Distributed Resource Allocation: Generic Model and Solution Based on Constraint Programming and Multi-Agent System for Machine to Machine Services

Distributed Resource Allocation: Generic Model and Solution Based on Constraint Programming and Multi-Agent System for Machine to Machine Services

Kamal Moummadi, Rachida Abidar, Hicham Medromi
DOI: 10.4018/jmcmc.2012040104
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Abstract

The growth of technological capabilities of mobile devices, the evolution of wireless communication technologies, and the maturity of embedded systems contributed to expand the Machine to machine (M2M) concept. M2M refers to data communication between machines without human intervention. The objective of this paper is to present the grand schemes of a model to be used in an agricultural Decision support System. The authors start by explaining and justifying the need for a hybrid system that uses both Multi-Agent System (MAS) and Constraint Programming (CP) paradigms. Then, the authors propose an approach for Constraint Programming and Multi-Agent System mixing based on controller agent concept. The authors present concrete constraints and agents to be used in a distributed architecture based on the proposed approach for M2M services and agricultural decision support. The platform is built in Java using general interfaces of both MAS and Constraint Satisfaction Problem (CSP) platforms and the conception is made by agent UML (AUML).
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2. Multi-Agent Approach

2.1. Introduction

The Agent-Oriented (AO) approach gives the ability to concept flexible systems with complex and sophisticated behavior, by combining highly modular components. These components represent agents having autonomy and interaction characteristics.

What is an agent? The term agent has many definitions. According to Wooldridge (1997) an agent is a software system that is:

  • Situated in some environment,

  • Capable of autonomous actions in order to meet its objectives.

  • Capable of communicating with other agents.

From this definition we can say that an agent is an entity that can act and react in his environment and interact with other agents.

An agent is everything that can be viewed as perceiving its environment through sensors and acting upon that environment through effectors (Russell & Norvig, 1995).

Intelligent agents continuously perform three functions: perception of dynamic conditions in the environment; action to affect conditions in the environment; and reasoning to interpret perceptions, solve problems, draw inferences, and determine actions (Wassim, 2004).

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