P2P networks are the mechanism used by cryptocurrencies to disseminate system information while keeping the whole system as much decentralized as possible. Cryptocurrency P2P networks have new characteristics that propose new challenges and avoid some problems of existing P2P networks. By characterizing the most relevant cryptocurrency network, Bitcoin, we provide details on different properties of cryptocurrency networks and their similarities and differences with standard P2P network paradigms. Our study allows us to conclude that cryptocurrency networks present a new paradigm of P2P networks due to the mechanisms they use to achieve high resilience and security. With this new paradigm, interesting research lines can be further developed, both in the focused field of P2P cryptocurrency networks and also when such networks are combined with other distributed scenarios.
In this paper, we present a broadcast dissemination protocol for messages in opportunistic networks (OppNet) that is efficient in terms of energy consumption and network capacity usage, while not increasing the number of excluded nodes (nodes not receiving messages). The majority of the OppNet broadcast delivery schemes proposed in the literature, do not take into consideration that reducing energy and buffer usage is of paramount importance in these wireless networks normally consisting of small devices. In our protocol, broadcast messages are limited by carefully selecting their prospective forwarders (storers). The keystone of our protocol is the use of Optimal Stopping Theory, which selects the best message storers at every stage of the algorithm, while holding back broad message dissemination until convenient conditions are met. The broadcast efficiency of the proposed protocol out competes other OppNet broadcast proposals in four well-known scenarios. Furthermore, the protocol reduces the number of both dropped messages and nodes not receiving messages, thus maximising network capacity usage, and the span of the message delivery.
In this paper we analyze a large scale delay tolerant network (DTN) of transoceanic aircraft. We assume that each airplane in our network is equipped with a simple communication system based on IEEE802.11b/g, with a communication link of around 20 km. The characterization of this large aeronautical DTN will be used to choose routing strategies for passenger or company data, only through the contacts between airplanes, in order to use this network as a cheaper alternative to other communications systems, or as backup when no other communication systems are available. Instead of relying on synthetic data, we carry our analysis from the actual traces of 2,550 trans-Atlantic flights in the ns-3 simulator, to provide a detailed study of the network connectivity and mobility metrics (node degree, clustering, any contact time and inter any contact time). The impact of other parameters (such as radio coverage) on the network is also analyzed.
In this paper we analyze information propagation inside a large scale delay tolerant network (DTN) of transoceanic aircraft. We characterized this network at LeN 2013, a scenario constructed from more than 2,500 traces of trans-Atlantic flights in which communications rely on the sporadic contacts between airplanes. We observe the traffic of this network and analyze how two epidemic based routing protocols behave in this scenario. We use simulations to compare their performance through metrics such as the network traffic per packet, end-to-end-delay and delivery ratio. The analysis of data propagation inside this DTN aims to evaluate the feasibility of using this network as a reliable way to deliver on-flight generated data (either from passengers or company) to the ground. This approach seeks to provide applications with a cheaper alternative to other communication systems. I. INT RODUCTIONData communication in aeronautical scenarios is very lim ited [12]. Airplanes periodically send to ground stations their identification, position, and company related data Gust a few tens of bytes per second). Any other control information is sent over traditional voice-based radio links. These limitations in data communication become more evident when looking for the causes of aerial accidents, as in the case of the ill-fated MH370's disappearance [16].Regarding passenger data communication, some companies have deployed, for domestic flights, solutions based on ex ternal antennae directed to ground [2]. As to transoceanic flights, very few companies choose to use expensive satellite links [6] while, in most of the cases, passengers must remain disconnected for hours. On the other hand, most of the research papers on aeronautic transoceanic communications propose the use of communication systems with large coverage (from 300 to 600 km) and thus consider airplanes connected to form an Aeronautical Ad-hoc Network (AANET) [13], [15], [12].Looking for a cheaper solution than those based on radio links with high coverage or satellite links, we proposed in LCN 2013 [14] a new approach based on aircraft equipped with IEEES02.11 bIg conununication links of only 20 km. This limited range leaded to a network with a reduced node degree, fully in range with the characteristics of Delay Tolerant Networks (DTNs) [7], [3]. To build our proposal, instead of using synthetic data, we departed from traces of 2,550 transAtlantic flights to reach a characterization of a large-scale real-world aeronautical DTN. We analyzed the distributions of active nodes, node degree, number of clusters, any contact time (ACT), and inter-any-contact time (IACT) of that network.The objective of this paper is to analyze how data propagates inside our proposed transoceanic aircraft delay tolerant net work, in order to evaluate the feasibility of using this network as a reliable way to deliver on-flight generated data (either from passengers or company) to the ground.Our contributions are as follows:• We provide an evaluation of two different routing proto cols for t...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.