I think Cloud computing and big data are the future research when it comes to distributed computing. Size of data are becoming increasingly bigger and bigger, also storage facilities are becoming a huge concern. This is where Cloud comes in, to help for easy storage and accessibility. Although both research areas are making waves at the moment and will surley be around for the next - say 5 years to come.

Internet of Things is the future buzzword

Mobile cloud computing is going to be a new era of research , there are many challenges with mobile and cloud's services compatibility. so lots of work is expected in near future.

@Rishabh, other than accessing services through mobile (as a access medium) from Cloud, in what way 'Mobile Cloud Computing' is going to differ from Cloud Computing? Kindly clarify...

Dear Madhan ,

There are some specific applications where mobile cloud computing needed:

Image processing, Natural language processing, Sharing GPS/Internet data, Sensor data applications, Mobile Commerce, Mobile Learning, Mobile Healthcare , Mobile Gaming

Some other Practical Applications like : Cloud Mobile Desktop, Multimedia search, Social networking, Keyword-based Searching ,Voice-based Searching ,Tag-based Searching

There are existing challenges with mobile cloud computing , those are basically two types:

A: challenges with Cloud computing:

Absence of Standards

Limited scalability

Unreliable availability of a service:

Service provider lock-in

Unable to deployment service over multiple CCSPs:

B: Challenges with mobile:

Loss of connection, Bandwidth/Latency, Limited resources, Division of application services

Although there are some existing solution and some other solutions are evolving , hope , you will understand better now .

Regards,

Rishabh

Can a data be classified as Small data, Big data, Bigger data, and Biggest data?

If so, how? If not, why?

Then what is a small data?

Interesting to read the comments. Here are some opinions. Cloud to a large extent is only a buzzword, given that most of the cloud offerings do not do much on elasticity. It has become synonymous with web, for many people. The use of virtualisation to provide elasticity is a powerful new step. There is nothing much else in cloud. Mobility has two aspects -- the mobile communication issues and mobiles as application front-ends. The change brought up by mobiity is that you can access things from anywhere, since by definition, mobiles are portable. With mobile phones, tablets and laptops almost converging to the point of indistinguishability, it brings up reliable communication as a challenge. Thus mobile+cloud is a major game changer -- since it fades away the notion of a desktop or laptop, the notion of compute servers and data servers, and simplifies the access mechanism for use by a wider segment of people. E.g. how many people would use, unguided, a desktop computer to perform some work like booking a ticket, compared to a mobile.

Big data is a different animal altogether -- not clear why that is put into this. Big data, as Stonebraker says raises issues when the data volume is very high (wont fit into main memory, or a single system), has high variety (no more RDBMS and SQL), or high velocity (handling the flow of data in real time, when the flow is high). This is an emerging area of enhancing technologies for dealing with these phenomena. It is not going to concern everyone.

Does a big datum has velocity or speed? How you define its direction? How can we calculate acceleration of a big-datum? Is it a big-datum (singular)or big-data (plural)?

It seems British people have not given only Independence (freedom) to the world from their rules, It seems their mother language English is also getting freedom day-by-day. For example, see here difference between a datum and data:

http://public.wsu.edu/~brians/errors/data.html

I was afraid that I used "a data" instead of "a datum" in my previous question!!

I think Big data would be in focus of future research. As every 1.2 year size of data doubling; managing this data, fast access, security concern kind of issues will remain in trends of research fields!

I think Big data will have a bright future. People are generating more and more data than ever before, maybe up to 50PB in 2015, This will lead to many actual problems. For example, how to storage, how to manage, how to search some items efficiently, how to find the relations between some special data(e.g., mobile social network),, All these fields need more innovations. New science theories and technologies will be invented to meet the challenges.

Mobility is becoming more and more important. Moblie devices will replace the computer in our daily life.

No one is dealing with or need to deal with all the data that is generated in the world. For any given problem, you need to deal with associated data. True, this can be large. But saying so much data in the world does not justify the big-data trend. Also if the data is not used substantially, the challenges are only limited to storage space. But if used heavily, then many other issues pop up.

