Yuemei Xu

A novel cache size optimization scheme based on manifold learning in Content Centric Networking

Content Centric Networking (CCN) is an emerging network architecture, shifting from an end-to-end connection to a content centric communication model. Each router in CCN has a content store module to cache the chunks passed by, and is arranged in an arbitrary network topology. It is important to allocate an appropriate cache size to each router in order to both improve the network performance and reduce the economic investment. Previous works have proposed several heterogeneous cache allocation schemes, but the gain brought by these schemes is not obvious. In this paper, we introduce a data mining method into the cache size allocation. The proposed algorithm uses manifold learning to analyze the regularity of network traffic and user behaviors, and classify routers based on their roles in the content delivery. Guided by the manifold learning embedding results, a novel cache size optimization scheme is developed. Extensive experiments have been performed to evaluate the proposed scheme. Simulation results show that the proposed scheme outperforms the existing cache allocation schemes in CCN.

Dislocation structure in a single-crystal nickel-base superalloy during low cycle fatigue

An investigation of dislocation structure in a single crystal nickel-base superalloy during low cycle fatigue (LCF) at 760 °C has been conducted. Dislocation bands are found to be produced first in the matrix in some defined directions. With an increase in cycle numbers, there is an increase in dislocation density in the bands and a decrease in the spacing between the bands, leading to the formation of the dislocation walls or cells. Sometimes, three-dimensional (3-D) networks are formed also by the interaction between two sets of parallel dislocations. The Burgers vectors of the dislocations in the network are 1/2 〈110〉. Clustering of dislocations eventually occurs at γ′/γ interfaces because of the obstruction of the γ′-particles to moving dislocations. Most of the dislocations observed in the γ′-phases are in the form of superdislocations. Dislocation shearing through theγ′-phase was found occasionally. Reprecipitation of γ′-phase induced by strain was also observed in the present study.

A dominating-set-based collaborative caching with request routing in content centric networking

Content Centric Networking (CCN) is a new emerging network architecture, shifting from an end-to-end connection to a content-centric communication model. A number of content-oriented characteristics, such as name-based routing, arbitrary topology and ubiquitous caching make caching in CCN different from the previous works. In this paper, we focus on the collaborative caching in CCN and propose a dominating-set-based collaborative caching mechanism, which jointly considers the content placement and request routing in a tightly-couple manner. Extensive experiments have been performed to evaluate the proposed scheme. Simulation results show that the proposed CollaCache proposal outperforms the existing caching and routing mechanisms in CCN.

FORMATION AND MICROSTRUCTURE OF LOCALIZED SHEAR BAND IN A LOW-CARBON STEEL

chinese acad sci,inst mech,beijing,peoples r china.;xu, yb (reprint author), chinese acad sci,inst met res,fatigue & fracture mat lab,shenyang 110015,peoples r china

Self assembly caching with dynamic request routing for Information-Centric Networking

Information-Centric Networking (ICN) enables caching of addressable content chunks in every cache-equipped router. So it is crucial to make the cached content to be visible locally, in order to satisfy the subsequent request. We achieve this goal in this paper with a novel caching scheme, which combines the content placement with dynamic request routing by selectively creating trails along the content delivery path. In addition, in-network caching requires search or replacement of cached chunks at line-speed, which resorts to the low complexity collaborative caching scheme and limits the cache size at each network level. Coordinate with the feasible cache size allocation, the proposed scheme automatically distributes the content to the proper cache location according to its popularity. Therefore, the proposed self assembly caching scheme could reduce caching redundancy and in turn, make more efficient utilization of available cache resources. The simulation results show that the proposed scheme outperforms existing algorithms.

A Policy-Based Web Service Redundancy Detection in Wireless Sensor Networks

Wireless sensor networks (WSNs) are attractive for monitoring and gathering physical information (e.g. temperature) via lots of deployed sensors. For the applications in WSNs, Web service is one of the recommended frameworks to publish, invoke, and manage services. However, the standard Web service description language (WSDL), defines only the service input and output while ignoring the corresponding input-to-output mapping relationships. This presents a serious challenge in distinguishing services with similar input and output interface. In this paper, we address this challenge by embedding the service policy into the traditional WSDL2.0 schema to describe the input-to-output mapping relationships. The service policy is then transformed into a policy binary tree so that the similarity between different Web services can be quantitatively evaluated. Furthermore, a new service redundancy detection approach is proposed based on this similarity. Finally, the case study and experimental analysis illustrate the applicability and capability of the proposed service redundancy detection approach.

Topology-aware virtual network embedding based on closeness centrality

Network virtualization aims to provide a way to overcome ossification of the Internet. However, making efficient use of substrate resources requires effective techniques for embedding virtual networks: mapping virtual nodes and virtual edges onto substrate networks. Previous research has presented several heuristic algorithms, which fail to consider that the attributes of the substrate topology and virtual networks affect the embedding process. In this paper, for the first time, we introduce complex network centrality analysis into the virtual network embedding, and propose virtual network embedding algorithms based on closeness centrality. Due to considering of the attributes of nodes and edges in the topology, our studies are more reasonable than existing work. In addition, with the guidance of topology quantitative evaluation, the proposed network embedding approach largely improves the network utilization efficiency and decreases the embedding complexity. We also investigate our algorithms on real network topologies (e.g., AT&T, DFN) and random network topologies. Experimental results demonstrate the usability and capability of the proposed approach.

LOCALIZED SHEAR DEFORMATION OF AN ALUMINUM-LITHIUM 8090-ALLOY DURING LOW-CYCLE FATIGUE

XU, YB (reprint author), CHINESE ACAD SCI,INST MET RES,NATL LAB FATIGUE & FRACTURE MAT,SHENYANG 110015,PEOPLES R CHINA

Design and evaluation of coordinated in-network caching model for content centric networking

In-network caching has been widely adopted in Content Centric Networking (CCN) to accelerate data delivery, mitigate server load and reduce network traffic. However, the line-speed requirement makes the in-network caching space very limited. With the rapid growth of network traffic, it is significant challenging to decide content placement in such limited cache space. To conquer this conflict, coordinated in-network caching schemes are needed so as to maximize the profit of ubiquitous caching capacities. In particular, in-network caching in CCN is deployed as an arbitrary network topology and naturally supports dynamic request routing. Therefore, content placement scheme and dynamic request routing are tightly coupled and should be addressed together. In this paper, we propose a coordinated in-network caching model to decide the optimal content placement and the shortest request routing path under constraints of cache space and link bandwidth in a systematic fashion. Via extensive simulations, the effectiveness and efficiency of our proposed model has been validated.

An adaptive per-application storage management scheme based on manifold learning in information centric networks

Abstract Information Centric Network (ICN) is an emerging network paradigm centered around the named contents rather than the host-to-host connectivity. The common characteristic of ICN leverages in-network caching to achieve an efficient and reliable content distribution but also brings challenges. The in-network caching technique equips all ICN routers with cache storage. However, no existing works focus on the cache storage sharing mechanism among different applications to satisfy the line speed requirements and diversity of applications in ICN. In this paper, we formulate the per-application storage management problem into an optimized resource allocation problem and introduce a manifold learning method to classify the priority of applications. Dynamic programming is adopted to solve the formulated problem and an adaptive per-application storage management scheme is proposed on the basis of the optimal solutions. Extensive experiments have been performed to evaluate the proposed scheme and show that our approach is superior to static partitioning and shared storage schemes.