A Peer-To-Peer (P2P) application uses an overlay network which is a virtual network constructed over the physical network. Traditional overlay construction methods do not take physical location of nodes into consideration, resulting in a large amount of redundant traffic. Some proximity-aware construction methods have been proposed to address this problem. These methods typically connect nearby nodes in the physical network. However, as the number of nodes increases, the path length of a route between two distant nodes rapidly increases. To alleviate this problem, we propose a technique which can be incorporated in existing overlay construction methods. The idea behind this technique is to employ long links to directly connect distant nodes. Through simulation experiments, we show that using our proposed technique, networks can achieve small path length and low communication cost while maintaining high resiliency to failures.

In this paper, we propose a file replication method to achieve load balancing in terms of write access to storage device ("write storage access load balancing" for short) in unstructured peer-to-peer (P2P) file-sharing networks in which the popularity trend of queried files varies dynamically. The proposed method uses a write storage access ratio as a load balance index value in order to stabilize dynamic P2P file-sharing environments adaptively. In the proposed method, each peer autonomously controls the file replication ratio, which is defined as a probability to create the replica of the file in order to uniform write storage access loads in the similar way to thermal diffusion phenomena. Theoretical analysis results show that the behavior of the proposed method actually has an analogy to a thermal diffusion equation. In addition, simulation results reveal that the proposed method has an ability to realize write storage access load balancing in the dynamic P2P file-sharing environments.

As a concept stemmed from social field, we argued that, in P2P networks, peers' recommendation behaviors and functional behaviors should be explicitly separated, thus we propose the HopRec scheme which uses hop-based recommendation ability to improve the accuracy of reputation ranking in P2P networks. Our contributions lie in the following aspects: firstly, we adopt the simple but effective idea to infer peer's recommendation ability (RA): the farer away that peer is from the initial malicious seeds, the higher RA that peer should have; Then, the computation of reputation rankings appropriately reflects peer's different RA. The simulation results show that, in comparison with Eigentrust-like algorithms, HopRec can be robust to sybils and front peers attacks, and achieve significant performance improvement. Moreover, we compare HopRec with two related schemes, Poisonedwater and CredibleRank, and found that: in hospitable P2P environment, HopRec can obtain better performance than Poisonedwater, and can achieve the comparable performance as CredibleRank, with less computation overhead then CredibleRank. Finally, we also show that, if the initial good and malicious seeds could be selected based on peers' degrees, then HopRec and CredibleRank can achieve perfect performance.

P2P (Peer-to-Peer) file sharing architectures have scalable and cost-effective features. Hence, the application of P2P architectures to media streaming is attractive and expected to be an alternative to the current video streaming using IP multicast or content delivery systems because the current systems require expensive network infrastructures and large scale centralized cache storage systems. In this paper, we investigate the P2P progressive download enabling Internet video streaming services. We demonstrated the capability of the P2P progressive download in both laboratory test network as well as in the Internet. Through the experiments, we clarified the contribution of the FTTH links to the P2P progressive download in the heterogeneous access networks consisting of FTTH and ADSL links. We analyzed the cause of some download performance degradation occurred in the experiment and discussed about the effective methods to provide the video streaming service using P2P progressive download in the current heterogeneous networks.

The security of P2P networks depends on building trust management among peers. However, current trust management models focus on preventing untrustworthy resources from spreading by malicious providers, but have few effects on reducing denial-of-service attacks of malicious consumers and free riding of selfish peers. Pointing to these problems, a bi-evaluation trust management model, called BiTrust, is proposed. In this model, the trustworthiness of a peer is divided into service and request trustworthiness. Service trustworthiness shows the resources reliability of providers, and request trustworthiness is used to deal with requests from consumers, which can keep away malicious consumers and encourage selfish peers to share resources. A generic method for evaluating service and request trustworthiness is described. Furthermore, the implementation strategies of the model are also depicted in this paper. The following analysis and simulation show that BiTrust is more effective on enhancing high-quality resources sharing among peers and more advanced in successful exchanges rate.

In this paper we propose a file replication scheme inspired by a thermal diffusion phenomenon for storage load balancing in unstructured peer-to-peer (P2P) file sharing networks. The proposed scheme is designed such that the storage utilization ratios of peers will be uniform, in the same way that the temperature in a field becomes uniform in a thermal diffusion phenomenon. The proposed scheme creates replicas of files in peers probabilistically, where the probability is controlled by using parameters that can be used to find the trade-off between storage load balancing and search performance in unstructured P2P file sharing networks. First, we show through theoretical analysis that the statistical behavior of the storage load balancing controlled by the proposed scheme has an analogy with the thermal diffusion phenomenon. We then show through simulation that the proposed scheme not only has superior performance with respect to balancing the storage load among peers (the primary objective of the present proposal) but also allows the performance trade-off to be widely found. Finally, we qualitatively discuss a guideline for setting the parameter values in order to widely find the performance trade-off from the simulation results.

