Content-access QoS in peer-to-peer networks using a fast MDS erasure code

This paper describes an enhancement of content access Quality of Service in peer to peer (P2P) networks. The main idea is to use an erasure code to distribute the information over the peers. This distribution increases the users’ choice on disseminated encoded data and therefore statistically enhances the overall throughput of the transfer. A performance evaluation based on an original model using the results of a measurement campaign of sequential and parallel downloads in a real P2P network over Internet is presented. Based on a bandwidth distribution, statistical content-access QoS are guaranteed in function of both the content replication level in the network and the file dissemination strategies. A simple application in the context of media streaming is proposed. Finally, the constraints on the erasure code related to the proposed system are analysed and a new fast MDS erasure code is proposed, implemented and evaluated

Increasing Market Interconnection: An analysis of the Italian Electricity Spot Market

In this paper we estimate the benefits resulting from interconnecting the Italian electricity spot market. The market is currently divided into two geographic zones – North and South – with limited interzonal transmission capacity that often induces congestion, and hence potential inefficiency. By simulating a fully interconnected market, we predict that the total spot market expenditure would reduce substantially. Moreover, since savings do not increase linearly with the size of new transmission capacity, even a slight increment to transmission capacity is found to bring substantial benefits to end users. Finally, our analysis shows that the (partly State owned) dominant firm in the market is not maximizing short-term profits.Transmission constraints, zonal pricing, congestion, electricity industry

MIncreasing Market Interconnection: an analysis of the Italian Electricity Spot Market

We estimate the bene ts resulting from completely interconnecting the Italian electricity spot market. The�market is currently divided into two geographic zones - North and South - with limited interzonal transmission capacity that often induces congestion, and hence potential inefficiency. By simulating a fully interconnected market for May 2004, we predict that the total spot market expenditure reduces substantially by almost four percent. Our analysis finds evidence that the (partly State owned) major firm in the market does not currently maximize its short-term profit, and would benefit as well from improved interconnection.Transmission constraints,self-regulated monopoly,zonal pricing,congestion

Implementing total productive maintenance in Nigerian manufacturing industries

Remarkable improvements have occurred recently in the maintenance management of physical assets and productive systems, so that less wastages of energy and resources occur. The requirement for optimal preventive maintenance using, for instance, justin-time (JIT) and total quality-management (TQM) techniques has given rise to whathas been called the total productive-maintenance (TPM) approach. This study explores the ways in which Nigerian manufacturing industries can implement TPM as a strategy and culture for improving its performance and suggests self-auditing and bench-marking as desirable prerequisites before TPM implementation

Telecommunication reforms, access regulation, and Internet adoption in Latin America

The authors review the stylized facts on regulatory reform in telecommunications and its effects on telecommunications development and Internet penetration in Latin America. Relying on data from the International Telecommunication Union, the Information for Development Program (InfoDev), and the World Bank for 1990-99, the authors then test econometrically the determinants of the differences in Internet penetration rates across Latin America. The results show that effective implementation of the reform agenda in telecommunications regulation could accelerate adoption of the Internet in Latin America-even though it is only part of the solution (income levels, income distribution, and access to primary infrastructure are the main determinants of growth in Internet connections and use). Regulation will work by cutting costs. Cost cutting will require that regulators in the region take a much closer look at the design of interconnection rules and at the tradeoffs that emerge from the complex issues involved. It will also require a commitment to developing analytical instruments, such as cost models, to sort out many of the problems. Appropriate cost models will generate benchmarks that are much more consistent with the local issues and with the local cost of capital than international benchmarks will ever be for countries in unstable macroeconomic situations. Cost cutting will require an equally strong commitment to imposing regulatory accounting systems that reduce the information asymmetrics that incumbents use to reduce the risks of entry. All these changes will ultimately require a stronger commitment by competition agencies, since in many countries a failure to negotiate interconnection agreements will raise competition issues just as often as it will raise regulatory questions.Rural Communications,Information Technology,Telecommunications Infrastructure,Knowledge Economy,Health Monitoring&Evaluation,Knowledge Economy,Information Technology,Health Monitoring&Evaluation,Rural Communications,Education for the Knowledge Economy

Payments for Progress: A Hands-Off Approach to Foreign Aid

There are significant differences of opinion about the merits of additional aid in meeting the MDGs, including whether and how aid should be given in ‘fragile states’, whether additional aid on the scale envisioned can be effectively used even in well-managed economies, and whether the aid system, particularly in highly aid-dependent countries, undermines instead of strengthens local institutions. We discuss an approach to scaling up foreign aid that would explicitly be aimed at strengthening local capacity and institutions, including in fragile states. “Payments for progress” would link additional aid to clear evidence of progress already achieved on the ground. This approach would give flexibility and autonomy to local institutions, providing an opening for local institutional experimentation, while at the same time ensuring that aid pays only for real, measurable achievements. Donors would bind themselves as a group to pay a specific amount for clear evidence of progress against one or more agreed goals in low-income developing countries. Developing country governments would present an independently audited statement reporting their progress on the measures, and donors would pay the agreed amount. Payments would be determined as a function of the outcomes, and not linked to the implementation of any particular policies, any other intermediate outputs, or “tied” to purchases from particular suppliers or companies. Governments that found ways to provide services efficiently and so reduce the costs of providing them would benefit from a larger surplus. We discuss the issues such an approach raises—in setting the benchmarks against which progress is measured, in avoiding cheating, and in managing unintended negative consequences of an incentives-based approach. We conclude with a summary of the advantages for donors and recipients.foreign aid, MDGs, aid-dependent countries, local capacity, fragile states, tied aid

Human-Machine Collaborative Optimization via Apprenticeship Scheduling

Coordinating agents to complete a set of tasks with intercoupled temporal and resource constraints is computationally challenging, yet human domain experts can solve these difficult scheduling problems using paradigms learned through years of apprenticeship. A process for manually codifying this domain knowledge within a computational framework is necessary to scale beyond the ``single-expert, single-trainee" apprenticeship model. However, human domain experts often have difficulty describing their decision-making processes, causing the codification of this knowledge to become laborious. We propose a new approach for capturing domain-expert heuristics through a pairwise ranking formulation. Our approach is model-free and does not require enumerating or iterating through a large state space. We empirically demonstrate that this approach accurately learns multifaceted heuristics on a synthetic data set incorporating job-shop scheduling and vehicle routing problems, as well as on two real-world data sets consisting of demonstrations of experts solving a weapon-to-target assignment problem and a hospital resource allocation problem. We also demonstrate that policies learned from human scheduling demonstration via apprenticeship learning can substantially improve the efficiency of a branch-and-bound search for an optimal schedule. We employ this human-machine collaborative optimization technique on a variant of the weapon-to-target assignment problem. We demonstrate that this technique generates solutions substantially superior to those produced by human domain experts at a rate up to 9.5 times faster than an optimization approach and can be applied to optimally solve problems twice as complex as those solved by a human demonstrator.Comment: Portions of this paper were published in the Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) in 2016 and in the Proceedings of Robotics: Science and Systems (RSS) in 2016. The paper consists of 50 pages with 11 figures and 4 table