Jae-Hyoung Yoo

End-User IPTV Traffic Measurement of Residential Broadband Access Networks

Offering IPTV to broadband access subscribers is a key challenge as well as a prospective revenue source for ISPs. Despite of its growing interest, no comprehensive study has presented the traffic details of real-world commercial IPTV services yet. We have measured commercial IPTV traffic via four different residential broadband access networks, namely xDSL, Cable, FTTB, and FTTH. In this paper, we present traffic statistics and insight of the IPTV traffic impact onto these end- subscriber broadband accesses. We also present the mathematical formulas to describe traffic behavior and bandwidth demand in IPTV VoD services.

Measurement of download and play and streaming IPTV traffic

Telecommunication service providers are eager for the benefits of IPTV services to penetrate into the lives of their broadband subscribers. A few multimedia delivery methods, such as multicast and P2P-style data bartering, are investigated in an attempt to reduce the network traffic at the backbone while preventing quality of experience degradation. While delivering fiber to households is still in its infancy in most parts of the world, the download and play delivery scheme has been deployed as an interim solution for video-on-demand service until fullscale multicast IPTV deployment in order to handle heterogeneous residential access networks. QoS-controlled streaming IPTV (e.g., multicast) is only available to customers with high-bandwidth broadband access. The research community has been heavily focused on how to reduce network load at the backbone and has overlooked the importance of traffic impact at the customer premises, which is very closely related to the quality of experience. This article provides a traffic impact analysis and a discussion of network-centric quality from the perspective of customers using real-world commercial traces in various user scenarios. We also present an overview of IPTV delivery schemes and user behavior models from previous measurement work. Finally, we illustrate a bandwidth demand estimation method for D&P scenarios.

Flow-level traffic matrix generation for various data center networks

The number of data centers deployed by governments, enterprises, and universities has been increased affected by the development of cloud computing technologies to reduce CAPAX and OPEX. Many architectures or topologies for data center networks have been proposed to address the diverse purposes and requirements. However, the construction of data centers incurs significant costs. Moreover, there are many technologies that can affect the structure of the data center. Before building a data center, it must be confirmed that it possesses the characteristics necessary to satisfy requirements. Efficient ways to find and confirm network characteristics include simulation and tests using a traffic generation method. Our proposed method is designed to generate network traffic that address many characteristics of data center networks explored by several studies. The proposed method generates network traffic utilizing flow-level traffic matrix, not directly generates packets. We used Python programming language to create traffic matrix and iPerf to generate network packets. To evaluate it, we compared the generation results to real network traffic collected from a data center network. The result shows that the generated traffic is similar with the real network traffic.

Dynamic control plane management for software‐defined networks

Summary Software-defined network (SDN) is an emerging network paradigm that allows flexible network management by providing programmability from a separated control plane. Because of the centralized management scheme that SDN adopts, intensive control plane overhead incurs as the scale of SDN increases. The control plane overhead is mainly caused by a massive amount of control messages generated during data plane monitoring and reactive flow instantiation. By far, very few works have addressed the overhead issue on reaction flow instantiation; therefore, we mainly focus on alleviating such overhead in this work. To achieve this goal, we propose a new control plane management (CPMan) method. CPMan aims to realize the following two objectives: first, reduce the number of control messages exchanged through the control channel and second, evenly distribute the control workload across multiple controllers to mitigate the potential performance bottleneck. To realize the former, we propose a lightweight feedback loop-based control scheme, whereas for the latter, we propose a dynamic switch-to-controller (DSC) placement scheme. To show the feasibility of our proposal, we implemented a prototype of the two proposed schemes on top of a carrier-grade SDN controller and validated its performance in an emulated network. We achieved approximately 57.13% overhead reduction with feedback loop-based control scheme, while achieved approximately 98.68% balance ratio with DSC placement scheme. Copyright

Scalable failover method for Data Center Networks using OpenFlow

With the emergence of significant amounts of mobile and cloud services, the scale of Data Center Networks (DCNs) has been growing rapidly. A DCN has different network requirements compared to a traditional Internet Protocol (IP) network, and the existing Ethernet/IP style protocols constrain the DCNs scalability and its manageability. In this paper, we present a scalable failover method for large scale DCNs. Because most of the current DCNs are managed in a logically centralized manner with a specialized topology and growth model, we adopt Fat-Tree [1] as the reference DCN topology and design our failover method using an OpenFlow-based approach. Further, to provide scalability, we design our failover algorithm in a local optimal manner, with which only three switches must be modified for handling a single fault, regardless of the size of the target network. We evaluate our failover method in terms of failover time by varying the network size and load balancing capability during failover. The experiment results show that our method scales well, even for a large-scale DCN with more than ten thousands hosts.

