewed as a super virtual
computer, and researchers explore further on
virtualisation techniques such as VMware, Virtual
Organisation Management, etc.
4) In terms of application domains:
 Grid combines with pervasive computing to
integrate sensor networks, mobile devices, etc.
 Many grid researchers collaborate with
application domain experts to jointly develop grid
applications such as data grid, computational
grid, medical grid, e-science grid, eco-grid,
rendering farm, financial grid and etc.
SOME PERTINENT QUESTIONS (1/2)
Some questions asked many years ago are still valid…:
1) There should be a universal grid 'Operating System'
that makes the underlying infrastructure completely
transparent – such an infrastructure should be
heterogeneous in nature, in terms of hardware and
OS, and independent of geographical and logical
domains….. (c.f. Globus..)…
2) There should be a 'grid computing language' that rides
on the said OS with all the appropriate data structures
and programme constructs – such a language should
be independent of the infrastructure beneath the OS,
but its compiler/interpreter should be intelligent
enough to take full advantage of the configurations
available.
SOME PERTINENT QUESTIONS (2/2)
Some questions asked many years ago are still valid…:
….
3) There should be clear and formal measures/criteria to
determine whether a given problem/application is
best implemented in a grid environment or otherwise
... (c.f. coarse/fine grain size/ granularity, total cost of
ownership, …. But why not something simpler? e.g. 3phase power..)
4) Grid computing should be made a public utility (as in
electricity, water, etc.) -- and with this should come
the means for provision of its services, metering and
payment like any other public utility.
Grid Acculturation
Attempts at National Initiatives
There have been many attempts at making grid
computing a national initiative, where some failed
while some succeeded to a certain extent but have
arguably not met the original goals and intentions.
Perhaps one of the reasons for this limited
success is the lack of understanding of the
different roles of the players within and those
related to the domain ….
 Grid Acculturation
Grid Acculturation – Acculturate Who?
 OVERALL
• Speak the same language
• Win-win-win situation
 Researchers (& Students)
•
•
•
•
•
Fundamentals (incl. abstraction, …)
Synergy (related domains, critical mass, specialise, …)
Incrementality (core, processors, .. , applications, …)
Heterogeneity (multiple platforms, applications, …)
Educate (others & themselves … security, support, …)
 Industry
•
•
•
•
Less confusion (tone down the hype, …)
Longer term perspectives (patience wins, ..)
Fundamentals (e.g. platform dependence kills, …)
Business model
 Decision Makers (Government)
• No Big Bang theory (need to make informed decisions, ..)
• Technology is not cheap (but no need for Father Christmas, ..)
• We do not have to be technology consumers
THANK YOU
TERIMA KASIH
MERCI
ARIGATO
GRAZZIE
SHUKRIYA
GRACIAS
XIE-XIE NI
SPASIBA
KAMSIAH / MMKOI
DANKE
JABAI INAU
MANGE TAK
NGGO BUTE KABU
NAN DHRI
KOP KUN KAH
Back-Up Slides
Computer Networks
APPLICATIONS
SERVICE MANAGEMENT
•Multimedia Conferencing
•Distributed Systems
(e.g. Digital Libraries)
•…
•Tokens & Charging
•Negotiator
•….
NETWORK MONITORING
•Intelligent Network Monitoring
•Fault Tolerance
•Down-time Management
•….
COMMUNICATION MANAGEMENT
•Resource Aggregation
•Services Aggregation
•…
NETWORK SECURITY
•Intrusion Detection
•Prevention Systems
•Cryptography
•….
TOOLS & ENABLERS
•Network Operating Systems
•Compression/Decompression
•Streaming
•..
COMMUNICATION PROTOCOLS
•Wired Protocols (e.g. Fast Ethernet)
•Wireless Protocols (e.g. Satellite)
•Emerging Protocols (IPV6)
•..
SECURITY
SPECIFIC APPLICATION
ORIENTED
•Secure game-play
•e-Voting
•…
CONFIDENTIALITY
TRUST
ABUSE
Enterprise
•Digital Signature
•Public key
infrastructure
•….
• Enterprise level
security
• Agent-Server Security
• Radius/Kerberos
• Honeypot/Honeynet
• Man-in-the-Middle
(MIM)
• Dos/DDoS
• Virus/Worm, Spam
• Drone Armies
Applications
• Biometrics
• Smart Card
• One time password
• Database security
• Web-based Application
Security
• SSL, SSH
• Buffer Overflow
• Format String
• Client-side (XST,XSS)
• SQL Injection
• Phising
•Authentication
•Non-repudiation
•Integrity
•Tripwire
• Cryptography
(inc. encryption, braid)
• steganography
• Parallelising
crypto operations
• Video/Image security
Data
OS
(incl. Drivers &
Registeries,
H/W Interfaces)
•Network security
•Mobile IPv6 security
•Tunneling
•….
• IPSec
• VPN
• Firewall
• Intrusion Prevention
• Trusted OS
PROTECTION
Physical Network
ANALYSIS
• Forensics
• Enterprise Audit
• Enterprise PenTest
• Appl. Forensics
• Appl. Audit
• Appl. Pentest
• Packet Spoofing
• Cryptanalysis
• Brute Force
• ISN Predictions
• Cache Poisoning
• Data Forensics
• Log/Alert Analysis
• False Positive
Reduction
• Rootkit
• Trojan Horse
• OS Fingerprinting
• Sniffing
• Hijacking
• Re-routing
• OS Forensics
• OS PenTest
• Intrusion Detection
BIOINFORMATICS
Wet Lab Experimentation (DNA/Genome Sequencing)
SEQUENCE
ANALYSIS
DNA / Genome
String of Nucleic Acids (A,T,C,G)
•Sequence search
•Verification
•Cleansing
•‘Parsing
•Classification
•….
Amino Acids
(V,S,W, .. – 20)
LITERATURE
SEARCH
•Meaning-based
•Literature
Manager
•….
Proteins / Peptides
Junk DNA / UNKNOWN GENES (NEW !!)
STRUCTURAL
ANALYSIS
1&2D3D
TRANSFn
•….
•….
Protein/Peptide
Database
Virtual
Experimentations
Junk / New !!
Database
Virtual
Experimentations
Protein-Based
Applications
DNA-Based
Applications
Dissemination
•Modelling
•Visualisation
•Matching
•Comparisons
•Simulation
•Transformation/
Mutation
•….
Input from MMU
There is a lot of work on applications for the GRID -- medical, education,
etc. Here in MMU, Dr. Ho Sin Ban and his ROs are looking into some of
that.
Nithiapidary is looking into increasing the efficiency of programs that
have many small-scale jobs by grouping them together.
Nathar Shah is beginning a study on how to make writing GRID programs
less problematic by using Aspect-Oriented programming. There is also
research at other universities into making GRID easier to set up -- making
installers, security issues, how to promote participation and prevent
cheating, etc.
Sin Ban, Nithia, and Nathar, do you have anything to add beyond what I
wrote above?