Robust measurement-based buffer overflow probability estimators for QoS provisioning and traffic anomaly prediction applications

Suitable estimators for a class of Large Deviation approximations of rare event probabilities based on sample realizations of random processes have been proposed in our earlier work. These estimators are expressed as non-linear multi-dimensional optimization problems of a special structure. In this paper, we develop an algorithm to solve these optimization problems very efficiently based on their characteristic structure. After discussing the nature of the objective function and constraint set and their peculiarities, we provide a formal proof that the developed algorithm is guaranteed to always converge. The existence of efficient and provably convergent algorithms for solving these problems is a prerequisite for using the proposed estimators in real time problems such as call admission control, adaptive modulation and coding with QoS constraints, and traffic anomaly detection in high data rate communication networks

Robust measurement-based buffer overflow probability estimators for QoS provisioning and traffic anomaly prediction applicationm

Suitable estimators for a class of Large Deviation approximations of rare event probabilities based on sample realizations of random processes have been proposed in our earlier work. These estimators are expressed as non-linear multi-dimensional optimization problems of a special structure. In this paper, we develop an algorithm to solve these optimization problems very efficiently based on their characteristic structure. After discussing the nature of the objective function and constraint set and their peculiarities, we provide a formal proof that the developed algorithm is guaranteed to always converge. The existence of efficient and provably convergent algorithms for solving these problems is a prerequisite for using the proposed estimators in real time problems such as call admission control, adaptive modulation and coding with QoS constraints, and traffic anomaly detection in high data rate communication networks

Service Level Constrained Inventory Systems

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151878/1/poms13060_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151878/2/poms13060.pd

A Framework for Reverse Logistics

Reverse Logistics has been stretching out worldwide, involving all the layers of supply chains in various industry sectors. While some actors in the chain have been forced to take products back, others have pro-actively done so, attracted by the value in used products One way or the other, Reverse Logistics has become a key competence in modern supply chains. In this paper, we present a content analysis of reverse logistics issues. To do so, we propose a content framework focusing on the following questions with respect to reverse logistics: why? what? how?; and, who?, i.e. driving forces and return reasons, what type of products are streaming back, how are they being recovered, and who is executing and managing the various operations. These four basic characteristics are interrelated and their combination determines to a large extent the type of issues arising from the resulting reverse logistics system.supply chain management;reverse logistics;content analysis;theory;framework

Political Risk and Regulatory Risk: Issues in Emerging Markets Infrastructure Concessions

Political and regulatory risks, cause damage to countries and investors because of investment diminishing. When investments take place, those could increase services prices. Present work has as its objectives to characterize theoretically the problem, to study existent measures to face it, to know the available instruments to deal with it, and to draw some general conclusions on political and regulatory risks, and some specific conclusions referred to infrastructure concessions. The article is limited to the study of opportunistic behavior or governments.regulatory risks; Issues in Emerging Markets; Infrastructure Concessions

How and why communications industry suppliers get “squeezed out” by outsourcing: cases, impact and the next phases

The communications systems,terminals,and service, industries, have undergone over the past ten years a significant technological internal evolution and external revolution at customer end (such as shifting to IP, wireless 3G and LTE evolutions, new terminals, broadband...). Very little management research has studied their survivability irrespective of changes in demand volumes, due to technological sourcing and outsourcing practices driven by other global industries serving as predators in view of the huge business potential of communications products and services. These other industries include computing software, semiconductor and contract manufacturing industries, many of with roots in emerging countries. This paper analyzes the implications of using in-sourced genuine non-proprietary open communications standards , of the wider use of in-sourced /purchased technologies ,and of outsourced contract manufacturing . The methodology used is equilibrium analyses from case analysis data. They show a trend towards active or passive knowledge leakage. Three specific areas will be mentioned as examples .The paper also shows the processes how eventually those industries in a later cycle bounce back.Communications industry; Communications industry suppliers; Business processes; Intellectual property; Technical competence; Customer bases

Modeling Supply Networks and Business Cycles as Unstable Transport Phenomena

Physical concepts developed to describe instabilities in traffic flows can be generalized in a way that allows one to understand the well-known instability of supply chains (the so-called ``bullwhip effect''). That is, small variations in the consumption rate can cause large variations in the production rate of companies generating the requested product. Interestingly, the resulting oscillations have characteristic frequencies which are considerably lower than the variations in the consumption rate. This suggests that instabilities of supply chains may be the reason for the existence of business cycles. At the same time, we establish some link to queuing theory and between micro- and macroeconomics.Comment: For related work see http://www.helbing.or