Results 1  10
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146
Performance Modeling of Epidemic Routing
 In Proceedings of IFIP Networking
, 2006
"... Abstract. In this paper, we develop a rigorous, unified framework based on Ordinary Differential Equations (ODEs) to study epidemic routing and its variations. These ODEs can be derived as limits of Markovian models under a natural scaling as the number of nodes increases. While an analytical study ..."
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Cited by 193 (11 self)
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Abstract. In this paper, we develop a rigorous, unified framework based on Ordinary Differential Equations (ODEs) to study epidemic routing and its variations. These ODEs can be derived as limits of Markovian models under a natural scaling as the number of nodes increases. While an analytical study of Markovian models is quite complex and numerical solution impractical for large networks, the corresponding ODE models yield closedform expressions for several performance metrics of interest, and a numerical solution complexity that does not increase with the number of nodes. Using this ODE approach, we investigate how resources such as buffer space and power can be traded for faster delivery, illustrating the differences among the various epidemic schemes considered. Finally we consider the effect of buffer management by complementing the forwarding models with Markovian and fluid buffer models.
On the Broadcast capacity in multihop wireless networks: Interplay of power, . . .
, 2007
"... In this paper we study the broadcast capacity of multihop wireless networks which we define as the maximum rate at which broadcast packets can be generated in the network such that all nodes receive the packets successfully within a given time. To asses the impact of topology and interference on t ..."
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Cited by 103 (5 self)
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In this paper we study the broadcast capacity of multihop wireless networks which we define as the maximum rate at which broadcast packets can be generated in the network such that all nodes receive the packets successfully within a given time. To asses the impact of topology and interference on the broadcast capacity we employ the Physical Model and Generalized Physical Model for the channel. Prior work was limited either by density constraints or by using the less realistic but manageable Protocol model [1], [2]. Under the Physical Model, we find that the broadcast capacity is within a constant factor of the channel capacity for a wide class of network topologies. Under the Generalized Physical Model, on the other hand, the network configuration is divided into three regimes depending on how the power is tuned in relation to network density and size and in which the broadcast capacity is asymptotically either zero, constant or unbounded. As we show, the broadcast capacity is limited by distant nodes in the first regime and by interference in the second regime. In the second regime, which covers a wide class of networks, the broadcast capacity is within a constant factor of the bandwidth.
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 77 (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.
Degenerate DelayCapacity Tradeoffs in AdHoc Networks with Brownian Mobility
 IEEE/ACM Trans. Netw
, 2006
"... Abstract — There has been significant recent interest within the networking research community to characterize the impact of mobility on the capacity and delay in mobile ad hoc networks. In this paper, we study the fundamental tradeoff between the capacity and delay for a mobile ad hoc network unde ..."
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Cited by 64 (2 self)
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Abstract — There has been significant recent interest within the networking research community to characterize the impact of mobility on the capacity and delay in mobile ad hoc networks. In this paper, we study the fundamental tradeoff between the capacity and delay for a mobile ad hoc network under the Brownian motion model. We show that the 2hop relaying scheme proposed by Grossglauser and Tse (2001), while capable of achieving Θ(1) pernode capacity, incurs an expected packet delay of Ω(log n/σ 2 n), where σ 2 n is the variance parameter of the Brownian motion model. We then show that in order to reduce the delay by any significant amount, one must be ready to accept a pernode capacity close to static ad hoc networks. In particular, we show that under a large class of scheduling and relaying schemes, if the mean packet delay is O(n α /σ 2 n), for any α < 0, then the pernode capacity must be O(1 / √ n). This result is in sharp contrast to other results that have recently been reported in the literature. I.
The multicast capacity of large multihop wireless networks
 In Proc. of ACM MobiHoc ’07
, 2007
"... We consider wireless ad hoc networks with a large number of users. Subsets of users might be interested in identical information, and so we have a regime in which several multicast sessions may coexist. We first calculate an upperbound on the achievable transmission rate per multicast flow as a fun ..."
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Cited by 49 (2 self)
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We consider wireless ad hoc networks with a large number of users. Subsets of users might be interested in identical information, and so we have a regime in which several multicast sessions may coexist. We first calculate an upperbound on the achievable transmission rate per multicast flow as a function of the number of multicast sources in such a network. We then propose a simple combbased architecture for multicast routing which achieves the upper bound in an order sense under certain constraints. Compared to the approach of constructing a Steiner tree to decide multicast paths, our construction achieves the same orderoptimal results while requiring little location information and no computational overhead.
