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Journal articles on the topic 'Peer-to-peer architecture (Computer networks)'

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Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2024

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1

Bhisikar, Swati, Simran Taneja, Omkar Yadav, and Swarnika Srivastava. "Peer-to-Peer File Sharing WebApp." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 8 (September 20, 2023): 21–35. http://dx.doi.org/10.17762/ijritcc.v11i8.7920.

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Peer-to-peer (P2P) networking has emerged as a promising technology that enables distributed systems to operate in a decentralized manner. P2P networks are based on a model where each node in the network can act as both a client and a server, thereby enabling data and resource sharing without relying on centralized servers. The P2P model has gained considerable attention in recent years due to its potential to provide a scalable, fault-tolerant, and resilient architecture for various applications such as file sharing, content distribution, and social networks.In recent years, researchers have also proposed hybrid architectures that combine the benefits of both structured and unstructured P2P networks. For example, the Distributed Hash Table (DHT) is a popular hybrid architecture that provides efficient lookup and search algorithms while maintaining the flexibility and adaptability of the unstructured network.To demonstrate the feasibility of P2P systems, several prototypes have been developed, such as the BitTorrent file-sharing protocol and the Skype voice-over-IP (VoIP) service. These prototypes have demonstrated the potential of P2P systems for large-scale applications and have paved the way for the development of new P2P-based systems.

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2

Tang, Weizhao, Lucianna Kiffer, Giulia Fanti, and Ari Juels. "Strategic Latency Reduction in Blockchain Peer-to-Peer Networks." ACM SIGMETRICS Performance Evaluation Review 51, no. 1 (June 26, 2023): 93–94. http://dx.doi.org/10.1145/3606376.3593572.

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Most permissionless blockchain networks run on peer-to-peer (P2P) networks, which offer flexibility and decentralization at the expense of performance (e.g., network latency). Historically, this tradeoff has not been a bottleneck for most blockchains. However, an emerging host of blockchain-based applications (e.g., decentralized finance) are increasingly sensitive to latency; users who can reduce their network latency relative to other users can accrue (sometimes significant) financial gains. In this work, we initiate the study of strategic latency reduction in blockchain P2P networks. We first define two classes of latency that are of interest in blockchain applications. We then show empirically that a strategic agent who controls only their local peering decisions can manipulate both types of latency, achieving 60% of the global latency gains provided by the centralized, paid service bloXroute, or, in targeted scenarios, comparable gains. Finally, we show that our results are not due to the poor design of existing P2P networks. Under a simple network model, we theoretically prove that an adversary can always manipulate the P2P network's latency to their advantage, provided the network experiences sufficient peer churn and transaction activity.

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3

Rooney, S., D. Bauer, and R. Deydier. "A federated peer-to-peer network game architecture." IEEE Communications Magazine 42, no. 5 (May 2004): 114–22. http://dx.doi.org/10.1109/mcom.2004.1299353.

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4

Tang, Weizhao, Lucianna Kiffer, Giulia Fanti, and Ari Juels. "Strategic Latency Reduction in Blockchain Peer-to-Peer Networks." Proceedings of the ACM on Measurement and Analysis of Computing Systems 7, no. 2 (May 19, 2023): 1–33. http://dx.doi.org/10.1145/3589976.

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Most permissionless blockchain networks run on peer-to-peer (P2P) networks, which offer flexibility and decentralization at the expense of performance (e.g., network latency). Historically, this tradeoff has not been a bottleneck for most blockchains. However, an emerging host of blockchain-based applications (e.g., decentralized finance) are increasingly sensitive to latency; users who can reduce their network latency relative to other users can accrue (sometimes significant) financial gains. In this work, we initiate the study of strategic latency reduction in blockchain P2P networks. We first define two classes of latency that are of interest in blockchain applications. We then show empirically that a strategic agent who controls only their local peering decisions can manipulate both types of latency, achieving 60% of the global latency gains provided by the centralized, paid service bloXroute, or, in targeted scenarios, comparable gains. Finally, we show that our results are not due to the poor design of existing P2P networks. Under a simple network model, we theoretically prove that an adversary can always manipulate the P2P network's latency to their advantage, provided the network experiences sufficient peer churn and transaction activity.

