The provision of advanced computational services within networks is rapidly becoming both feasible and economical. As computational services become popular, it is important to have effective methods for configuring application sessions so that they use resources efficiently. In this paper, we discuss the problem of configuring application sessions that require intermediate processing. The problem was introduced in an earlier paper, where we showed how to optimally configure sessions in programmable networks by reducing the session configuration problem to the problem of finding a shortest path in a special graph constructed for the particular problem. This layered graph method is quite flexible and can handle a variety of specific session configuration problems. However, it does not explicitly model limits on link bandwidth or processing capacity. In this paper, we show that the optimal session configuration problem is NP-hard when capacity is constrained. Nevertheless, we have found efficient heuristics for which the network performance closely approximates the performance that can be achieved with optimal session configurations.

Developments toward ubiquitous and pervasive computing have lead to application scenarios where a large number of sensors and computing devices are connected to the network. These devices might constantly send status information via multicast to a number of applications or users. One big challenge in this environment is the amount of data traffic generated by such sensors, which depends on the size of the data, the transmission frequency, and the number of senders and receivers. However, for certain applications it is sufficient to receive less accurate, aggregated data from a group of sources. This leads to the possibility of using programmable routers to perform such data aggregation inside the network. While the basic algorithm for data merging has been described in literature, we address how a large number of sources can be organized in a hierarchical structure to allow multiple users to get a view of all sensors at different levels of aggregation. With the control information that is provided by an aggregating node, the user can traverse the aggregation tree by joining different multicast sessions that transmit different levels of detail. This provides a novel communication paradigm that reduces the network overhead from continuously transmitting sources and organizes data in a way that it is useful to receivers. We provide two detailed example scenarios: A battlefield information system, which aggregates geographic location data of units, and a conferencing application, which aggregates audio data. We describe the aggregation algorithm that is used and analyze its effect on delay and jitter of periodic transmissions by the sources. We describe the hierarchical control structure that provides multiple levels of aggregation and how real-time transport protocol (RTP) can be used to implement it. The performance of the proposed scheme is evaluated with measurements that were done on an implementation of the audio aggregation application.

The provision of advanced computational services within networks is rapidly becoming both feasible and economical. We present a general approach to the problem of configuring application sessions that require intermediate processing by showing how the session configuration problem can be transformed to a conventional shortest path problem for unicast sessions or to a conventional Steiner tree problem for multicast sessions. We show, through a series of examples, that the method can be applied to a wide variety of different situations.

Video distribution over the Internet poses many challenges. Due to the best-effort nature of today's public data networks, end system applications cannot rely on either bandwidth or delay guarantees. We designed and implemented a prototype of a multicast video distribution architecture involving knowledgeable active routers, a scalable video codec based on the wavelet transformation, and a high-performance video scaling algorithm implemented as a router plug-in. The plug-in scales the video with an average overhead of only 22 /spl mu/s per video datagram and is installed on-the-fly on the routers after the sender starts transmitting video for the first time. Through experiments on our test network, we show that we can dramatically improve the video quality on the receivers (up to 15 dB PSNR) by scaling the video on the routers to almost any target bandwidth. The target bandwidth is evaluated by the router solely based on monitoring of the load situation of the router's downstream links and can be adjusted within 50 ms.