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35
Impact of human mobility on the design of opportunistic forwarding algorithms
 In Proc. IEEE Infocom
, 2006
"... Abstract — Studying transfer opportunities between wireless devices carried by humans, we observe that the distribution of the intercontact time, that is the time gap separating two contacts of the same pair of devices, exhibits a heavy tail such as one of a power law, over a large range of value. ..."
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Cited by 193 (13 self)
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Abstract — Studying transfer opportunities between wireless devices carried by humans, we observe that the distribution of the intercontact time, that is the time gap separating two contacts of the same pair of devices, exhibits a heavy tail such as one of a power law, over a large range of value. This observation is confirmed on six distinct experimental data sets. It is at odds with the exponential decay implied by most mobility models. In this paper, we study how this new characteristic of human mobility impacts a class of previously proposed forwarding algorithms. We use a simplified model based on the renewal theory to study how the parameters of the distribution impact the delay performance of these algorithms. We make recommendation for the design of well founded opportunistic forwarding algorithms, in the context of human carried devices. I.
The message delay in mobile ad hoc networks
, 2005
"... A stochastic model is introduced that accurately models the message delay in mobile ad hoc networks where nodes relay messages and the networks are sparsely populated. The model has only two input parameters: the number of nodes and the parameter of an exponential distribution which describes the ti ..."
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Cited by 94 (5 self)
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A stochastic model is introduced that accurately models the message delay in mobile ad hoc networks where nodes relay messages and the networks are sparsely populated. The model has only two input parameters: the number of nodes and the parameter of an exponential distribution which describes the time until two random mobiles come within communication range of one another. Closedform expressions are obtained for the Laplace–Stieltjes transform of the message delay, defined as the time needed to transfer a message between a source and a destination. From this we derive both a closedform expression and an asymptotic approximation (as a function of the number of nodes) of the expected message delay. As an additional result, the probability distribution function is obtained for the number of copies of the message at the time the message is delivered. These calculations are carried out for two protocols: the twohop multicopy and the unrestricted multicopy protocols. It is shown that despite its simplicity, the model accurately predicts the message delay for both relay strategies for a number of mobility models (the random waypoint, random direction and the random walker mobility models).
Delay and Capacity Tradeoffs in Mobile Ad Hoc Networks: A Global Perspective
"... Since the original work of Grossglauser and Tse, which showed that the mobility can increase the capacity of an ad hoc network, there has been a lot of interest in characterizing the delaycapacity relationship in ad hoc networks. Various mobility models have been studied in the literature, and the ..."
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Cited by 92 (2 self)
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Since the original work of Grossglauser and Tse, which showed that the mobility can increase the capacity of an ad hoc network, there has been a lot of interest in characterizing the delaycapacity relationship in ad hoc networks. Various mobility models have been studied in the literature, and the delaycapacity relationships under those models have been characterized. The results indicate that there are tradeoffs between the delay and the capacity, and that the nature of these tradeoffs is strongly influenced by the choice of the mobility model. Some questions that arise are: (i) How representative are these mobility models studied in the lieterature? (ii) Can the delaycapacity relationship be significantly different under some other “reasonable ” mobility model? (iii) What would the delaycapacity tradeoff in a real network be like? In this paper, we address these questions. In particular, we analyze, among others, some of the mobility models that have been used in the recent related works, under a unified framework. We relate the nature of the delaycapacity tradeoff to the nature of the node motion, thereby providing a better understanding of the delaycapacity relationship in ad hoc networks than earlier works.
Pocket switched networks: Realworld mobility and its consequences for opportunistic forwarding
, 2005
"... ..."
A community based mobility model for ad hoc network research
 in Proceedings of ACM REALMAN
, 2006
"... Validation of mobile ad hoc network protocols relies almost exclusively on simulation. The value of the validation is, therefore, highly dependent on how realistic the movement models used in the simulations are. Since there is a very limited number of available real traces in the public domain, syn ..."
