Analyzing the performance and fairness of BitTorrent-like networks using a general fluid model

In this paper, a general fluid model is developed to study the performance and fairness of BitTorrent-like networks. The fluid model incorporates two important features previously isolated from system performance models, user settings with multiple groups and inter-group data exchange induced by the choking algorithm. Our numerical results point out some key parameters of performance, such as the staying time of seeders. Generally, selfish behavior does not receive equal performance degradation, and in some scenarios users have strong incentives of free-riding. We also find content delivery can be greatly deterred when malicious free-riders are overwhelming.     

D-HOCS: an algorithm for discovering the hierarchical overlapping community structure of a social network

Social networks often demonstrate a hierarchical organization, with communities embedded within other communities; moreover, nodes can be shared between different communities, i.e. communities in social networks may be overlapping. In this paper, we define a hierarchical overlapping community structure to present overlapping communities of a social network at different levels of granularity. Discovering the hierarchical overlapping community structure of a social network can provide us a deeper understanding of the complex nature of social networks. We propose an algorithm, called D-HOCS, to derive the hierarchical overlapping community structure of social networks. Firstly, D-HOCS generates a probability transition matrix by applying random walk to a social network, and then trains a Gaussian Mixture Model using the matrix. Further D-HOCS derives overlapping communities by analyzing mean vectors of the Gaussian mixture model. Varying the number of components, D-HOCS repeatedly trains the Gaussian mixture model, detecting the overlapping communities at different levels of granularity. Organizing the overlapping communities into a hierarchy, D-HOCS can finally obtain the hierarchical overlapping community structure of the social network. The experiments conducted on synthetic and real dataset demonstrate the feasibility and applicability of the proposed algorithm. We further employ D-HOCS to explore Enron e-mail corpus, and obtain several interesting insights. For example, we find out a coordinator who coordinated many sections of the Enron Corporation to complete an important task during first half of 2001. We also identify a community that corresponds to a real organization in Enron Corporation.     

Competition in wearable device market: the effect of network externality and product compatibility

The rapid growth in consumer adoption of wearable devices has garnered the attention of both practitioners and academia. Competition in the wearable device market is both substantial and complicated. In this study, we investigate the impact of network externality on wearable device competition in a two-dimensional product differentiation model. We consider a market that has a broad array of products (horizontal differentiation) and various quality levels (vertical differentiation). We study two types of network externalities according to the product compatibility in two types of market structures. Our model indicates that firm profits are decreased by network externalities in horizontal dominance. Network externality also increases (decreases) the higher-quality (lower-quality) firm’s profit in vertical dominance. Moreover, firms should ensure that their products are incompatible with those of rivals when network externality is large, and they should release compatible products when network externality is small in horizontal dominance. Firms should always ensure that their products are compatible with those of competitors in vertical dominance.     

用于高速列车移动网络的资源分配实时算法

误码率高、频繁中断的高速列车移动场景宜采用多宿主容迟网络。但其资源分配计算复杂,实时性较差。基于效用差分法设计初始化过程资源分配算法,以保证过程中每一步的效用单调不减,算法时间复杂度降至O(n)。     

贝氏体型白口铸铁组织结构及其抗磨料磨损特性的研究

本文应用光学显微镜、电子显微镜、扫透电子显微镜和X-射线衍射仪对贝氏体型白口铸铁的组织结构和形态进行了观察和测试,同时还对上、下贝氏体在不同试验条件下的抗磨性和残余奥氏体在磨损过程中的行为进行了研究。     

Usage-based dynamic pricing of Web services for optimizing resource allocation

Web services technology is becoming an important technological trend in Web application development and integration. Based on open standards, such as SOAP, WSDL, and UDDI, Web services allow Web-based applications to communicate with each other through standardized XML messaging and to form loosely coupled distributed systems. Although the open feature of Web services benefits service providers in servicing consumers, the unlimited computing resources access of Web services to network bandwidth, storage throughput, and CPU time may lead to overexploitation of the resources when applications based on the Web services technology are widely accepted. Therefore, it is critical to optimize the operation of Web services, subject to the QoS requirements of service requests, to assure the total benefits of the service providers and the service consumers. This paper proposes a usage-based dynamic pricing approach to optimizing resource allocation of Web services in the principle of economics, and reports on a pilot implementation demonstrating the technical feasibility of the proposed approach.

How big data and analytics reshape the wearable device market – the context of e-health

The wearable device can be a key link between health care and big data and analytics (BDA). The benefits of BDA in health care have been widely acknowledged, but the uncertainty of the implementation of BDA has led some firms to hesitate in adopting this technology. In this research, we are keen to answer the key questions of whether the wearable device firms would adopt the BDA strategy, and how much effort they would put into it. We propose a competition model between the wearable device firms with and without BDA strategies, and consider the consumer’s preference towards BDA and network effects. Our model demonstrates that the investment on BDA directly affects the firm’s equilibrium price, market share and profit and at the same time, this strategy also affects the rival’s performances. When the firm with BDA strategy adopts different competition strategy: conservative or expansive, the outcomes of market are different. We also find that different market structures, fully covered and partially covered, have different impacts on the firms’ competition when the consumers have heterogeneous preference on BDA strategy.     

The nature of sellers’ cyber credit in C2C e-commerce: the perspective of social capital

With the fast evolution of e-commerce, it is getting harder for traditional credit management systems to service online businesses with diversified needs in dynamic scenarios. This paper studies the nature of cyber credit from the perspective of social capital. We propose the credit assessment model using social capital variables extracted from the reputation system of an e-commerce platform and the associated online social network. In addition, we consider the dynamic and diversified effects of online reputation on sellers’ cyber credit, and we verify the rationality of the credit assessment model through analyzing the relationship between cyber credit and social network variables. We take Alibaba C2C e-commerce market as our experimental study platform and use the social networking information from Sina’s microblogging services. We find that social capital variables can be used to effectively measure the cyber credit of online sellers in C2C businesses.     

User comments for news recommendation in forum-based social media

News recommendation and user interaction are important features in many Web-based news services. The former helps users identify the most relevant news for further information. The latter enables collaborated information sharing among users with their comments following news postings. This research is intended to marry these two features together for an adaptive recommender system that utilizes reader comments to refine the recommendation of news in accordance with the evolving topic. This then turns the traditional “push-data” type of news recommendation to “discussion” moderator that can intelligently assist online forums. In addition, to alleviate the problem of recommending essentially identical articles, the relationship (duplicate, generalization, or specialization) between recommended news articles and the original posting is investigated. Our experiments indicate that our proposed solutions provide an improved news recommendation service in forum-based social media.