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5

MAIER, RONALD, and JOHANNES SAMETINGER. "PEER-TO-PEER INFORMATION WORKSPACES IN INFOTOP." International Journal of Software Engineering and Knowledge Engineering 14, no. 01 (February 2004): 79–102. http://dx.doi.org/10.1142/s0218194004001531.

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Knowledge workers collaborate in teams, networks and communities in order to accomplish knowledge processes. They have to be supported with adequate organizational as well as information and communication technological (ICT) infrastructures. From an ICT perspective, requirements have changed when compared to more traditional (office) work due to the considerably higher complexity of data, the focus on communication across the boundaries of corporate ICT infrastructures and the mobility of knowledge workers. This requires the systematic handling of context and substantially extended functionality for collaboration in the knowledge workers' personal workspaces. In this paper, we outline typical knowledge processes and discuss ICT support for the personal management of information, of web content, of collaboration and of knowledge. We present Infotop, a tool that supports the creation and management of shared-context information workspaces and organizes knowledge resources in a peer-to-peer (p2p) architecture. We show how Infotop can be used to support typical knowledge work processes and discuss its dimensions, its user interface, its shared context workspaces, its architecture, and some thoughts on a prototype implementation currently under development.

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6

Haase, Peter, Ronny Siebes, and Frank van Harmelen. "Expertise-based peer selection in Peer-to-Peer networks." Knowledge and Information Systems 15, no. 1 (January 24, 2007): 75–107. http://dx.doi.org/10.1007/s10115-006-0055-1.

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7

Ferreira, Ronaldo A., Suresh Jagannathan, and Ananth Grama. "Locality in structured peer-to-peer networks." Journal of Parallel and Distributed Computing 66, no. 2 (February 2006): 257–73. http://dx.doi.org/10.1016/j.jpdc.2005.09.002.

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8

Lehikoinen, Juha, Ilkka Salminen, Antti Aaltonen, Pertti Huuskonen, and Juha Kaario. "Meta-searches in peer-to-peer networks." Personal and Ubiquitous Computing 10, no. 6 (December 7, 2005): 357–67. http://dx.doi.org/10.1007/s00779-005-0054-3.

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9

Mickens, James W., and Brian D. Noble. "Predicting node availability in peer-to-peer networks." ACM SIGMETRICS Performance Evaluation Review 33, no. 1 (June 6, 2005): 378–79. http://dx.doi.org/10.1145/1071690.1064263.

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10

Wang, Xiaoming, Yueping Zhang, Xiafeng Li, and Dmitri Loguinov. "On zone-balancing of peer-to-peer networks." ACM SIGMETRICS Performance Evaluation Review 32, no. 1 (June 2004): 211–22. http://dx.doi.org/10.1145/1012888.1005713.

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11

Pérez-Miguel, Carlos, Jose Miguel-Alonso, and Alexander Mendiburu. "High throughput computing over peer-to-peer networks." Future Generation Computer Systems 29, no. 1 (January 2013): 352–60. http://dx.doi.org/10.1016/j.future.2011.08.011.

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12

Ferreira, Ronaldo A., Mehmet Koyutürk, Suresh Jagannathan, and Ananth Grama. "Semantic indexing in structured peer-to-peer networks." Journal of Parallel and Distributed Computing 68, no. 1 (January 2008): 64–77. http://dx.doi.org/10.1016/j.jpdc.2007.06.003.

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13

OZTOPRAK, K., and G. B. AKAR. "Hybrid Fault Tolerant Peer to Peer Video Streaming Architecture." IEICE Transactions on Communications E91-B, no. 11 (November 1, 2008): 3627–38. http://dx.doi.org/10.1093/ietcom/e91-b.11.3627.

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14

TIAN, Chun-Qi, Jian-Hui JIANG, Zhi-Guo HU, and Feng LI. "A Novel Super-Peer Based Trust Model for Peer-to-Peer Networks." Chinese Journal of Computers 33, no. 2 (April 27, 2010): 345–55. http://dx.doi.org/10.3724/sp.j.1016..2010.00345.

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15

Korzun, Dmitry, and Andrei Gurtov. "Hierarchical architectures in structured peer-to-peer overlay networks." Peer-to-Peer Networking and Applications 7, no. 4 (March 14, 2013): 359–95. http://dx.doi.org/10.1007/s12083-013-0200-z.

