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A Peer-to-peer (P2P) network system has proved to be a popular and efficient approach for large-scale live video streaming and file sharing over the Internet. Such a system is always challenged by various issues and requires to be monitored and controlled for significant performance. Among them, one of the major performance issues in P2P networks is the flash crowd. When many users switch to a popular channel in a short span of time, the P2P system suffers from a serious join congestion problem, called the flash crowd problem. In such situations, systems can scale only up to a limit, both by available surplus bandwidth and intense competition among peers for their start-up, and hence, it not only decreases the efficiency but also creates a blockage of services for connected peers. Therefore, management of the flash crowd has been important and becoming paramount with the increased use of online services and the proliferation of various technologies like IoT, Edge & Mobile Computing, Crypto Currencies, and Torrenz-like services. A hierarchy-based admission control model with multiple threshold layers is proposed to mitigate the flash crowd in the P2P network paradigm. A fuzzy logic-based prediction mechanism is proposed to predict the control scheme applicable to the requested peers based on the parameters such as buffer size, bandwidth, etc. In case of the occurrence of the flash crowd, the model applies different control schemes depending upon which threshold layer it is predicted. These include saving the system resources, granting preferences to best-performing peers, dropping requests of worst-performing peers, a slight decrease in service quality, etc. We also characterize the credit score of peers, which denotes their performances. The model is simulated in OMNET++ along with the OverSim framework. Results from the simulation reveal a reduction in request drops, processing delays, and startup delays compared to other management schemes. [ABSTRACT FROM AUTHOR]

Peer-to-Peer (P2P) networks is a distributed structure, which is widely used in file sharing, distributed computing, deep search engines. Each node plays the dual role of client and server, which makes the P2P network further exacerbates the insecurity of P2P systems. For the behavior of nodes in P2P systems, requesting nodes are abstracted into customers and service nodes are abstracted into servers. An M/M/c queueing model is developed with dynamically changing servers in almost unobservable cases, strategies are introduced, including start-up period, working sleep of service nodes and negative customers, etc. Using the matrix-geometric solution and Gauss-Seidel iteration method, average waiting length, average sojourn time, total energy consumption and throughput are derived. Through numerical experiments, the process of P2P file sharing is simulated, the optimal value of social utility is obtained using Nash equilibrium and social optimal strategy, and a theoretical basis is provided for node scheduling in P2P systems. [ABSTRACT FROM AUTHOR]

In this paper, we study a new type of fuzzy relation system called fuzzy relational inequalities with addition-min-product composition operations to model a peer-to-peer (P2P) file sharing system. Some properties of this addition-min-product system are investigated. We then characterize the structure of the solution set. Furthermore, to reduce the network congestion and improve the stability of data transmission, a min–max programming problem with constraints of addition-min-product fuzzy relation inequalities is established and investigated. We divide this min–max programming problem into several subproblems with the constraint of a single equation. Based on the optimal solutions to these subproblems, we can solve the original fuzzy relation min–max programming problem. Two algorithms, with polynomial computational complexity, are developed to search for an optimal solution to our studied problem. The validity of the algorithms is examined through a numerical example. [ABSTRACT FROM AUTHOR]

The focus of this paper is to design and develop a Peer-to-Peer Presentation System (P2P-PS) that supports E-learning through live media streaming coupled with a P2P shared whiteboard. The participants use the "ask doubt" feature to raise and resolve doubts during a session of ongoing presentation. The proposed P2P-PS system preserves causality between ask doubt and its resolution while disseminating them to all the participants. A buffered approach is employed to enhance the performance of P2P shared whiteboard, which may be used either in tandem with live media streaming or in standalone mode. The proposed system further extends P2P interactions on stored contents (files) built on top of a P2P file sharing and searching module with additional features. The added features allow the creation of mash-up presentations with annotations, posts, comments on audio, video, and PDF files as well as a discussion forum. We have implemented the P2P file sharing and searching system on the de Bruijn graph-based overlay for low latency. Extensive experiments were carried out on Emulab to validate the P2P-PS system using 200 physical nodes. [ABSTRACT FROM AUTHOR]

Considering the requirement of the biggest download speed, a Peer-to-Peer (P2P) file sharing system can be reduced into a system of max–min fuzzy relation inequalities. In order to decrease the network congestion under some fixed priority grade of the terminals, fuzzy relation lexicographic programming is proposed to model the P2P file sharing system. For solving the proposed problem, we define concept of feasible index set and discuss some simple properties. Based on the feasible index set, a novel algorithm is developed to find the optimal solution with an illustrative example. [ABSTRACT FROM AUTHOR]

Spam appears in various forms and the current trend in spamming is moving towards multimedia spam objects. Image spam is a new type of spam attacks which attempts to bypass the spam filters that mostly text-based. Spamming attacks the users in many ways and these are usually countered by having a server to filter the spammers. This paper provides a fully-distributed pattern recognition system within P2P networks using the distributed associative memory tree (DASMET) algorithm to detect spam which is cost-efficient and not prone to a single point of failure, unlike the server-based systems. This algorithm is scalable for large and frequently updated data sets, and specifically designed for data sets that consist of similar occurring patterns.We have evaluated our system against centralised state-of-the-art algorithms (NN, k-NN, naive Bayes, BPNN and RBFN) and distributed P2P-based algorithms (Ivote-DPV, ensemble k-NN, ensemble naive Bayes, and P2P-GN). The experimental results show that our method is highly accurate with a 98 to 99% accuracy rate, and incurs a small number of messages—in the best-case, it requires only two messages per recall test. In summary, our experimental results show that the DAS-MET performs best with a relatively small amount of resources for the spam detection compared to other distributed methods. [ABSTRACT FROM AUTHOR]

