Sharp Bounds in Stochastic Network Calculus

The practicality of the stochastic network calculus (SNC) is often questioned on grounds of potential looseness of its performance bounds. In this paper it is uncovered that for bursty arrival processes (specifically Markov-Modulated On-Off (MMOO)), whose amenability to \textit{per-flow} analysis is typically proclaimed as a highlight of SNC, the bounds can unfortunately indeed be very loose (e.g., by several orders of magnitude off). In response to this uncovered weakness of SNC, the (Standard) per-flow bounds are herein improved by deriving a general sample-path bound, using martingale based techniques, which accommodates FIFO, SP, EDF, and GPS scheduling. The obtained (Martingale) bounds gain an exponential decay factor of ${\mathcal{O}}(e^{-\alpha n})$ in the number of flows $n$. Moreover, numerical comparisons against simulations show that the Martingale bounds are remarkably accurate for FIFO, SP, and EDF scheduling; for GPS scheduling, although the Martingale bounds substantially improve the Standard bounds, they are numerically loose, demanding for improvements in the core SNC analysis of GPS

OFLOPS: An Open Framework for OpenFlow Switch Evaluation

Abstract. Recent efforts in software-defined networks, such as OpenFlow, give unprecedented access into the forwarding plane of networking equipment. When building a network based on OpenFlow however, one must take into account the performance characteristics of particular OpenFlow switch implementations. In this paper, we present OFLOPS, an open and generic software framework that permits the development of tests for OpenFlow-enabled switches, that measure the capabilities and bottlenecks between the forwarding engine of the switch and the remote control application. OFLOPS combines hardware instrumentation with an extensible software framework. We use OFLOPS to evaluate current OpenFlow switch implementations and make the following observations: (i) The switching performance of flows depends on applied actions and firmware. (ii) Current OpenFlow implementations differ substantially in flow updating rates as well as traffic monitoring capabilities. (iii) Accurate OpenFlow command completion can be observed only through the data plane. These observations are crucial for understanding the applicability of Open-Flow in the context of specific use-cases, which have requirements in terms of forwarding table consistency, flow setup latency, flow space granularity, packet modification types, and/or traffic monitoring abilities.

Perspectives on Network Calculus – No Free Lunch, but Still Good Value

ACM Sigcomm 2006 published a paper [26] which was perceived to unify the deterministic and stochastic branches of the network calculus (abbreviated throughout as DNC and SNC) [39]. Unfortunately, this seemingly fundamental unification—which has raised the hope of a straightforward transfer of all results from DNC to SNC—is invalid. To substantiate this claim, we demonstrate that for the class of stationary andergodic processes, whichis prevalentin traffic modelling, the probabilistic arrival model from [26] is quasideterministic, i.e., the underlying probabilities are either zero or one. Thus, the probabilistic framework from [26] is unable to account for statistical multiplexing gain, which is in fact the raison d’être of packet-switched networks. Other previous formulations of SNC can capture statistical multiplexin

Commercial banks lending and economic growth in Malaysia: An Empirical Study / Tang Tuck Cheong

The objective of the study is to investigate, and explore the impact of commercial banks lending on economic growth in Malaysia with annual data for the period of 1960-98. The theoretical underpinning of the role of commercial banks lending to economic growth is based on combination of quantity theory of money and aggregate production function. The study shows an increasing of importance of commercial banks to economic growth. Obviously, commercial banks in Malaysia provided about 69 per cent to 72 per cent of total loan in banking system. The study shows an increasing rule of commercial banks lending in economic growth, GNP(Gross National Product), from RM0.073million in 1959 to RM1.14million in 1998 to generate a million of GNP in economic. The variables of Real Gross Domestic Product (RGDP), and commercial banks lending (LAc) are employed in the regression analysis. By using linear regression model (OLS), the finding reveals a short run (current year) positive influence of commercial banks lending to economic growth, but negative impact in long run (lagged explanatory variables). The findings also significantly explore the validity of theory in this study, Y=f(LAc). In addition, the commercial banks lending is found to be statistically significant variable to predict the future economic behavior