In the present paper, we propose an evolutionary P2P networking technique that dynamically and adaptively optimizes several P2P network topologies, in which all of the nodes are included at the same time, in an evolutionary manner according to given evaluation criteria. In addition, through simulations, we examine whether the proposed evolutionary P2P networking technique can provide reliable search capability in dynamic P2P environments. In simulations, we assume dynamic P2P environments in which each node leaves and joins the network with its own probability and in which search objects vary with time. The simulation results show that topology reconstruction by the evolutionary P2P networking technique is better than random topology reconstruction when only a few types of search objects are present in the network at any moment and these search objects are not replicated. Moreover, for the scenario in which the evolutionary P2P networking technique is more effective, we show through simulations that when each node makes several links with other nodes in a single network topology, the evolutionary P2P networking technique improves the reliable search capability. Finally, the number of links that yields more reliable search capability appears to depend on how often nodes leave and join the network.

We present the concept of folksonomical peer-to-peer (P2P) file sharing networks that allow participants (peers) to freely assign structured search tags to files. These networks are similar to folksonomies in the present Web from the point of view that users assign search tags to information distributed over a network. As a concrete example, we consider an unstructured P2P network using vectorized Kansei (human sensitivity) information as structured search tags for file search. Vectorized Kansei information as search tags indicates what participants feel about their files and is assigned by the participant to each of their files. A search query also has the same form of search tags and indicates what participants want to feel about files that they will eventually obtain. A method that enables file search using vectorized Kansei information is the Kansei query-forwarding method, which probabilistically propagates a search query to peers that are likely to hold more files having search tags that are similar to the query. The similarity between the search query and the search tags is measured in terms of their dot product. The simulation experiments examine if the Kansei query-forwarding method can provide equal search performance for all peers in a network in which only the Kansei information and the tendency with respect to file collection are different among all of the peers. The simulation results show that the Kansei query forwarding method and a random-walk-based query forwarding method, for comparison, work effectively in different situations and are complementary. Furthermore, the Kansei query forwarding method is shown, through simulations, to be superior to or equal to the random-walk based one in terms of search speed.

Most P2P systems divide a file into many pieces and fetch different pieces from many peers simultaneously. If one of the last few pieces is requested from an extremely slow peer, the overall download time may become excessive. The end-game mode was proposed to solve this problem. This method requests the last piece from all the connected peers at the same time. Unfortunately, the duplicated requests generate redundant traffic. This paper proposes a requesting method that does not increase overall download time as well as avoiding the redundant traffic. We also propose a combination of our requesting method and the end-game mode. The proposed methods are compared to the existing method with the end-game mode in simulations that use BitTorrent as a typical instance of the parallel retrieving P2P system. The results confirm that our requesting method can match the download times of the end-game mode while suppressing the redundant traffic. Our method enhances network performance by absorbing the difference in peer performance and providing steady download times without wasting traffic resources. Moreover, it is also confirmed that our combination method can distribute a file more quickly than other methods.

Searching mechanisms employed in unstructured overlay networks typically hit multiple peers for the desired content. We propose the use of a simple method that raises the hit rates of unpopular contents and balances the loads by choosing the peer holding the least contents as the provider when multiple candidates exist.

Worms are a common phenomenon in today's Internet and cause tens of billions of dollars in damages to businesses around the world each year. This article first presents various concepts related to worms, and then classifies the existing worms into four types- Internet worms, P2P worms, email worms and IM (Instant Messaging) worms, based on the space in which a worm finds a victim target. The Internet worm is the focus of this article. We identify the characteristics of Internet worms in terms of their target finding strategy, propagation method and anti-detection capability. Then, we explore state-of-the-art worm detection and worm containment schemes. This article also briefly presents the characteristics, defense methods and related research work of P2P worms, email worms and IM worms. Nowadays, defense against worms remains largely an open problem. In the end of this article, we outline some future directions on the worm research.

This paper introduces a methodology for engineering best-effort P2P algorithms into dependable P2P-based network control mechanism. The proposed method is built upon an iterative approach consisting of improving the original P2P algorithm by appropriate mechanisms and of thorough performance assessment with respect to dependability measures. The potential of the methodology is outlined by the example of timely routing control for vertical handover in B3G wireless networks. In detail, the well-known Pastry and CAN algorithms are enhanced to include locality. By showing how to combine algorithmic enhancements with performance indicators, this case study paves the way for future engineering of dependable network control mechanisms through P2P algorithms.

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.

