Global Network Resource Research Articles

Exploring the born global firms from the Asia Pacific

AbstractThis study aims to synthesize the extant research on the Born Global Firms (BGF) phenomenon, mainly focusing on the Asia Pacific region (APAC). We adopt the systematic literature review methodology to identify the main context-specific drivers (‘success factors’) and outcomes of BGFs’ accelerated internationalization and the challenges they face before, during, and after global expansion. The analysis and evaluation of relevant studies reveal several critical variables that need to be extensively investigated (separately and in tandem) by scholars in order to advance existing theories and, at the same time, explain the out-of-pattern behaviors of BGFs outside the typical ‘Western economy’ context. Among the core variables are international entrepreneurial orientation and culture adoption, organizational learning and networking strategies, global strategic human capital and network resources (as predictors of BGFs’ international performance) and resource constraints, institutional and cultural distances, and liabilities of newness, smallness, foreignness, outsidership, and emergingness (as constraints to BGFs’ success). By identifying the research gaps and proposing a comprehensive framework with promising avenues for future research into the phenomenon of BGFs from the APAC region, this study helps enhance our understanding of the global strategy formation and execution processes of international new ventures from ‘the East’ and stimulate interdisciplinary dialogue between international business, strategy, and entrepreneurship scholars.

A rule-based modeling approach for network application availability assessment under dynamic network restoration scheme

The efficient and accurate assessment method for application availability is essential for network operators to make the resilience-cost trade-off policy. However, the backup path of application is dynamically discovered upon both other application requests and global network resource distribution under network restoration scheme, makes the current analytical network availability models difficult for assessing application availability effectively in large-scale network scenarios. This paper proposed a rule-based modeling approach to capture application resilience behavior and measure the uncertainties during dynamic restoration process. Firstly, we propose an evolution object formalism for modeling the attributes of both logical application and network infrastructure. Secondly, the network evolution condition model is proposed to describe the failure modes of individual components. Finally, the network evolution rule is proposed, which utilizes general graph algorithm and resource match function as local rules to determine application restoration resource contention outcomes during the state transition. Through simulations, the proposed approach evaluates application availability in terms of recovery time during system state transition controlled by the rules. The effectiveness of the proposed approach is verified to an actual optical network case under two typical network restoration schemes and compare its accuracy against two analytical approaches based on RBD (Reliability Block Diagram) and Markov Chain. The sensitivity results reveal that link capacity has a more significant impact on application availability than link failures.

Distributed optimal resource allocation with second‐order multi‐Agent systems

AbstractThis paper studies the resource allocation problems with second‐order multi‐agent systems under the constraint of the global network resource. A novel distributed continuous‐time algorithm, which only uses the local information, is proposed. By using matrix transform and differential inequality technique, the exponential convergence is obtained under the undirected and connected graph. To reduce energy consumption and communication costs, a distributed event‐triggered algorithm is designed. It is proved that not only this algorithm converges exponentially to the optimal allocation, but also the event‐triggered time sequence does not exhibit Zeno‐behavior. Finally, numerical examples illustrate the effectiveness of theoretical results.

Distributed resource allocation algorithm for second-order multi-agent systems with external disturbances

This paper focuses on the distributed resource allocation problem of a second-order multi-agent system with external disturbances. The global network resource equality constraint is considered. A distributed algorithm with an exponential convergence rate is proposed based on an internal model for a known bounded disturbance. By using the active disturbance approach to design a reduced-order extended state observer, the proposed algorithm is modified to reject an unknown external disturbance. Moreover, exponential convergence is achieved through the Lyapunov theory when the disturbance is constant. When the differential of the disturbance is bounded, by adjusting the control parameter of the observer, the proposed algorithm converges to an arbitrarily small neighbourhood of the optimal solution. Finally, our simulation results demonstrate the effectiveness of our proposed algorithm.

Minimizing Subtle Errors in Computing Information of TCAM by Partial “N” Search Key Implementation