Dynamic control plane management for software-defined networks

Summary Software-defined network (SDN) is an emerging network paradigm that allows flexible network management by providing programmability from a separated control plane. Because of the centralized management scheme that SDN adopts, intensive control plane overhead incurs as the scale of SDN increases. The control plane overhead is mainly caused by a massive amount of control messages generated during data plane monitoring and reactive flow instantiation. By far, very few works have addressed the overhead issue on reaction flow instantiation; therefore, we mainly focus on alleviating such overhead in this work. To achieve this goal, we propose a new control plane management (CPMan) method. CPMan aims to realize the following two objectives: first, reduce the number of control messages exchanged through the control channel and second, evenly distribute the control workload across multiple controllers to mitigate the potential performance bottleneck. To realize the former, we propose a lightweight feedback loop-based control scheme, whereas for the latter, we propose a dynamic switch-to-controller (DSC) placement scheme. To show the feasibility of our proposal, we implemented a prototype of the two proposed schemes on top of a carrier-grade SDN controller and validated its performance in an emulated network. We achieved approximately 57.13% overhead reduction with feedback loop-based control scheme, while achieved approximately 98.68% balance ratio with DSC placement scheme. Copyright

Software defined networking-based traffic engineering for data center networks

Todays Data Center Networks (DCNs) contain tens of thousands of hosts with significant bandwidth requirements as the needs for cloud computing, multimedia contents, and big data analysis are increasing. However, the existing DCN technologies accompany the following two problems. First, power consumptions of a DCN is constant regardless of the utilization of network resources. Second, due to a static routing scheme, a few links in DCNs are experiencing congestions while other majority links are being underutilized. To overcome these limitations of the current DCNs, we propose a Software Defined Networking (SDN)-based Traffic Engineering (TE), which consists of optimal topology composition and traffic load balancing. We can reduce the power consumptions of the DCN by turning off links and switches that are not included in the optimal subset topology. To diminish network congestions, the traffic load balancing distributes ever-changing traffic demands over the found optimal subset topology. Simulation results revealed that the proposed SDN-based TE approach can reduce power consumptions of a DCN about 41% and Maximum Link Utilization (MLU) about 60% on average in comparison with a static routing scheme.

A smart home control system based on context and human speech

Traditionally, home appliances are controlled by switches or remote controllers manually. In order to control the appliances, a user have to be near the switches or carry remote controllers all the time. To alleviate this inconvenience, this paper proposes a control system for home appliances using human speech and context information. We present an architecture of the control system and a process to control home appliances composed of three steps: speech detection, speech recognition, and command execution. To validate our system, we show two useful case studies by testing it at POSTECH smart home and UPnP-OSGi simulator.

LISP controller: a centralized LISP management system for ISP networks

Summary As the current Internet architecture is suffering from scalability issues, the network research community has proposed alternative designs for the Internet architecture. Among those solutions that adopt the idea of locator/identifier split paradigm, the locator/identifier separation protocol (LISP) has been considered as the most promising solution because of its incrementally deployable feature. Despite various advantages provided by LISP, many ISPs are still conservative to adopt LISP into their production network because the standard LISP does not fully satisfy ISPs requirements on LISP-enabled services. In this paper, we define ISPs requirements on LISP-enabled commercial services and describe limitations of the standard LISP from an ISPs perspective. Also, we propose LISP controller, a centralized LISP management system. By using LISP controller, we evaluate three ISPs representative LISP use cases: traffic engineering, virtual machine live migration, and vertical handover. The results show that the proposed LISP controller provides centralized management, controllability, and fast map entry update, without any modifications on the standard LISP. LISP controller allows an ISP to control and manage its LISP-enabled services while satisfying ISPs requirements. Copyright

SAVE: Energy-aware Virtual Data Center embedding and Traffic Engineering using SDN

Cloud computing is a popular computing paradigm which provides the virtual resource as a form of VM to customers in an on demand manner. Existing provisioning solutions were only limited to provision computing resource (e.g., CPU, RAM and etc.), therefore, it was difficult to provide more advanced cloud services. Virtual Data Center (VDC) embedding, which is known as mapping the VDC resources to their physical counterparts, was recently introduced to provide more advanced cloud services. However, existing VDC embedding solutions were mostly focus on consolidating VMs in single physical data center. Therefore, in this work, 1) we expand the consolidated targets from VMs to network fabrics (e.g, paths and switches); 2) we also consider the VDC embedding problem in multiple physical data centers. In former point, a Traffic Engineering (TE) technique is required to realize the network fabrics consolidation. While, in latter point, a multi-data center VM live migration technique is required to realize the VM migration across the different data centers. SDN, which is a new network paradigm, can fulfill the requirements raised in above two points by providing flow-level virtualization and network address virtualization. With the help of SDN, we propose a Sdn Assisted Vdc Embedding solution - SAVE by consolidating network fabrics along with physical hosts. SAVE includes two VDC embedding algorithms with a TE heuristic, and a holistic system architecture is provided to realize the proposed algorithms. Our experiment results show the feasibility of the SAVE system architecture, and the effectiveness of the proposed algorithms.