A Novel Approach to Optical Switching for Intradatacenter Networking

Limei Peng,Chan-Hyun Youn,Wan Tang,Chunming Qiao IEEE 2012 Journal of lightwave technology Vol.30 No.2

<P>In this paper, we propose to apply a novel paradigm called labeled optical burst switching with home circuit (LOBS-HC) for intradatacenter networking to provide a high bisection bandwidth and significantly reduce the cost and energy consumption associated with electronic packet switching. The unique features of LOBS-HC that make it more suitable than either optical circuit switching (OCS) or optical packet/burst switching are exploited to enable all-to-all communications with a guaranteed lossless transmission bandwidth between any given pair of pods, while also supporting bursty transmissions through wavelength-sharing among home circuits (HCs) and statistical multiplexing. As a case study, hypercube-like topologies are considered for the interconnection among the pods within a datacenter. In particular, we first propose a simple but efficient HC assignment scheme called complementary HC for 2-D cube or ring, and then extend our works to n-cube and generalized hypercube by applying the concept of spanning balanced tree (SBT) for their HC assignment. Our analysis results show that with such datacenters, the minimum number of wavelengths needed in each case is significantly reduced from that needed with OCS and also, the network cost in terms of wires and transceivers needed is considerably reduced from that incurs with datacenters using electronic packet switching. We then evaluate the traffic performance of such hypercube-based datacenters using LOBS-HC through simulation experiments via the OPNET simulator. The performance results obtained for a variety of communication patterns and traffic models within a datacenter demonstrate the feasibility of the proposed approach.</P>

Theoretical Analyses of Lightpath Blocking Performance in CO-OFDM Optical Networks with/without Spectrum Conversion

Limei Peng,Chan-Hyun Youn,Chunming Qiao IEEE 2013 IEEE communications letters Vol.17 No.4

<P>This paper provides the first analysis of the impact of spectrum conversion on the lightpath blocking performance in the CO-OFDM optical networks. Two analytical models for the cases of using and not using spectrum convertors are developed for an H-hop end-to-end lightpath and a network, respectively. Numerical results show that the use of spectrum convertors can significantly improve the lightpath blocking performance.</P>

편승효과를 반영한 최상위 콘텐츠 추천 정확성 향상

Limei Peng,SunLu,박기진,강석균 한국경영과학회 2017 한국경영과학회 학술대회논문집 Vol.2017 No.4

Datacenter-Oriented Elastic Optical Networks: Architecture, Operation, and Solutions

( Limei Peng ),( Yantao Sun ),( Min Chen ),( Kiejin Park ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.11

With the exponentially increasing Internet traffic and emergence of more versatile and heterogeneous applications, the design of datacenter networks (DCNs) is subject to unprecedented requirements for larger capacity and more flexible switching granularities. Envisioning Optical-Orthogonal Frequency Division Multiplexing (O-OFDM) as a promising candidate for such a scenario, we motivate the use of O-OFDM as the underlying switching technology in order to provide sufficient switching capacity and elastic bandwidth allocation. For this purpose, this article reviews the recent progresses of DCN deployment and assesses the scenario where the O-OFDM transmission and switching technology is employed in the underlying transport plane. We discuss the key issues of the datacenter-oriented O-OFDM optical networks, and in particular, elaborate on a number of open issues and solutions including system interconnection architecture, routing and resource assignment, survivability, and energy-efficiency.

Investigation on static routing and resource assignment of elastic all-optical switched intra-datacenter networks

Peng, Limei,Park, Kiejin,Youn, Chan-Hyun Springer Science + Business Media 2016 Science China. Information sciences Vol.59 No.10

<P>In this paper, we explore the issue of static routing and spectrum/IT resource assignment (RSIA) of elastic all-optical switched intra-datacenter networks (intra-DCNs) by proposing anycast- and manycast-based integer linear programming (ILP) models. The objective is to jointly optimize the DCN resources, i.e., network transmission bandwidth and IT resources, under different situations. First, for given service-request matrices with unknown network transmission bandwidth and IT resources, we propose anycast and manycast ILP models to minimize the maximum numbers of required network and IT resources to accommodate all the service requests. For anycast RSIA issue, we proposed two different ILP models that are based on node-arc and link-path methods, respectively. Node-arc based manycast ILP model is also proposed for the first time to our knowledge. Second, for given network transmission bandwidth and IT resources and known service-request matrices, we propose node-arc based anycast ILP models to maximize the total number of successfully served service requests. To evaluate the efficiency of anycast and manycast models, all proposed ILP models are evaluated and compared with unicast ILP models. Simulation results show that anycast and manycast ILP models perform much better in efficiently using DCN resources and successfully accommodating more service requests when compared to unicast ILP models under the same network conditions.</P>

