Chen-Chi Wu

Quadrant of euphoria: a crowdsourcing platform for QoE assessment

Existing quality of experience assessment methods, subjective or objective, suffer from either or both problems of inaccurate experiment tools and expensive personnel cost. The panacea for them, as we have come to realize, lies in the joint application of paired comparison and crowdsourcing, the latter being a Web 2.0 practice of organizations asking ordinary unspecific Internet users to carry out internal tasks. We present in this article Quadrant of Euphoria, a user-friendly Web-based platform facilitating QoE assessments in network and multimedia studies, which features low cost, participant diversity, meaningful and interpretable QoE scores, subject consistency assurance, and a burdenless experiment process.

Crowdsourcing Multimedia QoE Evaluation: A Trusted Framework

Crowdsourcing has emerged in recent years as a potential strategy to enlist the general public to solve a wide variety of tasks. With the advent of ubiquitous Internet access, it is now feasible to ask an Internet crowd to conduct QoE (Quality of Experience) experiments on their personal computers in their own residences rather than in a laboratory. The considerable size of the Internet crowd allows researchers to crowdsource their experiments to a more diverse set of participant pool at a relatively low economic cost. However, as participants carry out experiments without supervision, the uncertainty of the quality of their experiment results is a challenging problem. In this paper, we propose a crowdsourceable framework to quantify the QoE of multimedia content. To overcome the aforementioned quality problem, we employ a paired comparison method in our framework. The advantages of our framework are: 1) trustworthiness due to the support for cheat detection; 2) a simpler rating procedure than that of the commonly-used but more difficult mean opinion score (MOS), which places less burden on participants; 3) economic feasibility since reliable QoE measures can be acquired with less effort compared with MOS; and 4) generalizability across a variety of multimedia content. We demonstrate the effectiveness and efficiency of the proposed framework by a comparison with MOS. Moreover, the results of four case studies support our assertion that the framework can provide reliable QoE evaluation at a lower cost.

An empirical evaluation of VoIP playout buffer dimensioning in Skype, Google talk, and MSN Messenger

VoIP playout buffer dimensioning has long been a challenging optimization problem, as the buffer size must maintain a balance between conversational interactivity and speech quality. The conversational quality may be affected by a number of factors, some of which may change over time. Although a great deal of research effort has been expended in trying to solve the problem, how the research results are applied in practice is unclear. In this paper, we investigate the playout buffer dimensioning algorithms applied in three popular VoIP applications, namely, Skype, Google Talk, and MSN Messenger. We conduct experiments to assess how the applications adjust their playout buffer sizes. Using an objective QoE (Quality of Experience) metric, we show that Google Talk and MSN Messenger do not adjust their respective buffer sizes appropriately, while Skype does not adjust its buffer at all. In other words, they could provide better QoE to users by improving their buffer dimensioning algorithms. Moreover, none of the applications adapts its buffer size to the network loss rate, which should also be considered to ensure optimal QoE provisioning.

Peer-to-Peer Application Recognition Based on Signaling Activity

Because of the enormous growth in the number of peer-to-peer (P2P) applications in recent years, P2P traffic now constitutes a substantial proportion of Internet traffic. The ability to accurately identify different P2P applications from the network traffic is essential for managing a number of network traffic issues, such as service differentiation and capacity planning. However, modern P2P applications often use proprietary protocols, dynamic port numbers, and packet encryptions, which make traditional identification approaches like port-based or signature-based identification less effective. In this paper, we propose an approach for accurately recognizing P2P applications running on monitored hosts based on signaling behavior, which is regulated by the underlying P2P protocol; therefore, each application possesses a distinguishing characteristic. We consider that the signaling behavior of each P2P application can serve as a unique signature for application identification. Our approach is particularly useful for three reasons: 1) it does not need to access the packet payload; 2) it recognizes applications based purely on their signaling behavior; and 3) it can identify particular P2P applications. The performance evaluation shows that 92% of a real-life traffic trace can be correctly recognized within a 5-minute monitoring period.

