Traffic classification has recently gained much attention in both academic and industrial research communities. Many machine learning methods have been proposed to tackle this problem and have shown good results. However, when applied to traffic with out-of-sequence packets, the accuracy of existing machine learning approaches decreases dramatically. We observe the main reason is that the out-of-sequence packets change the spatial representation of feature vectors, which means the property of linear mapping relation among features used in machine learning approaches cannot hold any more. To address this problem, this paper proposes an Improved Dynamic Time Warping (IDTW) method, which can align two feature vectors using non-linear alignment. Experimental results on two real traces show that IDTW achieves better classification accuracy in out-of-sequence traffic classification, in comparison to existing machine learning approaches.

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Peer-to-peer networks have recently become one of the hottest topics both in academic research and commercial applications. This paper presents development and current P2P network from aspects of architecture topology, discovery mechanism, developer platforms and application. Finally, challenges faced by P2P network are discussed.

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In UMTS (universal mobile telecommunications system) networks upgraded with HSPA (high speed packet access) technology, the high access bandwidth and advanced mobile devices make it applicable to share large files among mobile users by peer-to-peer applications. To receive files quickly is essential for mobile users in file sharing applications, mainly because they are subject to unstable signal strength and battery failures. While many researches present peer-to-peer file sharing architectures in mobile environments, few works focus on decreasing the time spent in disseminating files among users. In this paper, we present an efficient peer-to-peer file sharing design for HSPA networks called AFAM — Adaptive efficient File shAring for uMts networks. AFAM can decrease the dissemination time by efficiently utilizing the upload-bandwidth of mobile nodes. It uses an adaptive rearrangement of a node's concurrent uploads, which causes the count of the node's concurrent uploads to lower while ensuring that the node's upload-bandwidth can be efficiently utilized. AFAM also uses URF — Upload Rarest First policy for the block selection and receiver selection, which achieves real rarest-first for the spread of blocks and effectively avoids the “last-block” problem in file sharing applications. Our simulations show that, AFAM achieves much less dissemination time than other protocols including BulletPrime and a direct implementation of BitTorrent for mobile environments.

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Most peer-to-peer (P2P) systems build their own overlay networks for implementing peer selection strategies without taking into account the locality on the underlay network. As a result, a large quantity of traffic crossing internet service providers (ISPs) or autonomous systems (ASes) is generated on the Internet. Controlling the P2P traffic is therefore becoming a big challenge for the ISPs. To control the cost of the cross-ISP/AS traffic, ISPs often throttle and/or even block P2P applications in their networks. In this paper, we propose a router-aided approach for localizing the P2P traffic hierarchically; it features the insertion of additional delay into each P2P packet based on geographical location of its destination. Compared to the existing approaches that solve the problem on the application layer, our proposed method does not require dedicated servers, cooperation between ISPs and P2P users, or modification of existing P2P application software. Therefore, the proposal can be easily utilized by all types of P2P applications. Experiments on P2P streaming applications indicate that our hierarchical traffic localization method not only reduces significantly the inter-domain traffic but also maintains a good performance of P2P applications.

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The demand for data/audio streaming/video streaming multicast services in large scale networks has been increasing. Moreover, the improved transmission speed and mobile-device capability in wireless access networks enable people to use such services via their personal mobile devices. Peer-to-peer (P2P) architecture ensures scalability and robustness more easily and more economically than server-client architecture; as the number of nodes in a P2P network increases, the amount of workload per node decreases and lessens the impact of node failure. However, mobile users feel much larger psychological cost due to strict limitations on bandwidth, processing power, memory capacity, and battery life, and they want to minimize their contributions to these services. Therefore, the issue of how we can reduce this psychological cost remains. In this paper, we consider how effective a social networking service is as a platform for mobile P2P multicast. We model users' cooperative behaviors in mobile P2P multicast streaming, and propose a social-network based P2P streaming architecture for mobile networks. We also measured the psychological forwarding cost of real users in mobile P2P multicast streaming through an emulation experiment, and verify that our social-network based mobile P2P multicast streaming improves service quality by reducing the psychological forwarding cost using multi-agent simulation.

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The demand of using applications that assume bidirectional communication such as voice telephony and peer-to-peer using wireless stations has been increasing and especially, the rapid increase of uplink traffic from wireless terminals is expected. However, in uplink WLANs, the hidden-station problem remains to be solved. In this paper, we point out this hidden-station problem and clarify the following unfairness between UDP and TCP uplink flows: 1) the effect of collision caused by hidden-station relationship on throughput and 2) the instability of the throughput depending on the number of hidden stations. To solve these problems, we propose a virtual multi-AP access mechanism. Our mechanism first groups stations according to the hidden-station relationship and type of transport protocol they use then assigns a virtually isolated channel to each group, which enables STAs to communicate as if STAs in different groups are connected to different isolated APs (virtual APs: VAPs). It can mitigate the effect caused by collisions between hidden stations and eliminate the contention between UDP and TCP uplink flows. Its performance is shown through simulation.

