For real-time video streaming, tree-based Application Level Multicasts (ALMs) are effective with respect to transmission delay and jitter. In particular, multiple-tree ALMs can alleviate the inefficient use of upload bandwidth among the nodes. However, most conventional multiple-tree ALMs are constructed using a Distributed Hash Table (DHT). This causes considerable delay and consumes substantial network resources because the DHT, generally, does not take distances in the IP network into account. In addition, the network constructed by a DHT has poor churn resilience because the network needs to reconstruct all the substreams of the tree network. In this paper, we propose a construction method involving overlapped cluster trees for delivering streamed data that are churn resilient. In addition, these overlapped cluster trees can decrease both the delay and the consumption of network resources because the node-connecting process takes IP network distances into account. In the proposed method, clusters are divided or merged using their numbers of members to optimize cluster size. We evaluated the performance of the proposed method via extensive computer simulations. The results show that the proposed method is more effective than conventional multiple-tree ALMs.

In DHT network, a node can get/put a requested data by only log N look-up steps. However, conventional DHT network only supports single query look-up to search data. From the reason, each node in a DHT network must execute look-up process for each query even if a large number of put and get operations are executed. Therefore, this results in high network load in massive data management such as MapReduce, sensor network, and web information. To address the problem, we propose multiple queries look-up architecture using range information feedback (MARIF). MARIF extends the conventional KBR protocol to supports range information that is a scope of ID space a node keeps. When a source node receives range information from a destination node, the source node checks all queries in the range information and forwards queries matching the range information to the destination node directly. This effectively reduces the number of look-up queries and the network load for the IP network. In addition, MARIF can be implemented into conventional DHT networks and can easily be combined to effective DHT routing algorithms such as Chord, Kademlia, Pastry, and one-hop DHT. In evaluation, we implement MARIF into three DHT networks and compare its performance with that of conventional query bundling mechanisms based on the KBR protocol. The results show that MARIF reduces by up to 40% the total number of forwarding queries to put data compared with other mechanisms. In addition, MARIF saves the number of forwarding queries per look-up process by up to 85% compared to other mechanisms with low bundling overhead.

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 this paper, we propose an adaptive chunk scheduling for mesh-based peer-to-peer live streaming system, a hybrid class of push and pull chunk delivery approach. The proposed rule-based push-pull scheduler simultaneously pull video chunk from lower latency peers to fill up missing chunks and push video chunk adaptively for rapid chunk delivery. We performed comparative simulation study against rarest first push-pull and status-wise push-pull to prove the efficiency of our proposed algorithm. Mesh-push is made possible by effectively exploiting the information through buffer map exchange. The findings of performance evaluation have suggested a better video continuity and achieved lower source to end delay.

In this letter, we argue that user resources will be still useful in the information-centric network (ICN). From this point of view, we first examine how P2P utilizing user resources looks like in ICN. Then, we identify challenging research issues to utilize user resources in ICN.

Characterization of peer-to-peer (P2P) traffic is an essential step to develop workload models towards capacity planning and cyber-threat countermeasure over P2P networks. In this paper, we present a classification scheme for characterizing P2P file-sharing hosts based on transport layer statistical features. The proposed scheme is accessed on a virtualized environment that simulates a P2P-friendly cloud system. The system shows high accuracy in differentiating P2P file-sharing hosts from ordinary hosts. Its tunability regarding monitoring cost, system response time, and prediction accuracy is demonstrated by a series of experiments. Further study on feature selection is pursued to identify the most essential discriminators that contribute most to the classification. Experimental results show that an equally accurate system could be obtained using only 3 out of the 18 defined discriminators, which further reduces the monitoring cost and enhances the adaptability of the system.

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.

Establishing peer-to-peer (P2P) live streaming for mobile ad hoc network (MANET) requires an efficient scheme to deliver the real-time data in the infrastructure-less disaster environment. However, P2P membership management is difficult in the dynamic mobility and resource limited MANET. In this paper, we present a cross-layer design for P2P-MANET which integrates P2P DHT-based routing protocol and IPv6 routing protocol. Therefore, the proposed scheme can manage and recover the P2P overlay as well as selecting efficient routing path to multicast video streaming. The simulation results demonstrate that the proposed scheme performs relatively better than the layered approach or the off-the-shelf design in terms of the playback continuity and signaling overhead.

