FPSblo:A Blockchain Network Transmission Model Utilizing Farthest Point Sampling

Peer-to-peer(P2P)overlay networks provide message transmission capabilities for blockchain systems.Improving data transmission efficiency in P2P networks can greatly enhance the performance of blockchain systems.However,traditional blockchain P2P networks face a common challenge where there is often a mismatch between the upper-layer traffic requirements and the underlying physical network topology.This mismatch results in redundant data transmission and inefficient routing,severely constraining the scalability of blockchain systems.To address these pressing issues,we propose FPSblo,an efficient transmission method for blockchain networks.Our inspiration for FPSblo stems from the Farthest Point Sampling(FPS)algorithm,a well-established technique widely utilized in point cloud image processing.In this work,we analogize blockchain nodes to points in a point cloud image and select a representative set of nodes to prioritize message forwarding so that messages reach the network edge quickly and are evenly distributed.Moreover,we compare our model with the Kadcast transmission model,which is a classic improvement model for blockchain P2P transmission networks,the experimental findings show that the FPSblo model reduces 34.8%of transmission redundancy and reduces the overload rate by 37.6%.By conducting experimental analysis,the FPS-BT model enhances the transmission capabilities of the P2P network in blockchain.

Epidemiological modeling of passive worm propagation on the P2P file-sharing network

The peer-to-peer（P2P） file-sharing network as a vehicle of disseminating files has become very popular. The appearance of dozens of kinds of passive worms on this network has, however, made it unsecured. This problem has been paid attention and a few of models for passive worm propagation has been presented. Unfortunately, the dynamic properties of this network are ignored in these models. Given the fact, the characteristics of both this network and the passive worm are identified, and on this basis a new mathematical model of passive worm propagation on the P2P network is presented in applying epidemiology in this paper. Note that the dynamic properties of this network are considered in the presented model. The model has been validated by large scale simulation experiments, which demonstrates that the presented model may be used for analyzing the behaviors of passive worms and predicting the trend of their propagation.

Deadline-aware network coding for video on demand service over P2P networks

We are interested in providing Video-on-Demand (VoD) streaming service to a large population of clients using peer-to-peer (P2P) approach. Given the asynchronous demands from multiple clients, continuously changing of the buffered contents, and the continuous video display requirement, how to collaborate with potential partners to get expected data for future content delivery are very important and challenging. In this paper, we develop a novel scheduling algorithm based on deadline- aware network coding (DNC) to fully exploit the network resource for efficient VoD service. DNC generalizes the existing net- work coding (NC) paradigm, an elegant solution for ubiquitous data distribution. Yet, with deadline awareness, DNC improves the network throughput and meanwhile avoid missing the play deadline in high probability, which is a major deficiency of the con- ventional NC. Extensive simulation results demonstrated that DNC achieves high streaming continuity even in tight network conditions.

Mathematical Model Validation of Search Protocols in MP2P Networks

Broadcasting is a basic technique in Mobile ad-hoc network(MANET),and it refers to sending a packet from one node to every other node within the transmission range.Flooding is a type of broadcast where the received packet is retransmitted once by every node.The naive flooding technique,floods the network with query messages,while the random walk technique operates by contacting the subsets of every node’s neighbors at each step,thereby restricting the search space.One of the key challenges in an ad-hoc network is the resource or content discovery problem which is about locating the queried resource.Many earlier works have mainly focused on the simulation-based analysis of flooding,and its variants under a wired network.Although,there have been some empirical studies in peer-to-peer(P2P)networks,the analytical results are still lacking,especially in the context of P2P systems running over MANET.In this paper,we describe how P2P resource discovery protocols perform badly over MANETs.To address the limitations,we propose a new protocol named ABRW(Address Broadcast Random Walk),which is a lightweight search approach,designed considering the underlay topology aimed to better suit the unstructured architecture.We provide the mathematical model,measuring the performance of our proposed search scheme with different widely popular benchmarked search techniques.Further,we also derive three relevant search performance metrics,i.e.,mean no.of steps needed to find a resource,the probability of finding a resource,and the mean no.of message overhead.We validated the analytical expressions through simulations.The simulation results closely matched with our analyticalmodel,justifying our findings.Our proposed search algorithm under such highly dynamic self-evolving networks performed better,as it reduced the search latency,decreased the overall message overhead,and still equally had a good success rate.

