Network topology

About: Network topology is a research topic. Over the lifetime, 52259 publications have been published within this topic receiving 1006627 citations.

Random walks in peer-to-peer networks

Abstract: We quantify the effectiveness of random walks for searching and construction of unstructured peer-to-peer (P2P) networks. We have identified two cases where the use of random walks for searching achieves better results than flooding: a) when the overlay topology is clustered, and h) when a client re-issues the same query while its horizon does not change much. For construction, we argue that an expander can he maintained dynamically with constant operations per addition. The key technical ingredient of our approach is a deep result of stochastic processes indicating that samples taken from consecutive steps of a random walk can achieve statistical properties similar to independent sampling (if the second eigenvalue of the transition matrix is hounded away from 1, which translates to good expansion of the network; such connectivity is desired, and believed to hold, in every reasonable network and network model). This property has been previously used in complexity theory for construction of pseudorandom number generators. We reveal another facet of this theory and translate savings in random bits to savings in processing overhead.

Network component analysis: Reconstruction of regulatory signals in biological systems

Abstract: High-dimensional data sets generated by high-throughput technologies, such as DNA microarray, are often the outputs of complex networked systems driven by hidden regulatory signals. Traditional statistical methods for computing low-dimensional or hidden representations of these data sets, such as principal component analysis and independent component analysis, ignore the underlying network structures and provide decompositions based purely on a priori statistical constraints on the computed component signals. The resulting decomposition thus provides a phenomenological model for the observed data and does not necessarily contain physically or biologically meaningful signals. Here, we develop a method, called network component analysis, for uncovering hidden regulatory signals from outputs of networked systems, when only a partial knowledge of the underlying network topology is available. The a priori network structure information is first tested for compliance with a set of identifiability criteria. For networks that satisfy the criteria, the signals from the regulatory nodes and their strengths of influence on each output node can be faithfully reconstructed. This method is first validated experimentally by using the absorbance spectra of a network of various hemoglobin species. The method is then applied to microarray data generated from yeast Saccharamyces cerevisiae and the activities of various transcription factors during cell cycle are reconstructed by using recently discovered connectivity information for the underlying transcriptional regulatory networks.

The impact of multihop wireless channel on TCP throughput and loss

Abstract: This paper studies TCP performance over multihop wireless networks that use the IEEE 802.11 protocol as the access method. Our analysis and simulations show that, given a specific network topology and flow patterns, there exists a TCP window size W*, at which TCP achieves best throughput via improved spatial channel reuse. However, TCP does not operate around W*, and typically grows its average window size much larger; this leads to decreased throughput and increased packet loss. The TCP throughput reduction can be explained by its loss behavior. Our results show that network overload is mainly signified by wireless link contention in multihop wireless networks. As long as the buffer size at each node is reasonably large (say, larger than 10 packets), buffer overflow-induced packet loss is rare and packet drops due to link-layer contention dominate. Link-layer drops offer the first sign for network overload. We further show that multihop wireless links collectively exhibit graceful drop behavior: as the offered load increases, the link contention drop probability also increases, but saturates eventually. In general, the link drop probability is insufficient to stabilize the average TCP window size around W*. Consequently, TCP suffers from reduced throughput due to reduced spatial reuse. We further propose two techniques, link RED and adaptive pacing, through which we are able to improve TCP throughput by 5% to 30% in various simulated topologies. Some simulation results are also validated by real hardware experiments.