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.

基于Super-peer的P2P流媒体服务系统构架的研究

在分析比对现有P2P流媒体服务系统构架的基础上,提出了一种新的P2P流媒体服务系统构架,在构架中引入了带有冗余的Super-peer结构,使得该流媒体服务系统可以达到较高的效率和健壮性。

基于Super Peer的P2P e-Learning模型

在分析各种P2P网络特点的基础上,提出了分布式环境中基于超节点的P2P e-Learning模型。对特定peer组中超节点的加入和超节点的服务进行了具体描述。针对e-Learning的特性,给出了模型中的数据抽象和本体描述,并对该P2P网络模型在文件传输方面的性能做了分析。

Monitoring Peer-to-Peer Botnets:Requirements,Challenges,and Future Works

The cyber-criminal compromises end-hosts(bots)to configure a network of bots(botnet).The cyber-criminals are also looking for an evolved architecture that makes their techniques more resilient and stealthier such as Peer-to-Peer(P2P)networks.The P2P botnets leverage the privileges of the decentralized nature of P2P networks.Consequently,the P2P botnets exploit the resilience of this architecture to be arduous against take-down procedures.Some P2P botnets are smarter to be stealthy in their Commandand-Control mechanisms(C2)and elude the standard discovery mechanisms.Therefore,the other side of this cyberwar is the monitor.The P2P botnet monitoring is an exacting mission because the monitoring must care about many aspects simultaneously.Some aspects pertain to the existing monitoring approaches,some pertain to the nature of P2P networks,and some to counter the botnets,i.e.,the anti-monitoring mechanisms.All these challenges should be considered in P2P botnet monitoring.To begin with,this paper provides an anatomy of P2P botnets.Thereafter,this paper exhaustively reviews the existing monitoring approaches of P2P botnets and thoroughly discusses each to reveal its advantages and disadvantages.In addition,this paper groups the monitoring approaches into three groups:passive,active,and hybrid monitoring approaches.Furthermore,this paper also discusses the functional and non-functional requirements of advanced monitoring.In conclusion,this paper ends by epitomizing the challenges of various aspects and gives future avenues for better monitoring of P2P botnets.

P2P网络Peer访问Web Service的研究和实现

文章首先简要介绍了P2P网络和WebService的技术背景,接着提出了P2P网络与WebService集成的思想,为此提出WebServiceBroker的概念,从而实现P2P网络Peer透明访问WebService。

一种基于Super Peer结构的P2P视频点播系统的设计与实现

分析各种P2P网络的特点,为了使用户在视频点播过程中获得快速、稳定的流媒体数据,提出了一种采用Super Peer结构的P2P视频点播设计方案。讨论了以该方案为基础的拓扑树的构建、拓扑树的变更等关键技术,并对该系统进行了性能分析,证明其具有较好的可靠性和稳定性。

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.

Peer selecting model based on FCM for wireless distributed P2P files sharing systems

IIn order to improve the performance of wireless distributed peer-to-peer(P2P)files sharing systems,a general system architecture and a novel peer selecting model based on fuzzy cognitive maps(FCM)are proposed in this paper.The new model provides an effective approach on choosing an optimal peer from several resource discovering results for the best file transfer.Compared with the traditional min-hops scheme that uses hops as the only selecting criterion,the proposed model uses FCM to investigate the complex relationships among various relative factors in wireless environments and gives an overall evaluation score on the candidate.It also has strong scalability for being independent of specified P2P resource discovering protocols.Furthermore,a complete implementation is explained in concrete modules.The simulation results show that the proposed model is effective and feasible compared with min-hops scheme,with the success transfer rate increased by at least 20% and transfer time improved as high as 34%.

SSABC:a super-peer selection algorithm based on capacity

Combining the characteristics of peer-to-peer （P2P） and grid, a super-peer selection algorithm--SSABC is presented in the distributed network merging P2P and grid. The algorithm computes nodes capacities using their resource properties provided by a grid monitoring and discovery system, such as available bandwidth, free CPU and idle memory, as well as the number of current connections and online time. when a new node joins the network and the super-peers are all saturated, it should select a new super-peer from the new node or joined nodes with the highest capacity. By theoretical analyses and simulation experiments, it is shown that super-peers selected by capacity can achieve higher query success rates and shorten the average hop count when compared with super-peers selected randomly, and they can also balance the network load when all super-peers are saturated. When the number of total nodes changes, the conclusion is still valid, which explains that the algorithm SSABC is feasible and stable.

Super-peer网络中基于信誉的资源发现算法

在Super-peer网络模型下,提出一种基于信誉的资源发现算法,通过计算域内和域间节点的信誉度,将请求信息转发给信誉高的节点,在保证资源发现效率的同时提高资源查找的可靠性。

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.

基于Super-Peer架构的信息查询算法研究

本文介绍了传统P2P的基本结构,比较了其优点和不足,阐述了移动Agent的基本特性。在Super-Peer架构的P2P网络模型基础上提出了一种基于移动Agent的信息查询算法,并利用时延阀值控制整个算法,从而提高了查询效率。

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.

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.

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.

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.

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.

Research on Video on Demand Based on P2P Network

A P2P approaches to extend the ability of Video on Demand systems to serve more users. In the proposed system users share with each other the media data obtained and the media server is no longer the only source to get data from, thereby, the load on the media server could be greatly alleviated and the overall system capacity increases and more users could be served. The P2P streaming system introduces efficient searching;data transfer dynamically monitoring and initial buffering to maintain a high quality of playback. Its provider selection policy helps to reduce the load of the underlying network by avoiding remote data transfer.

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.