Woojin Seok

Designing a federated testbed as a distributed system

Traditionally, testbeds for networking and systems research have been stand-alone facilities: each is owned and operated by a single administrative entity, and is intended to be used independently of other testbeds. However, this isolated facility model is at odds with researchers’ ever-increasing needs for experiments at larger scale and with a broader diversity of network technologies. The research community will be much better served by a federated model. In this model, each federated testbed maintains its own autonomy and unique strengths, but all federates work together to make their resources available under a common framework.

A base station centralized simple clustering protocol for sensor networks

Sensor nodes in wireless sensor network are severely energy-constrained. This has been a key factor to limit its performance. So far, many energy-efficient routing protocols have been proposed. Cluster-based routing protocols have been paid much attention because of their advantages. However, the cluster-based routing protocols require information on the locations of the sensor nodes in the network to construct clusters. Due to cost, it is not feasible to know the locations of all sensor nodes in the network. In this paper, we propose a base station centralized simple clustering protocol (BCSP) which requires no location information of the sensor nodes. Instead, BCSP utilizes information on the remaining energy of each sensor node and the number of cluster heads which is changed depending on the circumstance of the sensor network. From performance experiments, BCSP shows better performance than low-energy adaptive clustering hierarchy (LEACH)

Data mining middleware for wide-area high-performance networks

In this paper, we describe two distributed, data intensive applications that were demonstrated at iGrid 2005 (iGrid Demonstration US 109 and iGrid Demonstration US121). One involves transporting astronomical data from the Sloan Digital Sky Survey (SDSS) and the other involves computing histograms from multiple high-volume data streams. Both rely on newly developed data transport and data mining middleware. Specifically, we describe a new version of the UDT network protocol called Composible-UDT, a file transfer utility based upon UDT called UDT-Gateway, and an application for building histograms on high-volume data flows called BESH (for Best Effort Streaming Histogram). For both demonstrations, we include a summary of the experimental studies performed at iGrid 2005.

Disruptive network applications and their impact on network neutrality

Network Neutrality principle states that in order to preserve the openness of the Internet, the end users should have equal access to all the content on the Internet, and the Internet Service Providers (ISP) should be prohibited from discriminating or blocking the content from any of the application providers. The Network Neutrality issue is important as it can have a considerable impact on the future Internet design principles and associated laws and policies. While the supporters of Network Neutrality, including the users and content providers, argue that non-blocking and non-discrimination should be prohibited by law, the opponents, including the ISPs, claim that such rules can prove to be a disincentive for them to invest in the network upgrades. In this paper, we provide a brief review of the Net Neutrality policies, focusing on the content provider discrimination. In addition we discuss some of the latest disruptive network applications being used in the Internet, such as zero rating apps, Over-the-Top applications, etc., and their impact on the Network Neutrality.

A simple dynamic clustering approach to achieve energy efficiency for wireless sensor networks

Purpose – Recent wireless communication and electronics technology has enabled the development of low‐cost, low‐power, and multi‐functional sensor nodes. However, the fact that sensor nodes are severely energy‐constrained has been an issue and many energy‐efficient routing protocols have been proposed to resolve it. Cluster‐based routing protocol is one of them. To achieve longer lifetime, some cluster‐based routing protocols use information on GPS‐based location of each sensor node. However, because of high cost, not all sensor nodes can be GPS‐enabled. The purpose of this paper is to propose a simple dynamic clustering approach to achieve energy efficiency for wireless sensor networks (WSN).Design/methodology/approach – Instead of using location information of each sensor node, this approach utilizes information of remaining energy of each sensor node and changes in the number of cluster head nodes dependent on the number of sensor nodes alive. Performance results are presented and compared with some re...