METrust: A Mutual Evaluation-based Trust Model for P2P Networks

It is necessary to construct an effective trust model to build trust relationship between peers in peer-to-peer （P2P） network and enhance the security and reliability of P2P systems. The current trust models only focus on the consumers＇ evaluation to a transaction, which may be abused by malicious peers to exaggerate or slander the provider deliberately. In this paper, we propose a novel trust model based on mutual evaluation, called METrust, to suppress the peers＇ malicious behavior, such as dishonest evaluation and strategic attack. METrust considers the factors including mutual evaluation, similarity risk, time window, incentive, and punishment mechanism. The trust value is composed of the direct trust value and the recommendation trust value. In order to inhibit dishonest evaluation, both participants should give evaluation information based on peers＇ own experiences about the transaction while computing the direct trust value. In view of this, the mutual evaluation consistency factor and its time decay function are proposed. Besides, to reduce the risk of computing the recommendation trust based on the recommendations of friend peers, the similarity risk is introduced to measure the uncertainty of the similarity computing, while similarity is used to measure credibility. The experimental results show that METrust is effective, and it has advantages in the inhibition of the various malicious behaviors.

An Anonymity Scheme Based on Pseudonym in P2P Networks

In this paper, we proposed an anonymity scheme based on pseudonym where peers are motivated not to share their identity. Compared with precious scheme such as RuP （Reputation using Pseudonyms）, our scheme can reduce its overhead and minimize the trusted center＇s involvement.

Hybrid ants-like search algorithms for P2P media streaming distribution in ad hoc networks

Media streaming delivery in wireless ad hoc networks is challenging due to the stringent resource restrictions,po-tential high loss rate and the decentralized architecture. To support long and high-quality streams,one viable approach is that a media stream is partitioned into segments,and then the segments are replicated in a network and served in a peer-to-peer(P2P) fashion. However,the searching strategy for segments is one key problem with the approach. This paper proposes a hybrid ants-like search algorithm(HASA) for P2P media streaming distribution in ad hoc networks. It takes the advantages of random walks and ants-like algorithms for searching in unstructured P2P networks,such as low transmitting latency,less jitter times,and low unnecessary traffic. We quantify the performance of our scheme in terms of response time,jitter times,and network messages for media streaming distribution. Simulation results showed that it can effectively improve the search efficiency for P2P media streaming distribution in ad hoc networks.

Greedysearch based service location in P2P networks

A model is built to analyze the performance of service location based on greedy search in P2P networks. Hops and relative QoS index of the node found in a service location process are used to evaluate the performance as well as the probability of locating the top 5% nodes with highest QoS level. Both model and simulation results show that, the performance of greedy search based service location improves significantly with the increase of the average degree of the network. It is found that, if changes of both overlay topology and QoS level of nodes can be ignored during a location process, greedy-search based service location has high probability of finding the nodes with relatively high QoS in small number of hops in a big overlay network. Model extension under arbitrary network degree distribution is also studied.

INCENTIVE MECHANISMS FOR TRUSTWORTHY ROUTING BASED ON GAME MODEL OF THE STRATEGIES OF NODES IN P2P NETWORKS

The trustworthiness and security of routing in the existing Peer-to-Peer (P2P) networks can not be ensured because of the diversity of the strategies of P2P nodes. This paper firstly uses game theory to establish game model of the strategies and profits of various types of routing nodes. Then,two incentive mechanisms for the corresponding stages of P2P trustworthy routing are proposed,namely trust associated mechanism and trust compensated mechanism. Simulation results show that the incentive mechanisms proposed in this paper will encourage cooperation actions of good nodes and restrain malicious actions of bad nodes,which ensure the trustworthiness of routing consequently.

