Researchers are looking for ways to reduce
the high cost of internet data storage and retrieval in cloud computing.
Key points
- The search is on to cut the costs of data storage on web-based and remote
servers
- Savings for heavy users of cloud computing – science, government and
industry – are potentially huge
- Swinburne researchers have set out to change the way users manage remote
databanks
Researchers are looking for ways to reduce the high cost of internet data
storage and retrieval in cloud computing – running software and managing data on
a remote computer, rather than your own.
Social media such as Facebook
and Flickr are simple examples of cloud computing, but the drain on resources
from these doesn't compare to the volumes of high-end data generated by the
world’s research institutions, healthcare systems and
industries.
Government agencies such as the Australian Taxation Office,
Bureau of Statistics, and Treasury are examples of heavy users of cloud
computing services, and the costs to them and others are high and rising. A new,
more cost-effective model is needed for heavy users of cloud computing and this
is the task of a team at Swinburne University of Technology.
As Professor
Yun Yang from the Swinburne University Centre for Computing and Engineering
Software Systems (SUCCESS) explains, cloud computing offers almost unlimited
space for data storage and processing, but the current usage charges mean the
costs are expanding at the same near-limitless rate.
Savings to
be made“Users have to pay for data storage, computation and
data transfer for these pay-as-you-go services. Also, unnecessary data storage
means greater electricity consumption, it is less environmentally friendly,
lessening the benefits of using cloud computing.
“In his report to the
federal government, Sir Peter Gershon estimated $1 billion can be saved if the
Australian government develops a data centre strategy – the core for cloud
computing – for the next 15 years.”
Professor Yang, who is working with
Professor John Grundy and Dr Jinjun Chen, illustrates the issue facing cloud
computing when he notes that scientific fields such as astronomy, high-energy
physics, bioinformatics and medical imaging technology can generate gigabytes of
data per second.
Professor Grundy, director of SUCCESS, also points out
that a complication for the Swinburne team is that researchers store two kinds
of data: raw data and the intermediate data generated from processing this
initial data. Raw data must be securely stored because it cannot be
regenerated.
The main catch, Professor Grundy says, lies in storing
intermediate data, and this gets expensive. But if the user deletes all the
intermediate datasets and has to regenerate them later through further
computation, the costs can be even higher.
“The trade-off is going to be
between storage cost and computation cost. Finding this balance is complex, and
there are currently no decision-making tools to advise on whether to store or
delete intermediate datasets, and if to store, which ones,” Professor Grundy
says.
Cloud cost calculatorsWith funding from an
Australian Research Council Discovery Project Grant, the researchers have
developed two potential strategies to make cloud computing more
affordable.
In the first, they have developed a mathematical model that
lets users calculate the minimum storage cost. The formula factors in the size
of the initial datasets, the rates charged by the service provider and the
amount of intermediate data stored in the specified time. “The formula can be
used to find the best deals for storing data in the cloud,” Professor Yang
says.
The second proposal, the Intermediate Data-dependency Graph (IDG),
answers whether to spend on storage or computation for intermediate
datasets.
“IDG records how each intermediate dataset is generated from
the ones before it. It shows the generation relationships of the datasets.” Or
in other words, how A leads to B, then C, and then to D. “The (data centre)
strategy can then decide which ones to delete.”
If deleted intermediate
datasets need to be regenerated, the system wouldn’t have to start at the
original data. Instead, guided by the IDG, the system could find the nearest
predecessors of the datasets. If the process has been A, B, C, D and C is
removed, the model would revert back to B for computation, rather than A. “This
can save computation cost, time and electricity consumption,” Professor Grundy
says.
The researchers have been evaluating the two solutions in tandem by
simulating a pulsar survey used to crunch information from radio
telescopes.
“Searching for pulsars – rapidly spinning stars that beam
light – is a typical scientific application,” Professor Yang says. “It generates
vast amounts of data – typically at one gigabyte per second. That data will be
processed and may be reanalysed by astronomers all over the world for years to
come.
“We used the prices offered by Amazon cloud’s cost model for this
evaluation. For example, 15 cents per gigabyte per month for storage, and 10
cents per hour for computation.”
From one set of raw beam data collected
by the telescope, the pulsar application generated six intermediate datasets.
The model generated three different cost scenarios. The minimum cost for one
hour of observation data from the telescope and storing intermediate data for 30
days was $200; for storing no data and regenerating when needed, $1000; and for
storing all intermediate data, $390.
This gave the researchers options
for which data to keep, and which to delete. “We could delete the intermediate
datasets that were large in size but with lower generation expenses, and save
the ones that were costly to generate, even though small in size,” Professor
Yang says.
These are only a few of the solutions the researchers have
come up with so far. To cater to different sectors, the group is also working on
models that will allow users to determine the minimum cost on-the-fly, and as
frequently as they wish.
ফেইসবুকও প্রোফাইল পিকচারের আকার বড় করা শুরু করলো। কিছুদিন আগে গুগল প্লাস তাদের ডিজাইনে আমূল পরিবর্তন আনে। এতে গুগল প্লাসের প্রতিটি সেকশনেই পরিবর্তন আনা হয়, বড় করা হয় ছবির আকার এবং ব্যতিক্রম করা হয় প্রোফাইল ও স্ট্রিম। দেখা যাচ্ছে ফেইসবুকও সেই পথেই এগুচ্ছে। খবর দি নেক্সট ওয়েবের।
স্মার্টফোন এবং ইলেকট্রনিক্স সামগ্রী নির্মাতা প্রতিষ্ঠান স্যামসাং সম্প্রতি বিভিন্ন সংবাদমাধ্যমে আমন্ত্রণ পত্র পাঠানো শুরু করেছে। জানা গেছে, স্যামসাং গ্যালাক্সি সিরিজের পরবর্তী স্মার্টফোনের ঘোষণা দেয়া হবে মে মাসের ৩ তারিখে। খবর ম্যাশএবল-এর।
সামাজিক যোগাযোগের সাইট ফেইসবুক সম্প্রতি অফার নামের নতুন একটি সুবিধা চালু করছে যার মাধ্যমে বিভিন্ন কোম্পানি তাদের ফ্যানদের নিউজ ফিডে বিভিন্ন অফার দিতে পারবেন বিনামূল্যে। খবর মার্কেটিং ল্যান্ড ডটকমের।
সম্প্রতি হ্যাকার গ্রুপ অ্যানোনিমাস টুইটারে দাবি করেছে, দুই মাসের মধ্যে দ্বিতীয়বারের মতো তারা মার্কিন গোয়েন্দা সংস্থা সেন্ট্রাল ইন্টেলিজেন্স এজেন্সির ওয়েবসাইট অচল করে দিয়েছে। খবর দি নেক্সট ওয়েব-এর।
সম্প্রতি পেপাল ডকুসাইন নামের একটি প্রতিষ্ঠানের সঙ্গে কাজ করা শুরু করেছে, যার ফলে ব্যবসা সংক্রান্ত লেনদেনগুলো আরও সহজ, দ্রুত ও নিরাপদে সম্পন্ন করা যাবে। খবর ম্যাশএবল-এর।
সম্প্রতি তথ্য-প্রযুক্তি বিষয়ক ওয়েবসাইট টেকডার্ট জানিয়েছে, উইকিপিডিয়ার মোবাইল অ্যাপ্লিকেশনে থাকা গুগল ম্যাপস মুছে ফেলা হয়েছে। এর বদলে ওপেনস্ট্রিটম্যাপ নামে ওপেনসোর্স আরেকটি ম্যাপ যোগ করা হয়েছে।