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We consider the following network model motivated, in particular, by blockchains and peer-to-peer live streaming. Data packet flows arrive at the network nodes and need to be disseminated to all other nodes. Packets are relayed through the network via links of finite capacity. A packet leaves the network when it is disseminated to all nodes. Our focus is on two communication disciplines, which determine the order in which packets are transmitted over each link, namely Random-Useful (RU) and Oldest-Useful (OU). We show that RU has the maximum stability region in a general network. For the OU we demonstrate that, somewhat surprisingly, it does not in general have the maximum stability region. We prove that OU does achieve maximum stability in the important special case of a symmetric network, given by the full graph with equal capacities on all links and equal arrival rates at all nodes. We also give other stability results, and compare different disciplines' performances in a symmetric system via simulation. Finally, we study the cumulative delays experienced by a packet as it propagates through the symmetric system, specifically the delay asymptotic behavior as N → ∞ . We put forward some conjectures about this behavior, supported by heuristic arguments and simulation experiments. [ABSTRACT FROM AUTHOR]

Substantial evidence has shown that involvement in peer-to-peer farming networks influences whether a farmer decides to try a new practice. Formally organized farmer networks are emerging as a unique entity that blend the benefits of decentralized exchange of farmer knowledge within the structure of an organization providing a variety of sources of information and forms of engagement. We define formal farmer networks as farmer networks with a distinct membership and organizational structure, leadership that includes farmers, and an emphasis on peer-to-peer learning. This study complements existing ethnographic research on the benefits of organized farmer networking by examining farmers in one longstanding formal farmer network, Practical Farmers of Iowa. Using a nested, mixed-method research design, we analyzed survey and interview data to understand how participation and forms of engagement in the network are associated with the adoption of conservation practices. Responses from 677 farmers from a regular member survey disseminated by Practical Farmers of Iowa in 2013, 2017, and 2020 were pooled and analyzed. GLM binomial and ordered logistic regression results indicate that greater participation in the network, particularly through in-person formats, has a strong and significant association with greater adoption of conservation practices. Logistic regression results show that building relationships in the network is the most important variable for predicting whether a farmer reported adopting conservation practices as a result of participation in PFI. In-depth interviews with 26 surveyed member farmers revealed that PFI supports farmers to adopt by providing information, resources, encouragement, confidence building, and reinforcement. In-person learning formats were more important to farmers relative to independent formats because they were able to have side conversations with other farmers, ask questions, and observe results. We conclude that formal networks are a promising way to expand the use of conservation practices, particularly through targeted efforts to increase relationship building in the network through face-to-face learning opportunities. [ABSTRACT FROM AUTHOR]

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]

Structured Peer-to-Peer (P2P) overlay networks are scalable and efficient networks. This efficiency comes at a cost as there is a need for regular maintenance of an overlay structure to handle the continuous churn of peers. This results in huge overhead in terms of maintenance traffic generated by peers. This problem becomes more critical when logical overlay topology differs from actual physical network topology, a common phenomenon in P2P overlay networks. In this paper, we present a novel approach to designing a Distributed Hash Table (DHT) based P2P overlays with the help of Software Defined Networks (SDN) concepts. SDN is an upcoming technology that provides enough flexibility in deciding application-specific network policies and rules dynamically. In our approach, we have attempted to bring the overlay topology closer to actual physical topology and reduce the maintenance traffic as much as possible. We have also tested our work on a hybrid network consisting of both virtual and physical switches. The experimental results suggest and establish the applicability of our approach. [ABSTRACT FROM AUTHOR]

The recent global demand for video streaming applications has paved the way for peer-to-peer streaming system (P2PSS). Strategic scheduling scheme and dynamic overlay topology are essential to maintain quality of service (QoS) and quality of experience (QoE) in P2PSS. The concept of P2PSS was tailored towards relying on active peers' bandwidth to achieve cheap and scalable means of distribution over the Internet, such that peers with highest bandwidth serve as backbones for others. However, selecting backbone peers in low-capacity network environment is challenging due to insufficient bandwidth and poor infrastructure, thereby resulting in poor QoS and unpleasant user's QoE. In this paper, we conducted a survey on users' experiences with live video in selected locations in Nigeria. We designed an adaptive P2P streaming protocol and performed a packet-level simulation in Network Simulator 3(NS-3). Diverse simulation scenarios were set up to evaluate the proposed streaming protocol. Trace files data were analysed to measure end-to-end delay, start-up delay, and throughput. Furthermore, the proposed streaming protocol was benchmarked against selected existing schemes. The evaluation results revealed a 7.4% and 28% reduction in start-up and in end-to-end delays and 9% increase in throughput. [ABSTRACT FROM AUTHOR]