P2P file-sharing networks allow peers (computers) to download files and make them available to other users on the network. The fear of downloading worm file is a reasonable reason to discourage users to utilize P2P file-sharing networks. So, peers may hesitate to open the downloaded files due to the concern of receiving poisoned files or being compromised by malwares. In this article, we present a model of spread of passive worm in P2P file-sharing networks, where susceptible peers which were already infected before, are reluctant to open new downloaded files. Here, we address this issue by introducing a modified SEIS model, where λe (average rate at which exposed peer opens a downloaded file) decreases with the number of reinfections n for a maximum of ℓ times (λe(n+1) = 휖λe(n)where 0<휖<1represents the hesitation value). Hence, for a susceptible peer which was already infected by the worm, the hesitation to open a new downloaded file is quantified by the two parameters (휖,ℓ). We studied numerically the effects of various system parameters on the time evolution of the peer states. At steady state and for every value of ℓ, there exists a critical value 휖c below which the system is infection-free. A phase diagram in the plane (휖,ℓ) is constructed that shows which phases are present according to the state variables. In addition, we introduced and evaluated the effect of different patch-based immunization strategies to show how they could block the spread of the worm in the system. The immunization patch is launched in the network at a time tl and will be out of order at a time tf (i.e. outdated patch). We found that the parameters (tl,tf, 휖) are very important to be defined when developing the immunization patch. [ABSTRACT FROM AUTHOR]

Two fundamental and persistent problems that still confront BitTorrent are unfairness and free riding. This paper proposes O-Torrent, a P2P content distribution mechanism that is derived in principal from BitTorrent. O-Torrent deploys the concept of unidirectional transfers among groups of peers who are arranged in rings. Each peer in O-Torrent can construct one ring and admit peers to it. A peer who constructs a ring becomes its father and hence its administrator. O-Torrent is fair, each peer must upload and participate in the sharing process in order to download. It implements an effective Serve/Request incentive mechanism which enhances the robustness of the mechanism. Furthermore, our results suggest that O-Torrent performs more effectively in punishing free riding behavior and provides better performance than BitTorrent. [ABSTRACT FROM AUTHOR]

To design peer-to-peer (P2P) software systems is a challenging task, because of their highly decentralized nature, which may cause unexpected emergent global behaviors. The last fifteen years have seen many P2P applications to come out and win favor with millions of users. From success histories of applications like BitTorrent, Skype, MyP2P we have learnt a number of useful design patterns. Thus, in this article we present a P2P pattern language (shortly, P2P-PL) which encompasses all the aspects that a fully effective and efficient P2P software system should provide, namely consistency of stored data, redundancy, load balancing, coping with asymmetric bandwidth, decentralized security. The patterns of the proposed P2P-PL are described in detail, and a composition strategy for designing robust, effective and efficient P2P software systems is proposed. [ABSTRACT FROM AUTHOR]

Mobile ad-hoc networks (MANETs) is a collection of wireless mobile nodes forming a temporary network without any fixed infrastructure or centralized administration. Although MANETs are easily deployed, they have several constraints such as; continuously changing topology, distributed operations, limitations of nodes radio interface. Recently, Ad-Hoc routing has become an important area of research due to the massive increase in wireless devices. Routing in MANETs is based on a cooperative multi-hop manner. However, due to the highly dynamic topology routing in MANETs is a true challenge. In this paper, we propose a new routing strategy for MANETs called Adaptive Hybrid Routing Strategy (AHRS). The basic idea of AHRS is to inform the network mobile nodes continuously with any changes in the network topology without flooding the network by a huge amount of control messages. AHRS is a hybrid routing strategy that can estimate failure time of links between network nodes through the historical information about link status. Accordingly, AHRS introduces not only the shortest available routes for data transmission, but also elects those reliable ones. AHRS uses no periodic routing advertisement messages but employs a special packet called ‘Carriage’ instead, thereby reducing the network bandwidth overhead and minimizing end-to-end transmission delay. AHRS has been compared against several well-known protocols, which are; DSDV, ZRP, AODV and DSR. Experimental results have shown that AHRS outperforms all competitive protocols as it introduces the minimal routing overheads, as well as a fast route delivery. [ABSTRACT FROM AUTHOR]

With the widespread use of Location-base Services(LBSs), the problem of location privacy has drawn significant attention from the research community. To protect the user’s exact location, a new notion of privacy, named geo-indistinguishability, that adapts differential privacy has been proposed for LBSs, recently. However, the obfuscation mechanism satisfying this privacy notion only works well in the case of snapshot LBS, which would not apply to the case of continuous LBSs due to the quick loss of privacy caused by the correlation between locations in the trace. In this paper, we propose a novel mechanism, namely AGENT, to protect the user’s location privacy in continuous LBSs. In AGENT, a R-tree is introduced to realize the reusable of generated sanitized locations, which achieves the notion of geo-indistinguishability with less consumption of privacy budget. Finally, empirical results over real-world dataset demonstrate that with the same utility, our mechanism consumes less privacy budget to obfuscate the same trace. [ABSTRACT FROM AUTHOR]

Congestion management capability is an important requirement for any quality of services (QoS) networking technology. Therefore, IEEE 802.1Qau has proceeded a congestion notification project whose aim is to develop a Carrier Ethernet congestion control scheme at Layer 2 for a data center network. A data center network should be efficient and robust to handle the growing demands of cloud computing. A congestion control scheme is a key component of data transport in this kind of network. The quantized congestion notification (QCN) scheme is a congestion management scheme, which has been standardized and designed to be implemented in the Carrier Ethernet. Coloured Petri net (CPN) is a modelling technique used with the Petri nets modelling tool. This technique is exploited to model and simulate the QCN in order to help understand the QCN scheme and derive performance measures. This paper proposes a formal model for the QCN scheme. Then, we verify the implementation of our model by simulations. Thus, the QCN queue and rate performances are evaluated using the CPN tools. Moreover, an improved model called TAI-QCN is proposed in order to enhance the QCN scheme. [ABSTRACT FROM AUTHOR]

