Model for autonomous agents in machine-to-machine navigation networks

Machine-to-machine (M2M) is an evolving architecture and tends to provide enormous services through the swarm presence of the networked devices. Localization is one of those services. Previous localization techniques require complex computation that is not suitable and affordable in such architecture. Moreover, integrating intelligent multiagents on these ubiquitous devices makes the network more independent and reactive requiring for a less complex localization model. This paper reviews the present localization techniques and discusses their infeasibility for M2M communication while proposing a mathematical model that is derived from Anderson model for the distributed structure of machine-type-communication network involving autonomous agents. This paper has made an attempt to use the property of Anderson model that structures the distributed objects. This paper also classifies autonomous agents according to their functionalities in a navigational network. Recently, Anderson model have been customized for implication of optical communication; in this paper, the proposed mathematical model involves intelligent agents for localization that aim to reduce complexity of positioning computations for nodes having restricted computational resources and battery life, which are the main characteristics of M2M communication.