Traditional P2P Research Articles

Multimedia Transfer Over Wi-Fi Direct Based on Fuzzy Clustering for Vehicular Communications

Introduction: Wi-Fi Direct technology enables users to share services in groups, and support Service discovery at the data link layer before creating a P2P Group, and it can be used as a collaborative application integrated into vehicles for multimedia transfer and group configuration between V2X. Compared to cellular networks, Wi-Fi Direct offers a high transmission data rate at a cheaper cost. However, there are numerous hurdles to using Wi-Fi Direct in vehicles, including the fact that Wi-Fi Direct communication has a relatively small coverage area, disconnection may occur multiple times, and the distance between vehicles changes often in a moving setting, which negatively affects the quality of service delivery. Previous studies disregarded the motion and direction of moving objects. Methods: The main contribution of this paper is to use Wi-Fi Direct among vehicles to reduce reliance on the 5G network, thereby addressing the previous challenges. In particular, the main contribution of this paper is to introduce a set of scenarios based on different speeds, directions, and distances between vehicles. The state of the packets is monitored in each scenario to compute the packets delay and loss. We present a new contribution to the services discovery by providing V2V IE with a set of services that reflect the user's interest, such as Web pages, SMS, Audio links, and Video links, using the Generic Advertisement Protocol GAS, and a comparison between the traditional P2P IE and the new V2V IE. Furthermore, the paper introduces a stable Wi-Fi Direct Fuzzy C-Means FCM clustering method based on important parameters impacting the group formation, such as the location, the destination, the direction, the speed of the vehicle, and the user’s Interests List. Results: Based on the results of the FCM, there is still uncertainty in choosing the appropriate time to provide the services to the vehicles. We propose a Type-2 Fuzzy Logic Handover T2FLH system to solve the problem of handling uncertainty about dealing with the available services. Using the simulation on OMNeT++, the proposed scenarios with the fuzzy c-means FCM clustering method are compared to get the best clusters. Then the results were compared with the Type-2 Fuzzy T2FLH system to extract the best scenarios. Conclusion: We concluded from the results of previous experiments that Wi-Fi Direct can be used with vehicles at low speeds and high speeds. In the case of low speeds, it works efficiently depending on OMNET++ results. Therefore, Wi-Fi Direct can be used in vehicle stations and work sites that use limited-speed vehicles such as Clarks machines to alert safety and provide them with information about the devices around them. Bearing in mind that the speed of devices is limited in work areas. In the case of high speeds, the results are significantly improved using the proposed Type-2 fuzzy Logic Handover T2FLH system to model uncertainty and imprecision in a better way. Relying on T2FLH has led to a decrease in the rate of Packets Loss and Delay because the selection of the available services with previously specified time in the neighboring table became more accurate and avoiding uncertainty, depending on calculating the size of the data and the WFD signal strength conjunction with the distance and speed between the vehicles.

Exploring 6G Wireless Communication: Application Technologies, Challenges and Future Direction

The data traffic has increased significantly along with the quick development of smart wireless technologies, and current 5G networks are still not completely prepared to handle future huge data traffic in the areas of services, data transfer, data storage, and processing. 6G is expected to offer very high-level extended 5G capabilities, such as a Tbps data transfer rate and a sub-millisecond response time. The main objective of this study is to be aware of new technologies being enhanced day by day and provide existing research content, issues, and directions for the future regarding 6G wireless networks. Therefore, a systematic literature review of research articles is provided by categorizing the selected studies published between 2019 and 2022 in terms of enabling technologies. First, the researcher discussed the need for 6G by predicting the explosive growth of mobile traffic from 2022 to 2030. Second, 6G requirements, trends, and services are addressed and contrasted with 5G in terms of a group of key performance indicators. Third, conduct a comparative analysis of 6G challenges and gaps, such as security and privacy, the need for a decentralized network, Omnipresent service coverage, and storage efficiency. So, it is essential to develop an accurate, faster, and well-organized system for the 6G wireless network. We have presented an efficient and secure mode R6GS, which combines blockchain and 6G to improve security from the lower to upper layers while also improving storage efficiency. Cybertwin technologies are used at the edge layer of the 6G network in the proposed model R6GS to improve security. The smart contracts, IPFS and Ethereum blockchain are used in the proposed R6GS model to enhance the 6G network's data integrity and data storage. It also processes and stores massive amounts of data at various network layers, which removes the large storage capacity issue of traditional P2P and Client/Server (C/S) networks due to centralized servers in 6G technology. For the performance evaluation, the model is evaluated through expert opinion. Moreover, the proposed R6GS model also improves time efficiency through the edge layer, because if a task is available at the edge layer, there is no need to send a request to the core layer. The server at the edge layer efficiently delivers data to end nodes. Furthermore, a taxonomy is presented in this study. To the best of our knowledge, the proposed methodology worked efficiently.

