INTER-TUBE BONDING AND DEFECTS IN CARBON NANOTUBES AND THE IMPACT ON THE TRANSPORT PROPERTIES AND MICRO-MORPHOLOGY

The transport properties of the carbon nanotubes (CNTs) are affected by the tube-tube interaction and the defects presented in the system. Inter-tube bonding, formed during spark plasma sintering (SPS) process, lowers the electrical/thermal resistivity at the tube-tube junctions and also causes new scattering mechanisms such as strong electron-phonon coupling (EPC) at low temperature. More evidences have been found by changing the SPS temperature and doping the CNTs to support the electron-phonon coupling is Kohn anomaly (KA) in as-SPSed CNTs. The phonon drag, appearing in thermoelectric power (TEP) of the as-SPSed CNTs at low temperature, can be explained in the framework of the KA. The thermal property of CNTs exhibits nearly two dimensional character when the inter-tube bonding is stronger. When orientated CNTs are SPSed, one of the highest thermal conductivity ~ 31 W/(m-K) reported in CNT bulk samples is achieved. In certain cases, defects in the CNTs not only change the transport properties but also modify the morphology of the CNTs. Helically coiled carbon nanotubes (HCNTs) and nanowires (HCNWs) are exact examples. A rational synthesis of HCNT/HCNW using In and Sn as catalyst in a thermal chemical vapor deposition (CVD) system has been demonstrated. A thermodynamic model has been proposed, where helix/coil formation is explained on the basis of the interactions between the specific catalyst particles and the growing nanostructure. While a model based on the mutual solubility of Fe with Sn and In, could explain the growth mechanism difference between the HCNTs and the HCNWs. Experimental results agree with these models qualitatively well

Distributed Flow Scheduling in an Unknown Environment

Flow scheduling tends to be one of the oldest and most stubborn problems in networking. It becomes more crucial in the next generation network, due to fast changing link states and tremendous cost to explore the global structure. In such situation, distributed algorithms often dominate. In this paper, we design a distributed virtual game to solve the flow scheduling problem and then generalize it to situations of unknown environment, where online learning schemes are utilized. In the virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is valid based on the analysis of the `Price of Anarchy'. In the unknown-environment generalization, our ultimate goal is the minimization of cost in the long run. In order to achieve balance between exploration of routing cost and exploitation based on limited information, we model this problem based on Multi-armed Bandit Scenario and combined newly proposed DSEE with the virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit Problem. Theoretical proof and simulation results both affirm this claim. To our knowledge, this is the first research to combine multi-armed bandit with distributed flow scheduling.Comment: 10 pages, 3 figures, conferenc

Circular External Difference Families: Construction and Non-Existence

The circular external difference family and its strong version, which themselves are of independent combinatorial interest, were proposed as variants of the difference family to construct new unconditionally secure non-malleable threshold schemes. In this paper, we present new results regarding the construction and non-existence of (strong) circular external difference families, thereby solving several open problems on this topic

Robust dynamic network traffic partitioning against malicious attacks

The continual growth of network traffic rates leads to heavy packet processing overheads, and a typical solution is to partition traffic into multiple network processors for parallel processing especially in emerging software-defined networks. This paper is thus motivated to propose a robust dynamic network traffic partitioning scheme to defend against malicious attacks. After introducing the conceptual framework of dynamic network traffic partitioning based on flow tables, we strengthen its TCP connection management by building a half-open connection separation mechanism to isolate false connections in the initial connection table (ICT). Then, the lookup performance of the ICT table is reinforced by applying counting bloom filters to cope with malicious behaviors such as SYN flooding attacks. Finally, we evaluate the performance of our proposed traffic partitioning scheme with real network traffic traces and simulated malicious traffic by experiments. Experimental results indicate that our proposed scheme outperforms the conventional ones in terms of packet distribution performance especially robustness against malicious attacks