Global-scale Networks Research Articles

JABS: A Blockchain Simulator for Researching Consensus Algorithms

The consensus algorithm is fundamental to the decentralization property of blockchain technology. Developing blockchain networks and consensus algorithms necessitates the analysis of variables on large global-scale networks through experiments. However, conducting experiments on test networks is expensive due to the high cost of necessary infrastructure. In this paper, JABS (Just Another Blockchain Simulator), a simulator specifically designed for researching large-scale blockchain consensus algorithms, is introduced. Superior performance in simulating real-world scale blockchain networks compared to other frameworks is demonstrated in this paper. JABS is faster, more efficient, and produces accurate results that are comparable to measurements from Bitcoin and Ethereum blockchain networks. JABS' modularity, which allows for the easy substitution of components without changing others, is highlighted. Additionally, JABS aids in the design and evaluation of new consensus algorithms. Improving the CasperFFG consensus algorithm is proposed and its improved performance using JABS is demonstrated.

Economic Integration of the Visegrad Four and Ukraine in the Context of Historical Narratives and Global Challenges

The article reveals the historical preconditions for the development of economic integration of Ukraine and the Visegrad Four from the standpoint of challenges relevant to the region of Central and Eastern Europe. The co-existence of the Rus’ people (ancient Ukrainians) with the Czech, Polish, Hungarian and Slovak ethnic groups is outlined, highlighting the significant events. They are presented in the context of building good neighbourly relations through overcoming contradictions. V4 is considered as an association of new political and economic order within the framework of European integration processes. The routes of economic integration of Ukraine and V4 have been assessed, revealing that this process is mainly limited to import operations and excludes real sector of the economy. A concept is developed for the V4+UA economic space, specifying the creation of a regionally integrated machine industry with fragmented production within a global-scale network and high added value.

Varifocal-Net: A Chromosome Classification Approach Using Deep Convolutional Networks.

Chromosome classification is critical for karyotyping in abnormality diagnosis. To expedite the diagnosis, we present a novel method named Varifocal-Net for simultaneous classification of chromosome's type and polarity using deep convolutional networks. The approach consists of one global-scale network (G-Net) and one local-scale network (L-Net). It follows three stages. The first stage is to learn both global and local features. We extract global features and detect finer local regions via the G-Net. By proposing a varifocal mechanism, we zoom into local parts and extract local features via the L-Net. Residual learning and multi-task learning strategies are utilized to promote high-level feature extraction. The detection of discriminative local parts is fulfilled by a localization subnet of the G-Net, whose training process involves both supervised and weakly supervised learning. The second stage is to build two multi-layer perceptron classifiers that exploit features of both two scales to boost classification performance. The third stage is to introduce a dispatch strategy of assigning each chromosome to a type within each patient case, by utilizing the domain knowledge of karyotyping. The evaluation results from 1909 karyotyping cases showed that the proposed Varifocal-Net achieved the highest accuracy per patient case (%) of 99.2 for both type and polarity tasks. It outperformed state-of-the-art methods, demonstrating the effectiveness of our varifocal mechanism, multi-scale feature ensemble, and dispatch strategy. The proposed method has been applied to assist practical karyotype diagnosis.

Inter-Domain Mobility Management Based on the Proxy Mobile IP in Mobile Networks

System Architecture Evolution (SAE) with Long Term Evolution (LTE) has been used as the key technology for the next generation mobile networks. To support mobility in the LTE/SAE-based mobile networks, the Proxy Mobile IPv6 (PMIP), in which the Mobile Access Gateway (MAG) of the PMIP is deployed at the Serving Gateway (S-GW) of LTE/SAE and the Local Mobility Anchor (LMA) of PMIP is employed at the PDN Gateway (P-GW) of LTE/SAE, is being considered. In the meantime, the Host Identity Protocol (HIP) and the Locator Identifier Separation Protocol (LISP) have recently been proposed with the identifier-locator separation principle, and they can be used for mobility management over the global-scale networks. In this paper, we discuss how to provide the inter-domain mobility management over PMIP-based LTE/SAE networks by investigating three possible scenarios: mobile IP with PMIP (denoted by MIP-PMIP-LTE/SAE), HIP with PMIP (denoted by HIP-PMIP-LTE/SAE), and LISP with PMIP (denoted by LISP-PMIP-LTE/SAE). For performance analysis of the candidate inter-domain mobility management schemes, we analyzed the traffic overhead at a central agent and the total transmission delay required for control and data packet delivery. From the numerical results, we can see that HIP-PMIP-LTE/SAE and LISP-PMIP-LTE/SAE are preferred to MIP-PMIP-LTE/SAE in terms of traffic overhead; whereas, LISP-PMIP-LTE/SAE is preferred to HIP-PMIP-LTE/SAE and MIP-PMIP-LTE/SAE in the viewpoint of total transmission delay.

