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In multi-tree-structured Peer-to-Peer (P2P) video streaming, video streams are delivered from the source peer to subscribing peers in such a way that each stream is divided into several sub-streams and those sub-streams are delivered through different spanning trees. In this paper, we focus on the delivery of all sub-streams to $n$ subscribers through spanning trees of depth two each, which will be referred to as the 2-hop delivery of sub-streams. The main contribution of the current paper is the derivation of a tight lower bound on the upload capacity of homogeneous peers so that 2-hop delivery is possible if and only if the upload capacity of each peer is greater than or equal to the derived bound.

The desirable global scalability of Grid systems has steered the research towards the employment of the peer-to-peer (P2P) paradigm for the development of new resource discovery systems. As Grid systems mature, the requirements for such a mechanism have grown from simply locating the desired service to compose more than one service to achieve a goal. In Semantic Grid, resource discovery systems should also be able to automatically construct any desired service if it is not already present in the system, by using other, already existing services. In this paper, we present a novel system for the automatic discovery and composition of services, based on the P2P paradigm, having in mind (but not limited to) a Grid environment for the application. The paper improves composition and discovery by exploiting a novel network partitioning scheme for the decoupling of services that belong to different domains and an ant-inspired algorithm that places co-used services in neighbouring peers.

In SOA environments, as the number of published Web Services grows, the provision of a robust, scalable and efficient discovery service is still an unresolved issue. In this paper we present a P2P-based infrastructure that leverages the semantic technologies to support a scalable and accurate service discovery process. The key concept of the presented idea is the creation of an overlay network organized in several semantic groups of peers, each specialized in answering queries pertaining to specific applicative domains. Groups are formed by clustering together peers offering services that are semantically related. A semantic query routing mechanism ensures the delivery of queries to the groups that are semantically "worth" to respond. In this paper the architecture details of the proposed solution is presented. A system prototype has also been implemented and validated through a case study deployed on the PlanetLab testbed.

Peer-to-peer (P2P) computing offers many attractive features, such as self-organization, load-balancing, availability, fault tolerance, and anonymity. However, it also faces some serious challenges. In this paper, we propose an Efficient Clustered Super-Peer P2P architecture (ECSP) to overcome the scalability and efficiency problems of existing unstructured P2P system. With ECSP, peers are grouped into clusters according to their topological proximity, and super-peers are selected from regular peers to act as cluster leaders and service providers. These super-peers are also connected to each other, forming a backbone overlay network operating as a distinct, yet integrated, application. To maintain the dynamically adaptive overlay network and to manage the routing on it, we propose an application level broadcasting protocol: Efa. Applying only a small amount of information about the topology of a network, Efa is as simple as flooding, a conventional method used in unstructured P2P systems. By eliminating many duplicated messages, Efa is much more efficient and scalable than flooding, and furthermore, it is completely decentralized and self-organized. Our experimental results prove that ESCP architecture, combined with the super-peer backbone protocol, can generate impressive levels of performance and scalability.

Replication is an important technique in peer-to-peer environment, where it increases data availability and accessibility to users despite site or communication failure. However, determining the number of replication and where to replicate the data are the major issues. This paper proposes a hybrid replication model for fixed and mobile network in order to achieve high data availability. For the fixed network, a data will be replicated synchronously in a diagonal manner of logical grid structure, while for the mobile network, a data will be replicated asynchronously based on commonly visited sites for each user. In comparison to the previous techniques, diagonal replication technique (DRG) on fixed network requires lower communication cost for an operation, while providing higher data availability, which is preferred for large systems.

The large amount of bandwidth and other resources required to deliver streaming media limits the number of concurrent users. We propose a virtual active network (VAN) architecture for streaming media data delivery over wide area networks. In the proposed architecture, cooperating proxies support multiplexing and delivery of live streaming media. The hierarchical delivery structure is dynamically adjusted based on user population distribution, usage patterns, and network conditions. The proposed system architecture provides (1) reliable and high quality live streaming media delivery; (2) lower server resource requirements at the content provider sites; (3) reduced inter-ISP traffic; (4) application level routing for rapid deployment; and (5) cost-effective media data delivery. To deal with one characteristics of live broadcasting events, burst traffic at the beginning of the events, our system features a unique function that dynamically clusters multiple proxy servers to form a server farm to handle a large number of user login events when needed. Experimental results show that the proposed VAN architecture consistently delivers reliable live data streams using resources within 10 percent of the theoretically possible lower bound. The experimental results also show the effectiveness of our load balance algorithms to handle various user patterns, server capacity, and network congestion events.