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16

Meher, Kunal, Gandharv More, Aanshi Singh, Danyl Fernandes, and Mathew Philip. "Peer-to-Peer Conferencing using Blockchain, WebRTC and SIP." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 8s (August 18, 2023): 651–56. http://dx.doi.org/10.17762/ijritcc.v11i8s.7252.

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The owner of the centralized video platform has more control over uploaded content than the content producer does. But the other Blockchain-based decentralized video services are attempting to reduce ad pressure and get rid of middlemen. The article suggests a combination of a safe encryption technique and an access control mechanism created "with technology" to create a successful decentralized video streaming platform built on the Blockchain. Peer-to-peer (P2P) overlays are one of the complicated network applications and services that have been migrated to the Web as a result of the increasing support for Web Real-Time Communication (WebRTC) standard in modern browsers for real-time communications. The expansion of access networks’ bandwidth also makes it possible for end users to start their own content businesses. This paper presents a preliminary proposal of metrics and technologies to move toward a decentralized cooperative architecture for large-scale, real-time live stream content de- livery based on WebRTC, without the requirement of a Content Delivery Network (CDN) infrastructure. The paper takes into account the light of the aforementioned aspects [6].

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17

LE, HANH, DOAN HOANG, and ANDREW SIMMONDS. "PARM: A PHYSICALLY-AWARE REFERENCE MODEL FOR PEER-TO-PEER OVERLAY INTERNETWORKING." Journal of Interconnection Networks 07, no. 04 (December 2006): 451–74. http://dx.doi.org/10.1142/s0219265906001806.

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Peer-to-Peer (P2P) technologies developed rapidly in different directions with various applications and routing mechanisms. Each of them deals with a particular task, and/or provides a specific service. They were developed separately without a unified architecture taking into account all the performance factors of a P2P system. This makes the P2P systems incomplete and their performances far from optimal. This trend also restricts the interoperability amongst the systems because of the lack of standardization in functional architectures of the P2P systems. As a result, tangible benefits for Internet users are limited because the edge-Internet resources are not sharable amongst the systems. Inspired by TCP/IP model, this paper introduces PARM: a Physically-Aware Reference Model for Overlay Internetworking, which is an open reference structure for designing better performance P2P systems. PARM divides major functional P2P system tasks into layers so that they can be tackled individually and efficiently. A Peer Name Service was developed to evaluate the model. The service interprets peer names into their current locations. Simulation results indicate that PARM helps to produce excellent performance overlays. The overlays can achieve desirable features such as decentralization, self-organization, scalability, low overhead and minimal delay penalty.

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18

Wai Chen and Shengwei Cai. "Ad hoc peer-to-peer network architecture for vehicle safety communications." IEEE Communications Magazine 43, no. 4 (April 2005): 100–107. http://dx.doi.org/10.1109/mcom.2005.1421912.

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19

Yan, Lu, and Xinrong Zhou. "On designing peer-to-peer systems over wireless networks." International Journal of Ad Hoc and Ubiquitous Computing 3, no. 4 (2008): 245. http://dx.doi.org/10.1504/ijahuc.2008.018910.

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20

Lv, Qin, Pei Cao, Edith Cohen, Kai Li, and Scott Shenker. "Search and replication in unstructured peer-to-peer networks." ACM SIGMETRICS Performance Evaluation Review 30, no. 1 (June 2002): 258–59. http://dx.doi.org/10.1145/511399.511369.

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21

Yang, Chunlin, and Xiuqi Li. "'Dominating-set-based' searching in peer-to-peer networks." International Journal of High Performance Computing and Networking 3, no. 4 (2005): 205. http://dx.doi.org/10.1504/ijhpcn.2005.008562.

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22

Wan, Haoyi, Norihiro Ishikawa, and Johan Hjelm. "Autonomous topology optimisation for unstructured Peer-To-Peer networks." International Journal of High Performance Computing and Networking 5, no. 5/6 (2008): 288. http://dx.doi.org/10.1504/ijhpcn.2008.025541.

