This paper discusses research into the capacity dimensioning of Virtual Private Network (VPN) access links for elastic traffic, such as the Web or ftp. Assuming that the core-VPN network is provisioned with a sufficiently large capacity, managing the capacity of the VPN access link comes to sharing the bandwidth for the elastic traffic of the two bottlenecks, the ingress and egress access links. In the case of a single bottleneck with a limited capacity for access links, the processor-sharing model provides a simple formula for mean transfer time, but here, the value may be less than the actual transfer time because multiple flow may compete the bandwidth of both ingress and egress links. In contrast, max-min fair sharing provides an accurate sharing model which is similar to the TCP, but it is difficult to obtain a closed form for performance statistics. We propose a closed form approximation for a max-min fair sharing model, within a specific but realistic topology, through an investigation into the difference between the max-min and the processor sharing model. Using approximation, we calculate the capacity dimensioning of VPN access links.

Sensor nodes are prone to failure and have limited power capacity, so the evaluation of fault tolerance and the creation of technology for improved tolerance are among the most important issues for wireless sensor networks. The placement of sensor nodes is also important, since this affects the availability of nodes within sensing range of a target in a given location and of routes to the base station. However, there has been little research on the placement of sensor nodes. Furthermore, all research to date has been based on deterministic node placement, which is not suitable when a great many sensor nodes are to be placed over a large area. In such a situation, we require stochastic node placement, where the sensor-positions are in accord with a probability density function. In this paper, we examine how fault tolerance can be improved by stochastic node placement that produces scale-free characteristics, that is, where the degree of the nodes follows a power law.

Since the TCP is the transport protocol for most Internet applications, evaluation of TCP throughput is important. In this paper, we establish a framework of evaluating TCP throughput by simple measurement. TCP throughput is generally measured by sending TCP traffic and monitoring its arrival or using data from captured packets, neither of which suits our proposal because of heavy loads and lack of scalability. While there has been much research into the analytical modeling of TCP behavior, this has not been concerned with the relationship between modeling and measurement. We thus propose a lightweight method for the evaluation of TCP throughput by associating measurement with TCP modeling. Our proposal is free from the defects of conventional methods, since measurement is performed to obtain the input parameters required to calculate TCP throughput. Numerical examples show the proposed framework's effectiveness.

This paper evaluates the performance of TCP over ATM by simulation studies to clarify its applicability to high-speed WANs. We compared the performance of TCP over ABR with that of TCP over UBR, and TCP over UBR with Early Packet Discard (EPD). As for TCP over UBR, TCP has all responsibilities for end-to-end performance. In this case, cell loss at the ATM layer degrades TCP performance. Optimum tuning of TCP parameters may mitigate this degradation problem, but cannot solve it. Using EPD with UBR can fairly reduce useless transmission of corrupted packets and improve TCP performance, but still have the problem on fairness. As a result, TCP over ABR was proved to be the most effective as long as it suppressed cell loss. It was also proved that, if we want to extract best performance by TCP over ABR, we need to choose TCP parameters such as window size or timer granularity, so that ABR rate control does not interact with TCP window control and retransmission control.

This paper investigates Available Bit Rate (ABR) traffic control based on the Explicit Forward Congestion Indication (EFCI). A flow control mechanism is specified for ABR service to control the source rate. Resource Management (RM) cells are used to convey feedback. A source sends a forward RM cell for at least every N cells sent. At the destination, a forward RM cell turns around as a backward RM cell and returns to the source. A data cell has EFCI-bit in its header field. A network element sets EFCI-bit if it is congested. A destination indicates congestion status of networks by using RM cells based on the value of the EFCI-bit of the data cells. A one-bit feedback scheme is used by the ATM Forum. However, indication schemes have also been proposed which use explicit indication of source rate based both on values of the EFCI-bit of data cells and on other information contained in a forward RM cell. We evaluated explicit indication schemes as well as a one-bit scheme by simulation. Simulation study showed explicit cell rate indication gives superior performance than one-bit indication especially for long round trip distances. In this paper, we report the results with brief discussion.