In recent times, security threats are predominant in almost all digital applications over the internet. One such threatening effect comes from GAMEOVER Zeus Botnet. These Botnets enter inside online networks and affect the Peer client list, through Internet Rely Chat (IRC). IRC includes applications like Tactical chat and On Chat. Zeus botnets gather the secret information of these users, such as bank data and military secrets. Moreover, the architecture is P2P and hence the location of GAMEOVER Zeus Botnet varies from the one to another botnets models. The threat of Zeus botnets loom large as they operate through the processes of identification of users, through which, they establish control over the hosts via P2P server. An intelligent method of identification of Zeus botnets in a distributed computing system using cryptographic schemes to defend against such attacks is the prime issue of research in this paper. An advanced Botnet capturing algorithm, named as modified cryptographic prefix IP anonymize (CPA) algorithm is proposed in this research paper to effectively counter the threats of Zeus bots. Essential features of the proposed CPA algorithm include prefixed IP mapped anonymizing in Internet Rely Chat, inbuilt adaptive security algorithm, which helps in network cleansing. If left unchecked, these Zeus botnets may result in consequent shutdown of the system. Hence, identification of the location of these botnets with the help of IP-prefix mapped method through modified CPA algorithm have been systematically presented in this paper. [ABSTRACT FROM AUTHOR]

k-means clustering, which partitions data records into different clusters such that the records in the same cluster are close to each other, has many important applications such as image segmentation and genes detection. While the k-means clustering has been well-studied by a significant amount of works, most of the existing schemes are not designed for peer-to-peer (P2P) networks. P2P networks impose several efficiency and security challenges for performing clustering over distributed data. In this paper, we propose a novel privacy-preserving k-means clustering scheme over distributed data in P2P networks, which achieves local synchronization and privacy protection. Specifically, we design a secure aggregation protocol and a secure division protocol based on homomorphic encryption to securely compute clusters without revealing the privacy of individual peer. Moreover, we propose a novel massage encoding method to improve the performance of our aggregation protocol. We formally prove that the proposed scheme is secure under the semi-honest model and demonstrate the performance of our proposed scheme. [ABSTRACT FROM AUTHOR]

Peer-assisted networks have recently emerged as an excellent tool for distributing video contents across the Internet. High peers' participation and cooperation in peer-assisted networks can drastically reduce the bandwidth cost, increased scalability and ease of deployment. However, the main factor which limits effective distribution of resources in this network is free riding; a situation in which a peer consumes resources freely but refuses to service other peers. This paper presents a new peer-assisted streaming model (AyoPeer) using game theoretics with the aim of minimizing free riding.The interactions between peers are fashioned after a famous Yoruba game called "Ayo". AyoPeer provides a reward and punishment mechanism that ensures the free-riders fail and cooperating peers succeeds with download. The experimental results revealed that AyoPeer mechanism outperform the existing scheme by ensuring fair distribution of resources, high cooperation among peers and resistance to free-riding peers. [ABSTRACT FROM AUTHOR]

Resource discovery on different unstructured and dynamic networks such as grid, peer-to-peer, and cloud networks is an inevitable challenging issue. The primary method for resource discovery on the unstructured networks is flooding a query on the network. All existing flooding algorithms for unstructured networks generate almost high additional duplicated queries. This high duplication of the unstructured networks causes a lot of network traffic. This paper, therefore, proposes a novel flexible Distributed Dynamic backbone-based Flooding (DDBF) algorithm for distributed unstructured networks. This paper explores Grid middleware, Peer-to-Peer (P2P) paradigm, and cloud networks resource discovery requirements and it proposes flooding algorithm based on the P2P networks using simulation. To evaluate and prove DDBF algorithm we, first, evaluated it on four fixed network topologies along with two different query flooder distributions, then we evaluated it with one dynamic network topology. The performance of the proposed DDBF algorithm was assessed with five different metrics. The result showed a dramatic decrease in the number of engaged flooder nodes, the number of duplicated queries and consequently, network delay compared with the state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

