The Internet is an extremely convenient network and has become one of the key infrastructures for daily life. However, it suffers from three serious problems; its structure does not suit traffic centralization, its power consumption is rapidly increasing, and its round-trip time (RTT) and delay jitter are large. This paper proposes an extremely energy efficient layer-3 network architecture for the future Internet. It combines the Service Cloud with the Cloud Router and application servers, with the Optical Aggregation Network realized by optical circuit switches, wavelength-converters, and wavelength-multiplexers/demultiplexers. User IP packets are aggregated and transferred through the Optical Aggregation Network to Cloud transparently. The proposed network scheme realizes a network structure well suited to traffic centralization, reduces the power consumption to 1/20-1/30 compared to the existing Internet, reduces the RTT and delay jitter due to its simplicity, and offers easy migration from the existing Internet.

This paper proposes the hierarchical cloud-router network (HCRN) to overcome the scalability limit in a multi-layer generalized multi-protocol label switching (GMPLS) network. We define a group of nodes as a virtual node, called the cloud-router (CR). A CR consists of several nodes or lower-level CRs. A CR is modeled as a multiple switching capability (SC) node when it includes more than one kind of SC, which is fiber SC, lambda SC, time-division multiplexing (TDM) SC, packet SC, even if there are no actual multiple switching capability nodes in the CR. The CR advertises its abstracted CR internal structure, which is abstracted link state information inside the CR. A large-scale, multi-layer network can then achieve scalability by advertising the CR internal structure throughout the whole network. In this scheme, the ends of a link connecting two CRs are defined as interfaces of the CRs. We adopt the CR internal cost scheme between CR interfaces to abstract the network. This CR internal cost is advertised outside the CR via the interfaces. Our performance evaluation has shown that HCRN can handle a larger number of nodes than a normal GMPLS network. It can also bear more frequent network topology changes than a normal GMPLS network.