The primary memory of the computer gets corrupted due to microparticles that possess a great deal of energy. This causes transient kind of errors and it is called subtle errors. High corruption of data in computer systems has been occurred because of these errors. Major sources of subtle errors include ionic particles, huge radiations say example alpha, beta and gamma rays, protons, neutrons etc., When TCAM configuration changes from 120 nm to 20 nm technology, there was a drastic increase in subtle errors more than multiples of eight. Devices operated in low power regions are more prone to subtle errors. Memory storage devices like secondary memory element called cache, registers are more feasible to subtle errors. 1 Behavior of subtle errors never damage circuit configuration but changes the information content leading to erroneous data. The proposed architecture is called N-SEARCH KEY TCAM, where in this system, it has been predicted that occurrence of subtle errors are very small. This innovative method of detecting and correcting both single and burst type of subtle errors has many modules like TCAM, Multiplexer, control circuit and Error correction code frame. Moreover, the proposed architecture N-SEARCH KEY ternary memory uses a special LUT for matching process. A key named Search key was generated which contains don’t care bits for matching subtle errors. Unlike regular TCAM, this design uses sequential LUT which enhances matching time of order [Formula: see text](wnlog2[Formula: see text]. Initially, proposed scheme have been used to find single bit subtle errors by changing forbearance factor ([Formula: see text] and chances of occurrence of error among TCAM information. The design was enhanced to detect multiple subtle errors and rectified the same. If match not occurs with predetermined information, then IP filter forbids the unauthorized users from using global network resources, thus providing better information security. By the proposed method, number of improper segregation ratio decreases with increase in Forbearance ratio parameter and time required to detect and correct the same is also considerably reduced. By controlling the forbearance factor [Formula: see text], the best duration schemes can be chosen. Through the given architecture, average time consumption for error checking of subtle errors would range from 0.6 to 0.7 [Formula: see text]s.

Selected benefits and threats arising from internet use by households and enterprises in Poland with respect to the COVID-19 pandemic

The internet has revolutionised the world over the past half of a century, and the COVID-19 pandemic has contributed to an increase in its importance. Although the global network brings with it more advantages than disadvantages, its existence also causes certain threats which have an impact on the life of Polish households and operations of Polish enterprises. This paper is theoretical and empirical in nature. Its aim is to explore the relationship between the internet and the COVID-19 pandemic, i.e. the time household members spend online. The impact of the two factors on survival in the market was examined in the case of enterprises. Moreover, the subjectively most important benefits and threats arising from the global network consumption in the opinion of the business entities mentioned above were illustrated. According to the respondents, facilitating communication is the main advantage of the internet (33.33%), whereas the spreading of hate on the internet is the major threat associated with its use (24.17%). The main benefit derived from the global network resources by enterprises is the possibility of obtaining raw materials from the most profitable sources (28.40%), whereas the major threat identified by them is that a negative opinion published on the internet can weaken the financial standing of a company or even make it disappear from the market (55.56%). Nearly 60% of household members found themselves spending more time online during the COVID-19 pandemic. Nearly 94% of the entrepreneurs who use the internet in running their businesses admitted that it helped them to keep their business in the market during the pandemic.

International federation of genomic medicine databases using GA4GH standards

We promote a shared vision and guide for how and when to federate genomic and health-related data sharing, enabling connections and insights across independent, secure databases. The GA4GH encourages a federated approach wherein data providers have the mandate and resources to share, but where data cannot move for legal or technical reasons. We recommend a federated approach to connect national genomics initiatives into a global network and precision medicine resource.

Nonsmooth Resource Allocation of Multiagent Systems With Disturbances: A Proximal Approach

This article aims to solve the nonsmooth resource allocation problem in the presence of a global network resource constraint and local set constraints in the framework of multiagent system optimization. It is assumed that multiagent systems are subject to some external disturbances, and the control inputs of the agents satisfy Lispchitz continuity. These two distinguished features render the existing distributed optimization algorithms, especially the subgradient-based algorithms inapplicable due to the employment of discontinuity of subgradients. To solve such a challenging resource allocation problem, a new kind of continuous-time proximal algorithm is designed with the aid of convex optimization theory and the internal-model technique. The proximal algorithm is further augmented by introducing an event-based communication scheme such that the continuous-time communication among the agents is avoided successfully. The theoretical analysis shows that the multiagent systems under the proposed algorithms can converge to the optimal solution of the considered problem, while the external disturbances are rejected. Besides, the Zeno behavior can be excluded for the proximal algorithm with event-based communication. Finally, the numerical simulations are given to verify the established theoretical results.