In recent years, live video streaming has become one of the most popular and prevalent applications of the Internet. The Peer-to-Peer (P2P) and Content Delivery Network (CDN) are popular approaches to stream video contents. These approaches respectively have faced some drastic challenges such as obtaining the desired Quality of Service (QoS) level and minimizing economic cost. The cloud computing infrastructures can reveal proper solutions to these problems. The P2P systems can eliminate their bandwidth shortage by renting resources from the cloud environment. This paper depicts CaR-PLive as a hybrid cloud-assisted P2P live streaming system. CaR-PLive uses video servers such as Amazon EC2 from cloud to stream video contents and rents Cloud Storage Services (CSSs) such as Amazon S3 to assist P2P live streaming system to reach the desired playback continuity. In CaR-PLive, we proposed two stages (sub-windows) sliding window for buffer management that a sub-window belongs to the P2P system and another one belongs to CSS. The objective of CAR-PLive is to optimize the size of sub-windows to minimize the overall rental cost of CSS restricted to a desired QoS level. We formulate this problem as an optimization problem and model it with Markov Decision Process (MDP) and then propose a reinforcement learning based algorithm to solve this problem. Finally, we evaluate the performance of CaR-PLive by performing extensive simulations and experiments with realistic settings. Simulation results demonstrate that CaR-PLive efficiently mitigates overall CSS billing cost in different system configurations and provides desired playback continuity in different system settings. [ABSTRACT FROM AUTHOR]

We consider the problem of live video streaming in peer-to-peer networks consisting of selfish peers aiming at maximizing peers' individual utilities. We use token as an internal currency to encourage peers to cooperate in video distribution. Peers gain tokens by accepting requests from other peers for uploading video chunks to them, and they spend tokens for sending requests to the other peers and downloading video chunks from them. To handle the heterogeneity in the bandwidth of peers, we assume the video is coded as multilayered and each layer has a different type of token. Peers can request for a different number of layers to have their best quality based on their available token pools. To address this problem, we first study the peers' optimal strategies using the formalism of repeated games, and then, we show that peers' optimal strategy for each layer is a threshold strategy based on the number of tokens held by the peer for that layer. Then, we show that the repeated game can be converted to a simple one-shot game. In this new game, we study the impact of other peers' strategy on peers' utilities and strategies. We show that the game has a Nash equilibrium. [ABSTRACT FROM AUTHOR]

Mutualcast is a one-to-many (peer-to-peer) scheme for content distribution that maximizes the overall throughput during a broadacast session. It is based on a fully-connected graph (full mesh topology), which introduces benefits such as robustness or simultaneous transmission from/to multiple devices. The main disadvantage of Mutualcast is scalability; it is constraint to a small P2P group for content distribution. In this paper, we make Mutualcast scalable. We propose a highly collaborative and scalable P2P tree-based architecture made of two main components: 1) Peer grouping or clustering and 2) Hierarchical tree-based content distribution. In step 1), peer nodes (content receivers) are grouped into equal-size clusters by using a proposed heuristic size-constrained algorithm based on k-means. In step 2), clusters (which become the nodes of the tree) are organized into a single hierarchical n-ary tree-based architecture, in which the root of the tree (Root Cluster) is the one closest to source peer, while intermediate and leaf clusters are positioned in the tree according to their delay-proximity to previously inserted clusters. During content distribution, the root cluster receives the blocks of content before any other cluster in the tree and directly from (and only from) the source peer; blocks are then passed on to the next hierarchical level down the tree in order (higher levels of the tree receive the content before lower levels). Inter-clusters and intra-clusters content distribution is performed concurrently and takes into account peers upload/download capacities to relay blocks of content. The evaluation of our hierarchical P2P architecture concentrates on the following metrics: scalability of the systems, overall end-to-end delay distribution, and efficient cluster size. Finally, our architecture is compared against two well-known P2P technologies in the literature, Super-Peer and Kademlia. [ABSTRACT FROM AUTHOR]

This paper is concerned with the clock synchronization problem for IEEE 1588 networks. First, the synchronization error is described as a bounded disturbance, and a linear extended state observer (LESO) is designed to estimate the lumped disturbance induced by the oscillator frequency drift and timestamps quantization errors. Then, the lumped disturbance is compensated by the proposed controller. The proposed approach has the advantage that it's able to deal with non-Gaussian disturbance induced by accumulated quantization errors. Simulations are provided to validate the effectiveness and superiority of the proposed approach. [ABSTRACT FROM AUTHOR]