Supporting Heterogenous Traffic on Top of Point-to-Multipoint Light-Trees

New 5 G and beyond services demand innovative solutions in optical transport to increase efficiency and flexibility and reduce capital (CAPEX) and operational (OPEX) expenditures to support heterogeneous and dynamic traffic. In this context, optical point-to-multipoint (P2MP) connectivity is seen as an alternative to provide connectivity to multiple sites from a single source, thus potentially both reducing CAPEX and OPEX. Digital subcarrier multiplexing (DSCM) has been shown as a feasible candidate for optical P2MP in view of its ability to generate multiple subcarriers (SC) in the frequency domain that can be used to serve several destinations. This paper proposes a different technology, named optical constellation slicing (OCS), that enables a source to communicate with multiple destinations by focusing on the time domain. OCS is described in detail and compared to DSCM by simulation, where the results show that both OCS and DSCM provide a good performance in terms of the bit error rate (BER) for access/metro applications. An exhaustive quantitative study is afterwards carried out to compare OCS and DSCM considering its support to dynamic packet layer P2P traffic only and mixed P2P and P2MP traffic; throughput, efficiency, and cost are used here as the metrics. As a baseline for comparison, the traditional optical P2P solution is also considered in this study. Numerical results show that OCS and DSCM provide a better efficiency and cost savings than traditional optical P2P connectivity. For P2P only traffic, OCS and DSCM are utmost 14.6% more efficient than the traditional lightpath solution, whereas for heterogeneous P2P + P2MP traffic, a 25% efficiency improvement is achieved, making OCS 12% more efficient than DSCM. Interestingly, the results show that for P2P only traffic, DSCM provides more savings of up to 12% than OCS, whereas for heterogeneous traffic, OCS can save up to 24.6% more than DSCM.

Grid-friendly pricing mechanism for peer-to-peer energy sharing market diffusion in communities

As a novel trading mode, the peer-to-peer (P2P) energy market cannot be accepted by the end-users immediately. There is an adoption process before all the energy prosumers participate in the P2P trading market. Therefore, we first employ a generalized Bass model to depict the P2P energy market diffusion process in the communities. Since the P2P market is still in the diffusion stage, we develop a hybrid P2P energy market consisting of traditional pool-based and P2P trading modes. Then, we establish the cost minimization models of energy prosumers, community managers, and system operators to analyze the market equilibrium in such a hybrid P2P energy market. The dynamic network usage costs are included in the system operator’s model to guarantee the market operation considering the heterogeneous prosumers. Finally, we propose a hybrid market-clearing method consisting of deep reinforcement learning and optimization algorithms. We model the generalized Bass model as an equivalent Markov process. The community manager and system operator can learn the near-optimal prices in their Markov decision processes with prosumers’ partial information. Numerical simulations demonstrate that the Markovian Bass model describes the P2P market adoption process precisely. The trading and network usage prices with and without considering the P2P energy market diffusion are compared and analyzed.

Is blockchain a cure for peer-to-peer lending?