In this paper, we design and implement a P2P cooperative proxy caching system based on a novel P2P cooperative proxy caching scheme. To effectively locate the cached web documents, a TTL-based routing protocol is proposed to manage the query and response messages in the P2P cooperative proxy cache system. Furthermore, we design a predict query-route algorithm to improve the TTL-based routing protocol by adding extra information in the query message packets. To select a suitable cache replacement algorithm for the P2P cooperative proxy cache system, three different cache replacement algorithms, LRU, LFU and SIZE, are evaluated using web trace based performance studies on the implemented P2P cooperative proxy cache system. The experimental results show that LRU is an overall better cache replacement algorithm for the P2P proxy cache system although SIZE based cache replacement approach produces slightly better cache hit ratio when cache size is very small. The performance studies also demonstrate that the proposed message routing protocols significantly improve the performance of the P2P cooperative proxy cache system, in terms of cache hit ratio, byte hit ratio, user request latency, and the number of query messages generated in the proxy cache system, compared to the flooding based message routing protocol.

In the last few years peer-to-peer (P2P) systems have gained ground for multipoint video content distribution over IP networks. P2P technologies give new opportunities to define an efficient multimedia streaming application, but at the same time they involve a set of technical challenges and issues due to the best-effort service offered by the underlying Internet, and its dynamic and heterogeneous nature. Stringent requirements in terms of end-to-end delay for real-time applications motivates the choice of a tree-structured topology against other topologies that have been introduced in the last research works, but mainly aimed at non-real-time services like video on demand and live streaming. The target of this paper is to present a platform for multipoint multimedia transmission based on a tree overlay network with jitter control and to show through experiments on real environment that our platform performs better than a traditional tree overlay network system in terms of PSNR, frame loss and playout frozen time.

Many peer-to-peer (P2P) applications require that nodes behave altruistically in order to perform tasks collectively. Here we examine a class of simple protocols that aim to self-organize P2P networks into clusters of altruistic nodes that help each other to complete jobs requiring diverse skills. We introduce a variant (called ResourceWorld) of an existing model (called SkillWorld) and compare results obtained in extensive (ten billion interactions) simulation experiments. It was found that for both model variants altruistic behavior was selected when certain cost/benefit constraints were met. Specifically, ResourceWorld selects for altruism only when the collective benefit of an action is at least as high as the individual cost. This gives a minimal method for realizing so-called "social rationality," where nodes select behaviors for the good of the collective even though actions are based on individual greedy utility maximization. Interestingly, the SkillWorld model evidences a kind of superaltruism in which nodes are prepared to cooperate even when the cost is higher than the benefit.

Massively distributed data mining in large networks such as smart device platforms and peer-to-peer systems is a rapidly developing research area. One important problem here is concept drift, where global data patterns (movement, preferences, activities, etc.) change according to the actual set of participating users, the weather, the time of day, or as a result of events such as accidents or even natural catastrophes. In an important case — when the network is very large but only a few training samples can be obtained at each node locally — no efficient distributed solution is known that could follow concept drift efficiently. This case is characteristic of smart device platforms where each device stores only one local observation or data record related to a learning problem. Here we present two algorithms to handle concept drift. None of the algorithms collects data to a central location, instead models of the data perform random walks in the network, while being improved using an online learning algorithm. The first algorithm achieves adaptivity by maintaining young as well as old models in the network according to a fixed age distribution. The second one measures the performance of models locally, and discards them if they are judged outdated. We demonstrate through a thorough experimental analysis that our algorithms outperform the known competing methods if the number of independent local samples is limited relative to the speed of drift: a typical scenario in our targeted application domains. The two algorithms have different strengths: while the age distribution approach is very simple and efficient, explicit drift detection can be useful in monitoring applications to trigger control action.

