The focus of this paper is to compare two popular end-to-end congestion control algorithm in the literature, namely, AIMD (additive increase/multiplicative decrease) and AIPD (additive increase/loss proportional decrease). We clarify the definitions of AIMD and AIPD algorithms, and compare them in various aspects such as convergence, steady state throughput, fairness characteristics, and the corresponding utility functions. The comparison is based on a simple mathematical analysis and a set of simulation results using the ns-2 simulator.

Corelite is a quality of service architecture that provides weighted max-min fairness for rate among flows in a network without maintaining any per-flow state in the core routers. There are three key mechanisms that work in concert to achieve the service model of Corelite: the introduction of markers in a packet flow by the edge routers to reflect the normalized rate of the flow; weighted fair marker feedback at the core routers upon incipient congestion detection; and linear increase/multiplicative decrease based rate adaptation of packet flows at the edge routers in response to marker feedback.

We describe a framework for video transmission over the Internet that features the coordinated operation of an application-layer video source coding algorithm and a transport-layer rate control mechanism. The proposed video coding scheme operates on a progressively encoded video stream and provides graceful resilience to network packet drops. The robustness is enabled through a generalized multiple description (MD) coding strategy, architectured as an adaptive array of packet-erasure correction codes. The video coding algorithm is matched to an efficient and reactive rate control mechanism that minimizes the fluctuation of rate and uses the profile of past losses to adjust the rate in a TCP-friendly manner. While the two constituent algorithms identified above are interesting in their own right, a key feature of this work is the integration of these algorithms in a simple framework that seeks to maximize the expected delivered video quality at the receiver through coordinated adaptation of the two components. We present simple simulation results to illustrate the utility of our approach.

Link-layer fairness models that have been proposed for wireline and packet cellular networks cannot be generalized for shared channel wireless networks because of the unique characteristics of the wireless channel, such as location-dependent contention, inherent conflict between optimizing channel utilization and achieving fairness, and the absence of any centralized control.

Linear increase/multiplicative decrease (LIMD) has typically been the congestion control paradigm of choice in the Internet. However, a major drawback of LIMD is that it reacts identically (and aggressively) to all packet losses, irrespective of the cause of loss. In this paper, we try to augment the basic LIMD congestion control with additional mechanisms to predict the cause of packet losses and react accordingly. To this end, we present the LIMD/H algorithm, which has the following features: (a) LIMD/H uses the "history" of packet losses and the evolution of transmission rate for a connection in order to distinguish between congestion-induced and non-congestion-induced packet losses; (b) LIMD/H reacts gently to non-congestion-induced losses and aggressively to congestion-induced losses, thereby achieving high efficiency, fairness, as well as quick reaction to the onset of congestion. We present an initial performance evaluation of LIMD/H using simulations and analysis.

No abstract available.

We present the BTLA (base tree link augmentation) multicast routing infrastructure for heterogeneous wireless/wireline networks. BTLA has two goals: (a) to reduce the latency and overhead of joins, leaves, and handoffs in regions that experience high group dynamics and mobility, and (b) to optimize the multicast tree for stable regions that do not experience frequent group dynamics. The BTLA consists of two components: (a) pre-computed minimum height spanning trees of the multicast network called base trees that are used to generate and update multicast trees with low latency and overhead under dynamic network conditions, and (b) link augmentation-based optimization of the multicast tree using additional links in the multicast network that are not a part of the base tree, in order to reduce the size of the multicast tree. The BTLA uses the base tree approach in dynamic regions and refines it with the link augmentation approach in stable regions. Initial performance evaluation shows that the BTLA is able to effectively support multicast communication involving both static and mobile hosts.

The main interest of previous researches for shape from shading was only on a Lambertian surface which consists of a diffuse reflectance surface. In practice, natural objects have hybrid reflectance, which limits the recovery of shape from intensity distribution. In this paper, we propose the method of determining shape using a neural network and diffuse illumination. The segmented region of sphere surface is used for a training set, which can be determined by shadow line and edge of surface. Diffuse illumination is used to avoid specular spike and highlight which usually cause many problems such as intensity disparities. The diffuse illumination method using flat paper allows us to reduce these phenomena with a simple scheme. The neural network and diffuse illumination method are useful for shape from shading, because it can be applied to objects of unknown reflectance properties, but it is applied only to Torrance-Sparrow style reflectance.

We propose the new method for analyzing the properties of surface reflectance and reconstructing the shape of an object using estimated reflectance parameters. We examine the hybrid reflectance surface which has a specular lobe and a diffuse component, which can be explained by the Torrance-Sparrow (1967) model. A sample sphere made of one material is used to estimate the reflectance properties by using the LMS algorithm. We can obtain the reference image which consists of the surface normal and brightness value using estimated reflectance parameters. The photometric matching method proposed is robust because it matches the object image with the reference image by considering its neighbour brightness distribution. It is expected that the proposed algorithm can be applied in vision inspection systems.

To recover 3-D shapes, a new algorithm which is based on the hybrid reflectance model and the indirect diffuse illumination method is presented. The photometric stereo method (PSM) is modified with the indirect diffuse illumination method (IDIM). We derive the surface reflectance function for a disk-type light source and make the 3-D reference table generated by applying the derived surface reflectance function to the hemisphere. The slant and tilt angle at each point of the intensity images which are the inputs for the algorithm is determined from the 3-D reference table. Finally, the 3-D shape of objects is recovered from the needle map.