SSthreshless Start: A Sender-Side TCP Intelligence for Long Fat Network

Measurement shows that 85% of TCP flows in the internet are short-lived flows that stay most of their operation in the TCP startup phase. However, many previous studies indicate that the traditional TCP Slow Start algorithm does not perform well, especially in long fat networks. Two obvious problems are known to impact the Slow Start performance, which are the blind initial setting of the Slow Start threshold and the aggressive increase of the probing rate during the startup phase regardless of the buffer sizes along the path. Current efforts focusing on tuning the Slow Start threshold and/or probing rate during the startup phase have not been considered very effective, which has prompted an investigation with a different approach. In this paper, we present a novel TCP startup method, called threshold-less slow start or SSthreshless Start, which does not need the Slow Start threshold to operate. Instead, SSthreshless Start uses the backlog status at bottleneck buffer to adaptively adjust probing rate which allows better seizing of the available bandwidth. Comparing to the traditional and other major modified startup methods, our simulation results show that SSthreshless Start achieves significant performance improvement during the startup phase. Moreover, SSthreshless Start scales well with a wide range of buffer size, propagation delay and network bandwidth. Besides, it shows excellent friendliness when operating simultaneously with the currently popular TCP NewReno connections.Comment: 25 pages, 10 figures, 7 table

Relativistic mean-field approximation with density-dependent screening meson masses in nuclear matter

The Debye screening masses of the $\sigma$, $\omega$ and neutral $\rho$ mesons and the photon are calculated in the relativistic mean-field approximation. As the density of the nucleon increases, all the screening masses of mesons increase. It shows a different result with Brown-Rho scaling, which implies a reduction in the mass of all the mesons in the nuclear matter except the pion. Replacing the masses of the mesons with their corresponding screening masses in Walecka-1 model, five saturation properties of the nuclear matter are fixed reasonably, and then a density-dependent relativistic mean-field model is proposed without introducing the non-linear self-coupling terms of mesons.Comment: 14 pages, 3 figures, REVTEX4, Accepted for publication in Int. J. Mod. Phys.

Processing of G4 DNA by Dna2 Helicase/nuclease and RPA provides insights into the mechanism of Dna2/RPA substrate recognition

The polyguanine-rich DNA sequences commonly found at telomeres and in rDNA arrays have been shown to assemble into structures known as G quadruplexes, or G4 DNA, stabilized by base-stacked G quartets, an arrangement of four hydrogen-bonded guanines. G4 DNA structures are resistant to the many helicases and nucleases that process intermediates arising in the course of DNA replication and repair. The lagging strand DNA replication protein, Dna2, has demonstrated a unique localization to telomeres and a role in de novo telomere biogenesis, prompting us to study the activities of Dna2 on G4 DNA-containing substrates. We find that yeast Dna2 binds with 25-fold higher affinity to G4 DNA formed from yeast telomere repeats than to single-stranded DNA of the same sequence. Human Dna2 also binds G4 DNAs. The helicase activities of both yeast and human Dna2 are effective in unwinding G4 DNAs. On the other hand, the nuclease activities of both yeast and human Dna2 are attenuated by the formation of G4 DNA, with the extent of inhibition depending on the topology of the G4 structure. This inhibition can be overcome by replication protein A. Replication protein A is known to stimulate the 5'- to 3'-nuclease activity of Dna2; however, we go on to show that this same protein inhibits the 3'- to 5'-exo/endonuclease activity of Dna2. These observations are discussed in terms of possible roles for Dna2 in resolving G4 secondary structures that arise during Okazaki fragment processing and telomere lengthening

The resilience of interdependent transportation networks under targeted attack

Modern world builds on the resilience of interdependent infrastructures characterized as complex networks. Recently, a framework for analysis of interdependent networks has been developed to explain the mechanism of resilience in interdependent networks. Here we extend this interdependent network model by considering flows in the networks and study the system's resilience under different attack strategies. In our model, nodes may fail due to either overload or loss of interdependency. Under the interaction between these two failure mechanisms, it is shown that interdependent scale-free networks show extreme vulnerability. The resilience of interdependent SF networks is found in our simulation much smaller than single SF network or interdependent SF networks without flows.Comment: 5 pages, 4 figure