In Peer to Peer systems (P2P); an only companion is connected to another associate in a different stockpiling framework. A different gathering of resolutions depicts disseminated hash tables outlines resources onto hubs in P2P system. It offers a “find - obtain” development where getting the advantages in the framework is available, and like this it can get back. DHT offers a liberal position of hubs and administrations yet don’t protect adjacent to vindictive hub moving lookups (the movement used to arrange the benefits in the system). Malicious hubs on a look-up pathway can precisely undermine question. Frameworks like Halo (in light of the harmony) reduction such ambushes by utilizing pointless lookup inquiries. To supply better affirmation; Reputation for Directory administrations is an establishment for training so as to boost lookups in abundance DHT how well new hubs administration lookup wishes. ReDS technique can be executed too for all intents and purposes any abundance DHT containing corona. Additionally, it perceives shared acknowledgment and dispenses with of difficult lookup paths. This acknowledgment does not wager on the partitioning of notoriety numbers and isolating is helpless to assaults that make larger part use of ReDS unfit. Corona is a plan that deeds the deterministic arranging of access to hubs in the harmony to introduce a “high-affirmation situate” through pointless investigates. Radiance was proposed to contain dynamic lookups and can browse different ways. Partitioned notoriety technique for Halo, has deterministic finger gathering. In deciding notoriety organize; the holes of attackers are diminished by utilizing unique Reciprocal Channel Variation based Identification (RCVI) technique. Load imbalance issue emerges through this lookup activity. Each Peer handles the heap by contrasting its ability. ReDS creates accomplishment lookup rates for Halo, yet next to think assailant was trying to brandish their notoriety achieves and in the presence of hub twirl. [ABSTRACT FROM AUTHOR]

Cloud computing is an emerging field in computer science. Users are utilizing less of their own existing resources, while increasing usage of cloud resources. There are many advantages of distributed computing over centralized architecture. With increase in number of unused storage and computing resources and advantages of distributed computing resulted in distributed cloud computing. In the distributed cloud environment that we propose, resource providers (RP) compete to provide resources to the users. In the distributed cloud all the cloud computing and storage services are offered by distributed resources. In this architecture resources are used and provided by the users in a peer to peer fashion. We propose using multi-valued distributed hash tables for efficient resource discovery. Leveraging the fact that there are many users providing resources such as CPU and memory, we define these resources under one key to easily locate devices with equivalent resources. We have evaluated the performance of resource discovery mechanisms for the distributed cloud and distributed cloud storage and compared the results with existing DHTs, peer to peer clients such as VUZE [1] and explored the feasibility and efficiency of the proposed schemes in terms of resource/service discovery and allocation. We use a simultaneous Auction mechanism and select a set of winners once we receive all contributions or bids. In a real world scenario, users request resources with multiple capabilities, and in order to find such resources we use a contribution mechanism where service providers will provide a contribution price to users for providing a resource. Users use our proposed auction mechanism to select the resources from the set of resource providers. We show that Nash equilibrium can be achieved and how we can avoid the problem of free riders in the distributed cloud. [ABSTRACT FROM AUTHOR]

Peer-to-Peer (P2P) traffic is widely used for the purpose of streaming media, file-sharing, instant messaging, games, software etc., which often involves copyrighted data. From the past decade, P2P traffic has been contributing to major portion of Internet traffic which is still rising and hence is consuming a lot of network traffic bandwidth. It also worsens congestion of network traffic significantly and degrades the performance of traditional client-server applications. Popularity of various P2P applications has led Internet Service Providers (ISPs) to face various challenges regarding efficiently and fairly utilizing network resources. The traditional methods of identifying P2P traffic such as port-based and payload-based are proving ineffective due to their significant limitations and can be bypassed. Hence, new approaches based on statistics or behaviour of network traffic needs to be developed and adopted in order to accurately identify existing and new P2P traffic which emerge over the time. This article presents a survey regarding various strategies involved in identifying P2P traffic. Furthermore, conceptual analysis of network traffic measurement and monitoring is also presented. [ABSTRACT FROM AUTHOR]

This paper considers the possibility of constructing new-generation conflict-free (both cellular and peer-to-peer) synchronous broadband wireless networks in which users can simultaneously transmit information in the same frequency band without conflicts (media access collisions). This kind of networks can be constructed by combining the theory of code division multiple access (CDMA) with the broadcasting method. Here, broadcasting means that the user transmits information to a group of users within its radio line of sight by inserting a message header into a unified codeword. [ABSTRACT FROM AUTHOR]

This paper gives an exact mathematical programming model and algorithm of the max-min fairness bandwidth allocation problem in multi-swarm peer-to-peer content sharing community. The proposed iterative method involves solution of LP and MILP problems of large scale. Based on real-world data traces, numerical experiments demonstrate that the new algorithm is computationally faster than an earlier developed one for larger problem sizes, and it provides better numerical stability. Moreover, even if its execution is stopped after some initial steps it still grants feasible solution with good approximation to max-min fairness. [ABSTRACT FROM AUTHOR]

We propose an algorithm that exploits the properties of Scalable Video Coding (SVC) in order to minimize the upload bandwidth at each peer. More specifically, we propose streaming different layers of the same video from different peers. The paper defines an optimization problem to handle the upload bandwidth at each peer. However, the solution to the proposed problem is NP complete. Therefore, we propose an approximation algorithm to solve this problem. In addition, seed servers are introduced in order to deal with extra load in the network. The proposed method provides better performance as compared to the current approaches that use single layer video in combination with SVC. We have compared our simulation results with the model proposed in Shabnam and Mohamed (2010). The simulation results show that the proposed model improves diversity, increases average video quality, reduces the effect of churn and manages flash crowds. [ABSTRACT FROM AUTHOR]

