Posts Tagged ‘Fog Computing’

A Foggy Edge, beyond the Clouds…

Thursday, February 14th, 2013 by Antonio Manzalini

Today there are plenty of open source software solutions that can be used to implement a fully open Cloud Computing environment; just to mention some of them: libcloud, OpenStack, NiftyName, Juju, appscale, SlapOS, buildout, supervisord, PyOCNI etc. Imagine using such solutions to create an ICT environment exploiting end-Users’ idle resources (instead of the servers in traditional data centers) for providing computing and storage services. This is Fog Computing at the Edge !

more-foggy-vancouverFog Computing is about extending the Cloud Computing paradigm up to the edge of the network, by using a sheer number of unused ICT resources. It is not just a new tech buzzword, but it is about the migration trend of processing power, storage capability and embedded communications towards the edge of the network, which means in the hands of the Users. Fog computing could be also about storage for disaster recovery.

This is going to become a reality today. Symform is an example of start-up offering disaster resilience as a “decentralized, distributed, virtual, and crowd-sourced” fog. Let’s see how it works. Some Symform’s Users act also as hosts by allocating some amount of their on-site unused storage for use by Symform: pricing is 15 cents per gigabyte per month but if they provide as much storage resource as twice the data they are uploading, then their fog storage is free. When a User uploads a file to Symform’s fog, the system replicates it for redundancy, shreds it into tiny pieces, encrypts each piece, and then distributes it to other Symform Users. The system splits each 64 megabyte block of data into 96 fragments; only 64 of those fragments are necessary to recreate the entire block.

One may wonder about the performance of Fog Computing. Well, this brings me back to folding@home, a crowdsourcing initiative about computing intensive simulations of protein folding and other types of molecular dynamics. Folding@home uses the idle processing resources of thousands of personal computers owned by volunteers. As of November 28, 2012, folding@home has 208,622 active CPU cores, 10,206 active GPUs, and 4,583 active PS3s, for a total of about 5 petaFlops! (a petaFlop is a quadrillion calculations – 1015 – per second). Titan, first supercomputer in the world, has reached today a speed of 17.59 petaFlops.

Just imagine the variety of ICT services that could be executed and provided by orchestrating the idle computing and storage local resources of millions of smart nodes at the edge…one may argue that not all types of services and applications can run entirely on the edge, however, there are several examples like disaster resilience, content aggregation and transformation, data collection and analytics, static data bases, and many others (even at lower OSI layers) which can benefit from the fog.

Emergence in the Edge ICT Fabric

Sunday, February 10th, 2013 by Antonio Manzalini

Fog Computing vision goes beyond Cloud Computing by arguing the use a sheer number of resources distributed at the edge of the network. Apparently another buzzword. On the other hand, today we are already witnessing a progressive migration of processing power, storage capability and embedded communications towards the edge of the network; this trend, coupled with devices miniaturization and costs reductions, will create the conditions whereby Users will literally “decide and drive”  future ICT networks and services. This will have big impacts. This floating “fog” of ICT resources at the edge will give rise to new biz models based on new forms of competition and cooperation between existing Providers, and new  ones entering the arena, including utilities, car manufacturers, consumers’ electronics, public administrations, communities, etc.

In these dynamical games we’ll see innovative proposals, rewarded directly by the market itself, which will be essential encouragement for further investments. So, ideally, in the edge ICT fabric it will be possible creating, programming, instantiating or migrating dynamically different types of virtual functionalities and services as well as alternatives of the same. No more ossified architectures. In other words sort of ephemeral networks of resources will plastically self-adapt to humans’ dynamics. And it shouldn’t be a surprise discovering that this follows the laws of emergence in “complex systems”!

Emergence of flocks of birds: each individual responds to local conditions with a similar rules set.

Emergence of flocks of birds: each individual responds to local conditions with a similar rules set.

Emergence is topic already acquiring a growing interest in social networks: there are interests in modeling and predicting the dynamics of groups of people, the viral diffusions of certain ideas or concepts, use of resources, or even the potential adoption of product and services.  Think about the the convergence of Internet and the social attitude of humans: beyond sites such as Facebook, LinkedIn, MySpace, Wikipedia, YouTube there is a broader process to form connections with others, build groups and to engage communications.  A political message, or a piece of news or a meme are examples of information that can spread from person to person, in an epidemic way. This can catch the attention of millions of people creating ephemeral human dynamics, made visible by on-line expressions.

 Modeling ICT social epidemics provides the opportunity to identify influential behaviors, or ways to predict, trigger or incentive mass adoptions of products or ICT services. Several mathematical approaches have been proposed for modeling these dynamics: a diffused idea is modeling the state of each person as a member of a lattice and updating it by using simple rules depending on the states of neighboring members. Each state could be represented by a set of variables such as cultural skill, preference, beliefs, etc. and each of them associated with a certain flipping energy, which is the cost of changing the state given its connection with other members, which are in other variables-states. At the end of the day, it’s about how environment conditions, or messages, will influence people and vice-versa how individuals influence each other and the environment.  In a next post I’ll provide some simulations examples.

 In summary, as in any complex system, also in the Edge ICT Fabric, it will a matter of taming complexity and extracting simplicity out of “local-to-global” dynamics.