File and data distribution can be easily classified as one of the basic uses of networks. With uses ranging from Short Message Service (SMS) to program updates, from micro-blogging to social networking, every network ...File and data distribution can be easily classified as one of the basic uses of networks. With uses ranging from Short Message Service (SMS) to program updates, from micro-blogging to social networking, every network today must support some type of file and data dissemination method. Infrastructure networks have already implemented these services using well known communication protocols. Ad hoc networks pose a greater challenge due to their sporadic network set-up. At a given time we do not know who is connected to the network, and whether the intended recipient of the data can be reached. In this paper we introduce Serval MeshMS, a protocol for ad hoc file and data distribution, enabling the diffusing of data through an ad hoc mesh network. It is based on a single-hop, store and disseminate opportunistic architecture, and has been shown to work over great distances. Preliminary implementations are encouraging, with surprising results achieved.展开更多
文摘File and data distribution can be easily classified as one of the basic uses of networks. With uses ranging from Short Message Service (SMS) to program updates, from micro-blogging to social networking, every network today must support some type of file and data dissemination method. Infrastructure networks have already implemented these services using well known communication protocols. Ad hoc networks pose a greater challenge due to their sporadic network set-up. At a given time we do not know who is connected to the network, and whether the intended recipient of the data can be reached. In this paper we introduce Serval MeshMS, a protocol for ad hoc file and data distribution, enabling the diffusing of data through an ad hoc mesh network. It is based on a single-hop, store and disseminate opportunistic architecture, and has been shown to work over great distances. Preliminary implementations are encouraging, with surprising results achieved.