Super-peer networks refer to a class of peer-to-peer networks in which some peers called super-peers are in charge of managing the network. A group of super-peer selection algorithms use the capacity of the peers for the purpose of super-peer selection where the capacity of a peer is defined as a general concept that can be calculated by some properties, such as bandwidth and computational capabilities of that peer. One of the drawbacks of these algorithms is that they do not take into consideration the dynamic nature of peer-to-peer networks in the process of selecting super-peers. In this paper, an adaptive super-peer selection algorithm considering peers capacity based on an asynchronous dynamic cellular learning automaton has been proposed. The proposed cellular learning automaton uses the model of fungal growth as it happens in nature to adjust the attributes of the cells of the cellular learning automaton in order to take into consideration the dynamicity that exists in peer-to-peer networks in the process of super-peers selection. Several computer simulations have been conducted to compare the performance of the proposed super-peer selection algorithm with the performance of existing algorithms with respect to the number of super-peers, and capacity utilization. Simulation results have shown the superiority of the proposed super-peer selection algorithm over the existing algorithms. [ABSTRACT FROM AUTHOR]

The exponentially-increasing demands on ubiquitous information exchange have inspired wide research interests and efforts on the 5th Generation (5G) of mobile communications system. Among diverse cutting-edge revolutionary technologies towards 5G networks, device-to-device (D2D) networks, where device nodes can communicate with each other by reusing the cellular network's spectrum in an underlay fashion. We in this paper propose the interference-constrained routing schemes over peer-to-peer (P2P) share enabled multi-hop D2D networks, where multiple D2D subscribers attempt to download the common data from multiple distributed D2D servers. In particular, we aim at optimizing the average download rate over subscribers subject to the interference constraint for cellular network's spectrum. We first focus on a typical case with two subscribers, two file servers, and two cellular users. We propose a Routing scheme with Direct P2P-Share (R-DPS), which allows subscribers to distribute their received data to each other via a detoured route. To offer better performances, we develop an improved Routing scheme, named Coverage-based P2P-Share (R-CPS). The R-CPS scheme can effectively make use of the broadcast nature of wireless channels to assure that each selected route can cover the other subscriber, rather than directly pass through them in the R-DPS scheme. We further study the generalized case where the number of subscribers, servers, and cellular users can be arbitrary. Particularly, we propose a Routing scheme with Location-Aware P2P-Share (R-LPS) mechanism, the core idea of which is to find a route passing by or directly through other subscribers. Simulation evaluations demonstrate that our proposed R-DPS and R-CPS schemes for the two-subscriber case and the R-LPS scheme for the generalized case all have the capability to effectively improve the data download rate as compared to the approach without enabling P2P support. [ABSTRACT FROM AUTHOR]

Cellular Learning Automata ( CLAs) are hybrid models obtained from combination of Cellular Automata ( CAs) and Learning Automata ( LAs). These models can be either open or closed. In closed CLAs, the states of neighboring cells of each cell called local environment affect on the action selection process of the LA of that cell whereas in open CLAs, each cell, in addition to its local environment has an exclusive environment which is observed by the cell only and the global environment which can be observed by all the cells in CLA. In dynamic models of CLAs, one of their aspects such as structure, local rule or neighborhood radius may change during the evolution of the CLA. CLAs can also be classified as synchronous CLAs or asynchronous CLAs. In a synchronous CLA, all LAs in different cells are activated synchronously whereas in an asynchronous CLA, the LAs in different cells are activated asynchronously. In this paper, a new closed asynchronous dynamic model of CLA whose structure and the number of LAs in each cell may vary with time has been introduced. To show the potential of the proposed model, a landmark clustering algorithm for solving topology mismatch problem in unstructured peer-to-peer networks has been proposed. To evaluate the proposed algorithm, computer simulations have been conducted and then the results are compared with the results obtained for two existing algorithms for solving topology mismatch problem. It has been shown that the proposed algorithm is superior to the existing algorithms with respect to communication delay and average round-trip time between peers within clusters. [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]

Multi-robot systems (MRSs) have a wide variety of applications, such as search and rescue in disaster scenarios, where many robots coordinate with each other to accomplish a task. Such MRS applications use infrastructureless environment in which robots rely on inherently unreliable ad hoc network to communicate with each other. Reliable communication among the peers can greatly enhance the performance of a multi-robot system. This paper proposes a reliable communication protocol (RCP) for applications in multi-robot systems. RCP acts as an interface between MRS applications and the underlying communication framework. RCP accepts data from MRS applications and reliably delivers it to other peers. RCP is transparent to MRS applications as well as the underlying communication hardware. To evaluate its performance, we have implemented RCP on seven Stargate micro-controllers that communicate with each other using an ad hoc network. Further, to test the performance of RCP in MRS applications involving higher number of peers, we have also implemented RCP on laptops with Intel i7 microprocessors. The obtained results show that RCP achieves reliability while reducing packet delivery time as well as the number of retries needed to deliver a failed packet. [ABSTRACT FROM AUTHOR]