In this article, we describe the desired attributes to build a system aimed to content distribution in enterprise networks. As a result of this characterisation, we propose several additions to BitTorrent, which is currently used for personal use, so it could efficiently work with large-scale enterprise networks. The modifications are necessary to address NAT, double NAT, and firewalls that are common in enterprise environments. To deal with these problems, the protocol is augmented and also a description of the mechanisms to handle these variations is given. Simulation experiments show that results for this proposed work are much more efficient than BitTorrent since we took advantage of distinctive characteristics in these networks. By efficient, we mean: 1) decrease time to download content, 2) provide support to external hosts (other LANs), while 3) WAN bandwidth is used in the best possible manner. [ABSTRACT FROM AUTHOR]

Peer-to-peer (P2P) file sharing system provides a platform that enables users to share their files over network and provides a rapid and scalable content distribution mechanism to access an explosive volume of shared files on the system. The search mechanism in these systems is mainly keyword-based, so, users may have to try different keywords to find the desired file, where increase the network traffic. Therefore, the existence of a tool in these clients that guide users towards the top-k most downloaded files is very beneficial in terms of user convenience and traffic reduction. We have proposed our algorithms by adding a new data structure to chord protocol. Chord has been widely used as a routing protocol in structured P2P networks. We validated our proposed algorithms through simulation by using PlanetSim simulator and studied the effect of several parameters on the performance of our algorithms. The results show very good performance, in terms of communication cost and response time. [ABSTRACT FROM AUTHOR]

In peer-to-peer (P2P) networks, each peer acts as the role of client and server. As a client, each peer is regarded as a service customer. It sends requests to other peers to download files and obtains resource allocation from them. As a server, each peer is thought as a service provider. It receives service requests from other peers and allocates its resources to them. To encourage cooperation between peers, fairness is very important in P2P networks since it fosters an incentive to the peers to offer resources to the network. We formulate a fair resource allocation model for P2P networks and investigate the utility optimization problem by Lagrangian method. In order to realize the optimal resource allocation, we present a novel price-based resource allocation scheme by applying the first order Lagrangian method and low-pass filtering scheme, so that a service provider can allocate its resources to its customers based on offered prices, achieving the efficient and fair allocation of the available resources to the serviced customers. Simulation results confirm that the proposed algorithm can achieve the optimum within reasonable convergence times. [ABSTRACT FROM AUTHOR]

Free riding is a major problem in peer-to-peer networks. Reputation management systems are generally employed to overcome this problem. In this paper, a new reputation based scheme called probabilistic resource allocation is proposed. This strategy probabilistically decide whether to provide the resource to requesting peer or not. Aforesaid method gives selection preference to higher reputation peers and at the same time provides some finite probability of interaction between those peers who don't have good reputation about each other. This avoids disconnection between the aforesaid peers. The proposed scheme also introduces a new mechanism for resource distribution which not only allocates resources based on peers' reputation but simultaneously maximizes network utility also. Algorithm for formation of interest groups based upon both similarity of interests and reputation between peers is also presented. [ABSTRACT FROM AUTHOR]

In recent years, the BitTorrent (BT) has been one of the most efficient mechanisms for Peer-to-Peer (P2P) non-realtime content distribution. Many approaches for streaming videos over BT have been proposed by modifying the piece selection policy to cope with the real time requirement. Most of them provide the continuity of video playback at the cost of the variety of pieces on P2P streaming networks. In this paper, we propose the novel urgency-aware BT streaming mechanism, called UR-Aware, which intends to enhance the video streaming efficiency over BT on P2P networks by balancing playback continuity and distribution of piece rareness. There are two sets for piece downloading, called Uset and Rset. The Uset contains the most urgent pieces of video playback, while the Rset contains the rarest pieces. Downloading bandwidth of a peer is dynamically allocated to the two sets based on the number of consecutive pieces beyond these playback position in Uset. Furthermore, to implicitly preserve the continuity of pieces for future playback, consecutive k pieces are grouped as a section which would be selected to insert into Rset based on its rareness. The experimental results show that the UR-Aware has the best performance among other BT streaming approaches in terms of video download time, piece late rate, and network throughput. In addition, the accumulated standard deviation of UR-Aware is closest to that of the native BT among those approaches, which also confirms the superiority of UR-Aware on video streaming over BT. [ABSTRACT FROM AUTHOR]

Online Social Networks (OSNs) are becoming more and more popular on the Web. Distributed Online Social Networks (DOSNs) are OSNs which do not exploit a central server for storing users data and enable users to have more control on their profile content, ensuring a higher level of privacy. In a DOSN there are some technical challenges to face. One of the most important challenges is the data availability problem when a user is offline. In this paper we propose DiDuSoNet, a novel P2P Distributed Online Social Network where users can exercise full access control on their data. Our system exploits trust relationships for providing a set of important social services, such as trustness, information diffusion, and data availability. In this paper we show how our system manages the problem of data availability by proposing a new P2P dynamic trusted storage approach. By following the Dunbar concept, our system stores the data of a user only on a restricted number of friends which have regular contacts with him/her. Differently from other approaches, nodes chosen to keep data replicas are not statically defined but dynamically change according to users churn. In according to our previous work, we use only two online profile replicas at time. By using real Facebook data traces we prove that our approach offers high availability. [ABSTRACT FROM AUTHOR]

The rise of Cloud Computing has progressively dimmed the interest in volunteer and peer-to-peer computing, in general. However, efficient and cost-effective large scale distributed collaborative environments cannot be achieved leveraging upon the Cloud alone. In this paper, we propose a novel hybrid P2P/cloud approach where components and protocols are autonomically configured according to specific target goals, such as cost-effectiveness, reliability and availability. The proposed approach is based on the Networked Autonomic Machine (NAM) framework, which allows distributed system designers to include different kinds of cost and performance constraints. As an example, we show how the NAM-based approach can be used to design collaborative storage systems, enabling the definition of an autonomic policy to decide, according to cost minimization and data availability goals, how to part data chunks among peer nodes and Cloud, based on the local perception of the P2P network. [ABSTRACT FROM AUTHOR]