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Cited by 76 (7 self)
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Validation of mobile ad hoc network protocols relies almost exclusively on simulation. The value of the validation is, therefore, highly dependent on how realistic the movement models used in the simulations are. Since there is a very limited number of available real traces in the public domain, synthetic models for movement pattern generation must be used. However, most widely used models are currently very simplistic, their focus being ease of implementation rather than soundness of foundation. As a consequence, simulation results of protocols are often based on randomly generated movement patterns and, therefore, may differ considerably from those that can be obtained by deploying the system in real scenarios. Movement is strongly affected by the needs of humans to socialise or cooperate, in one form or another. Fortunately, humans are known to associate in particular ways that can be mathematically modelled and that have been studied in social sciences for years. In this paper we propose a new mobility model founded on social network theory. The model allows collections of hosts to be grouped together in a way that is based on social relationships among the individuals. This grouping is then mapped to a topographical space, with movements influenced by the strength of social ties that may also change in time. We have validated our model with real traces by showing that the synthetic mobility traces are a very good approximation of human movement patterns. We have also run simulations of AODV and DSR routing protocols on the mobility model and show how the message delivery ratio is affected by this type of mobility. 1.
Crossing Over the Bounded Domain: From Exponential to Powerlaw Intermeeting Time in MANET
, 2007
"... Intermeeting time between mobile nodes is one of the key metrics in a Mobile Adhoc Network (MANET) and central to the endtoend delay and forwarding algorithms. It is typically assumed to be exponentially distributed in many performance studies of MANET or numerically shown to be exponentially di ..."
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Cited by 46 (5 self)
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Intermeeting time between mobile nodes is one of the key metrics in a Mobile Adhoc Network (MANET) and central to the endtoend delay and forwarding algorithms. It is typically assumed to be exponentially distributed in many performance studies of MANET or numerically shown to be exponentially distributed under most existing mobility models in the literature. However, recent empirical results show otherwise: the intermeeting time distribution in fact follows a powerlaw. This outright discrepancy potentially undermines our understanding of the performance tradeoffs in MANET obtained under the exponential distribution of the intermeeting time, and thus calls for further study on the powerlaw intermeeting time including its fundamental cause, mobility modeling, and its effect. In this paper, we rigorously prove that a finite domain, on which most of the current mobility models are defined, plays an important role in creating the exponential tail of the intermeeting time. We also prove that by simply removing the boundary in a simple twodimensional isotropic random walk model, we are able to obtain the empirically observed powerlaw decay of the intermeeting time. We then discuss the relationship between the size of the boundary and the relevant timescale of the network scenario under consideration. Our results thus provide guidelines on the design of new mobility models with powerlaw intermeeting time distribution, new protocols including packet forwarding algorithms, as well as their performance analysis.
Designing Mobility Models based on Social Network Theory
 ACM SIGMOBILE Mobile Computing and Communication Review
, 2007
"... Validation of mobile ad hoc network protocols relies almost exclusively on simulation. The value of the validation is, therefore, highly dependent on how realistic the movement models used in the simulations are. Since there is a very limited number of available real traces in the public domain, syn ..."
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Cited by 35 (3 self)
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Validation of mobile ad hoc network protocols relies almost exclusively on simulation. The value of the validation is, therefore, highly dependent on how realistic the movement models used in the simulations are. Since there is a very limited number of available real traces in the public domain, synthetic models for movement pattern generation must be used. However, most widely used models are currently very simplistic, their focus being ease of implementation rather than soundness of foundation. Simulation results of protocols are often based on randomly generated movement patterns and, therefore, may differ considerably from those that can be obtained by deploying the system in real scenarios. Movement is strongly affected by the needs of humans to socialise or cooperate, in one form or another. Fortunately, humans are known to associate in particular ways that can be mathematically modelled and that have been studied in social sciences for years. In this paper we propose a new mobility model founded on social network theory. The model allows collections of hosts to be grouped together in a way that is based on social relationships among the individuals. This clustering is then mapped to a topographical space, with movements influenced by the strength of social ties that may also change in time. We have validated our model with real traces by showing that the synthetic mobility traces are a very good approximation of human movement patterns. The impact of the adoption of the proposed algorithm on the performance of AODV and DSR is also presented and discussed. I.
Delay and Capacity Tradeoffs for Wireless Ad Hoc Networks with Random Mobility
, 2005
"... In this paper, we study the delay and capacity tradeoffs for wireless ad hoc networks with random mobility. We consider some simple distributed scheduling and relaying protocols that are motivated by the 2hop relaying protocol proposed by Grossglauser and Tse (2001). We consider a model in which t ..."
