We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

The Object Management Group's (OMG) Model Driven Architecture (MDA) strategy envisages a world where models play a more direct role in software production, being amenable to manipulation and transformation by machine. Model Driven Engineering (MDE) is wider in scope than MDA. MDE combines process and analysis with architecture. This article sets out a framework for model driven engineering, which can be used as a point of reference for activity in this area. It proposes an organisation of the modelling 'space' and how to locate models in that space. It discusses different kinds of mappings between models. It explains why process and architecture are tightly connected. It discusses the importance and nature of tools. It identifies the need for defining families of languages and transformations, and for developing techniques for generating/configuring tools from such definitions. It concludes with a call to align metamodelling with formal language engineering techniques.

Model Driven Engineering

/pdf/economics-of-natural-resources-and-the-environment-43k62iyyte.pdf

Economics of natural resources and the environment

https://bura.brunel.ac.uk/bitstream/2438/13152/4/Fulltext.pdf

Critical analysis of Big Data challenges and analytical methods

[서평]「Component Software」 - Beyond Object-Oriented Programming -

Performance evaluation of NoSQL big-data applications using multi-formalism models

We consider the problem of self-deployment and relocation in mobile wireless networks, where nodes are both sensors and actuators. We propose a unified, distributed algorithm that has the following features. During deployment, our algorithm yields a regular tessellation of the geographical area with a given node density, called monitoring configuration. Upon the occurrence of a physical phenomenon, network nodes relocate themselves so as to properly sample and control the event, while maintaining the network connectivity. Then, as soon as the event ends, all nodes return to the monitoring configuration. To achieve these goals, we use a virtual force-based strategy, which proves to be very effective even when compared to an optimal centralized solution.

A Distributed Sensor Relocatlon Scheme for Environmental Control

Fluid (or Hybrid) Petri Nets are Petri net based models with two classes of places: discrete places that carry a natural number of distinct objects (tokens), and fluid places that hold a positive amount of fluid, represented by a real number. With respect to previous formulations, the FSPN model presented in this paper, is augmented with a new primitive, called flush-out arc. A flush-out arc connects a fluid place to a timed transition, and has the effect of instantaneously emptying the fluid place when the transition fires. The paper discusses the modeling power of the augmented formalism, and shows how the dynamics of the underlying stochastic process can be analytically described by a set of integro-differential equations. A procedure is presented to automatically derive the solution equations from the model specifications. The whole methodology is illustrated by means of various examples.

/pdf/fluid-stochastic-petri-nets-augmented-with-flush-out-arcs-496nz69n4c.pdf

Fluid Stochastic Petri Nets Augmented with Flush-out Arcs: Modelling and Analysis

Modeling and analysing very large stochastic systems composed of interacting entities is a very challenging and complex task. The usual approach, relying on the generation of the whole state space, is bounded by the state space explosion, even if symmetry properties, often included in the model, allow to apply lumping techniques and building the overall model by means of tensor algebra operations. In this paper we resort to the mean field theory. The main idea of the mean field theory is to focus on one particular tagged entity and to replace all interactions with the other entities with an average or effective interaction. The reduction of a multibody problem into an effective one-body problem makes the solution easier while at the same time taking into account the contribution of an averaged interdependence of the whole system on the specific entity. We apply the mean field approach to very large systems of interacting continuous time Markov chains, in which the averaged interaction depends on the distribution of the entity population in each state. We report several examples of interacting Markovian queues, showing the potentialities of the proposed technique.

/pdf/analysis-of-large-scale-interacting-systems-by-mean-field-2veab4a0be.pdf

Marco Gribaudo

Papers

Performance evaluation of NoSQL big-data applications using multi-formalism models

A Distributed Sensor Relocatlon Scheme for Environmental Control

Fluid Stochastic Petri Nets Augmented with Flush-out Arcs: Modelling and Analysis

Analysis of Large Scale Interacting Systems by Mean Field Method

Exploiting mean field analysis to model performances of big data architectures