An Efficient Approach for Cost Optimization of the Movement of Big Data

With the emergence of cloud computing, Big Data has caught the attention of many researchers in the area of cloud computing. As the Volume, Velocity and Variety (3 Vs) of big data are growing exponentially, dealing with them is a big challenge, especially in the cloud environment. Looking at the current trend of the IT sector, cloud computing is mainly used by the service providers to host their applications. A lot of research has been done to improve the network utilization of WAN (Wide Area Network) and it has achieved considerable success over the traditional LAN (Local Area Network) techniques. While dealing with this issue, the major questions of data movement such as from where to where this big data will be moved and also how the data will be moved, have been overlooked. As various applications generating the big data are hosted in geographically distributed data centers, they individually collect large volume of data in the form of application data as well as the logs. This paper mainly focuses on the challenge of moving big data from one data center to other. We provide an efficient algorithm for the optimization of cost in the movement of the big data from one data center to another for offline environment. This approach uses the graph model for data centers in the cloud and results show that the adopted mechanism provides a better solution to minimize the cost for data movement

Policy options for improving regional fertilizer markets in West Africa:

A primary motivation for this study is to identify a key set of policy options for improving fertilizer markets in West Africa (among Economic Community of West African States member countries) in ways that ultimately will help improve the efficiency of regional markets and lower the transaction costs and fiscal burdens of increasing fertilizer use in the region. Guided by the 2008 fertilizer crisis, many governments are tempted to impose fertilizer subsidies to reduce fertilizer prices. Yet, in an environment riddled with inefficiencies that contribute to the high costs of using fertilizers, the introduction of subsidies only adds more fiscal burden.To carry out the study, we undertook four country case studies to review the key constraints and bottlenecks along the fertilizer supply chain. The countries were Ghana, Mali, Nigeria, and Senegal, and the research included field visits in 2009 and 2010. The current paper is based on the country case study results, complemented by a literature review and analysis of secondary data sources.common fertilizer market, fertilizer use and supply, harmonization of products and regulations, improved technology, policy environment, regional market integration, structure and performance of markets, supply chain,

Move Big Data to the Cloud: an Online Cost-Minimizing Approach

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The data chase : what's out there on trade costs and nontariff barriers ?

Trade costs and nontariff barriers are at the forefront of discussions on competitiveness and expanding trade opportunities for developing countries. This paper provides a summary overview of data and indicators relevant to these issues and has been informed by work underway at the World Bank on trade facilitation over the past several years to catalogue data sets and indicators. Although there has been progress in expanding data sets and developing policy-relevant indicators on trade costs and barriers, much more is needed. In order to assess progress toward achieving the Millennium Development Goals, evaluating the impact of development projects, and whether meeting Aid for Trade goals will be met, for example, a dedicated and expansive new effort to collect and assess data is needed. This paper attempts to highlight gaps in data on trade costs and provides insight into the type of new data that might be developed in the future.Transport Economics Policy&Planning,Economic Theory&Research,Trade Law,Free Trade,Trade Policy

TechNews digests: Jan - Nov 2009

TechNews is a technology, news and analysis service aimed at anyone in the education sector keen to stay informed about technology developments, trends and issues. TechNews focuses on emerging technologies and other technology news. TechNews service : digests september 2004 till May 2010 Analysis pieces and News combined publish every 2 to 3 month

India and the multilateral trading system after Seattle - toward a proactive role

The authors argue that India should engage more actively in the multilateral trading system for four reasons: First, such engagement could facilitate domestic reform, and improve access to export markets. If the government could show that domestic reform would pay off with increased access to markets abroad, those who gain from such access - whether they export textiles, software, professional services, or other products - could represent a countervailing voice to reform's opponents. In turn, the need for this external payoff to secure domestic reform makes India a credible bargainer, which could induce trading partners, to open their markets to India. Second, external commitments can foster good domestic policies, by providing guarantees against the reversal of current policies, or lending credibility to promises of future reform. Such pre-commitments could help strike a balance between the reluctance to unleash competition immediately, and the desire not to be held perpetual hostage to vested interests, or weak domestic industries. Third, engagement can help enforce India's market access rights. If other countries do not eliminate quotas on textiles, and clothing as scheduled, India can credibly threaten to withdraw its obligations under the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPs). Fourth, multilateral tariff reduction could reduce the disadvantage (to India) of not being part of regional agreements. The value of multilateral engagement might be limited, if the prospects for securing increased market access are dim, as the failed Seattle negotiations might appear to suggest. India must credibly test negotiating pessimism by showing its willingness to open its markets in return for improved access to foreign markets. Success is not certain, but India's chances are improved if aligns itself with countries pressing for sound policies of open trade.Environmental Economics&Policies,Labor Policies,Economic Theory&Research,Rules of Origin,ICT Policy and Strategies,TF054105-DONOR FUNDED OPERATION ADMINISTRATION FEE INCOME AND EXPENSE ACCOUNT,Environmental Economics&Policies,Economic Theory&Research,Trade and Regional Integration,ICT Policy and Strategies

All Politics Is Global: Explaining International Regulatory Regimes

Has globalization diluted the power of national governments to regulate their own economies? Are international governmental and nongovernmental organizations weakening the hold of nation-states on global regulatory agendas? Many observers think so. But in All Politics Is Global , Daniel Drezner argues that this view is wrong. Despite globalization, states--especially the great powers--still dominate international regulatory regimes, and the regulatory goals of states are driven by their domestic interests. As Drezner shows, state size still matters. The great powers--the United States and the European Union--remain the key players in writing global regulations, and their power is due to the size of their internal economic markets. If they agree, there will be effective global governance. If they don't agree, governance will be fragmented or ineffective. And, paradoxically, the most powerful sources of great-power preferences are the least globalized elements of their economies. Testing this revisionist model of global regulatory governance on an unusually wide variety of cases, including the Internet, finance, genetically modified organisms, and intellectual property rights, Drezner shows why there is such disparity in the strength of international regulations.globalization, politics, governance, international regulatory regimes, nongovernmental organizations, states, great powers

Applying Deep Learning To Airbnb Search

The application to search ranking is one of the biggest machine learning success stories at Airbnb. Much of the initial gains were driven by a gradient boosted decision tree model. The gains, however, plateaued over time. This paper discusses the work done in applying neural networks in an attempt to break out of that plateau. We present our perspective not with the intention of pushing the frontier of new modeling techniques. Instead, ours is a story of the elements we found useful in applying neural networks to a real life product. Deep learning was steep learning for us. To other teams embarking on similar journeys, we hope an account of our struggles and triumphs will provide some useful pointers. Bon voyage!Comment: 8 page