The blockchain, a decentralized ledger system, has been considered a revolutionary technology to transform businesses, including the financial markets. As peer-to-peer (P2P) lending is also known for decentralization in the sense that individuals borrow from and lend to each other directly, bypassing traditional banks, we explore the possibility and benefits of blockchains in P2P lending. We first provide an economic analysis of existing P2P lending problems, including herding and platform-borrower collusion, with and without the blockchain mechanism. We note that, compared with the existing markets, blockchain-backed P2P lending is highly effective in privacy preservation and borrower quality distinction. Since the role of intermediaries is eliminated in the blockchain world, the chance of platform-borrower collusion is also minimized. Moreover, we show that borrowers and lenders can expect additional surplus when the origination fee in traditional P2P lending is replaced with a smaller tokenization cost and when borrowers present a more accurate financial incentive in a smart contract. With the smart contract, borrowers are allowed to propose optimal interest rates based on their creditworthiness and capacity of repayment while detailed personal information is not required. Additionally, we demonstrate that small investors’ surplus can be further enhanced due to the elimination of herding.

GDPR-Aware Revocable P2P File-Sharing System Over Consortium Blockchain

With the rise of blockchain technology, the peer-to-peer (P2P) network system has once again caught people's attention to equipping a blockchain with a big storage capacity. In the traditional P2P file-sharing network systems, such as InterPlanetary File System (IPFS), data stored in the other nodes cannot be revoked by the owner and can only be removed by other nodes themselves. To comply with the criteria of the European Union's General Data Protection Regulation, it is important to ensure that personal data can be completely removed by their owners. To improve the privacy and security of the P2P file-sharing system, we propose a revocable and monitorable P2P file-sharing system over a consortium blockchain to achieve revocation of files in the decentralized environment. By using a trusted execution environment, such as Intel Software Guard Extensions (SGX), the proposed scheme can verify the integrity of the executables of the P2P file-sharing system and generate a file authentication code for each IPFS node to make sure that the system is synchronized correctly. This scheme elaborately integrates the autonomous smart contracts and Intel SGX hardware to obtain the monitorable merit. The experimental results suggest that enhancing the security and privacy take modest computing costs into consideration. To the best of our knowledge, this scheme is the first attempt to achieve the P2P file-sharing system with securely revocable functions.

Data Propagation for Low Latency Blockchain Systems

Broadcasting plays a vital role in the consensus mechanisms of blockchain systems, since the consensus of each block must wait until the previous block is received by (nearly) all the nodes in the blockchain systems. Therefore, optimizing the performance of broadcasting can significantly improve the performance of the blockchain system. However, compared with other traditional P2P applications such as file downloading or video delivery, the broadcasting in blockchain has two new requirements, namely low redundancy and low propagation latency, which all the existing mechanisms (e.g. flooding, structural DHT etc.) can not meet well. In this paper, we propose Swift, a new broadcasting mechanism for blockchain systems. It optimizes the P2P topology construction and broadcast algorithm in the structured network based on unsupervised learning and greedy algorithm, effectively reducing the propagation latency of the blockchain P2P network while avoiding the waste of redundant bandwidth. We implemented a prototype of Swift and evaluated its performance on a testbed network that consists of 1000 blockchain nodes. The experimental findings show that Swift can reduce propagation latency by 19.8% with similar bandwidth consumption, generating an 18% increase in the throughput performance of the blockchain. Finally, with the increase in connections, Swift can simultaneously achieve low latency and maintain a relatively stable redundant bandwidth waste, instead of linearly increasing in flooding.

BlockchainBot: A Novel Botnet Infrastructure Enhanced by Blockchain Technology and IoT

Although the traditional P2P botnet has significant resilience against termination, its dependence on neighbor lists (NL) has left it vulnerable to infiltration and destruction. In addition, it is not sufficient in protecting the botmaster’s identity. To overcome these weaknesses, we proposed BlockchainBot, a botnet model that leveraged IoT devices as maintainers, and integrated blockchain, also known as distributed ledger technology (DLT). The BlockchainBot was able to fully deploy bots on public blockchains. It was versatile for multiple botnet applications and eliminated the dependence on NL. In addition, we further introduced a novel method, the forking of a channel, to kick out spy nodes that infiltrate a botnet. To further enforce the resistance against a single point of failure (SPoF), we introduced bot-cluster dispersing to prevent clustering around full nodes and more evenly scatter bots to prevent hostile takeovers. The analysis of the security of BlockchainBot indicated that it had strong resilience against DDoS attacks, Sybil attacks, and forensic investigations. Furthermore, the security of the forking of the channel and bot-cluster dispersing were also shown to be effective. The robustness of the BlockchainBot against the Sybil attack was also briefly discussed. Experimental results authenticated the effectiveness and performance of the BlockchainBot, as compared to previous models.