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Cited by 31 (4 self)
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In this paper, we study the delay and capacity tradeoffs for wireless ad hoc networks with random mobility. We consider some simple distributed scheduling and relaying protocols that are motivated by the 2hop relaying protocol proposed by Grossglauser and Tse (2001). We consider a model in which the nodes are placed uniformly on a sphere, and move in accordance with an i.i.d. mobility model. We consider two i.i.d mobility models: Brownian mobility model and random waypoint mobility model. We show that under a distributed GrossglauserTse 2hop relaying protocol, the delay scales as &Theta;(T_p(n)n) for random waypoint mobility model, and O(T_p(n)log&sup2;n) for Brownian mobility model, where T_p(n) is the transmission time of the packet. In the case, where only nearest neighbor transmissions are allowed, the delay is shown to scale as &Omega(T_p(n)&radic;n), for all possible scheduling and relaying protocols. In the case of random waypoint mobility model, we show that delay/capacity &ge; &Theta;(T_p(n)n) is a necessary tradeoff. Two protocols which achieve the lower bound of &Theta;(T_p(n)n) are considered, and their relative performance in terms of delay/capacity tradeoff is established. Our results indicate that significant improvement in the delay can be achieved by reducing the packet size, at high node speeds.
Ooi, “Analysis and implications of student contact patterns derived from campus schedules
 in MobiCom ’06: Proceedings of the 12th annual international conference on Mobile computing and networking
, 2006
"... Characterizing mobility or contact patterns in a campus environment is of interest for a variety of reasons. Existing studies of these patterns can be classified into two basic approaches – model based and measurement based. The model based approach involves constructing a mathematical model to gene ..."
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Cited by 30 (1 self)
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Characterizing mobility or contact patterns in a campus environment is of interest for a variety of reasons. Existing studies of these patterns can be classified into two basic approaches – model based and measurement based. The model based approach involves constructing a mathematical model to generate movement patterns while the measurement based approach measures locations and proximity of wireless devices to infer mobility patterns. In this paper, we take a completely different approach. First we obtain the class schedules and class rosters from a universitywide Intranet learning portal, and use this information to infer contacts made between students. The value of our approach is in the population size involved in the study, where contact patterns among 22341 students are analyzed. This paper presents the characteristics of these contact patterns, and explores how these patterns affect three scenarios. We first look at the characteristics from the DTN perspective, where we study intercontact time and time distance between pairs of students. Next, we present how these characteristics impact the spread of mobile computer viruses, and show that viruses can spread to virtually the entire student population within a day. Finally, we consider aggregation of information from a large number of mobile, distributed sources, and demonstrate that the contact patterns can be exploited to design efficient aggregation algorithms, in which only a small number of nodes (less than 0.5%) is needed to aggregate a large fraction (over 90%) of the data.
On Achievable Delay/Capacity Tradeoffs in Mobile Ad Hoc Networks
 in Workshop on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (Wi’Opt
, 2004
"... Recent work of Gupta and Kumar (2000) has shown that in a multihop wireless network the throughput capacity per sourcedestination pair goes to zero as the node density increases. While it has been shown that a constant throughput scaling per sourcedestination pair can be achieved in mobile ad hoc ..."
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Cited by 28 (1 self)
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Recent work of Gupta and Kumar (2000) has shown that in a multihop wireless network the throughput capacity per sourcedestination pair goes to zero as the node density increases. While it has been shown that a constant throughput scaling per sourcedestination pair can be achieved in mobile ad hoc networks, the delay related aspects have not been considered in detail. In this paper, we study the delaycapacity tradeoff in mobile ad hoc networks. We consider two canonical random mobility models in this paper; the Brownian mobility model (BMM) and the random waypoint mobility model (RWMM). We show that under the distributed 2hop relaying protocol proposed by Grossglauser and Tse (2001), the packet delay scales as &Theta;(T_p(n)n) under the RWMM and O(T_p(n)n log&sup2;(n)) under the BMM, where T_p(n) is the packet transmission time. We then show that the delay scales as &Omega;(T_p(n)&radic;n), under a broad class of scheduling and relaying protocols. Further, we show that the tradeoff: delay/capacity &ge; &Theta;(T_p(n)n), is necessary as well as sufficient under our settings. We then propose two distributed protocols which achieve the above mentioned lower bound on the packet delay, and evaluate their performance in terms of the delaycapacity tradeoff.