Multicasting in delay tolerant networks

Gao, Wei; Li, Qinghua; Zhao, Bo; Cao, Guohong

doi:10.1145/1530748.1530790

Cited by 490 publications

(300 citation statements)

References 20 publications

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“…Using Markov Chain based models, such as the ones presented in this paper, the results are obtained in a faster way. Recent works has shown that the occurrence of contacts between two mobile nodes follows a Poisson distribution λ [3,4,9,18]. This has been shown valid for both human and vehicles mobility patterns.…”

mentioning

confidence: 85%

“…This assumption has been shown to hold in several mobility scenarios of both human and vehicles [3,4,18]. For example, in [4] it is shown that for random waypoint and random direction mobility models the parameter λ is related to the mean speed of nodes v, through the following empirical expression λ ≈ 8wrv πl 2 , r l, where r is the communication range and l is the side of the square network area.…”

Section: System Modelmentioning

confidence: 99%

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A Fast Model for Evaluating the Detection of Selfish Nodes Using a Collaborative Approach in MANETs

Hernández-Orallo

Olmos

Cano

et al. 2013

Wireless Pers Commun

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Mobile ad-hoc networks (MANETs) rely on network cooperation schemes to work properly. Nevertheless, if nodes have a selfish behaviour and are unwilling to cooperate, the overall network performance could be seriously affected. The use of watchdogs is a well-known mechanism to detect selfish nodes.In this paper we propose a collaborative watchdog approach, which is based on the fast diffusion of selfish nodes awareness. Then, we introduce an analytical model to evaluate the time of detection and the overhead (number of messages) of our collaborative watchdog approach for detecting one selfish node. This model is extended for the case of several selfish nodes, including a mean-max approximation for a feasible computation when the number of selfish nodes is high. The results show that a collaborative watchdog is a very efficient approach since the detection time of selfish nodes is reduced, and the overall overhead is very low.

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mentioning

confidence: 85%

Section: System Modelmentioning

confidence: 99%

A Fast Model for Evaluating the Detection of Selfish Nodes Using a Collaborative Approach in MANETs

Hernández-Orallo

Olmos

Cano

et al. 2013

Wireless Pers Commun

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“…More specifically, we solve two cases by providing the conditions on the Bernoulli arrival processes of users to locations such that the resulting aggregate inter-contact time distribution is either heavy-tailed or exponential. The two cases are important as they have often emerged from the analysis of real mobility traces [5] [7]. Our derivation shows how these different aggregate behaviors can result from simple heterogenous Bernoulli arrival processes, which are very convenient to deal with for mathematical analysis.…”

Section: Aggregate Contact Processmentioning

confidence: 95%

“…Less clear is how inter-contact times are characterised. Many hypotheses have been made (about them featuring an exponential distribution [7], a Pareto distribution [5], a Pareto with exponential cut-off distribution [8], a LogNormal distribution [6], etc. ), but the problem has yet to be solved.…”

Section: Introductionmentioning

confidence: 99%

SPoT: Representing the social, spatial, and temporal dimensions of human mobility with a unifying framework

Karamshuk

Boldrini

Conti

et al. 2014

Pervasive and Mobile Computing

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Modeling human mobility is crucial in the analysis and simulation of opportunistic networks, where contacts are exploited as opportunities for peer-topeer message forwarding. The current approach with human mobility modeling has been based on continuously modifying models, trying to embed in them the mobility properties (e.g., visiting patterns to locations or specific distributions of inter-contact times) as they came up from trace analysis. As a consequence, with these models it is difficult, if not impossible, to modify the features of mobility or to control the exact shape of mobility metrics (e.g., modifying the distribution of inter-contact times). For these reasons, in this paper we propose a mobility framework rather than a mobility model, with the explicit goal of providing a flexible and controllable tool for modeling mathematically and generating simulatively different possible features of human mobility.Our framework, named SPoT, is able to incorporate the three dimensions -spatial, social, and temporal -of human mobility. The way SPoT does it is by mapping the different social communities of the network into different locations, whose members visit with a configurable temporal pattern. In order to characterize the temporal patterns of user visits to locations and the relative positioning of locations based on their shared users, we analyze the traces of real user movements extracted from three location-based online social networks (Gowalla, Foursquare, and Altergeo). We observe that a Bernoulli process effectively approximates user visits to locations in the majority of cases and that locations that share many common users visiting them frequently tend to be located close to each other. In addition, we use these traces to test the flexibility of the framework, and we show that SPoT Preprint submitted to Elsevier July 16, 2013 is able to accurately reproduce the mobility behavior observed in traces. Finally, relying on the Bernoulli assumption for arrival processes, we provide a throughout mathematical analysis of the controllability of the framework, deriving the conditions under which heavy-tailed and exponentially-tailed aggregate inter-contact times (often observed in real traces) emerge.

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“…We first implemented the evaluation system using Cambridge trace [9], [13], which was gathered by two groups of undergraduate students from University of Cambridge. We used the method of [14] to compute the individual contact rates of node pairs by averaging the statistics from the trace. We then averaged the contact rates of users in the same community as well as across communities to implement simulations.…”

Section: A Evaluation System Setupmentioning

confidence: 99%

Impact of Selfishness in Device-to-Device Communication Underlying Cellular Networks

Gao

Zhang

Chen

et al. 2017

IEEE Trans. Veh. Technol.

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Abstract-In a device-to-device (D2D) communication underlaying cellular network, user equipment are required to operate cooperatively and unselfishly to transmit data as relays. However, most users more or less behave in a selfish way, which makes user selfishness a key factor that affects the performance of the whole communication system. We focus on the impact of user selfishness on D2D communications. By separating the user selfishness into two types in accordance with two D2D transmission modes, which are connected D2D transmission and opportunistic D2D transmission, we propose a time-varying graph model that characterizes the impacts of both individual and social selfishness on the D2D communications. Simulation results obtained under the realistic networking settings indicate that the interaction between connected and opportunistic selfishness worsens the impairment caused by individual selfishness. Additionally, when concerning social selfishness, inside-community selfishness can be ignored in some occasions, while otherwise its role is heavily influenced by community numbers.

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Multicasting in delay tolerant networks

Cited by 490 publications

References 20 publications

A Fast Model for Evaluating the Detection of Selfish Nodes Using a Collaborative Approach in MANETs

A Fast Model for Evaluating the Detection of Selfish Nodes Using a Collaborative Approach in MANETs

SPoT: Representing the social, spatial, and temporal dimensions of human mobility with a unifying framework

Impact of Selfishness in Device-to-Device Communication Underlying Cellular Networks

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