In mesh-based Peer-to-Peer (P2P) live video streaming systems packet scheduling is an important factor in overall video playback quality. In mesh based P2P video streaming systems, each video sequence is divided into chunks, which are then distributed by multiple suppliers to the receivers. The suppliers need to be coordinated by the receiver through specifying a transmission schedule for each of them. Many previous studies on scheduling of P2P streaming tend to mainly focus on networking issues which strongly depend on a particular P2P architecture such as tree or mesh. These algorithms suffer from some design issues: 1) they are too complex to deploy, 2) they do not take video characteristics into account and 3) they do not have sender-side transmission policy. To address all three of these problems, we propose a new chunk scheduling scheme which consists of two parts: i) receiver-side scheduler and ii) sender-side transmission order scheme. The proposed receiver-side scheduler considers the contribution level of each video frame as well as the frame's urgency in order to define a priority for each video frame. It attempts to request frames with highest priority from peers which can deliver them in a shorter time. We also design a new chunk transmission order scheme that decides which requested chunk will be sent out first based on its importance to the requesting neighbor. Our simulation results show that the proposed scheduling scheme improves the overall quality of the perceived video in mesh-based P2P video streaming architectures substantially. [ABSTRACT FROM AUTHOR]

Taking advantage of the huge potential of consumers' untapped computing power, self-organizing cloud is a novel computing paradigm where the consumers are able to contribute/sell their computing resources. Meanwhile, host machines held by the consumers are connected by a peer-to-peer (P2P) overlay network on the Internet. In this new architecture, due to large and varying multitudes of resources and prices, it is inefficient and tedious for consumers to select the proper resource manually. Thus, there is a high demand for a scalable and automatic mechanism to accomplish resource allocation. In view of this challenge, this paper proposes two novel economic strategies based on mechanism design. Concretely, we apply the Modified Vickrey Auction (MVA) mechanism to the case where the resource is sufficient; and the Continuous Double Auction (CDA) mechanism is employed when the resource is insufficient. We also prove that aforementioned mechanisms have dominant strategy incentive compatibility. Finally, extensive experiment results are conducted to verify the performance of the proposed strategies in terms of procurement cost and execution efficiency. [ABSTRACT FROM AUTHOR]

Private BitTorrent community, known as 'BitTorrent Darknet' or 'Private Tracker (PT)', has received much attention in the research literature recently. Different from public BitTorrent community, PT can only be accessed by its registered members, and it can provide ultra-high downloading speed due to its effective Sharing Ratio Enforcement (SRE) incentive mechanism which stimulates members to contribute content as much as possible. Although the downloading performance in PTs with high Seeder-to-Leecher Ratio (SLR) is much better than in public BitTorrent communities, our measurements show that SRE mechanism can induce 'Poor Downloading Motivation' problem for members who want to increase their sharing ratios to survive and thrive in PT. This problem may discourage PT members' enthusiasm from contributing to community. To improve sustainability of PTs, we adopt the Predator-prey model to analyze high SLR phenomenon, study the optimal stable SLR range to PTs. Moreover, we develop a queuing model to simulate the seeding/leeching process in a single torrent in PT, and try to maximize the swarming performance with minimum seeding peers. This solution can help PT achieve the optimal SLR range. [ABSTRACT FROM AUTHOR]

Peer-to-peer(P2P) services heavily rely on users' cooperation to achieve desired performance. However, most current P2P systems only encourage short-term and direct cooperation between peers. The lack of incentives for long term and indirect cooperation has severely limited the performance of P2P systems. On the other hand, recent measurements on large-scale networks show that peers' behavior often demonstrates strong social patterns. In this paper, we design and implement a social P2P network, named SocialTrust, based on peers' common interests. In SocialTrust, each peer tries to find a small number of friends and maintains long term social links with them. We also propose a distributed trust mechanism. The trust between two friends reflects their cooperation level and serves as the credit limit between them. A peer with higher trust can download data from its friends more efficiently. The trust can be propagated among friends to support indirect reciprocity. We formally prove that the proposed distributed trust mechanism is secure and can defend against various forms of attacks. By adding asmall number of long term social links to the existing P2P network, SocialTrust relaxes the constraint of direct incentive mechanisms and encourages peers to perform various forms of long-term cooperation. Both trace-driven simulation and real Internet experiments show that SocialTrust can significantly improve file availability and download performance of current P2P file sharing systems. [ABSTRACT FROM AUTHOR]