SDN-based offloading policy to reduce the delay in fog-vehicular networks

Integrating fog computing with vehicular networks led to the rapidly growing demands of vehicle applications regarding computation-intensive and low response time with meeting the request deadline. The limited resources of the fog node have made it unable to meet the demands of such applications. Offloading the requests to other Off-Load Destination (OLD) is a suitable solution for the fog node to deal with these demands. Nonetheless, this simultaneously faces two challenges. The first challenge is the offloading to a nearby fog node which stills not the fully efficient choice when this nearby fog node is busy. The second challenge is the selection decision of the optimal OLD where the fog node incurs additional burden through getting status information of all neighboring fog nodes, affecting the selection decision, which is why it may not fulfill the request deadline. To solve the first challenge, a new hybrid offloading architecture has been proposed, where the underutilized resources of Vehicular Fog Computing (VFC) are joined with the cloud to be an OLD, thus increase the processing chance of the offloaded requests. The second challenge has been solved by optimizing the selection decision of the fog node via taking the global network resources benefit of Software Defined Network (SDN) in the proposed offloading architecture to design an SDN-based offloading policy. The selection decision problem is formulated as a Binary-Linear Programming and solved by CPLEX software. The simulation results show that our proposed improves the performance of the fog node by providing less response time and significantly outperforming other offloading policies.

Cooperative channel assignment for VANETs based on multiagent reinforcement learning

Dynamic channel assignment (DCA) plays a key role in extending vehicular ad-hoc network capacity and mitigating congestion. However, channel assignment under vehicular direct communication scenarios faces mutual influence of large-scale nodes, the lack of centralized coordination, unknown global state information, and other challenges. To solve this problem, a multiagent reinforcement learning (RL) based cooperative DCA (RL-CDCA) mechanism is proposed. Specifically, each vehicular node can successfully learn the proper strategies of channel selection and backoff adaptation from the real-time channel state information (CSI) using two cooperative RL models. In addition, neural networks are constructed as nonlinear Q-function approximators, which facilitates the mapping of the continuously sensed input to the mixed policy output. Nodes are driven to locally share and incorporate their individual rewards such that they can optimize their policies in a distributed collaborative manner. Simulation results show that the proposed multiagent RL-CDCA can better reduce the one-hop packet delay by no less than 73.73%, improve the packet delivery ratio by no less than 12.66% on average in a highly dense situation, and improve the fairness of the global network resource allocation.

USE OF IT FOR FUTURE FOREIGN LANGUAGE TEACHERS’ LINGUISTIC SELF-EDUCATION

The article substantiates that large-scale implementation of information technologies will facilitate methodological support of future foreign language teachers’ linguistic self-education.
 The main functions and advantages of the author’s multimedia training package “English for Self-Education”, designed to support future foreign language teachers’ linguistic self-educational activities, are characterized. It is defined that the package is an open-ended multipurpose programmatic learning system, containing didactic, methodological, informational and reference materials. The package is based on general pedagogical, ergonomic and specific principles of informatization of education.
 It has a dual structure, which includes two levels. The first level contains 1) lexical-informational component that provides working with lexical and theoretical material, 2) training element, which enables practicing knowledge and skills, as well as mastering methods and means of autonomous managing, regulating and correcting the process of linguistic self-education, 3) control aspect, which allows realizing independent monitoring and evaluating the degree and quality of acquired knowledge and skills. The second level considerably extends didactic possibilities and educational resources of the package. It covers a wide range of extra learning materials of theoretical and practical nature that are available both in the package itself and beyond its limits through providing the access to the “virtual reality” within external resources of global network. All the above not only makes for activating students’ cognitive activity but also significantly enriches their language and sociocultural practice.
 The package enables comprehensive independent study of a foreign language, exercising self-diagnostics in order to detect gaps in the student’s foreign-language competence, performing intensive linguistic self-educational activities, constant monitoring the level of autonomously mastered foreign-language material, carrying out search for information, etc.
 Thus, the package provides optimal conditions for future foreign language teachers’ linguistic self-educational activities. Students have an opportunity to actualize the adaptive algorithm of building the individual trajectory of linguistic self-education in accordance with their psychological features and personal educational needs.
 It is shown that working with the package results in students’ receiving an external and internal educational products, namely improving foreign-language knowledge and skills, along with gaining personal experience of linguistic self-educational activities.
 It is grounded by the example of the proposed package that comprehensive use of IT significantly optimizes the process of linguistic self-education.

A sensing layer network resource allocation model based on trusted groups

There are many heterogeneous sensing nodes in the sensing layer of the Internet of Things, and the amount of data transmission is huge, which puts high requirements on the allocation of network bandwidth. At the same time, untrusted sensing nodes maliciously invade network resources. Therefore, how to confirm whether a sensing node is trusted and reasonably allocate network resources is an urgent problem to be solved. To resolve this issue, this paper proposes a sensing network resource allocation model based on trusted groups. Through the sensing node computing environment and behavior measurement, we can identify and exclude untrusted nodes, so the trusted group can be built. Then the network resources are distributed from a global perspective. Based on the available bandwidth of the link, a network resource fusion model of IPv4 and IPv6 is proposed. On this basis, a global network resource allocation model is further proposed. Afterwards, real-time monitoring of data transmission behavior ensures data security during transmission. Simulation experiments show that this mechanism can effectively optimize the bandwidth allocation in the data transmission process and has little effect on the running efficiency of existing network applications. At the same time, it can effectively guarantee the trust of nodes and achieve trusted data transmission.