The new vision of the Web as a global intelligent repository needs advanced knowledge structure to manage complex data and services. From this perspective, the use of formal models to represent information on the web is a suitable way to allow the cooperation of users and services. This paper describes a general ontological approach to represent knowledge using multimedia data and linguistic properties to bridge the gap between the target semantic classes and the available low-level multimedia descriptors. We choose to implement our approach in a system to edit, manage and share multimedia ontology in the WEB. The system provides tools to add multimedia objects by means of user interaction. The multimedia features are automatically extracted using algorithms based on standard MPEG-7 descriptors.

Page Rank is the basis of the most modern search engines for both Internet and P2P networks, it is defined as the importance of a web page or the reputation value of a peer, viewed as a vote from all the web pages (peers) that link to it, weighted by their importance or reputation. With the exponential growth of the web size and peer nodes of Internet, knowing where to search becomes a really hard problem, optimizing and focusing search is often resolved by computing and comparing page rank values for web page or files. In this work, we present an overview of several top page ranking algorithms for Internet and P2P networks, then analyze and compare their computing performance and precision, finally give some simulation results in power law networks.

The new P2P-C/S hybrid architecture is put forward and the communication mechanism and node selection algorithms for the hybrid architecture are discussed in detail. Because the architecture and the communication protocol can change the degree of participation of the server and the peers, it can ease the burden of Source Node or improve the expansibility and stability of the system. The BTPublisher, which is improved on the base of the popular BitTorrent, is based on the hybrid architecture. In the system, because the SourceNode is introduced to the traditional P2P network, the BTPublisher can have the characters of high expansibility and high-efficiency transmission.

With its own unique advantages, Peer-to-peer (or P2P) system has gained tremendous momentum in recent years. Their applications become more and more extensive. P2P is used in large-scale, which has facilitated the development of the technology used in network and challenged the use of network bandwidth. Particularly, the application of large-scale audio/video file sharing system and software based on P2P consumes a large fraction of bandwidth resource, and even causes network congestion and decrease of the performance of other businesses. Thus, to ensure the Quality of Service of other normal businesses, a reliable method of inspecting and identifying P2P flows and controlling the consumption of network bandwidth of P2P flows is highly demanded in this paper, we proposed a novel method which can inspect and recognize the P2P traffic based on Transport Layer. With the method, we can control P2P traffic more efficiently.

Peer-to-Peer Video-on-Demand (P2P VoD) over Internet has become an effective and popular way to provide video information to users. The knowledge of video popularity is very important for system operation, such as video caching on peer-to-peer network. The video popularity distribution at a given time is quite well understood. However, in this paper, we study how the video popularity changes with time, classifying them into different types, and apply the results to design a novel popularity prediction model, which is derived by analyzing the video’s user rating information as well as time-variation. Based on this model, we propose a dynamic popularity-based cache replication strategy (DPCR). The simulation results demonstrate that our proposed algorithm can greatly reduce servers' workload and improve the streaming quality.

As the energy consumption of storage systems is grows at a staggering rate, hybrid clusters have gained increasing importance as a potential approach to tackle this challenge. By introducing low-power nodes, data-driven companies like Facebook and Baidu have reduced the energy consumption effectively in their Master/Slave based storage systems. However, the Master/Slave based systems have several typical disadvantages such as low scalabilities and single points of failure. The P2P based systems with high scalabilities utilizes file location algorithms instead of table lookup mechanisms, thus resulting in a problem of how to utilize the different storage nodes discriminatively. In this paper, a hierarchical storage strategy called vnode hierarchical remapping (VHR) is proposed based on ’a P2P distributed system called ZDFS. The strategy guarantees the high scalability and viability of ZDFS, and takes advantage of different storage nodes. Several test cases running on X86 and ARM hybrid clusters are carried out, and the test results demonstrate that the VHR works well, it achieves a good I/O performance and low data access response time while reducing the energy consumption by 44.8%.

The new vision of the Web as a global intelligent repository needs advanced knowledge structure to manage complex data and services. From this perspective, the use of formal models to represent information on the web is a suitable way to allow the cooperation of users and services. This paper describes a general ontological approach to represent knowledge using multimedia data and linguistic properties to bridge the gap between the target semantic classes and the available low-level multimedia descriptors. We choose to implement our approach in a system to edit, manage and share multimedia ontology in the WEB. The system provides tools to add multimedia objects by means of user interaction. The multimedia features are automatically extracted using algorithms based on standard MPEG-7 descriptors.