The Chord peer-to-peer system is considered, together with CAN, Tapestry and Pastry, as one of the pioneering works on peer-to-peer distributed hash tables (DHT) that inspired a large volume of papers and projects on DHTs as well as peer-to-peer systems in general. Chord, in particular, has been studied thoroughly, and many variants of Chord have been presented that optimize various criteria. Also, several implementations of Chord are available on various platforms. Though Chord is known to be very efficient and scalable and it can handle churn quite well, no protocol is known yet that guarantees that Chord is self-stabilizing, i.e., the Chord network can be recovered from any initial state in which the network is still weakly connected. This is not too surprising since it is known that the Chord network is not locally checkable for its current topology. We present a slight extension of the Chord network, called Re-Chord (reactive Chord), that turns out to be locally checkable, and we present a self-stabilizing distributed protocol for it that can recover the Re-Chord network from any initial state, in which the n peers are weakly connected. in O( nlog n) communication rounds. We also show that our protocol allows a new peer to join or an old peer to leave an already stable Re-Chord network so that within O((log n)) communication rounds the Re-Chord network is stable again. [ABSTRACT FROM AUTHOR]

Content Distribution Networks (CDNs) are widely used to distribute data to large number of users. Traditionally, content is being replicated among a number of surrogate servers, leading to high operational costs. In this context, Peer-to-Peer (P2P) CDNs have emerged as a viable alternative. An issue of concern in P2P networks is that of free riders, i.e., selfish peers who download files and leave without uploading anything in return. Free riding must be discouraged. In this paper, we propose a criterion, the Give-and-Take (G&T) criterion, that disallows free riders. Incorporating the G&T criterion in our model, we study a problem that arises naturally when a new peer enters the system: viz., the problem of downloading a 'universe' of segments, scattered among other peers, at low cost. We analyse this $\mathcal {N}\mathcal {P}-$hard problem, and characterize the optimal download cost under the G&T criterion. We propose an optimal algorithm, and provide a sub-optimal algorithm that is nearly optimal, but runs much more quickly; this provides an attractive balance between running time and performance. Finally, we compare the performance of our algorithms with that of a few existing P2P downloading strategies in use. We also study the computation time for prescribing the strategy for initial segment and peer selection for the newly arrived peer for various existing and proposed algorithms, and quantify cost-computation time trade-offs. [ABSTRACT FROM AUTHOR]

Peer-to-peer (P2P) networks feature resource sharing in a distributed network environment. How to efficiently find out target objects (i.e., data, file, etc.) distributed in a P2P network is the remarkable process for resource sharing. The searching efficiency highly depends on the popularity of the target object. However, the popularity varies since peer joining or leaving a P2P network is very dynamic. Many researches aimed at finding a good searching scheme in such a variable environment with a better trade-off among long searching time, a large amount of duplicated query messages and a low successful search hit rate. In this paper, we propose a Cloning Random Walker assisted by Weakly Connected Dominating Set (CloneRW+WCDS) method to adaptively locate the target object in a P2P network. Our simulation results also depict that our proposed scheme can perform a better trade-off among the search delay, message overhead per hit and success rate while conducting resource searching in a P2P network. [ABSTRACT FROM AUTHOR]

Borrowing from concepts in expander graphs, we study the expansion properties of real-world, complex networks (e.g., social networks, unstructured peer-to-peer, or P2P networks) and the extent to which these properties can be exploited to understand and address the problem of decentralized search. We first produce samples that concisely capture the overall expansion properties of an entire network, which we collectively refer to as the expansion signature. Using these signatures, we find a correspondence between the magnitude of maximum expansion and the extent to which a network can be efficiently searched. We further find evidence that standard graph-theoretic measures, such as average path length, fail to fully explain the level of 'searchability' or ease of information diffusion and dissemination in a network. Finally, we demonstrate that this high expansion can be leveraged to facilitate decentralized search in networks and show that an expansion-based search strategy outperforms typical search methods. [ABSTRACT FROM AUTHOR]