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P2P情報共有では,参加ユーザによるコンテンツの提供という貢献行動が不可欠であるが,貢献行動にはストレージや帯域などのリソースの拠出が伴うため,これによりユーザはコストを被ることになる.そこでP2P情報共有において,ユーザの貢献を促すため貢献に対して報酬を付与するインセンティブメカニズムが考案されている.一方,B3G(Beyond 3rd Generation)やMobile WiMAXのような新たな広域高速無線アクセスの浸透により,今後,無線アクセス環境におけるP2P通信に対する強いニーズが見込まれる.固定端末に加え,無線アクセス環境下の端末がP2P情報共有に参加する場合,アクセスの多様性に伴ってコストが多様化し,インセンティブメカニズムにおける適切な報酬配分が困難となる.そこで,多様なアクセスを用いるユーザが混在する環境で,各ユーザが自身の効用最大化のみを目指した場合にも,報酬を適切にユーザに付与することでサービスを最適性の高い状態に均衡させるメカニズムとしてEMOTIVERが提案されている.本稿ではEMOTIVERの詳細を説明するとともに,その拡張性について検討する.

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Internet traffic classification is an essential step for stable service provision. The payload signature classifier is considered a reliable method for Internet traffic classification but is prohibitively computationally expensive for real-time handling of large amounts of traffic on high-speed networks. In this paper, we describe several design techniques to minimize the search space of traffic classification and improve the processing speed of the payload signature classifier. Our suggestions are (1) selective matching algorithms based on signature type, (2) signature reorganization using hierarchical structure and traffic locality, and (3) early packet sampling in flow. Each can be applied individually, or in any combination in sequence. The feasibility of our selections is proved via experimental evaluation on traffic traces of our campus and a commercial ISP. We observe 2 to 5 times improvement in processing speed against the untuned classification system and Snort Engine, while maintaining the same level of accuracy.

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DHT routing algorithms can provide efficient mechanisms for resource placement and lookup for distributed file sharing systems. However, we must still deal with irregular and frequent join/leave of nodes and the problem of load unbalancing between nodes in DHT-based file sharing systems. This paper presents an efficient file backup scheme based on dynamic DHT key space clustering in order to guarantee data availability and support load balancing. The main idea of our method is to dynamically divide the DHT network into a number of clusters, each of which locally stores and maintains data chunks of data files to guarantee the data availability of user data files even when node churn occurs. Further, high-capacity nodes in clusters are selected as backup nodes to achieve adequate load balancing. Simulation results demonstrate the superior effectiveness of the proposed scheme over other file replication schemes.

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This paper looks at the history of research in the Technical Committee on Information Networks from the time of its inception to the present and provides an overview of the latest research in this area based on the topics discussed in recent meetings of the committee. It also presents possible future developments in the field of information networks.

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In peer-to-peer (P2P) content sharing, users can share their content by contributing their own resources to one another. However, since there is no incentive for contributing contents or resources to others, users may attempt to obtain content without any contribution. To motivate users to contribute their resources to the service, incentive-rewarding mechanisms have been proposed. On the other hand, emerging wireless technologies, such as IEEE 802.11 wireless local area networks, beyond third generation (B3G) cellular networks and mobile WiMAX, provide high-speed Internet access for wireless users. Using these high-speed wireless access, wireless users can use P2P services and share their content with other wireless users and with fixed users. However, this diversification of access networks makes it difficult to appropriately assign rewards to each user according to their contributions. This is because the cost necessary for contribution is different in different access networks. In this paper, we propose a novel incentive-rewarding mechanism called EMOTIVER that can assign rewards to users appropriately. The proposed mechanism uses an external evaluator and interactive learning agents. We also investigate a way of appropriately controlling rewards based on the system service's quality and managing policy.

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During the 1980s, two research programs in formal semantics were established: dynamic semantics (DS), which provides a discourse interpretation, and generalized quantifier theory (GQT), which deals with quantification in natural languages. In the 1990s, proposals to integrate GQT into DS were made; unfortunately, many of them failed to include the problems of anaphora in contexts of quantification. This paper redefines problems of quantification as problems of characterization of finite classes. It defines a semantic framework, dynamic theory for discourse interpretation, and demonstrates how problems of plural pronominal anaphora can be treated properly within it.

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