Haifei Li

An E-learning Ecosystem Based on Cloud Computing Infrastructure

Recently the research community has believed that an e-learning ecosystem is the next generation e-learning. However, the current models of e-learning ecosystems lack the support of underlying infrastructures, which can dynamically allocate the required computation and storage resources for e-learning ecosystems. Cloud computing is a promising infrastructure which provides computation and storage resources as services. Hence, this paper introduces Cloud computing into an e-learning ecosystem as its infrastructure. In this paper, an e-learning ecosystem based on Cloud computing infrastructure is presented. Cloud computing infrastructure and related mechanisms allow for the stability, equilibrium, efficient resource use, and sustainability of an e-learning ecosystem.

On automated e‐business negotiations: Goal, policy, strategy, and plans of decision and action

In recent years, there has been increasing interest in automated e‐business negotiations. The automation of negotiation requires a decision model to capture the negotiation knowledge of policymakers and negotiation experts so that the decision‐making process can be carried out automatically. Current research on automated e‐business negotiations has focused on defining low‐level tactics (or negotiation rules) so that automated negotiation systems can carry out automated negotiation processes. These low‐level tactics are usually defined from a technical perspective, not from a business perspective. There is a gap between high‐level business negotiation goals and low‐level tactics. In this article, we distinguish the concepts of negotiation context, negotiation goals, negotiation strategy, and negotiation tactics and introduce a formal decision model to show the relations among these concepts. We show how high‐level negotiation goals can be formally mapped to low‐level tactics that can be used to affect the behavior of a negotiation system during the negotiation process. In business, a business organization faces different negotiation situations (or contexts) and determines different sets of goals for different negotiation contexts. In our decision model, a business policymaker sets negotiation goals from different perspectives, which are called goal dimensions. A negotiation policy is a functional mapping from a negotiation context to some quantitative measures (or goal values) for the goal dimensions to express how competitive the policymaker wants to reach that set of goals. A negotiation expert who has the experience and expertise to conduct negotiations would define the negotiation strategies needed for reaching the negotiation goals. Formally, a negotiation strategy is a functional mapping from a set of goal values to a set of decision‐action rules that implement negotiation tactics. The selected decision‐action rules can then be used to control the execution of an automated negotiation system, which conducts a negotiation on behalf of a business organization.

An overlay multicast protocol for live streaming and delay-guaranteed interactive media

In many collaborative multimedia applications, there is often a requirement for simultaneously supporting live streaming and shareable interaction. A major challenge in designing such an application by overlay multicast is how to simultaneously provide scalable live streaming and delay-guaranteed interactive media. Live streaming by overlay multicast incurs additional application-layer latency, which conflicts with the delay-sensitive property of interactive media. To handle this dilemma, in this paper, we propose a layered degree-constrained overlay multicast protocol, which organizes the overlay multicast tree as a layered degree-constrained core tree and an extended tree. The core tree maintains available resources in its top layers for subsequent two-way interaction, whereas the extended tree expands the core tree for one-way live streaming. Our simulation and experimental results show that the proposed overlay multicast protocol can simultaneously provide delay-guaranteed interactive media as well as scalable live streaming.

The IDEAL approach to Internet-based negotiation for e-business

With the emergence of e-business as the next killer application for the Web, automating bargaining-type negotiations between clients (i.e., buyers and sellers) has become increasingly important. With IDEAL (Internet based Dealmaker for e-business), we have developed an architecture and framework, including a negotiation protocol, for automated negotiations among multiple IDEAL servers. The main components of IDEAL are a constraint satisfaction processor (CSP) to evaluate a proposal, an Event-Trigger-Rule (ETR) server for managing and triggering the execution of rules which make up the negotiation strategy (rules can be updated at run-time to deal with the dynamic nature of negotiations), and a cost-benefit analysis to help in the selection of alternative strategies. We have implemented a fully functional prototype system of IDEAL to demonstrate automated negotiations among buyers and suppliers participating in a supply chain.

A united approach to discover multimedia Web services

Web services technology has been making steady progress since its initial emergence in the beginning of this century. Since multimedia data have become ubiquitous on the Internet, it is not surprising that multimedia Web services have been receiving attention by the Web services community. On the Web services platform, UDDI is the current de facto service discovery approach. However, researchers have noticed that the UDDI business model has not really achieved its designated goal. We have proposed an approach to complement UDDI with WSIL in the Web services discovery. The idea behind Unified Web Service Discovery (UWSD) is to use both the brokering-based approach and the trust-based approach in Web services discovery. Further, UWSD is designed for handling multimedia service discovery with specific QoS considerations. The services discovered by UWSD are separated into two groups. The first group contains a relatively limited number of services that are trustworthy and guaranteed. The second group contains a large number of services, but the content is not guaranteed to be trustworthy. A markup language is also designed to facilitate the discovery process. We believe that the UWSD approach can better meet the current demand of multimedia Web services discovery.