Peers in Mobile P2P (MP2P) networks exploit both the structured and unstructured styles to enable communication in a peer-to-peer fashion. Such networks involve the participation of two types of peers: benign peers and malicious peers. Complexities are witnessed in the determination of the identity of the peers because of the user mobility and the unrestricted switching (ON/OFF) of the mobile devices. MP2P networks require a scalable, distributed and light-weighted secure communication scheme. Nevertheless, existing communication approaches lack the capability to satisfy the requirements above. In this paper, we propose an Adaptive Trusted Request and Authorization model (ATRA) over MP2P networks, by exploiting the limited historical interaction information among the peers and a Bayesian game to ensure secure communication. The simulation results reveal that regardless of the peer's ability to obtain the other such peer's trust and risk data, the request peers always spontaneously connect the trusted resource peers and the resource peers always preferentially authorize the trusted request peers. Performance comparison of ATRA with state-of-the-art secure communication schemes over MP2P networks shows that ATRA can: (a) improve the success rate of node typing identification, (b) reduce time required for secure connections found, (c) provide efficient resource sharing, and (d) maintain the lower average cost. [ABSTRACT FROM AUTHOR]

A Peer-to-Peer (P2P) network can boost its performance if peers are provided with underlying network-layer routing topology. The task of inferring the network-layer routing topology and link performance from an end host to a set of other hosts is termed as network tomography, and it normally requires host computers to send probing messages. We design a passive network tomography method that does not require any probing messages and takes a free ride over data flows in P2P networks. It infers routing topology based on end-to-end delay correlation estimation (DCE) without requiring any synchronization or cooperation from the intermediate routers. We implement and test our method in the real world Internet environment and achieved the accuracy of 92 % in topology recovery. We also perform extensive simulation in OMNeT++ to evaluate its performance over large scale networks, showing that its topology recovery accuracy is about 95 % for large networks. [ABSTRACT FROM AUTHOR]

Due to the inefficient resource adjustment, the current P2P file sharing systems cannot achieve the balanced relationship between supplements and demands over the resources. In this case, the uploading bandwidth of the system node cannot be utilized efficiently and the overall system QoS is degraded. In this paper, an adaptive resource scheduling mechanism called Push mechanism, is proposed, in which 'proactive' strategies are provided to handle the unbalance supplement-demand relationship of some resource. Specifically, the system firstly forecasts which resource will becoming insufficient, then it pre-increase the uploaders over such resource so that the system performance is improved. Through numerical practical experiment in download platform of Tencent, it is proved that the proposed mechanism increases the downloading rate, saves the traffic on the server and optimizes the system performance. [ABSTRACT FROM AUTHOR]

An important issue in Peer-to-Peer networks is to encourage users to share with others as they use the resources of the network. However, some nodes may only consume from users without giving anything in return. To fix this problem, we can incorporate trust management systems with network infrastructures. Current trust managements are usually made for unstructured overlays and have several shortcomings. They are made to be very similar to e-commerce scoring websites which may not be the best design for fairness in P2P networks. Several problems may arise with their designs such as difficulties to provide a complete history of freeloaders or lack of an autonomous removal mechanism in case of severe attacks. In this paper, we argue that such systems can be deployed more efficiently by using a structured paradigm. For this purpose, we propose C-Trust, a trust management system which is focused on fairness for P2P networks. This is done by getting help from current circular structured designs. This method is able to mark freeloaders, identify their severity of abusion and punish them accordingly. We are also able to effectively protect both Seeder-to-Leecher and Leecher-to-Leecher transactions. This feature is specially important for fairness which other trust systems have not considered so far. [ABSTRACT FROM AUTHOR]

P2P Botnets are one of the most malevolent threats to the Internet users due to their resiliency against takedown efforts. In this paper, we propose a bot detection system that is capable of detecting stealthy bots in a network. This system treats network traffic as a data stream, segregating the traffic into two parallel streams. The detection is based on failure traffic and communication traffic. The traffic is analyzed during small time window, and the infected hosts are reported immediately. The network administrator can monitor the status of hosts in the network and can take the necessary action before the infected hosts harm the system or can involve in the attacks. Experiments and evaluation of the proposed system on a variety of P2P data transfer applications and P2P botnets have demonstrated high accuracy of detection. The scalability of the proposed system is exhibited through its implementation on Hadoop MapReduce. [ABSTRACT FROM AUTHOR]

Security is a critical constraint for the expansion of Peer-to-Peer (P2P) networks. The autonomy, dynamic and distribution natures benefit both valid and malicious users and also lead that P2P networks are extremely susceptible to malicious users. Exploiting a reputation-based trust model is a feasible solution in such an open environment to build trust relationship among peers. While most of existing trust models focus on restraining the abuse and malicious attacks, intentions and sharing capabilities of peers are mostly ignored. In this paper, we present a self-nominating trust model based on hierarchical fuzzy systems to quantify the behaviors of peers. The reputation is defined based on eight factors, where three promising factors are provided by resource holders to demonstrate their desires, and four capability factors are recorded by requesters to identify the provider's service capability. The approach degree based updating recommendation is deployed to aggregate the global trust metrics. Experimental results illustrate that our trust model effectively improves the efficiency and security of P2P systems. [ABSTRACT FROM AUTHOR]