It is a good time to write a book on Big-Data and sell it. Who will read it? How will it benefit our-society, research, and science? It will be next issue. Although libraries are already full of books, and no way to maintain those libraries especially in countries like India, but still there could be some space found in a couple of libraries to keep Big-Books on Big-Bogus data. Many libraries stopped buying hard copies of journals. Many top-most journals are also stopped by many libraries. Not many libraries are maintained from painting, updating new furniture, and make other comfort to readers. If am an author of such a book, I will give a title or sub-title: Big-Bob with Big-Data.

My doctoral works aims developing a cloud based distributed data mining architecture for Mobile Business Intelligence. Conventional algorithms doesn't fit for the Mobile BI. Generally Data Mining algorithms consumes lots of memory in generating data mining models and that will not fit in Mobile Environment.

If anyone is working on the same field, please let me know.

@Ganesdh: These proceedings are a "Big-Business", much more bigger than Bib-Data. You can see Proceedings are on every topic, not only on Big-Data!

You can work on Cloud Computing! What are computing there? Every week one big-truck comes on my door to pickup garbage bin. Some people also collect a few things from those garbage trucks, where they dump, and they use to recycle. A big-data is same as a truck full of garbage, and we also need "Statistical - Janitor/ Janitress" to clean big-data. I am not against such jobs. I feel that some big-data could be useful, and can be used as a recycle machine! For example, from big-data, I found Mr. John is buying a packet of cigarette every week. I am doing a survey to estimate the proportion of smokers in a village/city. John is selected in my sample, and I asked to John in a survey question: Are you smoker? John replied, "No." John had a fear of increasing his insurance by a health-company. Can big-data help me now? May or may not be. I asked another question to John that you are buying a packet of cigarettes every week. John replied, "I am buying for my wife, not for me!!" Now my question: Can I get such information from big-data? If so, then big-data could be useful after cleaning it for a specific purpose.

Just now

I think Cloud computing and big data are the future research when it comes to distributed computing. Size of data are becoming increasingly bigger and bigger, also storage facilities are becoming a huge concern. This is where Cloud comes in, to help for easy storage and accessibility. Although both research areas are making waves at the moment and will surley be around for the next - say 5 years to come.

@Uchechukwu: Storatge facilities are also becoming bigger and bigger. I feel people should work more on increasing storage facilities. May be 3-D jump-drive or pen-drive. 20 years ago, there was no CD, no DVD or Jump-drive avaible to a lay-man. We were using DOS commands. How many new kids know now about DOS?

Please see my round table discussion in August 2013 at Montreal, Canada:

http://www.amstat.org/meetings/jsm/2013/onlineprogram/AbstractDetails.cfm?abstractid=309557

Sathyan: "cloud based distributed data mining architecture for Mobile Business Intelligence" -- lot of good buzz words. Can you be specific on what this means? Using mobile is often as front end to the application (more so, since you are talking of cloud based, distributed, etc). The actual mining, etc will happen in the cloud -- in the servers lying elsewhere. So, mobile memory or compute power is not an issue at all. What does mobile BI mean, other than running the application through your mobile? Curious to know your rationale for the topic and your focus...

Hello Sasi,

1) The Data Mining models are so big that can't fit in Mobile Memory Infrastructure. For instance Decision Tree Classification models doesn't fit in Mobile Memory. How do you optimize these models to fit into the mobile infrastructure and also the network bandwidth. Data Mining algorithms are time consuming process, complicated user interaction, how do we achieve through Mobile? Can we automate the whole data mining process, for instance "customer segmentation application", needs lots of undivided user attention to orchestrate the whole process. The normal desktop data mining algorithsm will not fit the same for mobile environment, there are unique challenges that towards building a new generation of distributed data mining algorithms.

2) The other thing is to how to enable real time data mining through Mobile.

I agree to Amandeep Sidhu's point of view...

It depends according to the uses and application of them to be able to answer this question correctly, because all of those having several pons & cons. Thus, Why you don't say the future of research is the combination between all of them.