Detecting VoIP Traffic Based on Human Conversation Patterns

Owing to the enormous growth of VoIP applications, an effective means of identifying VoIP is now essential for managing a number of network traffic issues, such as reserving bandwidth for VoIP traffic, assigning high priority for VoIP flows, or blocking VoIP calls to certain destinations. Because the protocols, port numbers, and codecs used by VoIP services are shifting toward proprietary, encrypted, and dynamic methods, traditional VoIP identification approaches, including port- and payload-based schemes, are now less effective. Developing a traffic identification scheme that can work for general VoIP flows is therefore of paramount importance. In this paper, we propose a VoIP flow identification scheme based on the unique interaction pattern of human conversations . Our scheme is particularly useful for two reasons: 1) flow detection relies on human conversations rather than packet timing; thus, it is resistant to network variability; and 2) detection is based on a short sequence of voice activities rather than the whole packet stream. Hence, the scheme can operate as a traffic management module to provide QoS guarantees or block VoIP calls in real time. The performance evaluation, which is based on extensive real-life traffic traces, shows that the proposed method achieves an identification accuracy of 95% in the first 4 seconds of the detection period and 97% in 11 seconds.

On the challenge and design of transport protocols for MMORPGs

Although MMORPGs are becoming increasingly popular as well as a highly profitable Internet business, there is still a fundamental design question: Which transport protocol should be used—TCP, UDP, or some other protocol? In this paper, we first evaluate whether TCP is suitable for MMORPGs, and then propose some novel transport strategies for this genre of games. Our analysis of a trace collected from a TCP-based MMORPG called ShenZhou Online indicates that TCP is unwieldy and inappropriate for MMORPGs. We find that the degraded network performance problems are due to the following characteristics of MMORPG traffic: 1) tiny packets, 2) a low packet rate, 3) application-limited traffic generation, and 4) bi-directional traffic. Since not all game packets require reliable transmission or in-order delivery, transmitting all packets with a strict delivery guarantee causes high delays and delay jitters. Therefore, our proposed transport strategies assign game packets with appropriate levels of transmission guarantee depending on the requirements of the packets’ contents. To compare the performance of our approach with that of existing transport protocols, we conduct network simulations with a real-life game trace from Angel’s Love. The results demonstrate that our strategies significantly reduce the end-to-end delay and delay jitter of packet delivery. Finally, we show that our strategies effectively raise satisfaction levels of the game players.

Inferring Speech Activity from Encrypted Skype Traffic

Normally, voice activity detection (VAD) refers to speech processing algorithms for detecting the presence or absence of human speech in segments of audio signals. In this paper, however, we focus on speech detection algorithms that take VoIP traffic instead of audio signals as input. We call this category of algorithms network-level VAD. Traditional VAD usually plays a fundamental role in speech processing systems because of its ability to delimit speech segments. Network-level VAD, on the other hand, can be quite helpful in network management, which is the motivation for our study. We propose the first real-time network-level VAD algorithm that can extract voice activity from encrypted and non-silence-suppressed Skype traffic. We evaluate the speech detection accuracy of the proposed algorithm with extensive real-life traces. The results show that our scheme achieve reasonably good performance even high degree of randomness has been injected into the network traffic.

A Lightweight Key Agreement Protocol with User Anonymity in Ubiquitous Computing Environments

In a smart living environment, a person can use various intelligent devices to obtain his desired services at any time and any place. For convenience, most of these devices are small and of limited power and computation capacity. Therefore, an admired protocol should take these into consideration. In particular, identification and key agreement are basic mechanisms when a user wants to get a secure service from a server over the public networks. However, if the users identity is transmitted in a plaintext, an adversary can intercept the information and use it to launch some attacks. In this paper, we propose a key agreement protocol with user anonymity based on elliptic curve discrete logarithm problem. In our protocol, the storage and computation costs are very low and the server does not maintain a password file for identifying the users. Therefore, our protocol is suitable for applying ubiquitous computing environments.