Toward integrated Cloud–Fog networks for efficient IoT provisioning: Key challenges and solutions

Peng, Limei,Dhaini, Ahmad R.,Ho, Pin-Han Elsevier 2018 Future generation computer systems Vol.88 No.-

<P><B>Abstract</B></P> <P>Fog computing has been proposed as one of the promising technologies for the construction of a scalable network infrastructure in the user’s vicinity, with the purpose of serving the tremendous amount of daily generated latency-sensitive Internet-of-Things (IoT) data. In provisioning the emerging IoT data in addition to the legacy Cloud services, the Cloud and Fog form a natural continuum of one another and the integration of these two key technologies would offer a promising infrastructure full with IoT resources for IoT data provisioning.</P> <P>In this article, we present iCloudFog, a reconfigurable architecture that enables an agile integration of Fog and Cloud networks. iCloudFog allows to construct different Fog types (i.e., wireless, wired, or hybrid) to fit the different characteristics of IoT devices and data, and Fog nodes. Due to its nature, iCloudFog presents several unique key research challenges that have not yet been addressed in existing literatures, such as network dimensioning and configuration, resource management/QoS, security/privacy, and positioning/localization. We discuss these challenges and suggest promising approaches to resolve them. Effective design and implementation of solutions based on the suggested approaches would allow iCloudFog to play a salient role towards the successful provisioning of future IoT applications and services.</P> <P><B>Highlights</B></P> <P> <UL> <LI> We first provide a literature review of the work related to the integration of Cloud–Fog networks. </LI> <LI> We then present iCloudFog, a scalable and agile integrated Cloud–Fog architecture that provisions Fog and IoT networks dynamically based on the Cloud and IoT nodes’ availability and capability, and network requirements. </LI> <LI> We identify the key challenges that emerge in the process of constructing the iCloudFog framework, such as network dimensioning, security and IoT job scheduling, and indoor localization, and suggest viable approaches to address these challenges. </LI> </UL> </P>

Performance Evaluation in Cache-Enabled Cross-haul Networks

Haoran Mei,Limei Peng 한국통신학회 2019 한국통신학회 학술대회논문집 Vol.2019 No.1

GEP-based Framework for Immune- Inspired Intrusion Detection

( Wan Tang ),( Limei Peng ),( Ximin Yang ),( Xia Xie ),( Yang Cao ) 한국인터넷정보학회 2010 KSII Transactions on Internet and Information Syst Vol.4 No.6

Immune-inspired intrusion detection is a promising technology for network security, and well known for its diversity, adaptation, self-tolerance, etc. However, scalability and coverage are two major drawbacks of the immune-inspired intrusion detection systems (IIDSes). In this paper, we propose an IIDS framework, named GEP-IIDS, with improved basic system elements to address these two problems. First, an additional bio-inspired technique, gene expression programming (GEP), is introduced in detector (corresponding to detection rules) representation. In addition, inspired by the avidity model of immunology, new avidity/affinity functions taking the priority of attributes into account are given. Based on the above two improved elements, we also propose a novel immune algorithm that is capable of integrating two bio-inspired mechanisms (i.e., negative selection and positive selection) by using a balance factor. Finally, a pruning algorithm is given to reduce redundant detectors that consume footprint and detection time but do not contribute to improving performance. Our experimental results show the feasibility and effectiveness of our solution to handle the scalability and coverage problems of IIDS.

Energy-efficient multiperiod planning of optical core network to support 5G networks

Li, Bingbing,Peng, Limei,Hao, Yixue,Miao, Yiming,Hassan, Mohammad Mehedi Associazione elettrotecnica ed elettronica italian 2017 Transactions on emerging telecommunications techno Vol.28 No.9

A Development of LDA Topic Association Systems Based on Spark-Hadoop Framework

Park, Kiejin,Peng, Limei Korea Information Processing Society 2018 Journal of information processing systems Vol.14 No.1

Social data such as users' comments are unstructured in nature and up-to-date technologies for analyzing such data are constrained by the available storage space and processing time when fast storing and processing is required. On the other hand, it is even difficult in using a huge amount of dynamically generated social data to analyze the user features in a high speed. To solve this problem, we design and implement a topic association analysis system based on the latent Dirichlet allocation (LDA) model. The LDA does not require the training process and thus can analyze the social users' hourly interests on different topics in an easy way. The proposed system is constructed based on the Spark framework that is located on top of Hadoop cluster. It is advantageous of high-speed processing owing to that minimized access to hard disk is required and all the intermediately generated data are processed in the main memory. In the performance evaluation, it requires about 5 hours to analyze the topics for about 1 TB test social data (SNS comments). Moreover, through analyzing the association among topics, we can track the hourly change of social users' interests on different topics.