A feasible MapReduce peer-to-peer framework for distributed computing applications

This article presents a MapReduce Peer-to-Peer (P2P) framework that enables a MapReduce implementation on P2P networks to support a class of MapReduce-based computing applications. This framework can be useful for researchers who cannot afford expensive and dedicated clusters for infrequent demands of solving distributed computing problems. The framework also allows Internet users from social and P2P network communities to perform large data processing experiments on distributed environment. The article describes the architecture and prototyping implementation of a MapReduce P2P system. The main features of this system include exploiting leisure computing resources on P2P networks efficiently for computation, providing MapReduce operations using task management for various distributed computing problems, and supporting peer failure management for improving fault tolerance on Internet environment. We have evaluated and compared the MapReduce P2P implementation with a Hadoop MapReduce implementation on local and global-scale networks. The article also includes a discussion of applying the framework to a realistic distributed case-based reasoning system.

Using Friends as Sensors to Detect Global-Scale Contagious Outbreaks

Recent research has focused on the monitoring of global–scale online data for improved detection of epidemics, mood patterns, movements in the stock market political revolutions, box-office revenues, consumer behaviour and many other important phenomena. However, privacy considerations and the sheer scale of data available online are quickly making global monitoring infeasible, and existing methods do not take full advantage of local network structure to identify key nodes for monitoring. Here, we develop a model of the contagious spread of information in a global-scale, publicly-articulated social network and show that a simple method can yield not just early detection, but advance warning of contagious outbreaks. In this method, we randomly choose a small fraction of nodes in the network and then we randomly choose a friend of each node to include in a group for local monitoring. Using six months of data from most of the full Twittersphere, we show that this friend group is more central in the network and it helps us to detect viral outbreaks of the use of novel hashtags about 7 days earlier than we could with an equal-sized randomly chosen group. Moreover, the method actually works better than expected due to network structure alone because highly central actors are both more active and exhibit increased diversity in the information they transmit to others. These results suggest that local monitoring is not just more efficient, but also more effective, and it may be applied to monitor contagious processes in global–scale networks.

Economics 2.0: The Natural Step towards a Self-Regulating, Participatory Market Society

Despite all our great advances in science, technology and financial innovations, many societies today are struggling with a financial, economic and public spending crisis, over-regulation, and mass unemployment, as well as lack of sustain-ability and innovation. Can we still rely on conventional economic thinking or do we need a new approach? Is our economic system undergoing a fundamental transformation? Are our theories still doing a good job with just a few exceptions, or do they work only for “good weather” but not for “market storms”? Can we fix existing theories by adapting them a bit, or do we need a fundamentally different approach? These are the kind of questions that will be addressed in this paper. I argue that, as the complexity of socio-economic systems increases, networked decision-making and bottom-up self-regulation will be more and more important features. It will be explained why, besides the “homo economicus” with strictly self-regarding preferences, natural selection has also created a “homo socialis” with other-regarding preferences. While the “homo economicus” optimizes the own prospects in separation, the decisions of the “homo socialis” are self-determined, but interconnected, a fact that may be characterized by the term “networked minds.” Notably, the “homo socialis” manages to earn higher payoffs than the “homo economicus.” I show that the “homo economicus” and the “homo so-cialis” imply a different kind of dynamics and distinct aggregate outcomes. Therefore, next to the traditional economics for the “homo economicus” (“economics 1.0”), a complementary theory must be developed for the “homo socialis.” This economic theory might be called “economics 2.0” or “socionomics.” The names are justified, because the Web 2.0 is currently promoting a transition to a new market organization, which benefits from social media platforms and could be characterized as “participatory market society.” To thrive, the “homo socialis” requires suitable institutional settings such a particular kinds of reputation systems, which will be sketched in this paper. I also propose a new kind of money, so-called “qualified money,” which may overcome some of the problems of our current financial system. In summary, I discuss the economic literature from a new perspective and argue that this offers the basis for a different theoretical framework. This opens the door for a new economic thinking and a novel research field, which focuses on the effects, implications, and institutional requirements for global-scale network interactions and highly interdependent decisions.