We observe that P2P traffic has peculiar characteristics as opposed to the other type of traffic such as web browsing and file transfer. Since they exploit swarm effect -- a multitude of end points downloading the same content piece by piece nearly at the same time, thus, increasing the effectiveness of caching -- the same pieces of data end up traversing the network over and over again within mostly a short time window. In the light of this observation, we propose a network layer packet-level caching for reducing the volume of emerging P2P traffic, transparently to the P2P applications -- without affecting operations of the P2P applications at all -- rather than banning it, restricting it, or modifying P2P systems themselves. Unlike the other caching techniques, we aim to provide as generic a caching mechanism as possible at network layer -- without knowing much detail of P2P application protocols -- to extend applicability to arbitrary P2P protocols. Our preliminary evaluation shows that our approach is expected to reduce a significant amount of P2P traffic transparently to P2P applications.

With an enhanced client computer performance and network bandwidth, content distribution services are receiving much attention. However client/server model and peer-to-peer model require vast cost for content distributions. These costs pose an impediment to broaden commercialization of content distribution services via the Internet. Content distribution cost consists of investment for server and network infrastructure which client/server model and peer-to-peer model require respectively. Thus, We focus on network infrastructure, especially in peer-to-peer content distribution networks which drastically increase traffic volume. The main feature of our proposal is utilization of inexpensive inter-ISP connections. This paper presents methods to constitute peer-to-peer content distribution networks that realizes lower cost content distribution and a reduction in the amount of inter-ISP traffic and its costs by considering the priority in usage of ISP interconnections in its distribution. Our proposal extends BitTorrent, which has been widely deployed by several content providers to reduce the load in congested servers and the distribution costs. Our performance evaluations show that our proposal achieves a reduction in network infrastructure costs and improved performance such as distribution time.

In this paper, we propose a fault tolerant hybrid p2p-CDN video streaming arhitecture to overcome the problems caused by peer behavior in peer-to-peer (P2P) video streaming systems. Although there are several studies modeling and analytically investigating peer behaviors in P2P video streaming systems, they do not come up with a solution to guarantee the required Quality of the Services (QoS). Therefore, in this study a hybrid geographical location-time and interest based clustering algorithm is proposed to improve the success ratio and reduce the delivery time of required content. A Hybrid Fault Tolerant Video Streaming System (HFTS) over P2P networks conforming the required QoS and Fault Tolerance is also offered. The simulations indicate that the required QoS can be achieved in streaming video applications using the proposed hybrid approach.

In 2006, Miranda et al. proposed an anonymity scheme to achieve peers' anonymity in Peer-to-Peer (P2P) reputation systems. In this paper, we show that this scheme can not achieve peers' anonymity in two cases. We also propose an improvement which solves the problem and improves the degree of anonymity.

Managing increasing traffic from Instant Messengers and P2P applications is becoming more important nowadays. We present an in-kernel architecture of management gateway, namely kP2PADM, built upon open-source packages with several modifications and design techniques. First, the in-kernel design streamlines the data path through the gateway. Second, the dual-queue buffer eliminates head-of-line blocking for multiple connections. Third, a connection cache reduces useless reconnection attempts from the peers. Fourth, a fast-pass mechanism avoids slowing down the TCP transmission. The in-kernel design approximately doubles the throughput of the design in the user space. The internal benchmarks also analyze the impact of each function on performance.

Using Bloom filters is one of the most popular and efficient lookup methods in P2P networks. A Bloom filter is a representation of data item indices, which achieves small memory requirement by allowing one-sided errors (false positive). In the lookup scheme besed on the Bloom filter, each peer disseminates a Bloom filter representing indices of the data items it owns in advance. Using the information of disseminated Bloom filters as a clue, each query can find a short path to its destination. In this paper, we propose an efficient extension of the Bloom filter, called a Deterministic Decay Bloom Filter (DDBF) and an index dissemination method based on it. While the index dissemination based on a standard Bloom filter suffers performance degradation by containing information of too many data items when its dissemination radius is large, the DDBF can circumvent such degradation by limiting information according to the distance between the filter holder and the items holders, i.e., a DDBF contains less information for faraway items and more information for nearby items. Interestingly, the construction of DDBFs requires no extra cost above that of standard filters. We also show by simulation that our method can achieve better lookup performance than existing ones.

Abnormal traffic that causes various problems on the Internet, such as P2P flows, DDoS attacks, and Internet worms, is increasing; therefore, the importance of methods that identify and control abnormal traffic is also increasing. Though the application of frequent-itemset-mining techniques is a promising way to analyze Internet traffic, the huge amount of data on the Internet prevents such techniques from being effective. To overcome this problem, we have developed a simple frequent-itemset-mining method that uses only a small amount of memory but is effective even with the large volumes of data associated with broadband Internet traffic. Using our method also involves analyzing the number of distinct elements in the itemsets found, which helps identify abnormal traffic. We used a cache-based implementation of our method to analyze actual data on the Internet and demonstrated that such an implementation can be used to provide on-line analysis of data while using only a small amount of memory.