FogBrain

continuous reasoning for managing next-gen distributed applications

FogBrain methodology is fully described in the following article:

Stefano Forti, Antonio Brogi
Continuous Reasoning for Managing Next-Gen Distributed Applications,
ICLP 2020 (Technical Communications), EPTCS, vol. 325, pp. 164–177, 2020.

If you wish to reuse source code in this repo, please consider citing it.

Background & Prerequisites

FogBrain is written in Prolog. Prolog programs are finite sets of clauses of the form:

a :- b1, ... , bn.

stating that a holds when b1 and ... and bn holds, where n >= 0 and a, b1 ..., bn are atomic literals. Clauses with empty condition are also called facts. Prolog variables begin with upper-case letters, lists are denoted by square brackets, and negation by \+.

Before using FogBrain you need to install the latest stable release of SWI-Prolog.

QuickStart & Interactive Docs

All information on FogBrain can be found here, along with a quickstart example and interactive documentation on the current release.

Tutorial

To try FogBrain:

1. Download or clone this repository.

2. Open a terminal in the project folder and run swipl fogbrain.pl.

3. Inside the running program either run the query

   :- fogBrain(vrApp, P).

   The output will be a first placement for the application described in app.pl onto the infrastructure described in infra.pl. E.g.

   %7,955 inferences, 0.000 CPU in 0.006 seconds (0% CPU, Infinite Lips)
   P = [on(vrDriver, accesspoint9), on(sceneSelector, cabinetserver0), on(videoStorage, cloud0)]

4. Open the file infra.pl and change some of the links or nodes involved in the placement output at step 3. E.g.

    node(cloud0,[ubuntu, mySQL, gcc, make], inf, []). --> node(cloud0,[], inf, []).

5. Repeat step 3. The output will only compute a new placement for suffering services (i.e. mapped onto overloaded nodes, or relying upon saturated end-to-end links for interacting with other services) and require many less inferences with respect to computing the initial placement. E.g.

   2 ?- fogBrain(vrApp,P).
   % 387 inferences, 0.000 CPU in 0.000 seconds (0% CPU, Infinite Lips)  
   P = [on(videoStorage, cloud1), on(vrDriver, accesspoint9), on(sceneSelector, cabinetserver0)] 

In this example the new placement is computed by saving around 95% of inferences with respect to the first deployment.