Jampots: A Mashup System towards an E-learning Ecosystem

Although E-Learning has grown into a revolutionary way of learning and is currently widely accepted, it still faces many problems, especially in its implementations. The research community has believed that an E-Learning ecosystem is the next generation E-Learning. Nowadays, the current trend of Web 2.0 has a strong impact on E-Learning. In this paper, mashups are used to build an E-Learning ecosystem. A mashup approach to an E-Learning ecosystem enhances the flourish and sustainability of E-Learning in a productive and cost-effective way. This paper describes the concepts of vertical stack, users and operations in a mashup E-Learning ecosystem. A prototype system, named Jampots, has been built. Jampots has features such as openness, reusability, lightweight structure, end user-orientation and self-regulation.

Combining Adaptive Filtering and IF Flows to Detect DDoS Attacks within a Router

Traffic matrix-based anomaly detection and DDoS attacks detection in networks are research focus in the network security and traffic measurement community. In this paper, firstly, a new type of unidirectional flow called IF flow is proposed. Merits and features of IF flows are analyzed in detail and then two efficient methods are introduced in our DDoS attacks detection and evaluation scheme. The first method uses residual variance ratio to detect DDoS attacks after Recursive Least Square (RLS) filter is applied to predict IF flows. The second method uses generalized likelihood ratio (GLR) statistical test to detect DDoS attacks after a Kalman filter is applied to estimate IF flows. Based on the two complementary methods, an evaluation formula is proposed to assess the seriousness of current DDoS attacks on router ports. Furthermore, the sensitivity of three types of traffic (IF flow, input link and output link) to DDoS attacks is analyzed and compared. Experiments show that IF flow has more power to expose anomaly than the other two types of traffic. Finally, two proposed methods are compared in terms of detection rate, processing speed, etc., and also compared in detail with Principal Component Analysis (PCA) and Cumulative Sum (CUSUM) methods. The results demonstrate that adaptive filter methods have higher detection rate, lower false alarm rate and smaller detection lag time.

A Segment-Based Storage and Transcoding Trade-off Strategy for Multi-version VoD Systems in the Cloud

Multi-version video-on-demand (VoD) providers either store multiple versions of the same video or transcode video to multiple versions in real time to offer multiple-bitrate streaming services to heterogeneous clients. However, this could incur tremendous storage cost or transcoding computation cost. There have been some works regarding trading off between transcoding and storing whole videos, but they did not take into account video segmentation and internal popularity. As a result, they were not cost-efficient. This paper introduces video segmentation and proposes a segment-based storage and transcoding trade-off strategy for multi-version VoD systems in the cloud. First, we split each video into multiple segments depending on the video internal popularity. Second, we describe the transcoding relationships among versions using a transcoding weighted graph, which can be used to calculate the version-aware transcoding cost from one version to another. Third, we take the video segmentation, version-aware transcoding weighted graph, and video internal popularity into account to propose a storage and transcoding trade-off strategy, which stores multiple versions of popular segments and transcodes unpopular segments. We then formulate it as an optimization problem and present a heuristic divide-and-conquer algorithm to get an approximate optimal solution. Finally, we conduct extensive simulations to evaluate the solution; the results show that it can significantly lower the storage and transcoding cost of multi-version VoD systems.

Designing privacy policies for adopting RFID in the retail industry

Radio frequency identification (RFID) technologies can potentially improve the productivity of retailers. In this paper, we propose a role-based, enterprise-level, RFID-oriented privacy authorization model for supporting the privacy policies in utilizing RFID in retail industry.

An Emotion Regulation Model in an E-Learning Environment

Emotions play an important role in an e-learning process. Optimal emotions can enhance learning enthusiasm, but negative emotions can suppress learning’s interest. According to the basic emotion regulation theory, the paper proposes a model of emotion regulation, and provides an optimal mood to learners in an e-Learning environment. The model evaluates an e-learner’s current emotions with emotional lexicon and semantic rules, and uses the emotion regulation strategy scale to determine the learner’s strategy of emotional regulation, then uses specific adjustments to remedy negative emotions presented to the e-learner. Finally, the paper presents a prototype that has been built to validate the model in an emotion-chat system.