PABO: Mitigating Congestion via Packet Bounce in Data Center Networks

In today's data center, a diverse mix of throughput-sensitive long flows and delay-sensitive short flows are commonly presented in shallow-buffered switches. Long flows could potentially block the transmission of delay-sensitive short flows, leading to degraded performance. Congestion can also be caused by the synchronization of multiple TCP connections for short flows, as typically seen in the partition/aggregate traffic pattern. While multiple end-to-end transport-layer solutions have been proposed, none of them have tackled the real challenge: reliable transmission in the network. In this paper, we fill this gap by presenting PABO -- a novel link-layer design that can mitigate congestion by temporarily bouncing packets to upstream switches. PABO's design fulfills the following goals: i) providing per-flow based flow control on the link layer, ii) handling transient congestion without the intervention of end devices, and iii) gradually back propagating the congestion signal to the source when the network is not capable to handle the congestion.Experiment results show that PABO can provide prominent advantage of mitigating transient congestions and can achieve significant gain on end-to-end delay

Divergence analysis and processing for Mandarin-English parallel text exploitation

Previous work shows that the process of parallel text exploitation to extract mappings between language pairs raises the capability of language translation. However, while this process can be fully automated, one thorny problem called “divergence” causes indisposed mapping extraction. Therefore, this paper discuss the issues of parallel text exploitation, in general, with special emphasis on divergence analysis and processing. In the experiments on a Mandarin-English travel conversation corpus of 11,885 sentence pairs, the perplexity with the alignments in IBM translation model is reduced averagely from 13.65 to 4.18

Energy-Efficient Flow Scheduling and Routing with Hard Deadlines in Data Center Networks

The power consumption of enormous network devices in data centers has emerged as a big concern to data center operators. Despite many traffic-engineering-based solutions, very little attention has been paid on performance-guaranteed energy saving schemes. In this paper, we propose a novel energy-saving model for data center networks by scheduling and routing "deadline-constrained flows" where the transmission of every flow has to be accomplished before a rigorous deadline, being the most critical requirement in production data center networks. Based on speed scaling and power-down energy saving strategies for network devices, we aim to explore the most energy efficient way of scheduling and routing flows on the network, as well as determining the transmission speed for every flow. We consider two general versions of the problem. For the version of only flow scheduling where routes of flows are pre-given, we show that it can be solved polynomially and we develop an optimal combinatorial algorithm for it. For the version of joint flow scheduling and routing, we prove that it is strongly NP-hard and cannot have a Fully Polynomial-Time Approximation Scheme (FPTAS) unless P=NP. Based on a relaxation and randomized rounding technique, we provide an efficient approximation algorithm which can guarantee a provable performance ratio with respect to a polynomial of the total number of flows.Comment: 11 pages, accepted by ICDCS'1

Realizing value from project implementation under uncertainty : an exploratory study using system dynamics

Project Implementation is not a trivial task even after careful planning and scheduling. One of the reasons is the existence of unexpected events at strategic and operational levels during the project execution process. This paper presents a system dynamics model of a project monitoring and control system. Embedded with both strategic and tactical uncertainties, the model experiments with typical remedial actions to disturbances during the implementation of a project under a behavioral paradigm. Simple proportional adjustment seems to work well under low levels of unexpected disturbances but prospect theory-based behavior works better under extreme situations. Our findings indicate over-reacting behavior, which is influenced by biases and reporting errors, can generate project escalation. Thus, thresholds for remedial actions should be implemented in project control and monitoring systems to avoid over-reacting behavior leading to escalation and waste of resources

The impact of post-trade transparency on price efficiency and price discovery: Evidence from the Taiwan Stock Exchange

Purpose The purpose of this paper is to examine the impact of post-trade transparency on price efficiency and price discovery. Design/methodology/approach The authors use an exogeneous change in market transparency in the Taiwan Stock Exchange that mandates the disclosure of unexecuted orders of the five best bid and ask prices after each trade, and conduct an event study analysis. Findings After the change, price efficiency enhances for both large and small firms, although the impact on stock prices is greater when the firm is larger. The authors also find that post-change trading reveals more private information for large firms but more public information for small firms. The findings support the view that transparency has a positive impact on market quality. Originality/value The paper adds to a large body of literature investigating the relationship between transparency and market behavior, especially the ongoing debate about whether trading transparency positively affects price dynamics. The findings also have important policy implications for the regulators

Robust Optimization Design of Bolt-Shotcrete Support Structure in Tunnel

The uncertainty of rock and soil parameters is one of the key problems to limit the stability of tunnel support structure. Based on this, a robust optimization design method is proposed to reduce the sensitivity of support system to the uncertainty of rock and soil parameters. By defining the design parameters, noise factors and system response, a robust design system for bolt-shotcrete support structure is established. The non-dominant solutions of system robustness and support cost consist of the Pareto Front, then an knee point recognition method is designed to further filter all non-dominant solutions and determine the only optimal solution. The robust optimization design of the bolt-shotcrete support structure is carried out with a tunnel as the engineering background. The results show that the method can not only improve the stability and adaptability of the supporting structure, but also reduce the economic cost to the greatest extent, which provides a reference for the optimization design of other geotechnical engineering supporting structures