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23

Watanabe, Kenichi, Tomoya Enokido, and Makoto Takizawa. "Trustworthiness of acquaintances in Peer-to-Peer overlay networks." International Journal of High Performance Computing and Networking 6, no. 2 (2009): 160. http://dx.doi.org/10.1504/ijhpcn.2009.027466.

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24

Salvadori Baptista do Carmo, Gustavo, Jamil Salem Barbar, and Fernanda Barbosa Coelho. "A New Classification for Peer-to-peer Networks Architectures." IEEE Latin America Transactions 4, no. 6 (December 2006): 416–22. http://dx.doi.org/10.1109/tla.2006.4472146.

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25

SAGARA, K. "A Distributed Authentication Platform Architecture for Peer-to-Peer Applications." IEICE Transactions on Communications E88-B, no. 3 (March 1, 2005): 865–72. http://dx.doi.org/10.1093/ietcom/e88-b.3.865.

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26

Badis, Lyes, Mourad Amad, Djamil Aïssani, and Sofiane Abbar. "P2PCF: A collaborative filtering based recommender system for peer to peer social networks." Journal of High Speed Networks 27, no. 1 (March 29, 2021): 13–31. http://dx.doi.org/10.3233/jhs-210649.

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The recent privacy incidents reported in major media about global social networks raised real public concerns about centralized architectures. P2P social networks constitute an interesting paradigm to give back users control over their data and relations. While basic social network functionalities such as commenting, following, sharing, and publishing content are widely available, more advanced features related to information retrieval and recommendation are still challenging. This is due to the absence of a central server that has a complete view of the network. In this paper, we propose a new recommender system called P2PCF. We use collaborative filtering approach to recommend content in P2P social networks. P2PCF enables privacy preserving and tackles the cold start problem for both users and content. Our proposed approach assumes that the rating matrix is distributed within peers, in such a way that each peer only sees interactions made by her friends on her timeline. Recommendations are then computed locally within each peer before they are sent back to the requester. Our evaluations prove the effectiveness of our proposal compared to a centralized scheme in terms of recall and coverage.

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27

Awan, Asad, Ronaldo A. Ferreira, Suresh Jagannathan, and Ananth Grama. "Unstructured peer-to-peer networks for sharing processor cycles." Parallel Computing 32, no. 2 (February 2006): 115–35. http://dx.doi.org/10.1016/j.parco.2005.09.002.

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28

PAPADAKIS, HARRIS, PARASKEVI FRAGOPOULOU, EVANGELOS P. MARKATOS, MARIOS D. DIKAIAKOS, and ALEXANDROS LABRINIDIS. "HASH-BASED OVERLAY PARTITIONING IN UNSTRUCTURED PEER-TO-PEER SYSTEMS." Parallel Processing Letters 19, no. 01 (March 2009): 57–71. http://dx.doi.org/10.1142/s0129626409000067.

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Unstructured peer-to-peer (P2P) networks suffer from the increased volume of traffic produced by flooding. Methods such as random walks or dynamic querying managed to limit the traffic at the cost of reduced network coverage. In this paper, we propose a partitioning method of the unstructured overlay network into a relative small number of distinct subnetworks. The partitioning is driven by the categorization of keywords based on a uniform hash function. The method proposed in this paper is easy to implement and results in significant benefit for the blind flood method. Each search is restricted to a certain partition of the initial overlay network and as a result it is much more targeted. Last but not least, the search accuracy is not sacrificed to the least since all related content is searched. The benefit of the proposed method is demonstrated with extensive simulation results, which show that the overhead for the implementation and maintenance of this system is minimal compared to the resulted benefit in traffic reduction.

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29

GARCÉS-ERICE, L., E. W. BIERSACK, K. W. ROSS, P. A. FELBER, and G. URVOY-KELLER. "HIERARCHICAL PEER-TO-PEER SYSTEMS." Parallel Processing Letters 13, no. 04 (December 2003): 643–57. http://dx.doi.org/10.1142/s0129626403001574.

