Modelling mobility: A discrete revolution

Clementi, Andrea E. F.; Monti, Angelo; Silvestri, Riccardo

doi:10.1016/j.adhoc.2010.09.002

Cited by 11 publications

(19 citation statements)

References 15 publications

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“…The stationary (agent) spatial distribution gives the probability that an agent lies in a position (x, y) and it has been derived in [12]. The stationary (agent) destination distribution gives the probability that an agent, conditioned to lie in position (x0, y0), is traveling toward destination (x, y) and it has been determined in [10]. Theorem 1.…”

Section: The Mrwp Modelmentioning

confidence: 99%

“…Explicit formulas for the stationary spatial and destination probability distributions have been derived in [12,10]. The stationary distributions of some other versions of the RWP have been obtained in [4,6,19,21].…”

Section: Introductionmentioning

confidence: 99%

“…This version of the RWP is motivated by scenarios where agents travel over an urban zone and try to minimize the number of turns while keeping the chosen route as short as possible [12,10,20].…”

Section: Introductionmentioning

confidence: 99%

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Fast flooding over Manhattan

Clementi

Monti

Silvestri

2010

Proceedings of the 29th ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing

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We consider a Mobile Ad-hoc NETwork (MANET) formed by n agents that move at speed v according to the Manhattan Random-Way Point model over a square region of side length L. The resulting stationary (agent) spatial probability distribution is far to be uniform: the average density over the "central zone" is asymptotically higher than that over the "suburb". Agents exchange data iff they are at distance at most R within each other.We study the flooding time of this MANET: the number of time steps required to broadcast a message from one source agent to all agents of the network in the stationary phase. We prove the first asymptotical upper bound on the flooding time. This bound holds with high probability, it is a decreasing function of R and v, and it is tight for a wide and relevant range of the network parameters (i.e. L, R and v).A consequence of our result is that flooding over the sparse and highly-disconnected suburb can be as fast as flooding over the dense and connected central zone. Rather surprisingly, this property holds even when R is exponentially below the connectivity threshold of the MANET and the speed v is very low.

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Section: The Mrwp Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fast flooding over Manhattan

Clementi

Monti

Silvestri

2010

Proceedings of the 29th ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Torkestani (2012) [130] present a mobility prediction model based on Gauss-Markov and used learning automata for a boundless simulation area with no obstacles. Clementi et al (2011) [131] develop a Markov trace model to analyze mobility in complex mobility systems (e.g., vehicular-mobile systems) using discrete mathematics. A limited attempt is made to relate Markov models to real-world situations.…”

Section: The Gauss-markov Modelmentioning

confidence: 99%

Building Realistic Mobility Models for Mobile Ad Hoc Networks

Pullin¹,

Pattinson²,

Kor³

2018

Informatics

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A mobile ad hoc network (MANET) is a self-configuring wireless network in which each node could act as a router, as well as a data source or sink. Its application areas include battlefields and vehicular and disaster areas. Many techniques applied to infrastructure-based networks are less effective in MANETs, with routing being a particular challenge. This paper presents a rigorous study into simulation techniques for evaluating routing solutions for MANETs with the aim of producing more realistic simulation models and thereby, more accurate protocol evaluations. MANET simulations require models that reflect the world in which the MANET is to operate. Much of the published research uses movement models, such as the random waypoint (RWP) model, with arbitrary world sizes and node counts. This paper presents a technique for developing more realistic simulation models to test and evaluate MANET protocols. The technique is animation, which is applied to a realistic scenario to produce a model that accurately reflects the size and shape of the world, node count, movement patterns, and time period over which the MANET may operate. The animation technique has been used to develop a battlefield model based on established military tactics. Trace data has been used to build a model of maritime movements in the Irish Sea. Similar world models have been built using the random waypoint movement model for comparison. All models have been built using the ns-2 simulator. These models have been used to compare the performance of three routing protocols: dynamic source routing (DSR), destination-sequenced distance-vector routing (DSDV), and ad hoc n-demand distance vector routing (AODV). The findings reveal that protocol performance is dependent on the model used. In particular, it is shown that RWP models do not reflect the performance of these protocols under realistic circumstances, and protocol selection is subject to the scenario to which it is applied. To conclude, it is possible to develop a range of techniques for modelling scenarios applicable to MANETs, and these simulation models could be utilised for the evaluation of routing protocols.

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“…Helpful guidelines for traffic engineers about the study and application of counting distributions are also contained in Gerlough and Huber (1975) and in May (1990). After a few decades theoretical research has restarted and some works in the field have been produced by Jabari and Liu (2012), Clementi, Monti and Silvestri (2011) and Cao, Tai and Chan (2012) who have analysed some statistical models for counting distributions.…”

Section: Introductionmentioning

confidence: 99%

Update on the Statistical Analysis of Traffic Countings on Two-Lane Rural Highways

Mauro¹,

Branco²

2013

MAS

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This paper deals with the problem of model identification, calibration and validation for traffic countings on two-lane rural highways. A criterion for preliminary selection of arrival laws as a function of appropriate sample statistics and a technique for deciding whether sample data sets of traffic counting are congruent with stationary time series behavior are suggested; besides arrival laws currently used in research and engineering practice, the Neyman distribution has been also applied although it is not frequently implemented in the field of traffic engineering. Moreover, this work aims at applying these methods to a set of empirical data derived from a recent survey on two two-lane rural highways; the arrival laws that best agree with the observations are found and the relations between the parameters identifying the arrival laws and the flow rates are worked out. Finally, the results have been compared to those achieved in similar observations, carried out by one of the authors in the past.

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Modelling mobility: A discrete revolution

Cited by 11 publications

References 15 publications

Fast flooding over Manhattan

Fast flooding over Manhattan

Building Realistic Mobility Models for Mobile Ad Hoc Networks

Update on the Statistical Analysis of Traffic Countings on Two-Lane Rural Highways

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