Design and implementation of QoS measurement and network diagnosing framework for IP multicast in advanced collaborative environment

The access grid for collaborative environment exploits IP multicast. Although the IP multicast is quite a promising technology, it faces lots of challenges such as unreliable data transport and unstable network infrastructure. As a first step to achieve reliability and stability in IP multicast, it is essential to monitor and debug multicast networks. In this paper we introduce MMag, a user-oriented multicast monitoring tool for the access grid. The MMag provides both application and network level monitoring facilities to assess delivery statistics and to diagnose multicast problems. The implementation has been tested and will support access grid operators with a simple yet extensive view of multicast performance.

Congestion detection for QoS-enabled wireless networks and its potential applications

We propose a mechanism for monitoring load in quality of service (QoS)-enabled wireless networks and show how it can be used for network management as well as for dynamic pricing. Mobile network traffic, especially video, has grown exponentially over the last few years and it is anticipated that this trend will continue into the future. Driving factors include the availability of new affordable, smart devices, such as smart-phones and tablets, together with the expectation of high quality user experience for video as one would obtain at home. Although new technologies such as long term evolution (LTE) are expected to help satisfy this demand, the fact is that several other mechanisms will be needed to manage overload and congestion in the network. Therefore, the efficient management of the expected huge data traffic demands is critical if operators are to maintain acceptable service quality while making a profit. In the current work, we address this issue by first investigating how the network load can be accurately monitored and then we show how this load metric can then be used to provide creative pricing plans. In addition, we describe its applications to features like traffic offloading and user satisfaction tracking.

Load metric for QoS-enabled cellular networks and its possible use in pricing strategies

Mobile network traffic has grown exponentially in recent years, and it is expected that this trend will continue in the future. Important driving forces include new affordable smartphones, and the many new connected devices on the market. Also, the rollout of faster HSPA+ and LTE networks is expected to improve the customer experience. Therefore, the efficient management of the expected huge data traffic demands is critical if operators are to maintain acceptable service quality, while making a profit. One of the alternatives is to increase the capacity by allocating more spectrum but this is a finite resource. In this paper we address this issue by proposing a dynamic, flexible pricing model that allows an operator to efficiently utilize the available resources, while fairly charging the customers for resources they utilize. To support the proposed model, we first introduce a novel metric for monitoring the load on the network.

Optimizing System Performance for Uncompressed HDTV over 10-Gigabit Ethernet

Guaranteeing network bandwidth and system performance becomes important technical matters to make seamless delivery of bulky data at high speed. Tuning system and network parameters including jumbo frame, kernel buffer size, and interrupt coalescence determines end-to-end transmission throughput. Additionally, fine-tuning of the parameters alleviates workload on high-end systems. Until now, many studies have concentrated on how to increase transmission throughput but rarely discussed how to mitigate system workload. In this paper, we have investigated various tuning parameters, which positively affect networking and processing performance of uncompressed HDTV system.

multiFIA Multi-dimensional future Internet architecture

Rapid growth in Internet of Things (IoT) has resulted in the need for effective management and provisioning of resources in an IoT-based system. The resource may be an entity (virtual or physical) that constitutes the IoT system, such as network elements, gateways, cloud data stores, and sensors. The dynamic and constantly changing nature of request by a typical user for resource allocation demands end-to-end slices of an IoT system. In order to meet such requests, end-to-end slices need to be integrated, ultimately making it necessary to control and aggregate diverse types of resources from IoT, cloud infrastructures, and network functions. To that end, in this paper, we propose a framework for IoT resources management and provisioning. Our proposed approach enables to automate resource management and provisioning for users across IoT, clouds, and network functions by virtualizing access to underlying IoT resources and utilizing APIs to employ those resources. Furthermore, our proposed approach aims to establish and manage end-to-end slices of various types of resources from distributed and diverse infrastructure. In this paper, we present multiFIA — multi-dimensional Future Internet Architecture — which permits IoT system designers to accommodate multiple user demands by establishing end-to-end slices of the overall IoT network. We outline multiFIA components and layers and also describe our approach to an implementation of multiFIA.