Peer-to-peer multi-risk insurance and mutual aid

Peer-to-peer (P2P) insurance is a decentralized network in which participants pool their resources together to compensate those who suffer losses. The rise of P2P insurance in Western countries, such as Friendsurance and Lemonade, has been viewed as a disruption to the traditional insurance industry in the same way Uber is to the taxi industry. A similar business model of mutual aid, such as the model developed by Xianghubao, has become popular in the East. It is a model designed to provide financial support to those in need and to distribute the cost among all participants.Despite the fast-changing landscape in this field, there has been scarce literature on the theoretical underpinning of P2P insurance and mutual aid. This paper presents the first effort to build a unified framework to quantify and assess the exchange of risks in a network of participants from different risk classes. Under this framework, the paper aims to address several essential research questions, including the fair exchange of heterogeneous risks and the optimality of algorithmic designs under various criteria. The modeling of multi-risk exchange is done with a P2P network structure. We show that these network structures not only can be used to explain the current practice in the industry, but also provide new tools to develop better designs. The paper concludes with a comparison of traditional insurance and P2P risk sharing from the standpoint of stability and cost reduction.

Coordinated P2P electricity trading model with aggregated alliance and reserve purchasing for hedging the risk of deviation penalty

The increasing of distributed energy and flexible load incentivize market participants to participate in a more active market. A coordinated peer to peer (P2P) trading model with an aggregated alliance and reserve purchasing is proposed in this paper. Under such a coordinated trading model, the market participants form an alliance, where the agents perform aggregated alliance and purchase reserve from a mobile energy storage supplier. To reduce the risk of deviation penalty in P2P trading, the agents seek to maximize the welfare of the entire alliance in the P2P process, while considering product differentiation and deviation risks. The proposed trading model design comprises: (i) a coordinated P2P market design with the aggregated alliance and reserve purchasing, (ii) a two-stage P2P market-clearing model to maximize trading utility while reducing the risk of deviation. To solve this two-stage multivariable coupling problem in a distributed way, we propose a primal–dual based ADMM method. Through the case study, compared with the traditional P2P trading model, the proposed market model can reduce the deviation penalty and improve the comprehensive welfare, while the convergence can be effectively guaranteed.

A Smart Contract-Based P2P Energy Trading System with Dynamic Pricing on Ethereum Blockchain.

We implement a peer-to-peer (P2P) energy trading system between prosumers and consumers using a smart contract on Ethereum blockchain. The smart contract resides on a blockchain shared by participants and hence guarantees exact execution of trade and keeps immutable transaction records. It removes high cost and overheads needed against hacking or tampering in traditional server-based P2P energy trade systems. The salient features of our implementation include: 1. Dynamic pricing for automatic balancing of total supply and total demand within a microgrid, 2. prevention of double sale, 3. automatic and autonomous operation, 4. experiment on a testbed (Node.js and web3.js API to access Ethereum Virtual Machine on Raspberry Pis with MATLAB interface), and 5. simulation via personas (virtual consumers and prosumers generated from benchmark). Detailed description of our implementation is provided along with state diagrams and core procedures.

Analysis and modelling the effects of mobility, Churn rate, node’s life span, intermittent bandwidth and stabilization cost of finger table in structured mobile P2P networks

