Low latency IP mobility management: Protocol and analysis

Mobile IP is one of the dominating protocols that enable a mobile node to remain reachable while moving around in the Internet. However, it suffers from long handoff latency and route inefficiency. In this article, we present a novel distributed mobility management architecture, ADA (Asymmetric Double-Agents), which introduces double mobility agents to serve one end-to-end communication. One mobility agent is located close to the MN and the other close to the CN. ADA can achieve both low handoff latency and low transmission latency, which is crucial for improvement of user perceived QoS. It also provides an easy-to-use mechanism for MNs to manage and control each traffic session with a different policy and provide specific QoS support. We apply ADA to MIPv6 communications and present a detailed protocol design. Subsequently, we propose an analytical framework for systematic and thorough performance evaluation of mobile IP-based mobility management protocols. Equipped with this model, we analyze the handoff latency, single interaction delay and total time cost under the bidirectional tunneling mode and the route optimization mode for MIPv6, HMIPv6, CNLP, and ADA. Through both quantitative analysis and NS2-based simulations, we show that ADA significantly outperforms the existing mobility management protocols. © 2011 Liu et al; licensee Springer

A cooperative cellular and broadcast conditional access system for Pay-TV systems

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.The lack of interoperability between Pay-TV service providers and a horizontally integrated business transaction model have compromised the competition in the Pay-TV market. In addition, the lack of interactivity with customers has resulted in high churn rate and improper security measures have contributed into considerable business loss. These issues are the main cause of high operational costs and subscription fees in the Pay-TV systems. As a result, this paper presents the Mobile Conditional Access System (MICAS) as an end-to-end access control solution for Pay-TV systems. It incorporates the mobile and broadcasting systems and provides a platform whereby service providers can effectively interact with their customers, personalize their services and adopt appropriate security measurements. This would result in the decrease of operating expenses and increase of customers' satisfaction in the system. The paper provides an overview of state-of-the-art conditional access solutions followed by detailed description of design, reference model implementation and analysis of possible MICAS security architectures.Strategy & Technology (S&T) Lt

Reconfigurable Security: Edge Computing-based Framework for IoT

In various scenarios, achieving security between IoT devices is challenging since the devices may have different dedicated communication standards, resource constraints as well as various applications. In this article, we first provide requirements and existing solutions for IoT security. We then introduce a new reconfigurable security framework based on edge computing, which utilizes a near-user edge device, i.e., security agent, to simplify key management and offload the computational costs of security algorithms at IoT devices. This framework is designed to overcome the challenges including high computation costs, low flexibility in key management, and low compatibility in deploying new security algorithms in IoT, especially when adopting advanced cryptographic primitives. We also provide the design principles of the reconfigurable security framework, the exemplary security protocols for anonymous authentication and secure data access control, and the performance analysis in terms of feasibility and usability. The reconfigurable security framework paves a new way to strength IoT security by edge computing.Comment: under submission to possible journal publication

Design of a shared whiteboard component for multimedia conferencing

This paper reports on the development of a framework for multimedia applications in the domain of tele-education. The paper focuses on the protocol design of a specific component of the framework, namely a shared whiteboard application. The relationship of this component with other components of the framework is also discussed. A salient feature of the framework is that it uses an advanced ATM-based network service. The design of the shared whiteboard component is considered representative for the design as a whole, and is used to illustrate how a flexible protocol architecture utilizing innovative network functions and satisfying demanding user requirements can be developed

Early aspects: aspect-oriented requirements engineering and architecture design

This paper reports on the third Early Aspects: Aspect-Oriented Requirements Engineering and Architecture Design Workshop, which has been held in Lancaster, UK, on March 21, 2004. The workshop included a presentation session and working sessions in which the particular topics on early aspects were discussed. The primary goal of the workshop was to focus on challenges to defining methodical software development processes for aspects from early on in the software life cycle and explore the potential of proposed methods and techniques to scale up to industrial applications

Whole-Chain Recommendations

With the recent prevalence of Reinforcement Learning (RL), there have been tremendous interests in developing RL-based recommender systems. In practical recommendation sessions, users will sequentially access multiple scenarios, such as the entrance pages and the item detail pages, and each scenario has its specific characteristics. However, the majority of existing RL-based recommender systems focus on optimizing one strategy for all scenarios or separately optimizing each strategy, which could lead to sub-optimal overall performance. In this paper, we study the recommendation problem with multiple (consecutive) scenarios, i.e., whole-chain recommendations. We propose a multi-agent RL-based approach (DeepChain), which can capture the sequential correlation among different scenarios and jointly optimize multiple recommendation strategies. To be specific, all recommender agents (RAs) share the same memory of users' historical behaviors, and they work collaboratively to maximize the overall reward of a session. Note that optimizing multiple recommendation strategies jointly faces two challenges in the existing model-free RL model - (i) it requires huge amounts of user behavior data, and (ii) the distribution of reward (users' feedback) are extremely unbalanced. In this paper, we introduce model-based RL techniques to reduce the training data requirement and execute more accurate strategy updates. The experimental results based on a real e-commerce platform demonstrate the effectiveness of the proposed framework.Comment: 29th ACM International Conference on Information and Knowledge Managemen