First Measurements of Ambient Total Gaseous Mercury (TGM) at the EvK2CNR Pyramid Observatory in Nepal

As part of the Global Mercury Observation System (GMOS) project, a global-scale network of ground-based atmospheric monitoring sites is being developed with the objective of expanding the global coverage of atmospheric mercury (Hg) measurements and improving our understanding of global atmospheric Hg transport. An important addition to the GMOS monitorng network has been the high altitude EvK2CNR Pyramid Observatory, located at an elevation of 5,050 meters a.s.l. in the eastern Himalaya Mountains of Nepal. Monitoring of total gaseous mercury (TGM) using the Tekran 2537A Mercury Vapor Analyzer began at the EvK2CNR Pyramid Observatory in November 2011. From 17 November 2011 to 23 April 2012, the mean concentration of TGM at the Pyramid was 1.2 ng m−3. A range of concentrations from 0.7 to 2.6 ng m−3 has been observed. These are the first reported measurements of atmospheric Hg in Nepal, and currently this is the highest altitude monitoring station for atmospheric Hg in the world. It is anticipated that these high quality measurements, in combination with the other continuous atmospheric measurments being collected at the Pyramid station, will help to further our understanding of Hg concentrations in the free troposphere and the transport of atmospheric Hg on the global scale.

Fast Detection of Distributed Global Scale Network Attack Symptoms and Patterns in High-speed Backbone Networks

Traditional attack detection schemes based on packets or flows have very high computational complexity. And, network based anomaly detection schemes can reduce the complexity, but they have a limitation to figure out the pattern of the distributed global scale network attack. In this paper, we propose an efficient and fast method for detecting distributed global-scale network attack symptoms in high-speed backbone networks. The proposed method is implemented at the aggregate traffic level. So, our proposed scheme has much lower computational complexity, and is implemented in very high-speed backbone networks. In addition, the proposed method can detect attack patterns, such as attacks in which the target is a certain host or the backbone infrastructure itself, via collaboration of edge routers on the backbone network. The effectiveness of the proposed method are demonstrated via simulation.

Recent progress and future directions of ChinaFLUX

The eddy covariance technique has emerged as an important tool to directly measure carbon dioxide, water vapor and heat fluxes between the terrestrial ecosystem and the atmosphere after a long history of fundamental research and technological developments. With the realization of regional networks of flux measurements in North American, European, Asia, Brazil, Australia and Africa, a global-scale network of micrometeorological flux measurement (FLUXNET) was established in 1998. FLUXNET has made great progresses in investigating the environmental mechanisms controlling carbon and water cycles, quantifying spatial-temporal patterns of carbon budget and seeking the “missing carbon sink” in global terrestrial ecosystems in the past ten years. The global-scale flux measurement also built a platform for international communication in the fields of resource, ecology and environment sciences. With the continuous development of flux research, FLUXNET will introduce and explore new techniques to extend the application fields of flux measurement and to answer questions in the fields of bio-geography, eco-hydrology, meteorology, climate change, remote sensing and modeling with eddy covariance flux data. As an important part of FLUXNET, ChinaFLUX has made significant progresses in the past three years on the methodology and technique of eddy covariance flux measurement, on the responses of CO2 and H2O exchange between the terrestrial ecosystem and the atmosphere to environmental change, and on flux modeling development. Results showed that the major forests on the North-South Transect of Eastern China (NSTEC) were all carbon sinks during 2003 to 2005, and the alpine meadows on the Tibet Plateau were also small carbon sinks. However, the reserved natural grassland, Leymus chinensis steppe in Inner Mongolia, was a carbon source. On a regional scale, temperature and precipitation are the primary climatic factors that determined the carbon balance in major terrestrial ecosystems in China. Finally, the current research emphasis and future directions of ChinaFLUX were presented. By combining flux network and terrestrial transect, ChinaFLUX will develop integrated research with multi-scale, multi-process, multi-subject observations, placing emphasis on the mechanism and coupling relationships between water, carbon and nitrogen cycles in terrestrial ecosystems.

Some results of S-transform analysis of the transient planetary-scale wind oscillations in the lower thermosphere

Technique appropriate to the analysis of lower thermospheric wind data recorded by global-scale networks of ground-based instruments are discussed. The S-transform technique is shown to be effective in the analysis of the main features of travelling planetary waves and this method is applied to the time series of horizontal-velocity data obtained during the DYANA campaign (January–March, 1990). The analysis reveals strongly transient behavior of the day-to-day lower thermosphere wind variations, as well as their specific longitudinal structure. In particular, it was found that the revealed quasi-15 day and quasi-5 day wind oscillations may be described as transient westwardpropagating waves with zonal wavenumber s = 1, while an oscillation with the a period near 7 days is tentatively identified as having a wavenumber s = 0.