In the infrastructure-less disaster environment, the application of the peer-to-peer (P2P) group conference over mobile ad hoc network (MANET) can be used to communicate with each other when the rescue crews search the survivors but work separately. However, there still are several problems of in-time multimedia delivery in P2P-MANET: (1) MANET mobility influences the maintenance of P2P overlay. (2) P2P overlay is not proximal to MANET topology, this leads to the inefficient streaming delivery. (3) The unreliable wireless connection leads to the difficulty of multi-source P2P group conferencing. Therefore, P2P conferencing cannot work well on MANET. To overcome the above disadvantages, in this paper, we present a cross-layer P2P group conferencing mechanism over MANET, called RING (Real-time Intercommunication Network Gossip). The RING uses the ring overlay to manage peers and utilizes the cross-layer mechanism to force the ring overlay to be proximal to MANET topology. Therefore, RING can lead efficient in-time multimedia streaming delivery. On the other hand, the ring overlay can deal with peer joining/leaving fast and simply, and improves the delivery efficiency with the minimum signaling overhead. Through mathematical theory and a series of experiments, we demonstrate that RING is workable and it can shorten the source-to-end delay with minimal signaling overhead.

Bittorrent is one of the most popular and successful applications in the current Internet. However, we still have little knowledge about the topology of real Bittorrent swarms, how dynamic the topology is, and how it affects overall behavior. This paper describes an experimental study of the overlay topologies of real-world Bittorrent networks, focusing on the activity of the nodes of its P2P topology and especially their dynamic relationships. Peer Exchange Protocol (PEX) messages are analyzed to infer topologies and their properties, capturing the variations of their behavior. Our measurements, verified using the Kolmogorov-Smirnov goodness of fit test and the likelihood ratio test and confirmed via simulation, show that a power-law with exponential cutoff is a more plausible model than a pure power-law distribution. We also found that the average clustering coefficient is very low, supporting this observation. Bittorrent swarms are far more dynamic than has been recognized previously, potentially impacting attempts to optimize the performance of the system as well as the accuracy of simulations and analyses.

This letter analyzes a resource chain trust model for P2P reputation-based systems. Many researchers have given a lot of efforts to reputation-based system area and some of them have made good theoretical models. Problems are to spread malicious contents whereas the remark that such models only concentrate on the relationship between the node and its direct neighbors is still controversial. To solve the problems, we introduced the RCM (Resource Chain Model) and the Enhanced RCM. In this letter, we analyze the models and then show usage of our models can help us to find the best and safest location efficiently and decrease the number of malicious transaction.

P2P (peer-to-peer) file sharing systems have been in operation for years. However, recent studies show that many peers in P2P networks are free-riders, who download files but are unwilling to share. This paper proposes a randomized search algorithm that considers the potential of a peer for information exchange and controlled query forwarding in the search process. Based on churn situations, the simulation results in this study demonstrate that the proposed algorithm can reduce network traffic and search latency while searching for files in the system.

In the network operator-friendly P2P traffic control technique such as P4P, peers are supposed to select their communication partners by following a guidance issued by the network operator. Thus, the guidance has significant impact on the traffic control. However, detailed performance study of available guidances is missing. Most existing approaches do not show how they affect intra-domain traffic control in detail while mostly focusing on inter-domain traffic control. In this paper, we try to understand how the guidances affect the intra and inter-domain traffic control for better guidance improving the traffic control. Through simulations, we reveal the following. The performance-based guidance reflecting the networking status shows attractive results in distributing the traffic over intra-domain links and in reducing the cross-domain traffic and the charging volume of inter-domain link compared to the distance-based guidance enforcing simple localization. However, the performance-based guidance shows one limitation that can cause unstable traffic control. To overcome the identified limitation, we propose peer-assisted measurement and traffic estimation approach. Then, we verify our approach through simulations.

This paper presents a novel chunk selection strategy for peer-to-peer video streaming, called enr-first selection policy, which simultaneously considers both block rarity and playback deadline. The policy intends to boost overall network-wide streaming performance, while ensuring good playback continuity of individual peers. The efficacy of the proposed scheme is validated through our performance evaluation study that demonstrates a substantial gain.