A Novel Approach to Improve the Security of P2P File-Sharing Systems

The recent and unprecedented surge of public interest in peer-to-peer (P2P) file-sharing systems has led to a variety of interesting research questions. How to minimize threats in such an open community is an impor-tant research topic. Trust models have been widely used in estimating the trustworthiness of peers in P2P file-sharing systems where peers can transact with each other without prior experience. However, current P2P trust models almost take no consideration for the nature of trust, fuzzy, complex and dynamic, which results in low efficiency in resisting the attacks of malicious nodes. In this paper, a new trust model named NatureTrust that can alleviate the shortage brought by the nature of trust is proposed. In order to cope with the fuzzy characteristic of trust, linguistic terms are used to express trust. Additionally, fuzzy inference rules are employed to evaluate trust of each transaction so as to handle the complex characteristic of trust. Fur-thermore, risk factor is deployed into NatureTrust to represent and reason with the dynamic characteristic of trust. Both risk and trust factors are considered in evaluating the trustworthiness of each peer. Experimental results show that the trust model analyzed here thus stands against malicious act effectively.

Cluster based hierarchical resource searching model in P2P network

For the problem of large network load generated by the Gnutella resource-searching model in Peer to Peer （P2P） network, a improved model to decrease the network expense is proposed, which establishes a duster in P2P network, auto-organizes logical layers, and applies a hybrid mechanism of directional searching and flooding. The performance analysis and simulation results show that the proposed hierarchical searching model has availably reduced the generated message load and that its searching-response time performance is as fairly good as that of the Gnutella model.

Analytical Comparison of Resource Search Algorithms in Non-DHT Mobile Peer-to-Peer Networks

One of the key challenges in ad-hoc networks is the resource discovery problem.How efciently&quickly the queried resource/object can be resolved in such a highly dynamic self-evolving network is the underlying question?Broadcasting is a basic technique in the Mobile Ad-hoc Networks(MANETs),and it refers to sending a packet from one node to every other node within the transmission range.Flooding is a type of broadcast where the received packet is retransmitted once by every node.The naive ooding technique oods the network with query messages,while the random walk scheme operates by contacting subsets of each node’s neighbors at every step,thereby restricting the search space.Many earlier works have mainly focused on the simulation-based analysis of ooding technique,and its variants,in a wired network scenario.Although,there have been some empirical studies in peer-to-peer(P2P)networks,the analytical results are still lacking,especially in the context of mobile P2P networks.In this article,we mathematically model different widely used existing search techniques,and compare with the proposed improved random walk method,a simple lightweight approach suitable for the non-DHT architecture.We provide analytical expressions to measure the performance of the different ooding-based search techniques,and our proposed technique.We analytically derive 3 relevant key performance measures,i.e.,the avg.number of steps needed to nd a resource,the probability of locating a resource,and the avg.number of messages generated during the entire search process.

Deep Q-Learning Based Optimal Query Routing Approach for Unstructured P2P Network

Deep Reinforcement Learning(DRL)is a class of Machine Learning(ML)that combines Deep Learning with Reinforcement Learning and provides a framework by which a system can learn from its previous actions in an environment to select its efforts in the future efficiently.DRL has been used in many application fields,including games,robots,networks,etc.for creating autonomous systems that improve themselves with experience.It is well acknowledged that DRL is well suited to solve optimization problems in distributed systems in general and network routing especially.Therefore,a novel query routing approach called Deep Reinforcement Learning based Route Selection(DRLRS)is proposed for unstructured P2P networks based on a Deep Q-Learning algorithm.The main objective of this approach is to achieve better retrieval effectiveness with reduced searching cost by less number of connected peers,exchangedmessages,and reduced time.The simulation results shows a significantly improve searching a resource with compression to k-Random Walker and Directed BFS.Here,retrieval effectiveness,search cost in terms of connected peers,and average overhead are 1.28,106,149,respectively.

A Scalable and Robust DHT Protocol for Structured P2P Network

Distributed Hash Tables (DHTs) were originated from the design of structured peer-to-peer (P2P) systems. A DHT provides a key-based lookup service similar to a hash table. In this paper, we present the detailed design of a new DHT protocol, Tambour. The novelty of the protocol is that it uses parallel lookup to reduce retrive latency and bounds communication overhead to a dynamically adjusted routing table. Tambour estimates the probabilities of routing entries' liveness based on statistics of node lifetime history and evicts dead entries after lookup failures. When the network is unstable, more routing entries will be evicted in a given period of time, and the routing tables will be getting smaller which minimize the number of timeouts for later lookup requests. An experimental prototype of Tambour has been simulated and compared against two popular DHT protocols. Results show that Tambour outperforms the compared systems in terms of bandwith cost, lookup latency and the overall efficiency.