This work introduces decentralized query processing techniques based on MIDAS, a novel distributed multidimensional index. In particular, MIDAS implements a distributed k-d tree, where leaves correspond to peers, and internal nodes dictate message routing. MIDAS requires that peers maintain little network information, and features mechanisms that support fault tolerance and load balancing. The proposed algorithms process point and range queries over the multidimensional indexed space in only O(log n) hops in expectance, where n is the network size. For nearest neighbor queries, two processing alternatives are discussed. The first, termed eager processing, has low latency (expected value of O(log n) hops) but may involve a large number of peers. The second, termed iterative processing, has higher latency (expected value of O(log n) hops) but involves far fewer peers. A detailed experimental evaluation demonstrates that our query processing techniques outperform existing methods for settings involving real spatial data as well as in the case of high dimensional synthetic data. [ABSTRACT FROM AUTHOR]

In this paper, we present one of the first and most extensive characterizations of closed community-based P2P systems. Such systems are organic groups of peer-to-peer (P2P) clients, which can be joined only by users belonging to a certain network (e.g., connected to a given Internet Service Provider (ISP)). A number of factors motivate the growth of these communities, such as quality of content, anonymity of transfers, and the potential for better performance that enhances user experience. Our study is conducted in two contrasting environments-a campus network and a national ISP-located in different continents. In both cases, large-scale closed communities have been found to be the predominant P2P systems in use. We shed light both on the factors motivating the growth of such communities, and present results characterizing the extensiveness of their usage, the performance achievable by the systems, and the implications of such communities for network providers. While our findings are interesting in their own right, they also offer important lessons for ongoing research that seeks to localize traffic within ISP boundaries. In particular, our results suggest that (i) in ISPs with heterogeneous access technologies, the performance benefits to users on localizing P2P traffic is largely dependent on the degree of seed-like behavior of peers behind high-bandwidth access technologies; and (ii) while localization can reduce the traffic on Internet peering links, it has the potential to cause a significant increase in traffic on internal links of providers, potentially requiring upgrades of network links. [ABSTRACT FROM AUTHOR]

An important concern for an efficient use of distributed computing is dealing with load balancing to ensure all available nodes and their shared resources are equally exploited. In large scale systems such as volunteer computing platforms and desktop grids, centralized solutions may introduce performance bottlenecks and single points of failure. Accordingly fully distributed alternatives have been considered, due to their inherent robustness and reliability. In extremely dynamic contexts, scheduling middlewares should adapt their job scheduling policies to the actual availability and overcome the volatility and heterogeneity typical of the underlying nodes. To deal with the dynamicity of a large pool of resources, self-organizing and adaptive solutions represent a promising research direction. Solutions based on bio-inspired methodologies are particularly suitable, as they inherently provide the desired features. In this paper we present a fully distributed load balancing mechanism, called ozmos, which aims at increasing the efficiency of distributed computing systems through peer-to-peer interaction between nodes. The proposed algorithm is based on a Chord overlay, and employs ant-like agents to spread information about the current load on each node, to reschedule tasks from overloaded systems to underloaded ones, and to relocate incompatible tasks on suitable resources in heterogeneous grids. By means of several evaluation scenarios we demonstrate the effectiveness of the proposed solution in achieving system-wide load balancing, both with homogeneous and heterogeneous resources. In particular we consider the load balancing performance of our approach, its scalability, as well as its communication efficiency. [ABSTRACT FROM AUTHOR]

The growing popularity of Peer-to-Peer (P2P) technology in real applications in recent years has sparked increasing interest from both academia and industry in designing resilient P2P networks for these applications. Routing is a crucial technique to support successful P2P applications, and designing robust routing mechanisms is still a technical challenge for P2P systems and applications due to their inherent dynamics. This paper addresses the issue of resilient routing in unstructured P2P networks. To this end, we first propose a novel query routing approach to improving query performance in unstructured P2P networks, and then develop a mobile agent based network reconfiguration mechanism that provides a combined node and link failure diagnosis and restoration to maintain routing performance even in dynamic network environments. Simulated results show that the proposed query routing approach can achieve a good tradeoff between query hit rates and space costs in scale-free networks and that the mobile agent based network reconfiguration mechanism outperforms the existing methods in different types of network topologies. [ABSTRACT FROM AUTHOR]

