This paper proposes a traffic-adaptive dynamic routing method, which we have named RAG, for connectionless packet networks. Conventional traffic control methods discard the packets which cause congestion. Furthermore, conventional routing methods propagate control messages all over the network for gathering global topology information, and this causes more congestion. In contrast, RAG estimates traffic conditions all over a network without any communication between nodes and makes the best use of free links so that packets make detours to avoid congestive sites. RAG adopts distributed control based on game theory (non-communication, non-zero-sum, two-person). With RAG, nodes play a packet-forwarding game without any communication with each other, and each node controls ordering and routing of the forwarding packets based on the node's individual payoff table which is dynamically reconstructed by observation of surrounding nodes. Nodes cooperate with each other, except for punishment for disloyalty. Repetition of these local operations in nodes aims at the emergence of the gradual network-global traffic balancing. The results of experiments in comparison with the conventional shortest path first (SPF) routing method show that the throughput is about 1.58 times higher with the new method.

We extend the Rabin cryptosystem to the Eisenstein and Gauss fields. Methods for constructing the complete representation class and modulo operation of the ideal are presented. Based on these, we describe the methods of encryption and decryption. This proposed cryptosystem is shown to be as intractable as factorization, and recently presented low exponent attacks do not work against it.

As network services become more diverse and powerful, service applications that perform such services are acquiring an ever-larger amount of complicated and changeable relationships. We present a network dependence graph (NDG) that captures both data and control flow relationships between components of service applications that work collaboratively. This graph is constructed based on analysis of both the behavior of each of the service applications and their configuration, which describes the device names they refer to, and allows network slicing to be implemented as a simple graph traversal. Network slicing is the extraction of necessary and minimum service components that may affect the execution of a specified service application; it helps a network manager to find the location of service faults lurking somewhere in the network. We also present a method for locating faults that uses network slicing and a system based on this method.

We show that under some conditions an attacker can break the public-key cryptosystem proposed by J. Schwenk and J. Eisfeld at Eurocrypt '96 which is based on the difficulty of factoring over the ring Z/nZ [x], even though its security is as intractable as the difficulty of factoring a rational integer. We apply attacks previously reported against RSA-type cryptosystems with a low exponent to the Schwenk-Eisfeld cryptosystem and show a method of breaking the Schwenk-Eisfeld signature with a low exponent.

Analysing and modeling of traffic play a vital role in designing and controlling of networks effectively. To construct a practical traffic model that can be used for various networks, it is necessary to characterize aggregated traffic and user traffic. This paper investigates these characteristics and their relationship. Our analyses are based on a huge number of packet traces from five different networks on the Internet. We found that: (1) marginal distributions of aggregated traffic fluctuations follow positively skewed (non-Gaussian) distributions, which leads to the existence of "spikes", where spikes correspond to an extremely large value of momentary throughput, (2) the amount of user traffic in a unit of time has a wide range of variability, and (3) flows within spikes are more likely to be "elephant flows", where an elephant flow is an IP flow with a high volume of traffic. These findings are useful in constructing a practical and realistic Internet traffic model.