Towards a Robust and Scalable Semantic Service Discovery Scheme for Mobile Ad hoc Network

Abstract

Mobile Ad hoc Networks (MANET) are characterized as an infrastructure-less communication networks formed among a set of stranger nodes. Service Discovery is a challenging problem in such networks due to their non-deterministic and improvised nature. This manuscript addresses two main issues related to service discovery in MANET i.e. consistency management and knowledge representation. Consistency management i.e. the problem of maintaining a coherent view of the services in the network is a taxing job due to the sharp variations in the service availability information in MANET. Similarly, the lack of a standard mechanism for representation of data and resources on the network engenders syntactic and semantic interoperability issues during discovery of services. The use of a colossal schema to describe the services can resolve the issue of noninteroperability, but this approach is certainly not viable because of the limited capabilities of nodes. In view of these challenges, this paper presents a robust and scalable network layer semantic service discovery scheme. A network layer service discovery scheme is presented that finds out the requested service jointly with the corresponding route to the provider of service. For ensuring the robustness of the process, a network layer consistency management scheme is also proposed that maintains the valid state of the services by exploiting the vigilance of network layer. To solve the knowledge representation issue, we recommend a scalable multi-tiered approach based on a general purpose ontology called Software Ontology for Ad hoc and Vehicular Network Applications (SLAVE). The multi-tiered approach keeps a portion of global schema at individual nodes of the network and advocates progressive growth of schema information. The proposed scheme has been simulated in JIST/SWANS simulator. The simulation results assert the robustness and scalability of the consistency manager and knowledge representation scheme respectively.