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Structured peer-to-peer (P2P) lookup services organize peers into a flat overlay network and offer distributed hash table (DHT) functionality. Data is associated with keys and each peer is responsible for a subset of the keys. In hierarchical DHTs, peers are organized into groups, and each group has its autonomous intra-group overlay network and lookup service. Groups are organized in a top-level overlay network. To find a peer that is responsible for a key, the top-level overlay first determines the group responsible for the key; the responsible group then uses its intra-group overlay to determine the specific peer that is responsible for the key. We provide a general framework for hierarchical DHTs with scalable overlay management. We specifically study a two-tier hierarchy that uses Chord for the top level. Our analysis shows that by using the most reliable peers in the top level, the hierarchical design significantly reduces the expected number of hops. We also present a method to construct hierarchical DHTs that map well to the Internet topology and achieve short intra-group communication delay. The results demonstrate the feasibility of locality-based peer groups, which allow P2P systems to take full advantage of the hierarchical design.

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30

Jin, Xing, and S. H. Gary Chan. "Detecting malicious nodes in peer-to-peer streaming by peer-based monitoring." ACM Transactions on Multimedia Computing, Communications, and Applications 6, no. 2 (March 2010): 1–18. http://dx.doi.org/10.1145/1671962.1671965.

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31

Liu, Lu, Nick Antonopoulos, and Stephen Mackin. "Fault-tolerant peer-to-peer search on small-world networks." Future Generation Computer Systems 23, no. 8 (November 2007): 921–31. http://dx.doi.org/10.1016/j.future.2007.03.002.

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32

Shavitt, Y., E. Weinsberg, and U. Weinsberg. "Mining Music from Large-Scale, Peer-to-Peer Networks." IEEE Multimedia 18, no. 1 (January 2011): 14–23. http://dx.doi.org/10.1109/mmul.2011.13.

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33

Chan, Yu Wei, Tsung Hsuan Ho, Po Chi Shih, and Yeh Ching Chung. "Malugo: A peer-to-peer storage system." International Journal of Ad Hoc and Ubiquitous Computing 5, no. 4 (2010): 209. http://dx.doi.org/10.1504/ijahuc.2010.032995.

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34

Mundinger, Jochen, Richard Weber, and Gideon Weiss. "Analysis of peer-to-peer file dissemination." ACM SIGMETRICS Performance Evaluation Review 34, no. 3 (December 2006): 12–14. http://dx.doi.org/10.1145/1215956.1215963.

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35

Chen, Minghua, Miroslav Ponec, Sudipta Sengupta, Jin Li, and Philip A. Chou. "Utility maximization in peer-to-peer systems." ACM SIGMETRICS Performance Evaluation Review 36, no. 1 (June 12, 2008): 169–80. http://dx.doi.org/10.1145/1384529.1375477.

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36

Wang, Hong, Hiroyuki Takizawa, and Hiroaki Kobayashi. "A dependable Peer-to-Peer computing platform." Future Generation Computer Systems 23, no. 8 (November 2007): 939–55. http://dx.doi.org/10.1016/j.future.2007.03.004.

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37

Hsu, Ching-Hsien, Hai Jin, and Franck Cappello. "Special section: Peer-to-peer grid technologies." Future Generation Computer Systems 26, no. 5 (May 2010): 701–3. http://dx.doi.org/10.1016/j.future.2010.02.005.

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38

Piotrowski, Tadeusz, Suman Banerjee, Sudeept Bhatnagar, Samrat Ganguly, and Rauf Izmailov. "Peer-to-peer streaming of stored media." ACM SIGMETRICS Performance Evaluation Review 34, no. 1 (June 26, 2006): 371–72. http://dx.doi.org/10.1145/1140103.1140325.

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39

Li, Qi, and Dong Chen. "Peer to Peer Distributed Solar Energy Trading." ACM SIGMETRICS Performance Evaluation Review 50, no. 4 (April 26, 2023): 44–46. http://dx.doi.org/10.1145/3595244.3595260.