This paper presents novel hybrid push-pull protocols for peer-to-peer video streaming. Our approaches intend to reap the best of push- and pull-based schemes by adaptively switching back and forth between the two modes according to video chunk distributions. The efficacy of the proposed protocols is validated through an evaluation study that demonstrates substantial performance gains.

Recently, video streaming services using P2P (Peer-to-Peer) have attracted attention to solve the problem of load concentration on servers and to reduce large latency. Many P2P streaming systems, like Coolstreaming, however, take a complicated approach to control playback timing severely. This leads to less churn resiliency and less adaptability to fluctuation of network traffic. Therefore, we focus on a simple and robust approach to realize “pseudo” streaming with high quality, which is based on BitTorrent. In the existing methods with the simple approach, peers download pieces just closer to playback timing to decrease the playback discontinuity. However, these methods do not consider the constitution of video structure in sophisticated manner. P2P streaming system must consider several important metrics for high-quality and fair distribution. Therefore, in this paper, we propose a new P2P video streaming system considering the cooperation of three important metrics; video structure, playback timing, and piece dispersion on network. In this system, users vary three piece selections to suit the delivery status. Specifically, users preferentially download pieces which affect the video quality, which are closer to playback timing, and which improve the delivery efficiency. Moreover, we show the effectiveness of the proposed method by computer simulation.

We propose two types of autonomic and distributed cooperative behaviors of peers for peer-to-peer (P2P) file-sharing networks. Cooperative behaviors of peers are mediated by query trails, and allows the exploration of better trade-off points between file search and storage load balancing performance. Query trails represent previous successful search paths and indicate which peers contributed to previous file searches and were at the same time exposed to the storage load. The first type of cooperative behavior is to determine the locations of replicas of files through the medium of query trails. Placement of replicas of files on strong query trails contributes to improvement of search performance, but a heavy load is generated due to writing files in storage to peers on the strong query trails. Therefore, we attempt to achieve storage load balancing between peers, while avoiding significant degradation of the search performance by creating replicas of files in peers adjacent to peers on strong query trails. The second type of cooperative behavior is to determine whether peers provide requested files through the medium of query trails. Provision of files by peers holding requested files on strong query trails contributes to better search performance, but such provision of files generates a heavy load for reading files from storage to peers on the strong query trails. Therefore, we attempt to achieve storage load balancing while making only small sacrifices in search performance by having peers on strong query trails refuse to provide files. Simulation results show that the first type of cooperative behavior provides equal or improved ability to explore trade-off points between storage load balancing and search performance in a static and nearly homogeneous P2P environment, without the need for fine tuning parameter values, compared to replication methods that require fine tuning of their parameters values. In addition, the combination of the second type and the first type of cooperative behavior yields better storage load balancing performance with little degradation of search performance. Moreover, even in a dynamic and heterogeneous P2P environment, the two types of cooperative behaviors yield good ability to explore trade-off points between storage load balancing and search performance.

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.

When P2P systems are used for data sensitive systems, the data availability has become an important issue. The availability-based replication using individual node availability is the most popular method keeping high data availability efficiently. However, since the individual node availability is derived by the individual lifetime information of each node, the availability-based replication may select useless replicas. In this paper, we explore the relative MTTF (Mean Time To Failure)-based incentive scheme for the more efficient availability-based replication. The relative MTTF is used to classify the guaranteed replicas which can get the incentive node availability, and these replicas help reduce the data traffic and the number of replicas without losing the target data availability. Results from trace-driven simulations show that the replication using our relative MTTF-based incentive scheme achieves the same target data availability with 41% less data traffic and 24% less replicas.

Next generation network characteristics increase the complexity in the design and provision of advanced services, making inappropriate the selection of traditional approaches. Future networks are becoming larger in scale, more dynamic and more heterogeneous. In order to cope with these requirements, services are expected to adapt to environmental conditions and require minimum human intervention. In this paper a new model for providing autonomous and decentralized services is proposed, especially focusing on mobile ad hoc networks (MANETs). Using a newly proposed four-layered approach, service development may be realized independently from the underlying physical network. In a reference implementation, it is demonstrated that it is possible to set up an overlay network that hides any network changes from the service layer. Multiple mechanisms have been adapted in order to efficiently -- in terms of message exchanges and convergence time -- operate over an ad hoc environment. Finally, it is demonstrated that a specific service could operate over a dynamic network with multiple failures.