Today P2P (Peer-to-Peer) networks are gaining popularity for sharing the contents. Due to massive spreading of Internet, these networks are also growing fast. MP2P (Mobile P2P) networks are attracting many users due to increase in the Internet-based mobile applications. These networks suffer from many challenges which are not considered for analysis and modelling adequately. We focus on few challenges like mobility of users, churn rate, intermittent bandwidth, shorter life span of mobile nodes, stabilization of finger table, etc. in this paper. We analytically analyse these challenges and define the effects of different parameters over the performance. Traditional P2P protocols are designed for wired networks and when these are implemented for mobile networks then mobility effect of users adds more challenge for researchers. We select two types of mobility models namely FF (Fluid Flow) and RWP (Random Waypoint) models to model the users’ mobility. The churn rate of the mobile nodes makes network overlay management and content searching more difficult in MP2P networks. We select finger table-based protocols which are widely deployed in the P2P networks. But these protocols can’t perform well in the mobile P2P networks due to mobility of the users. The mobility of the users and churn rate of the mobile nodes create failure in lookup of finger table and induce more cost to update the finger table. We consider these challenges and quantify the failure rate of mobile nodes, life span of mobile nodes, available bandwidth, cost of stabilization of finger table per node, etc. in this proposal. The proposed model is useful for modelling the performance of MP2P networks performance in various wireless environments like Mobile Ad hoc Networks (MANETs), Wireless Mesh Networks (WMNs), Wireless Sensor Networks (WSNs), Vehicular Ad hoc Networks (VANETs), Wireless LAN (WLAN), Wireless MAN (WMAN), etc.

PJ-Sec: secure node joining in mobile P2P networks

The advancement of portable mobile wireless devices such as smart-phones, PDA, etc., brought mobile peer-to-peer (P2P) as an extension of traditional P2P networks to provide efficient, low-cost communication among them in a cellular network. It is challenging to assign a unique identifier to each user, as an adversary can target to disrupt the P2P system, by carefully selecting user IDs or obtaining many pseudo-IDs. This work proposes a robust node-ID assignment mechanism for secure peer joining in mobile P2P system called PJ-Sec. PJ-Sec facilitates to generate nodeID for a joining peer by a collaborative effort of an existing peer (within the vicinity) and pre-selected vicinity head. PJ-Sec is formally analyzed using AVISPA model checker and found to be attack resistant.

Structuring communities for sharing human digital memories in a social P2P network

A community is sub-network inside P2P networks that partition the network into groups of similar peers to improve performance by reducing network traffic and high search query success rate. Large communities are common in online social networks than traditional file-sharing P2P networks because many people capture huge amounts of data through their lives. This increases the number of hosts bearing similar data in the network and hence increases the size of communities. This article presents a Memory Thread-based Communities for our Entity-based social P2P network that partition the network into groups of peers sharing data belonging to an entity–person, place, object or interest, having its own digital memory or be a part another memory. These connected peers having further similarities by organizing the network using linear orderings. A Memory-Thread is the collection of digital memories having a common reference key and organized according to some form of correlation. The simulation results show an increase in network performance for the proposed scheme along with a decrease in network overhead and higher query success rate compared to other similar schemes. The network maintains its performance even while the network traffic and size increase.

A New CR-Chord Based P2P Protocol in the Presence of Malicious Nodes

As is known, P2P networks work differently from traditional server-client architecture. Each node can act both a server and a client role. Traditional structural P2P systems are not architectures developed with security in the foreground. Therefore, there are many security vulnerabilities, and when malicious nodes are present in the system, P2P can adversely affect the functioning of the system. With the proposed method, secure nodes are kept in a specific table, taking into account the security gaps in structured peer-to-peer (P2P) networks, and subsequent queries are made over these secure nodes. In addition to the CR-Chord algorithm, half cycles were used to find more reliable cycles in dense malicious environments and increase lookup performance. This enabled P2P network to operate more robust. The lookup performance of the developed method was compared with Cyclic-Routing Chord algorithm in OverSim simulation environment. According to the obtained results, the developed Half Cyclic Routing Chord (HCR-Chord) algorithm was observed to give better results. Keywords: P2P Networks, Chord, Malicious Node, HCR-Chord DOI: 10.7176/JSTR/5-12-31

Modeling of Agent-Based Complex Network to Detect the Trust of Investors in P2P Platform

Due to the lopsided nature of investor investment-related model research under the traditional P2P environment, and in order to improve the research effect, this study proposes an agent-based complex network testing investor trust model. This model is based on interest trust, and combines with the Bayesian method to effectively evaluate the model trust, and builds a multi-steady-state agent system based on this. At the same time, it effectively analyzes the evolutionary mechanism of the system, and validates the model's application in combination with comparative experiments. The research shows that the model can effectively improve the success rate of executing tasks and shorten the distance between cooperative agents, thus ensuring the reliability of the selection of cooperative objects and providing theoretical reference for subsequent related research.

