Recently, P2PTV is a popular application to deliver video streaming data over the Internet. On the overlay network, P2PTV applications create logical links between pairs of peers considering round trip time (RTT) without physical network consideration. P2PTV packets are shared over a network without localization awareness which is a serious problem for Internet Service Providers (ISPs). A delay-insertion-based traffic localization scheme was proposed for solving this problem. However, this scheme sometimes leads the newly joining peer to download streaming traffic from a local neighbor peer which has only scarce upload bandwidth. This paper proposes a novel scheme of delay-insertion-based traffic localization in which the router estimates relay capability to each relay peer candidate and leads the newly joining peer to connect to a neighbor peer with sufficient performance for relaying video data. Parameters were evaluated for the optimized condition in the relay capability estimation process. In addition, experiments conducted on a real network show that our proposed scheme can prevent the newly joining peer from downloading video data from peers with insufficient relay capability and maintain video quality close to normal in a P2PTV system while ensuring efficient traffic localization at the level of the Autonomous System (AS) network.

Most P2PTV systems select a neighbor peer in an overlay network using RTT or a random method without considering the underlying network. Streaming traffic is shared over a network without localization awareness, which is a serious problem for Internet Service Providers. In this paper, we present a novel scheme to achieve P2PTV traffic localization by inserting delay into P2P streaming packets, so that the length of the inserted delay depends on the AS hop distance between a peer and its neighbor peer. Experiments conducted on a real network show that our proposed scheme can perform efficient traffic localization.

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.

Our prior papers proposed a traffic engineering scheme to further localize traffic in peer-assisted content delivery networks (CDNs). This scheme periodically combines the content files and allows them to obtain the combined content files while keeping the price unchanged from the single-content price in order to induce altruistic clients to download content files that are most likely to contribute to localizing network traffic. However, the selection algorithm in our prior work determined which and when content files should be combined according to the cache states of all clients, which is a kind of unrealistic assumption in terms of computational complexity. This paper proposes a new concept of virtual local server to reduce the computational complexity. We could say that the source server in our mechanism has a virtual caching network inside that reflects the cache states of all clients in the ‘actual’ caching network and combines content files based on the virtual caching network. In this paper, without determining virtual caching network according to the cache states of all clients, we approximately estimated the virtual caching network from the cache states of the virtual local server of the local domain, which is the aggregated cache state of only altruistic clients in a local domain. Furthermore, we proposed a content selection algorithm based on a virtual caching network. In this paper, we used news life-cycle model as a content model that had the severe changes in cache states, which was a striking instance of dynamic content models. Computer simulations confirmed that our proposed algorithm successfully localized network traffic.

We introduce a new kind of P2P traffic localization technique, called Netpherd, benefiting from the network virtualization technique for its successful deployment. Netpherd exploits one feature of P2P applications, a peer selection adaptation (i.e., preferring peers who are likely to provide better performance) for the traffic localization. Netpherd tries to enable local peers (i.e., peers in target network domain) to communicate with each other by affecting the peer selection adaptation. To affect the peer selection adaptation, Netpherd adds artificial delay to inter-domain traffic going to local peers. Our experiment conducted over Internet testbed verifies that Netpherd achieves the traffic localization and also improves the content download performance with the network delay insertion. In addition, we show that how the network virtualization technique can be utilized for efficient and graceful implementation of Netpherd.

In content services where people purchase and download large-volume contents, minimizing network traffic is crucial for the service provider and the network operator since they want to lower the cost charged for bandwidth and the cost for network infrastructure, respectively. Traffic localization is an effective way of reducing network traffic. Network traffic is localized when a client can obtain the requested content files from other a near-by altruistic client instead of the source servers. The concept of the peer-assisted content distribution network (CDN) can reduce the overall traffic with this mechanism and enable service providers to minimize traffic without deploying or borrowing distributed storage. To localize traffic effectively, content files that are likely to be requested by many clients should be cached locally. This paper presents a novel traffic engineering scheme for peer-assisted CDN models. Its key idea is to control the behavior of clients by using content-oriented incentive mechanism. This approach enables us to optimize traffic flows by letting altruistic clients download content files that are most likely contributed to localizing traffic among clients. In order to let altruistic clients request the desired files, we combine content files while keeping the price equal to the one for a single content. This paper presents a solution for optimizing the selection of content files to be combined so that cross traffic in a network is minimized. We also give a model for analyzing the upper-bound performance and the numerical results.

In this paper, we examine a new P2P traffic localization approach that exploits peer selection adaptation (i.e., preferring peers who are likely to provide better performance), called Netpherd. Netpherd enables peers to communicate with local domain peers by manipulating networking performance across network domains (i.e., adding an artificial delay to inter-domain traffic). Our feasibility study shows that Netpherd reduces the inter-domain traffic by influencing peer selection adaptation. Netpherd also improves download performance of the peers who know many local domain peers. We discuss one guideline to improve Netpherd based on the feasibility study and verify the guideline with evaluation results.