Are mobile apps really apps ??

I'd say more than 50% of the apps that I use are not "self-sustaining" apps. They wont work without the internet. They are dumb apps that are driven by webservices / web data. I am really wondering if the mobile apps are really apps or just an extension of the web data into our mobiles..Many pundits claim that this is the age of mobility and that mobile computing / technologies will dominate over the traditional computing systems. In a way we all see that. We see a lot more smart mobile devices being used compared to 4 - 5 yrs ago. Sure! they are a revolution but I think the internet / web is a more powerful phenomenon than the mobile revolution. Instead of using browsers on a desktop / laptop to access data from the cloud, we (or atleast I) are using so called mobile apps to access the same cloud. I use facebook / twitter more from my iPhone than my laptop. Infact mobile computing is boosting up cloud computing.
Sometimes I am at the crossroads of technology wondering which bus (mobile / cloud /..) to take. As a lover of CS and a passionate programmer, I'd always want to wet my hands & feet with every major technology. Ofcourse I want to write mobile apps and ofcourse I want to get much more involved with the cloud but IMHO the cloud will last longer than the mobile. The cloud will be the base and power much more than the mobile world. So why is the cloud growing in power ??? simple coz it has the data. I am getting reminded of deep throat advising Bob Woodward "Follow the money"... For us its "Follow the data"

Amazon's EC2

Last week in the PLUG (Philly Linux User Group)meeting, we had Toby giving us an overview of Amazons Elastic Cloud Compute (EC2). It was quite interesting. EC2 aims to remove the headache of planning and maintaining a data center. You can get an instance (the minimum config is like 1.7 Ghz proc with 160GB drive and 2GB RAM) which is like a Xen VM. So we can install and configure this instance however we want and if we want to scale our app or whatever we have, we can just pay and add more processor or RAM or storage. This is kinda nice but Toby briefed about some of the problems as well. Like, they dont have persistent storage. If the instance crashes for some reason, you would lose the data that is in memory. Just few days ago, Amazon announced that it has brought in persistence to EC2. Also Ec2 is not good for hosting transaction oriented applications but would be good for some distributed app. Toby pointed that Ec2 with Hadoop would be a great combination. It was good to know about the pros and cons of EC2. I had one of my biggest doubts clarified. I was earlier improperly comparing EC2 with Google App Engine. Both of the support as a platform for cloud computing but in their own different ways. EC2 offers a machine instance called Amazon Machine Image (AMI) where you get to install the OS and other applications that you want and can run absolutely anything you want. Google App Engine is a platform to host web applications where the infrastructure is completely managed by Google

Parallelism the new / next big thing ??

Read an article which talks about how Parallel programming will become a central theme in the time to come. Due to the focus shift towards multi-core processors, there is a great need for parallel programmers and looks like only 1% of world-wide developer community has an idea on parallel programming. With news like these, I was excited to read about the launch of Parallel computing research centers at UIUC. MS and Intel backs this research center with $10 million in funding. All these events and facts makes it interesting to concentrate more on my current semester on Computer System Architecture where we have just started talking about multi-core processors.

Algorithms and Computing power

While talking about Algorithms, we mostly care about time and space complexity. we try to analyze a given algorithm by figuring out how fast it runs and how much time it takes. Depending on the time factor we classify the problems into one of the complexity classes (P, NP , NP-Complete or NP-Hard). We claim that algorithms which can solve problems, in polynomial time in the size of their inputs (ie P class of problems) are tractable. we worry a lot if a problem takes exponential time. We have lots of great brains working out to solve several hard problems in polynomial time or atleast get a feasible solution algorithm in polynomial time. Now when Moore's law is still holding good and when Intel and other chip makers envision tera computing, would the complexity theory go extinct ? I mean if our processors could crunch trillions of numbers and operations / sec, would we still classify problems on polynomial time ? Agreed that we cant take growth in processing power for granted but I am sure that advancements in computing power will greatly influence the way we define, analyze and solve problems.