Toward Fine-Grained, Privacy-Preserving, Efficient Multi-Domain Network Resource Discovery

Multi-domain network resource reservation systems are being deployed, driven by the demand and substantial benefits of providing predictable network resources. However, a major lack of existing systems is their coarse granularity, due to the participating networks’ concern of revealing sensitive information, which can result in substantial inefficiencies. This paper presents Mercator, a novel multi-domain network resource discovery system to provide fine-grained, global network resource information, for collaborative sciences. The foundation of Mercator is a resource abstraction through algebraic-expression enumeration ( i.e. , linear inequalities/equations), as a compact representation of multiple properties of network resources ( e.g. , bandwidth, delay, and loss rate) in multi-domain networks. In addition, we develop an obfuscating protocol, to address the privacy concerns by ensuring that no participant can associate the algebraic expressions with the corresponding member networks. We also introduce a super-set projection technique to increase Mercator’s scalability. We implement a prototype Mercator and deploy it in a small federation network. We also evaluate the performance of Mercator through extensive experiments using real topologies and traces. Results show that Mercator 1) efficiently discovers available networking resources in collaborative networks on average four orders of magnitude faster, and allows fairer allocations of network resources; 2) preserves the member networks’ privacy with little overhead; and 3) scales to a collaborative network of 200 member networks.

Novel Node-Ranking Approach and Multiple Topology Attributes-Based Embedding Algorithm for Single-Domain Virtual Network Embedding

Network virtualization (NV) is a promising approach to remove the ossification of current Internet. Virtual network embedding (VNE) is the key issue in NV which efficiently and effectively maps various of virtual networks (VNs), with different node and link resource requests, onto the shared substrate network(s) with finite underlying resources. Previous VNE algorithms in the literature are mostly heuristic. Single network topology attribute and each node’s local resources are assisted to rank nodes in most heuristic algorithms, leading to inefficient resource utilization of substrate network in the long run. To deal with this issue, we propose the network topology attribute and network resource-considered algorithm (VNE-NTANRC). The VNE-NTANRC algorithm adopts a novel node-ranking approach to rank all substrate and virtual nodes before embedding each given VN. The novel node-ranking approach has two subapproaches and considers five important network topology attributes and global network resources altogether. One subapproach is able to calculate all node values (NoV) directly. The other subapproach, stimulating from the Google PageRank website algorithm, enables to calculate NoVs in a stable state. Simulation results reveal that VNE-NTANRC algorithm outperforms typical and latest heuristic algorithms, only considering single network topology attribute and local resources.

A 2-Layers Virtual Network Mapping Algorithm Based on Node Attribute and Network Simplex

Network virtualization is one of the most important techniques to overcome Internet ossification, which can enable multiple networks to run on a common infrastructure. Virtual network mapping is a key process of network virtualization to efficiently map virtual network onto the substrate network within constraints of node and link resource. However, previous VNM heuristic algorithms completely separate the node mapping stage from link mapping stage and ignore the effect of link mapping results on physical node ranking, which may lead to higher mapping cost and distributed distribution of virtual nodes on the substrate network. The shortest path algorithm is used at most to resolve virtual link mapping which results in longer mapping time. To address these issues, a two-layer virtual network mapping algorithm named simplex-VNM is proposed based on node attribute and network simplex in this paper. In node mapping layer, a new node ranking approach which considers topology attributes, global network resources, and mapped physical node information provides candidate nodes and node mapping cost for link mapping layer. Then, in link mapping layer, network simplex algorithm which has smaller time complexity compared to traditional shortest path algorithms has been introduced to find the optimal link mapping solution under the result of node mapping layer. Finally, according to the results of two layers, the virtual node and relevant links will be mapped with minimal total mapping cost. Extensive simulation results have demonstrated that our proposed method behaves better than four other algorithms that consider node attribute and use shortest path algorithm in terms of total mapping cost and mapping time.