Having the ability to generate, share, and use ambient multimedia and sensory data in real-time using both traditional sensors as well as non-traditional ones (such as smart device users) is a pioneering practice that requires specialized network capabilities and visualization metaphors. The network must support both service discovery and cache sharing to allow users to generate real-time sensory data, upload them or share them with end-users searching for the same data. Visualization and coloring schemes must support both streaming and stored sensory data to allow users to interact with either recent or up-to-the-minute ambient sensory data on either smart devices or the server. This article describes the design and reports on the simulation performance of a social network application that allows a group of users on an ad-hoc network to share real-time multimedia and ambient data with respect to venues of potential interest. At the graphical interface level, we present an intuitive interface that allows users to capture and share, often with a single hand, an array of sensory data comfortably and efficiently using touch screen smart devices. At the network level, we describe an architectural model that is supported by a specific design strategy for service discovery and caching to facilitate data sharing. The performance of the architectural model is then evaluated to show that it can efficiently handle bulk of sensory data, when accessed using smart devices in a peer-to-peer environment. [ABSTRACT FROM AUTHOR]

3D face reconstruction is an efficient method for pedestrian recognition in non-cooperative environment because of its outstanding performance in robust face recognition for uncontrolled pose and illumination changes. Visual sensor network is widely used in target surveillance as powerful unattended distributed measurement systems. This paper proposes a collaborative multi-view non-cooperative 3D face reconstruction method in visual sensor network. A peer-to-peer paradigm-based visual sensor network is employed for distributed pedestrian tracking and optimal face image acquisition. Gaussian probability distribution-based multi-view data fusion is used for target localization, and kalman filter is applied for target tracking. A lightweight face image quality evaluation method is presented to search optimal face images. A self-adaptive morphable model is designed for multiview 3D face reconstruction. To adjust the self-adaptive morphable model, the optimal face images and their poses estimation are used. Cooperative chaotic particle swarm optimization is employed for parameters optimization of the self-adaptive morphable model. Experimental results on real data show that the proposed method can acquire optimal face images and achieve non-cooperative 3D reconstruction efficiently. [ABSTRACT FROM AUTHOR]

Cloud computing technology offers the possibility of inter-organizational medical data sharing at a larger scale. The different organizations can maintain their own cloud environment while exchanging healthcare data among them in a peer-to-peer(P2P) fashion according to some defined polices. However, there are many security and privacy challenges that hamper the adoption of cloud computing solutions in healthcare domain. Besides, due to the privacy sensitivity of healthcare data, an organization may not wish to disclose its identity to others when exchanging data in the network to avoid different attacks by the intruders. Hence, anonymously authenticated data exchange is essential between the different peer organizations. In this paper we propose an anonymous on-the-fly secure data exchange protocol for such environment based on pairing-based cryptography. Our proposed solution allows cloud peers to dynamically generate temporary identities that are used to produce a session key for each session of data exchange. The proposed protocol is robust against different attacks, such as target-oriented, man-in-the middle, masquerade, and message manipulation attacks. [ABSTRACT FROM AUTHOR]

P2P collusive piracy, where paid P2P clients share the content with unpaid clients, has drawn significant concerns in recent years. Study on the follow relationship provides an emerging track of research in capturing the followee (e.g., paid client) for the blocking of piracy spread from all his followers (e.g., unpaid clients). Unfortunately, existing research efforts on the follow relationship in online social network have largely overlooked the time constraint and the content feedback in sequential behavior analysis. Hence, how to consider these two characteristics for effective P2P collusive piracy prevention remains an open problem. In this paper, we proposed a multi-bloom filter circle to facilitate the time-constraint storage and query of P2P sequential behaviors. Then, a probabilistic follow with content feedback model to fast discover and quantify the probabilistic follow relationship is further developed, and then, the corresponding approach to piracy prevention is designed. The extensive experimental analysis demonstrates the capability of the proposed approach. [ABSTRACT FROM AUTHOR]

Incentive schemes are designed to promote cooperation in distributed systems, in which peers are free to decide how much to contribute. A variety of incentive schemes have been proposed in peer-to-peer file-sharing systems, touted to have special advantages in certain scenarios. However, only little research has been done on comparing these incentive schemes under an identical scenario. Fairness is an important indicator to evaluate an incentive scheme, because good fairness can enable proper rewarding to collaborative peers and punishment to strategic peers. In this paper, the correlation map between return and investment of peers is used to depict the fairness degree of different incentive schemes. The fairness and efficiency of several representative incentive schemes are compared under rate-based metrics (all chunks have an identical value) and value-based metrics (different chunks have different values). [ABSTRACT FROM AUTHOR]

The Peer-to-Peer (P2P) architecture has been successfully used to reduce costs and increase the scalability of Internet live streaming systems. However, the effectiveness of these applications depends largely on user (peer) cooperation. In this article we use data collected from SopCast, a popular P2P live application, to show that there is high correlation between peer centrality-out-degree, out-closeness, and betweenness-in the P2P overlay graph and peer cooperation. We use this finding to propose a new regression-based model to predict peer cooperation from its past centrality. Our model takes only peer out-degrees as input, as out-degree has the strongest correlation with peer cooperation. Our evaluation shows that our model has good accuracy and does not need to be trained too often (e.g., once each 16 min). We also use our model to sketch a mechanism to detect malicious peers that report artificially inflated cooperation aiming at, for example, receiving better quality of service. [ABSTRACT FROM AUTHOR]

This paper presents a novel fountain code-based hybrid P2P and cloud storage system. While most cloud storage systems guarantees data retrievability of high level, they may be vulnerable to data privacy since the stored data may be exposed to others by accident or design. On the other hand, P2P storage system keeps any peer from accessing the whole data by dividing the data into small pieces and distributing them to multiple participating peers, but may degrade data retrievability due to unstable peers. The proposed hybrid storage system attempts to enhance data retrievability and privacy by effectively distributing fountain encoded symbols to cloud server system and participating peers. It is demonstrated that the proposed hybrid storage system achieves the desired level of data retrievability with a short upload time, and enhance privacy by preventing others from reading the contents. [ABSTRACT FROM AUTHOR]