Collaborative extreme learning machine with a confidence interval for P2P learning in healthcare

In modern e-healthcare systems, medical institutions can provide more reliable diagnoses by introducing Machine-Learning (ML)-based classifiers. These ML classifiers are frequently trained with huge numbers of patients’ data to keep updated with new diseases and changes in current disease patterns. To increase the accuracy in prediction process, Peer-to-Peer (P2P) learning systems have been explored by many studies by which medical institutions can share their data with others: the more data are available, the more accurate the predictions. However, the traditional P2P network system requires much time in which the training data are shared among the nodes in the network. The system also spends much time on learning from samples where the data labels are unknown. Moreover, some nodes may perform certain computations which had already been computed by other nodes, resulting in redundant computations. In this paper, in order to deal with samples having unknown data labels, we propose a Collaborative Extreme Learning Machine (CELM) with a Confidence Interval (CI), which is an enhanced version of the traditional Extreme Learning Machine (ELM). Our proposed model eliminates redundant calculations of the network nodes (the e-healthcare institutions) to improve the learning efficiency, and improves the prediction accuracy by considering where plausible predictions lie. The extensive experimental analysis shows that the proposed model is efficient and achieves high accuracy (up to 98%) in diagnosing clinical events by analyzing patients’ medical records.

Self-organizing Community Learning Based on P2P Network in a University Computer Foundation Course

In order to solve the problem of lack of targeted guidance for learners in the community learning process, an improved algorithm for constructing com-munities was proposed. The algorithm used P2P architecture. Through the improved learning rules, the links between learners with similar interests were continuously strengthened. The community structure was automatically adjusted. In the end, learners with similar interests were grouped together. Taking university computer basic courses as an example, a self-organizing community learning system based on p2p network-based university comput-er basic courses was constructed. The results showed that compared with the traditional P2P architecture learning algorithm, this algorithm achieved better community construction quality and higher community construction speed. Therefore, this method can improve the learning effect of the university computer basic curriculum community.

Comparison of QoS optimisation techniques in adaptive smart device peer-to-peer overlay networks

Smart device networks form the backbone of many Internet of Things (IoT) applications. The performance of these systems depended on many factors. This includes their ability to connect to each other and network latency. In this paper, two algorithms are discussed that build a Peer-to-peer (P2P) overlay network. The focus is on real-time end-to-end remote instrumentation for IoT applications. P2P overlay networks are used for various purposes from content distribution through to media sharing. In contrast to traditional P2P systems, IoT systems can be highly sensitive to network latency and require low bandwidth. The main contributions of this paper are two algorithms to create overlay networks that assign peer nodes to super-peer nodes. The network contains a large number of smart devices and the key aim is to minimize system wide network latency. Other constraints regarding the nodes ability include the ability to become a super-peer node such as connectivity and limited processing capacities of the smart devices are also considered in context of a P2P remote instrumentation system. Both algorithms create a 3-hop network where the latency is lowered as much as possible with the given set of nodes. The algorithms have been validated through simulation.

An information discovery scheme for IoS of agricultural services using improved chord-ONS model

To solve the problems in EPC early network discovery service mode, we have analysed many aspects, such as load balance, robustness, and content privacy. We explain the architecture and workflow of structured P2P based ONS resolution system, and analyse advantages and disadvantages of current P2P-ONS system. Then the improved scheme is put forward which adopts hierarchical P2P network architecture to form ONS resolution system. It proposes a two-level chord-ONS architecture including routing performance analysis, storage and query of system information, nodes joining in or out, and selection of super nodes. The routing strategy based on node performance for super nodes and common nodes is also put forward. By the analysis of simulation results we find that the improved routing mechanism is better than the structured chord routing mechanism in query hopping, query delay and stability. It is more suitable for internet of things with huge dynamic and huge amount of information and it also shows comprehensive performance compared to traditional structured P2P network.