Network address translation traversal based on Bernoulli laws of large number in P2P streaming system

P2P streaming application must realize network address translation （NAT） traversal. To handle low success ratio of the existing NAT traversal algorithm, UPnP-STUN （UPUN） and port-mapping sample estimation （PMSE） algorithm are recommended in this paper. UPUN is the combination of UPnP and STUN, and PMSE utilizes port mapping samples added by symmetric NAT for different sessions to estimate regularity of port mapping of symmetric NAT, which takes advantage of the Bernoulli law of large numbers. Besides, for the situation that both peers are behind NAT, and to handle heavy relay server load when many inner peers want to communicate with each other, a peer auxiliary-relay （PAR） algorithm is presented. PAR lets outer peers with sufficient bandwidth act as relay servers to alleviate pressure of real server, which could avoid NAT traversal failure caused by single point failure of relay server. Finally, experiments show that the proposed algorithms could improve the success ratio significantly for NAT traversal in P2P streaming application as well as improve P2P streaming application applicability.

Modeling active worm propagation on the P2P network

This paper analyzes the characteristics of the Peer-to-Peer （P2P） active worm and its attacking mechanism, and then proposes a mathematical model of propagation of the P2P active worm applying Epidemiology. Based on the analysis on the protocols of realistic P2P systems, a software which can be used to simulate the P2P network environment and the propagation of P2P active worm is imple- mented in this paper. A large number of simulation experiments are performed using the developed simulation software. The results from these simulation experiments validate the proposed model, which means that the model can be used to analyze the spreading behaviors of the P2P active worm and predict its trend.

AR Display Method of a Person＇s Identifier near the Head on a Camera Screen Based on the GPS Information and Face Detection Using Ad hoc and P2P Networking

The spread of social media has increased contacts of members of communities on the lntemet. Members of these communities often use account names instead of real names. When they meet in the real world, they will find it useful to have a tool that enables them to associate the faces in fiont of them with the account names they know. This paper proposes a method that enables a person to identify the account name of the person （＂target＂） in front of him/her using a smartphone. The attendees to a meeting exchange their identifiers （i.e., the account name） and GPS information using smartphones. When the user points his/her smartphone towards a target, the target＇s identifier is displayed near the target＇s head on the camera screen using AR （augmented reality）. The position where the identifier is displayed is calculated from the differences in longitude and latitude between the user and the target and the azimuth direction of the target from the user. The target is identified based on this information, the face detection coordinates, and the distance between the two. The proposed method has been implemented using Android terminals, and identification accuracy has been examined through experiments.

Risks and Countermeasures of Chinese P2P Lending Network in the Internet Financial Background

In the era of big data-oriented development in today＇s society, with the Internet as the background of the financial lending rapid development of P2P network, and its role in promoting economic development has played, but also generated a lot of negative impact. In this paper, the basic concepts of lending comb P2P networks, based on analyzes the risks faced by P2P networks borrowing against these risks P2P network is proposed to strengthen the regulatory lending advice and countermeasures.

The credit risk of the borrower＇s credit in P2P network

P2P network lending refers to the individual through the oJfline trading platform provided by the Business Company provides small loans to other individuals. According to the sea tree Lingyi data stalistics, as of November 2014. China has 1371 P2P network lending company, than by the end of2013 638 over more than doubled. Since 2014,The cumulative volume of the whole network lending industry is up to 431.2 billion yuan. With the increasing social awareness in the industry, the future of the number and amount of P2P network lending companies in China will continue to grow rapidly. However, at present our P2P network credit risk management issues is serious, lacking of professional risk management personnel,who audit on the borrower＇s credit mostly limited to the upload information of borrowers. Credit rating is largely dependent on the subjective judgment of the risk control personnel and audit staff, which can not meet the requirements of the transaction participants in the loan security measures.This paper to pat the loan company were empirical research, through the logistic model to find the breach the key influence factors, to construct the borrower＇s credit risk evaluation methods, and to provide the P2P network lending risk control with specific policy recommendations.