Dealing with the churn problem is an important requirement in distributed systems in general and more precisely in structured peer-to-peer overlay networks due to their dynamicity. This problem refers to the change in the set of participating nodes due to the frequent joins, leaves or failures. Such variations induce at worst the loss of objects and at least performance degradation. This is due to the reorganization of the set of replicas of the affected objects. Till now, this problem has been mostly addressed at the p2p routing level to ensure the reach ability of peers by maintaining the consistency of the logical neighbors. However, the main challenge for structured p2p systems is to protect the ability of the system to locate any present object. At the storage level, avoiding data losses is still an issue when a reconfiguration of the participant peers occurs. In this paper and after presenting first the existing replication techniques, we propose the zone replication technique used in both Chord and Kademlia protocols in order to attenuate churn effects. Finally, we point out some ways that can lead to better and maybe robust replication protocols. [ABSTRACT FROM AUTHOR]

Due to limited radio range and mobility of nodes in mobile ad hoc networks (MANETs), the network partitioning and merging could occur frequently. When structured peer-to-peer (P2P) overlays are running over MANETs, then network partition in the physical network can also cause network partition at the overlay layer. Existing approaches for structured P2P overlay over MANETs do not detect network partition at the overlay layer. This paper proposes a cross-layer approach to detect network partition at the overlay layer for structured P2P overlay over MANETs. Simulation results show that the proposed approach is highly effective and efficient in terms of routing overhead, success ratio and false-negative ratio. [ABSTRACT FROM AUTHOR]

Social media data are increasingly being used in disaster management for information dissemination, establishment of situational awareness of the 'big picture' of the disaster impact and emerged incidences over time, and public peer-to-peer backchannel communications. Before we can fully trust the situational awareness established from social media data, we need to ask whether there are biases in data generation: Can we simply associate more tweets with more severe disaster impacts and therefore higher needs for relief and assistance in that area? If we rely on social media for real-time information dissemination, who can we reach and who has been left out? Due to the uneven access to social media and heterogeneous motivations in social media usage, situational awareness based on social media data may not reveal the true picture. In this study, we examine the spatial heterogeneity in the generation of tweets after a major disaster. We developed a novel model to explain the number of tweets by mass, material, access, and motivation (MMAM). Empirical analysis of tweets about Hurricane Sandy in New York City largely confirmed the MMAM model. We also found that community socioeconomic factors are more important than population size and damage levels in predicting disaster-related tweets. [ABSTRACT FROM AUTHOR]

Recently P2P networks and theirs applications have become increasingly popular. On the other hand, considering ever increasing industrial and scholarly popularity of Vehicular Ad hoc Networks (VANETs), implementation P2P network over VANET has attracted attentions recently. One of the most important applications in P2P networks is content discovery. Regarding the difficulties of structured and unstructured protocols over VANET, this paper presents a new framework for sharing and content discovery which formed a structured overlay to overcome problems likes broadcasting storm which is the main problem of unstructured methods. On the other hand, this paper tries to solve the instability of structured overlay networks as the main problem of them, by applying geographical and semantic partitioning. Simulation results clarified higher performance of proposed framework in comparison to previous protocols. Furthermore, applying G-Network queue network, we have modeled the behavior of proposed framework and then, optimize it by gradient descent optimization method. [ABSTRACT FROM AUTHOR]

Combining ontologies in expressive fragments of Description Logics in inherently distributed peer-to-peer settings with autonomous peers is still a challenge in the general case. Although several modular ontology representation frameworks have been proposed for combining Description Logics knowledge bases, each of them has its own strengths and limitations. In this paper, we consider networks of peers, where each peer holds its own ontology within the $${\mathcal {SHIQ}}$$ fragment of Description Logics, and subjective beliefs on how its knowledge can be coupled with the knowledge of others. To allow peers to reason jointly with their coupled knowledge, while preserving their autonomy on evolving their knowledge, data, and subjective beliefs, we propose the $$E\text {-}{\mathcal {SHIQ}}$$ representation framework. The article motivates the need for $$E\text {-}{\mathcal {SHIQ}}$$ and compares it to existing representation frameworks for modular Description Logics. It discusses the implementation of the $$E\text {-}{\mathcal {SHIQ}}$$ distributed reasoner and presents experimental results on the efficiency of this reasoner. [ABSTRACT FROM AUTHOR]

The state of art authentication schemes are tightly linked with encryption or crypto systems, which provides concrete foundations to move towards the concept of access control by confirming the user identity. However the openness of the computer network makes the identity credentials vulnerable even transmitted as cipher text especially in lots of peer-to-peer (P2P) networks. The malicious attackers can possibly steal and fake the user identity by eavesdropping, hijacking, cryptanalysis and forging. In this paper, a novel identity authentication mechanism is proposed based on the reverse usage of the Network Covert Channel (NCC) which is originally designed by attackers to create stealth communication. Different from NCC, where the packet intervals can be exploited as the data carrier to transmit the unauthorized information, we exploit such capability in Network-Covert-Channel-based Identity Authentication (NCCIA) to transmit the identity tag. By validating user identity in a covert manner, we provide a more secure authentication method compared with many existing approaches. A NCCIA demo system is designed on a FTP Platform to verify our method. The experiments demonstrate the NCCIA can prevent the attackers from eavesdropping while maintaining transmission efficiency. [ABSTRACT FROM AUTHOR]

Peer-to-Peer (P2P) technology has experienced its great popularity for resource sharing in current network services. However, lacking of prior experience and knowledge about other peers' reputation, P2P suffer from malicious behaviors launched by malicious peers. Developing effective strategies to establish trust model for the P2P system is a good way to address this problem. In this paper, we propose a novel topological potential weighted community-based recommendation trust (TPCommuTrust) model architecture, which is based on topological potential weighted community credential to score and rate peers' previous data transactions. Contributed by topological potential, which characterizes repercussion effect between peers, the reputation model of the peers is created. The unique and efficient mechanism is proposed to perform data transaction based on credentials intra and inter-community. Moreover, how TPCommuTrust can provide an access control against malicious peers is illustrated as well. Simulation results show that TPCommuTrust model is robust and highly efficient to identify malicious nodes. [ABSTRACT FROM AUTHOR]

