Dongeun Suh

Efficiency Analysis of WiFi Offloading Techniques

WiFi offloading is a promising technique for addressing the mobile data explosion problem. In this paper, we consider two types of WiFi offloading techniques: 1) opportunistic WiFi offloading, where data offloading is conducted only when a mobile node opportunistically meets WiFi access points (APs); and 2) delayed WiFi offloading, where data transfer is delayed with the expectation of future AP contacts. We developed analytical models on WiFi offloading efficiency, which is defined as the ratio of the amount of offloaded data to the total amount of data. Extensive simulation results are given to validate the analytical models and to demonstrate the effects of the average cellular residence time, the delay bound, the variability of the WiFi residence time, the WiFi data rate, and the average session duration on WiFi offloading efficiency.

QoE-enhanced adaptation algorithm over DASH for multimedia streaming

In dynamic adaptive streaming over HTTP (DASH), a client consecutively estimates the available network bandwidth and decides the transmission rate for the forthcoming video chunks to be downloaded. Even though several enhancements to DASH have been reported in the literature, they do not well-investigate the current buffer status to cope with fluctuating network conditions and thus do not achieve seamless video streaming. In this paper, we propose a novel rate adaptation algorithm called quality of experience (QoE)-enhanced adaptation algorithm over DASH (QAAD), which preserves the minimum buffer length to avoid interruption and minimizes the video quality changes during the playback. We implemented a DASH testbed and conducted extensive experiments. Experimental results demonstrate that under fluctuating network conditions, QAAD provides seamless streaming with stabilized video quality while the previous buffer-aware algorithm (i.e., QoE-aware DASH) frequently changes the video quality and undergoes the interruption.

Minimizing content download time in mobile collaborative community

Mobile collaborative community (MCC) is an emerging technology where multiple mobile nodes (MNs) conduct a job (e.g., large content download) in a cooperative manner. In this paper, we consider a scenario in which multiple MNs form MCC for content download through wireless wide area network (WWAN) and share of the downloaded content through wireless local area network (WLAN). In the collaborative content download for MCC, the content chunk size assigned to an MN and the sharing order of the received chunk should be carefully determined to reduce the content download time. Therefore, we formulate an optimization problem that jointly considers the chunk size and the sharing order to minimize the content download time. Specifically, the optimization problem is formulated as a mixed integer non-linear programming (MINLP) problem that is known as NP-hard. The original optimization problem is relaxed into a linear programming (LP) problem and a heuristic algorithm minimizing the content download time and operating in a polynomial time is proposed based on the 2-opt algorithm. Simulation results demonstrate that the proposed algorithm can achieve near-optimal performance to the MINLP optimal solution and can reduce the content download time compared with other algorithms by choosing proper chunk size and sharing order.

A proactive content pushing scheme for provider mobility support in information centric networks

Information-centric network (ICN) opens a new networking paradigm optimized for contents-oriented services by exploiting in-network caching and mitigating redundant transmissions. When such an ICN is deployed in mobile environments (i.e., the content provider or consumer is a mobile node), an appropriate mobility support protocol needs to be developed. Since the content consumer mobility can be tactically handled through the content consumer driven nature of ICN, the content provider mobility is investigated in this work. Specifically, we propose a proactive content pushing (PCP) scheme, in which the content provider proactively sends a set of contents that are expected to be requested in the near future to proximity ICN routers. Consequently, the PCP scheme can reduce the service disruption time owing to the content provider mobility.

Optimal placement of service function in service function chaining

In service function chaining (SFC), an ordered list of service functions (SFs) is specified for network services, and those SFs should be placed in appropriate service nodes (SNs) to satisfy the given service latency requirement. In this paper, we formulate an integer non-linear programming (INLP) problem for the optimal placement of SFs when the latency requirement for network services and network conditions (e.g., link latency and SN capacity) are given. Evaluation results show that the optimal placement can achieve lower latency than conventional schemes.

On performance of OpenDaylight clustering

Software-defined networking (SDN) is moving from its initial deployment in small-scale data center networks to large-scale carrier-grade networks. In such environments, high availability and scalability are two of the most prominent issues and thus extensive work is ongoing. In this paper, a well-known open source project, OpenDaylight (ODL) is analyzed in terms of network state database partition/synchronization and controller failover/load balancing mechanisms. We also present experimental results on the flow rule installation throughput and the failover time upon a controller failure in ODL.

Low-Complexity Master Controller Assignment in Distributed SDN Controller Environments

In a large-scale distributed software-defined networking environment, a switch is connected to multiple controllers for resiliency while assigned with one master controller, and only the master controller can install flow rules. Due to such permissions, the flow setup latency can be affected significantly depending on the master controller assignment and thus how to assign the master controller is a prominent issue. In this paper, we formulate a master controller assignment problem to minimize the average flow setup latency with consideration of the number of assigned master controllers along a path. A low-complexity master assignment (LCMA) algorithm is devised to solve the problem in a practical manner. Extensive simulation results over real-world network topologies demonstrate that LCMA achieves near-optimal performance and outperforms the existing assignment scheme in terms of the average flow setup latency under various settings.

Distributed service function failover mechanism in service function chaining

In service function chaining (SFC), end-to-end traffic flows are classified and processed by an ordered set of service functions (SFs). When SF in the chain fails, the corresponding traffic flows cannot be processed further to reach the destination until the failed SF recovers. To cope with the SF failure, failover mechanisms to instantly recover such failed SFs are mandatory. In this paper, we propose a distributed SF failover mechanism where a distributed failover agent (DFA) located along with each SF instance conducts failure detection/recovery of the failed SF. By doing so, the failed SFs can be recovered without interventions of the centralized SFC controller. Simulation results are shown that the distributed SF failover mechanism significantly reduces the average failover time by 56–76% compared to the centralized SF failover mechanism.

Toward Highly Available and Scalable Software Defined Networks for Service Providers

Software-defined networking is moving from its initial deployment in small-scale data center networks to large-scale carrier-grade networks. In such environments, high availability and scalability are two of the most prominent issues, and thus extensive work is ongoing. In this article, we first review the state of the art on high availability and scalability issues in SDN and investigate relevant open source activities. In particular, two well-known open source projects, OpenDaylight (ODL) and Open Network Operating System (ONOS), are analyzed in terms of high availability (i.e., network state database replication/synchronization and controller failover mechanisms) and scalability (i.e., network state database partition/ distribution and controller assignment mechanisms) issues. We also present experimental results on the flow rule installation/read throughput and the failover time upon a controller failure in ONOS and ODL, and identify open research challenges.

Mobility-aware DASH for cost-optimal mobile multimedia streaming services

For multimedia streaming in mobile environments, video bitrate should be carefully determined and different channel quality and pricing in heterogeneous wireless networks (e.g., cellular and WiFi networks) need to be considered. In this work, we propose a new bitrate adaptation (BA) technique called mobility-aware dynamic adaptive streaming over HTTP (MDASH), in which a cellular data usage is minimized through a Markov Decision Process (MDP) framework. Preliminary simulation results are shown that MDASH can reduce 23% of the cellular data usage without any playback interruptions while minimizing the temporal variations in the video quality.