27985449
Equilibria of a class of transport equations arising in congestion control
This paper studies a class of transport equations arising from stochastic models in congestion control. This class contains two cases of loss models as particular cases: the rate-independent case where the packet loss rate is independent of the throughput of the flow and the rate-dependent case where it depends on it. This class of equations covers both the case of persistent and of non-persistent flows. For the first time, we give a direct proof of the fact that there is a unique density solving the associated differential equation. This density and its mean value are provided as closed form expressions.
17794843
TCP throughput analysis under transmission error and congestion losses
This paper analyzes the performance of a large population of long lived TCP flows experiencing random packet losses due to both random transmission errors and congestion created by the sharing of a common tail drop bottleneck router. We propose a natural and simple model for the joint throughput evolution of the set of TCP sessions under such a mix of losses. For the case of Poisson transmission errors, we show that the asymptotic model where the population tends to infinity leads to a well defined and tractable dynamical system. In particular, we get the mean value of the throughput of each session as a function of the transmission error rate and the synchronization rate in the bottleneck router. The large population asymptotic model has two interesting and non-intuitive properties: 1) there exists a positive threshold (given in closed form) on the transmission error rate above which there are no congestion losses at all in steady state; 2) below this threshold, the mean throughput of each flow is an increasing function of the transmission error rate, so that the maximum mean value is in fact achieved when the transmission error rate is equal to this threshold. The finite population model and models based on other classes of point processes are also studied. In particular, a sufficient condition is obtained for the existence of congestion times in the case of arbitrary transmission error point processes.
9243298
Analysis of the competition between wired, DSL and wireless users in an access network
This paper analyzes the performance of a large population composed of several classes of long lived TCP flows experiencing packet losses due to random transmission errors and to congestion created by the sharing of a common tail-drop or RED bottleneck router. Each class has a different transmission error rate. This setting is used to analyze the competition between wired and wireless users in an access network, where one class (the wired class) has no or small (like BER in DSL) transmission error losses whereas the other class has higher transmission error losses, or the competition between DSL flows using different coding schemes. We propose a natural and simple model for the joint throughput evolution of several classes of TCP flows under such a mix of losses. Two types of random transmission error losses are considered: one where losses are Poisson and independent of the rate of the flow, and one where the losses are still Poisson but with an intensity that is proportional to the rate of the source. We show that the large population model where the population tends to infinity has a threshold (given in closed form) below which there are no congestion losses at all in steady state, and above which there is a stationary limiting regime in which we can compute both the mean value and the distribution of the rate obtained by each class of flow. We also show that the maximum mean value for the aggregated rate is achieved at the threshold.
26550730
Performance of Service Location Protocols in MANET Based on Reactive Routing Protocols
Automatic service discovery, the problem of discovering service providers by specifying desired properties of services, is an important and necessary component for collaboration in the ubiquitous computing environment such as MANET. This paper investigates the effects of the on-demand route discovery on the performance of service location protocols in MANET based on on-demand routing protocols. We first design a service discovery architecture in MANET based on AODV and evaluate both the distributed and centralized versions of the architecture by simulation. For evaluating the performance, we examine such performance metrics as service hit ratio, service discovery time, and control message overheads. The results show that the distributed scheme outperforms the centralized scheme in most simulation scenarios because of the on-demand routing overheads.
2500739
Efficient construction of multibit tries for IP lookup
Srinivasan and Varghese (1999) have proposed the use of multibit tries to represent routing tables used for Internet (IP) address lookups. They propose dynamic programming algorithms to determine the strides of optimal multibit fixed-stride and variable-stride tries. We improve on these algorithms by providing alternative dynamic programming formulations for both fixed-and variable-stride tries. While the asymptotic complexities of our algorithms are the same as those for the corresponding algorithms of Srinivasan and Varghese, experiments using real IPv4 routing table data indicate that our algorithms run considerably faster. Our fixed-stride trie algorithm is two to four times faster on a SUN workstation and 1.5 to three times faster on a Pentium IV PC. On a SUN workstation, our variable-stride trie algorithm is between two and 17 times faster than the corresponding algorithm of Srinivasan and Varghese; on a Pentium IV PC, our algorithm is between three and 47 times faster. An added feature of our variable-stride trie algorithm is the ability to insert and delete prefixes taking a fraction of the time needed to construct an optimal variable-stride trie "from scratch."
7329667
Iterative kernel principal component analysis for image modeling
In recent years, kernel principal component analysis (KPCA) has been suggested for various image processing tasks requiring an image model such as, e.g., denoising or compression. The original form of KPCA, however, can be only applied to strongly restricted image classes due to the limited number of training examples that can be processed. We therefore propose a new iterative method for performing KPCA, the kernel Hebbian algorithm, which iteratively estimates the kernel principal components with only linear order memory complexity. In our experiments, we compute models for complex image classes such as faces and natural images which require a large number of training examples. The resulting image models are tested in single-frame super-resolution and denoising applications. The KPCA model is not specifically tailored to these tasks; in fact, the same model can be used in super-resolution with variable input resolution, or denoising with unknown noise characteristics, in spite of this, both super-resolution and denoising performance are comparable to existing methods.
39411693
IP lookup by binary search on prefix length
Waldvogel et al. [ACM SIGCOMM, 1997, 25-36] have proposed a collection of hash tables (CHT) organization for an IP router table. IP lookup can be done with O(log l/sub dist/) hash-table searches, where l/sub dist/ is the number of distinct prefix-lengths (also equal to the number of hash tables in the CHT). Srinivasan and Varghese [ACM transactions on Computer Systems, Feb:1-40, 1999] have proposed the use of controlled prefix-expansion to reduce the value of l/sub dist/. The algorithm of [V. Srinivasan, 1999] does not minimize the storage required by the prefixes and markers for the resulting set of prefixes. We develop an algorithm that minimizes storage requirement but takes O(nW/sup 3/ + kW/sup 4/) time, where k is the desired number of distinct lengths, n is the number of prefixes, and W is the length of the longest prefix. Also, we propose improvements to the heuristic of [V. Srinivasan, 1999].
6524269
Real-time foreground-background segmentation using codebook model
We present a real-time algorithm for foreground-background segmentation. Sample background values at each pixel are quantized into codebooks which represent a compressed form of background model for a long image sequence. This allows us to capture structural background variation due to periodic-like motion over a long period of time under limited memory. The codebook representation is efficient in memory and speed compared with other background modeling techniques. Our method can handle scenes containing moving backgrounds or illumination variations, and it achieves robust detection for different types of videos. We compared our method with other multimode modeling techniques. In addition to the basic algorithm, two features improving the algorithm are presented-layered modeling/detection and adaptive codebook updating. For performance evaluation, we have applied perturbation detection rate analysis to four background subtraction algorithms and two videos of different types of scenes.