Detecting node failures within Peer-to-Peer networks is an inherent trade-off between timely detection and consuming bandwidth on network maintenance. In the absence of user-driven messages, the majority of P2P networks rely upon the exchange of periodic keep-alive messages to maintain connections and network topology. We investigate three novel algorithms which prioritise keep-alive messages to nodes that are more likely to have failed. In doing so, these algorithms significantly reduce the expected delay between failures occurring and their subsequent detection in comparison to the standard approach, whilst consuming similar levels of bandwidth. Our algorithms build upon several studies that have shown that older peers are more likely to remain in the network than their short-lived counterparts. Each of our algorithms increase the interval between successive keep-alive messages as peers age in the system, based upon the distribution of peer session times and the current age of peers. We extensively describe the details of each algorithm, before comparing them to the standard periodic approach using simulations based upon measured network data. Furthermore, we show that these algorithms are complimentary to existing gossip-based mechanisms and investigate alternate methods of ascertaining a node's age so that our algorithms can be robustly deployed in untrustworthy environments. [ABSTRACT FROM AUTHOR]

Peer-to-Peer networks attracted a significant amount of interest because of their capacity for resource sharing and content distribution. Content distribution applications allow personal computers to function in a coordinated manner as a distributed storage medium by contributing, searching, and obtaining digital content. Searching in unstructured P2P networks is an important problem, which has received considerable research attention. Acceptable searching techniques must provide large coverage rate, low traffic load, and optimum latency. This paper reviews flooding-based search techniques in unstructured P2P networks. It then analytically compares their coverage rate, and traffic overloads. Our simulation experiments have validated analytical results. [ABSTRACT FROM AUTHOR]

The accuracy of detecting an intrusion within a network of intrusion detection systems (IDSes) depends on the efficiency of collaboration between member IDSes. The security itself within this network is an additional concern that needs to be addressed. In this paper, we present a trust-based framework for secure and effective collaboration within an intrusion detection network (IDN). In particular, we design a trust model that allows each IDS to evaluate the trustworthiness of other IDSes based on its personal experience. We also propose an admission control algorithm for the IDS to manage the acquaintances it approaches for advice about intrusions. We discuss the effectiveness of our approach in protecting the IDN against common attacks. Additionally, experimental results demonstrate that our system yields significant improvement in detecting intrusions. The trust model further improves the robustness of the collaborative system against malicious attacks. The experimental results also support that our admission control algorithm is effective and fair, and creates incentives for collaboration. [ABSTRACT FROM AUTHOR]

In this paper we propose a Distributed Hash Table (DHT)-based peer-to-peer resource discovery protocol designed for large-scale Mobile Ad-hoc NETwork (MANET). The proposed Mobile Resource Discovery Protocol (MRDP) uses a distributed dynamic clustering algorithm to adaptively and rapidly group nodes in a MANET for resource discovery purpose, and utilizes DHTs to efficiently cache resource information in a peer-to-peer manner. We provide a probabilistic lower bound on the performance of the MRDP. We also present simulation results under different scenarios to show that MRDP has low message overheads and its performance is highly insensitive to the size of the MANET. These characteristics make MRDP suitable for large-scale MANETs. [ABSTRACT FROM AUTHOR]

The LOCKSS system is a world-wide peer-to-peer system for the preservation of academic journals and other archival information published on the Web. The system is deployed at over 200 libraries around the world and currently preserving titles of publishers representing more than 2000 academic titles. It consists of a large number of independent, low-cost, persistent Web caches that cooperate to detect and repair damage to their content by voting in “opinion polls.” Based on our experience working with the LOCKSS system, in this paper, we identify and characterize a fundamental tradeoff in the system’s ability to defend against adversaries with competing goals. In particular, the techniques used to defend against adversaries attempting stealth modification of content being preserved in the system are at odds with those used to identify nuisance adversaries simply trying to disrupt system procedures. We show that with a simple change to the design of the system’s preservation protocol we are able to create moderately strong defense against both of these competing adversaries simultaneously. [ABSTRACT FROM AUTHOR]

Recent platforms for Peer-to-Peer (P2P) based video distribution such as Zattoo and Joost are based on End-Host or Application Layer Multicast techniques. An on demand adaptation of audio/video data to end user terminals or to the transport and error characteristics of the client access technology is not supported. To address such issues in the scale of P2P Networks, we describe a cooperative service provisioning principle (CSP) based on the assumption that selected peers offer processing services to the community. In contrast to recent approaches our main focus in this paper is on the applicability of QoS estimation techniques to decrease time and measurement complexity of CSP. We provide a state of the art in landmark-based delay estimation and introduce a novel technique for landmark-based bottleneck bandwidth prediction showing favourable results for networks with widest path routing. [ABSTRACT FROM AUTHOR]