Peer-to-peer relay technique provides the opportunity of cooperative communication between users to achieve the transmission diversity. In this paper, the problem of relay selection and subcarrier allocation in peer-to-peer cooperative OFDMA system with channel distribution uncertainty is studied. The quality of service (QoS) requirements are characterized with the probabilistic constraints. The Kullback-Leibler (KL) divergence is adopted to describe the uncertainty of the channel state information (CSI), which follows a distribution deviated within a certain distance from the reference distribution. Since the probabilistic constraint is intractable, we resort to a tractable upper bound instead. The problem is solved by the interior point cutting plane (IPCP) method, which proceeds in round whereby an iterative method is designed to combine both golden section method and interior point method to find the saddle point of the constraint. Simulation results show the effectiveness of our algorithm. [ABSTRACT FROM AUTHOR]

P2P file-sharing systems have been suffering from file unavailability or poor download speed due to lack of enough seeds. To download rare files, users are typically forced to keep their desktops online for a long time, which is undesirable for most users. To get over this, several commercial P2P systems launched offline download service, also known as cloud download, which employs stable and high-capacity servers to take over users' download tasks, and thus users do not need to stay online all the time. This paper focuses on characterizing the performance of offline download, including the overall performance provision and the expected performance of individual download tasks. Through model characterization and experimental verification based on real-world trace, we are the first to confirm the feasibility and effectiveness of offline download for a large spectrum of P2P systems: over 90 % files can be successfully retrieved, and most of the downloads only take a few days. Furthermore, we disclose that the completion time of offline download is extremely volatile, and thus develop a method to accurately predict the expected performance of individual downloads. An instance of applying the prediction results is also presented to save the server-side bandwidth. Finally, we implement a prototype of offline download service, release it in a real P2P network, and present our work experience with it. [ABSTRACT FROM AUTHOR]

A network coding based peer-to-peer (P2P) file sharing system has been proposed in recent years. It uses the random combination of encoded pieces to make the file sharing more effective. Most of the conventional P2P file sharing systems adopt a random (or rarest piece first) transmission policy to avoid too many duplicated pieces and rare pieces occurring in the network. Network coding can simply solve this problem. However, some of the studies show that network coding brings the overhead of coding/decoding delay and message overhead; after all, the performance of network coding is not better than other schemes that are without network coding. Therefore, we propose a network coding based file sharing system over unstructured P2P networks considering the overhead from the network coding. We make comparisons with other schemes without network coding. Our simulation results show that the proposed network coding based file sharing system is better than others, when the network coding scheme and non-network coding scheme adopt the same network environment even though the network coding is executed under a limited computation resource. [ABSTRACT FROM AUTHOR]

This paper re-examines data from a survey commissioned by Industry Canada on the effects of internet peer-to-peer (P2P) file sharing activities on music purchasing behaviour. The survey was designed to 'inform Industry Canada's policy development work' (Quote from project Description from Industry Canada's website at downloaded 23 January 2012) and the need for copyright law reform in Canada in light of the technological innovation posed by P2P file sharing. The Journal of Evolutionary Economics published a study of the Industry Canada data by Andersen and Frenz (AF) in 2010 which claimed to show '... no association between the number of P2P files downloaded and CD album sales (Andersen and Frenz 2010 ibid p 374),' and '... that P2P file-sharing is not to blame for the decline in CD markets. Music markets are not simply undermined by free music downloading and P2P file-sharing (Ibid p375).' Our paper corrects a number of fundamental errors in this analysis of AF, in particular the fact AF biased their results by excluding from their analysis the group of consumers who had completely stopped purchasing CDs (potentially because of P2P activity) prior to 2005. This is the very group who were most responsive, or likely to have substituted P2P downloading for CD purchases. We use longitudinal analysis of how reported changes in P2P downloading by individuals related to their reported changes in CD demand between 2004 and 2005 to better test the hypothesis of whether P2P downloading may reduce CD demand. Contrary to AF's results we find negative and generally statistically significant partial correlations between CD purchases and P2P downloads under a number of specifications and sample definitions. The range of these estimated correlations is between −0.047 and −0.061. This implies that a 10 % growth in P2P downloads is associated with between a 0.47 and 0.61 % decline in CD purchases. Our estimated relationships between CD sales and P2P downloads are broadly consistent with market sales data up to the time of the Industry Canada survey, unlike AF. [ABSTRACT FROM AUTHOR]

It is a very difficult task to estimate abnormal objects and analyze reliability in peer-to-peer (P2P) networks. In the P2P network environment, successful execution of a program is conditional on the successful access of related files and software distributed throughout the P2P network. Abnormal phenomena in peer-to-peer systems occur very often. They occur in software and in data operated on by the computer itself or by a connected computer. This paper focuses on estimating abnormal objects and reliability in a P2P network that is very complex and different. We propose an estimation method for abnormal objects and reliability in a P2P network. First, we define a P2P static graph model, where the node is a computational unit and the edge is a communication unit in the P2P network. The computational unit is software or data installed on a computer. Second, we propose a converting algorithm where the P2P static graph model is converted to a colored Petri net model. Last, we estimate abnormal objects and the reliability of the P2P network. The technique successfully classifies abnormal objects and estimates reliability of the P2P network. This procedure provides a very useful method for detection of abnormal objects in a P2P network, which occur through abnormal faults of software and data. While we manage the P2P network, the reliability of the system can be predicted. [ABSTRACT FROM AUTHOR]