Distributed event-triggered algorithm for optimal resource allocation of multi-agent systems

This paper is concerned with solving the distributed resource allocation optimization problem by multi-agent systems over undirected graphs. The optimization objective function is a sum of local cost functions associated to individual agents, and the optimization variable satisfies a global network resource constraint. The local cost function and the network resource are the private data for each agent, which are not shared with others. A novel gradient-based continuous-time algorithm is proposed to solve the distributed optimization problem. We take an event-triggered communication strategy and an event-triggered gradient measurement strategy into account in the algorithm. With strongly convex cost functions and locally Lipschitz gradients, we show that the agents can find the optimal solution by the proposed algorithm with exponential convergence rate, based on the construction of a suitable Lyapunov function. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed scheme.

A Efficient Mapping Algorithm With Novel Node-Ranking Approach for Embedding Virtual Networks

Virtual network embedding (VNE) problem has been widely accepted as an important aspect in network virtualization (NV) area: how to efficiently embed virtual networks, with node and link resource demands, onto the shared substrate network that has finite network resources. Previous VNE heuristic algorithms, only considering single network topology attribute and local resources of each node, may lead to inefficient resource utilization of the substrate network in the long term. To address this issue, a topology attribute and global resource-driven VNE algorithm ( VNE-TAGRD ), adopting a novel node-ranking approach, is proposed in this paper. The novel node-ranking approach, developed from the well-known Google PageRank algorithm, considers three essential topology attributes and global network resources information before conducting the embedding of given virtual network request (VNR). Numerical simulation results reveal that the VNE-TAGRD algorithm outperforms five typical and latest heuristic algorithms that only consider single network topology attribute and local resources of each node, such as long-term average VNR acceptance ratio and average revenue to cost ratio.

Initialization-free distributed algorithms for optimal resource allocation with feasibility constraints and application to economic dispatch of power systems

In this paper, the distributed resource allocation optimization problem is investigated. The allocation decisions are made to minimize the sum of all the agents’ local objective functions while satisfying both the global network resource constraint and the local allocation feasibility constraints. Here the data corresponding to each agent in this separable optimization problem, such as the network resources, the local allocation feasibility constraint, and the local objective function, is only accessible to individual agent and cannot be shared with others, which renders new challenges in this distributed optimization problem. Based on either projection or differentiated projection, two classes of continuous-time algorithms are proposed to solve this distributed optimization problem in an initialization-free and scalable manner. Thus, no re-initialization is required even if the operation environment or network configuration is changed, making it possible to achieve a “plug-and-play” optimal operation of networked heterogeneous agents. The algorithm convergence is guaranteed for strictly convex objective functions, and the exponential convergence is proved for strongly convex functions without local constraints. Then the proposed algorithm is applied to the distributed economic dispatch problem in power grids, to demonstrate how it can achieve the global optimum in a scalable way, even when the generation cost, or system load, or network configuration, is changing.

독일청소년스포츠연맹(Deutsche Sportjugend) 사례 분석을 통한 청소년 스포츠활동 활성화 방안

Purpose: The purpose of this study was to explore the current status of German youth sports activities and strategies through the Deutsche Sportjugend (DSJ). Methods: Qualitative research methods were used to analyze the data. Research data from German Olympic Sports Confederation (DOSB) and Web portal (http://www.dsj.de) were collected for German youth sports programs. Results: The findings of this study are as follows: DSJ, founded in 2006 under DOSB, was a primary organization that manages and operates German youth sports activities. With the vision of “We empower youth through sports activities,” the DSJ aimed at enriching network system between schools and sports club, encouraging social activities through diverse sports programs, fostering prospective human resources as well as education of international cooperation, Olympic research, anti-doping and anti-violence. Conclusion: DSJ promoted the relationship between community and sports club and network system between federal adnl local government. DSJ enlarged the opportunities for youth to experience at international stage through sports. DSJ also inspired youth to learn citizenship, the culture of respect and consideration of underprivileged class, and raised the emphasis on creating jobs availability for youth, fostered the global network and human resource through sports.

A quantum network of clocks

The development of precise atomic clocks has led to many scientific and technological advances that play an increasingly important role in modern society. Shared timing information constitutes a key resource for positioning and navigation with a direct correspondence between timing accuracy and precision in applications such as the Global Positioning System (GPS). By combining precision metrology and quantum networks, we propose here a quantum, cooperative protocol for the operation of a network consisting of geographically remote optical atomic clocks. Using non-local entangled states, we demonstrate an optimal utilization of the global network resources, and show that such a network can be operated near the fundamental limit set by quantum theory yielding an ultra-precise clock signal. Furthermore, the internal structure of the network, combined with basic techniques from quantum communication, guarantees security both from internal and external threats. Realization of such a global quantum network of clocks may allow construction of a real-time single international time scale (world clock) with unprecedented stability and accuracy.