1 research outputs found

    Routing in Large Scale tactical mobile ad hoc Networks

    Get PDF
    The current Transformation of the military networks adopts the MANET as a main component of the tactical domain. Indeed, a MANET is the right solution to enable highly mobile, highly reactive and quickly deployable tactical networks. Many applications such as the Situational Awareness rely on group communications, underlying the need for a multicast service within the tactical environment where the MANET is employed as a transit network. The purpose of this thesis is to study the setting up of an optimal multicast service within this tactical environment. We firstly focus on defining the protocol architecture to carry out within the tactical network paying particular attention to the MANET. This network is interconnected with different types of networks based on IP technologies and implementing potentially heterogeneous multicast protocols. The tactical MANET is supposed to be made of several hundred of mobile nodes, which implies that the scalability is crucial in the multicast protocol architecture choice. Since the concept of clustering proposes interesting scalability features, we consider that the MANET is a clustered network. Thereby, we define two multicast routing protocols adapted to the MANET: firstly STAMP that is in charge of the multicast communications within each cluster and secondly SAFIR that handles multicast flows between the clusters. These two protocols that can be implemented independently, act in concert to provide an efficient and scalable multicast service for the tactical MANET. Then, we study the interoperability of these multicast protocols employed within the MANET with those employed in the heterogeneous networks that it is interconnected with in order to guarantee end-to-end seamless multicast services to users. Finally, since the multicast protocols proposed in this thesis rely on underlying unicast routing protocols, we propose, in the last chapter, a scalable unicast routing protocol based on OLS
    corecore