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Solar module prices have dramatically dropped in recent years, which in turn has facilitated distributed solar energy resources (DSERs) in smart grids. To manage electricity real time supply and demand, the utilities has shown the strong interest in deploying virtual power plants(VPPs) which enable solar generated energy trading to reduce the intermittent DSERs impact in electric grid. Unfortunately, the current energy trading approaches in residential VPPs typically require a trusted third party to take on the role of the middleman, DSER users are not allowed to trade their surplus solar energy independently and simultaneously to maximize potential benefits. In addition, these approaches do not achieve "fair" for both VPPs and DSERs users. To address this issue, we build a multi-agent deep reinforcement learning based peer to peer (P2P) new solar energy trading system-SolarTrader+, which enables unsupervised, distributed, and long term fair solar energy trading in residential VPPs. We apply deep reinforcement learning with neural networks as Q-value function approximator.We implement SolarTrader+ and evaluate it using data from U.S. residential VPP communities that are comprised of - 119 residential DSERs. Our results show that SolarTrader+ can reduce the aggregated VPP energy consumption by 83.8% when compared against a non-trading approach.

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40

Wang, Chia-Wei, Hung-Chang Hsiao, Wen-Hung Sun, Chung-Ta King, and Ming-Tsung Sun. "Building a tuple space on structured peer-to-peer networks." Journal of Supercomputing 40, no. 3 (April 4, 2007): 213–27. http://dx.doi.org/10.1007/s11227-006-0026-z.

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41

Xu Xiang, and Jianguo Chen. "A Secure Routing Protocol for Peer-to-Peer Network." Journal of Convergence Information Technology 5, no. 4 (June 30, 2010): 75–83. http://dx.doi.org/10.4156/jcit.vol5.issue4.8.

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Weijia You, Lu Liu, and Chenggong Lv. "Longitudinal Network Analysis of a Peer to Peer Community." Journal of Convergence Information Technology 6, no. 3 (March 31, 2011): 202–8. http://dx.doi.org/10.4156/jcit.vol6.issue3.23.

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43

Hong Tang, Yu Yan, Rong Hu, and CongCong Xing. "Traffic Modeling and Analysis on BitTorrent-Like Peer-to-Peer Networks." Journal of Convergence Information Technology 8, no. 4 (February 28, 2013): 173–81. http://dx.doi.org/10.4156/jcit.vol8.issue4.21.

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44

Gao, Guoqiang, Ruixuan Li, Kunmei Wen, and Xiwu Gu. "Proactive replication for rare objects in unstructured peer-to-peer networks." Journal of Network and Computer Applications 35, no. 1 (January 2012): 85–96. http://dx.doi.org/10.1016/j.jnca.2011.02.007.

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45

Zhang, Jianwei, Xinchang Zhang, Meng Sun, and Chunling Yang. "Maximizing streaming efficiency of multiple streams in peer-to-peer networks." Journal of Network and Computer Applications 124 (December 2018): 108–20. http://dx.doi.org/10.1016/j.jnca.2018.09.021.

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46

Liu, Lei, Xiaobin Hong, Jian Wu, and Jintong Lin. "Experimental Investigation of a Peer-to-Peer-Based Architecture for Emerging Consumer Grid Applications." Journal of Optical Communications and Networking 1, no. 1 (June 1, 2009): 57. http://dx.doi.org/10.1364/jocn.1.000057.

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47

Leu, Jenq-Shiou, Min-Chieh Yu, and Hsiao-Chuan Yueh. "Improving Network Coding Based File Sharing for Unstructured Peer-to-Peer Networks." Journal of Network and Systems Management 23, no. 4 (July 15, 2014): 803–29. http://dx.doi.org/10.1007/s10922-014-9323-7.

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48

Lehn, Max, Christof Leng, Robert Rehner, Tonio Triebel, and Alejandro Buchmann. "An online gaming testbed for peer-to-peer architectures." ACM SIGCOMM Computer Communication Review 41, no. 4 (October 22, 2011): 474–75. http://dx.doi.org/10.1145/2043164.2018528.

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49

Shah, Babar, and Ki-Il Kim. "Towards Enhanced Searching Architecture for Unstructured Peer-to-Peer Over Mobile Ad Hoc Networks." Wireless Personal Communications 77, no. 2 (December 18, 2013): 1167–89. http://dx.doi.org/10.1007/s11277-013-1560-7.

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Jesline, K. A. Mohamed Junaid, and K. L. Shunmuganathan. "A Peer to Peer Architecture for Optimized Energy Efficient Routing in Visual Sensor Networks." Wireless Personal Communications 94, no. 4 (June 20, 2016): 2325–30. http://dx.doi.org/10.1007/s11277-016-3444-0.

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