Scaling Laws for Overlaid Wireless Networks: A Cognitive Radio Network vs. a Primary Network
, 2008
"... We study the scaling laws for the throughputs and delays of two coexisting wireless networks that operate in the same geographic region. The primary network consists of Poisson distributed legacy users of density n, and the secondary network consists of Poisson distributed cognitive users of densit ..."
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Cited by 41 (7 self)
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We study the scaling laws for the throughputs and delays of two coexisting wireless networks that operate in the same geographic region. The primary network consists of Poisson distributed legacy users of density n, and the secondary network consists of Poisson distributed cognitive users of density m, with m> n. The primary users have a higher priority to access the spectrum without particular considerations for the secondary users, while the secondary users have to act conservatively in order to limit the interference to the primary users. With a practical assumption that the secondary users only know the locations of the primary transmitters (not the primary receivers), we first show that both networks can achieve the same throughput scaling law as what Gupta and Kumar [1] established for a standalone wireless network if proper transmission schemes are deployed, where a certain throughput is achievable for each individual secondary user (i.e., zero outage) with high probability. By using a fluid model, we also show that both networks can achieve the same delaythroughput tradeoff as the optimal one established by El Gamal et al. [2] for a standalone wireless network. Index Terms — Ad hoc networks, overlaid wireless networks, throughput, delay, cognitive radio networks.
Bounds for the capacity of wireless multihop networks imposed by topology and demand
 in Proc. ACM MobiHoc
, 2007
"... Existing work on the capacity of wireless networks predominantly considers homogeneous random networks with random work load. The most relevant bounds on the network capacity, e.g., take into account only the number of nodes and the area of the network. However, these bounds can significantly overes ..."
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Cited by 35 (0 self)
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Existing work on the capacity of wireless networks predominantly considers homogeneous random networks with random work load. The most relevant bounds on the network capacity, e.g., take into account only the number of nodes and the area of the network. However, these bounds can significantly overestimate the achievable capacity in real world situations where network topology or traffic patterns often deviate from these simplistic assumptions. To provide analytically tractable yet asymptotically tight approximations of network capacity we propose a novel spacebased approach. At the heart of our methodology lie simple functions which indicate the presence of active transmissions near any given location in the network and which constitute a tool well suited to untangle the interactions of simultaneous transmissions. We are able to provide capacity bounds which are tighter than the traditional ones and which involve topology and traffic patterns explicitly, e.g., through the length of Euclidean Minimum Spanning Tree, or through traffic demands between clusters of nodes. As an additional novelty our results cover unicast, multicast and broadcast and are asymptotically tight. Notably, our capacity bounds are simple enough to require only knowledge of node location, and there is no need for solving or optimizing multivariable equations in our approach.
Multicast Capacity of Large Homogeneous Multihop Wireless Networks
"... Abstract—Most existing work on multicast capacity of large homogeneous networks is based on a simple model for wireless channel, namely the Protocol Model [12], [19], [22]. In this paper, we exploit a local capacity tool called arena which we introduced recently in order to render multicast accessib ..."
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Cited by 29 (0 self)
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Abstract—Most existing work on multicast capacity of large homogeneous networks is based on a simple model for wireless channel, namely the Protocol Model [12], [19], [22]. In this paper, we exploit a local capacity tool called arena which we introduced recently in order to render multicast accessible to analysis also under more realistic, and notably less pessimistic channel models. Through the present study we find three regimes of the multicast capacity (λm) for a homogeneous network depending on the ratio of terminals among the nodes of the network. We note that the upper bounds we establish under the more realistic channel assumptions are only � log(n) larger than the existing bounds. Further, we propose a multicast routing and time scheduling scheme to achieve the computed asymptotic bound over all channel models except the simple Protocol Model. To this end, we employ percolation theory among other analytical tools. Finally, we compute the multicast capacity of large mobile wireless networks. Comparing the result to the static case reveals that mobility increases the multicast capacity. However, the mobility gain decreases when increasing the number of terminals in a fixed size mobile network. I.
Toward stochastic anatomy of inter–meeting time distribution under general mobility models,” in ACM
 North Carolina State University
, 2008
"... Recent discovery of the mixture (powerlaw and exponential) behavior of intermeeting time distribution of mobile nodes presents new challenge to the problem of mobility modeling and its effect on the network performance. Existing studies on this problem via the average intermeeting time become i ..."
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Cited by 22 (3 self)
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Recent discovery of the mixture (powerlaw and exponential) behavior of intermeeting time distribution of mobile nodes presents new challenge to the problem of mobility modeling and its effect on the network performance. Existing studies on this problem via the average intermeeting time become insufficient when the intermeeting time distribution starts to deviate from exponential one. This insufficiency necessarily leads to the increasing difficulty in the performance analysis of forwarding algorithms in mobile adhoc networks (MANET). In this paper, we analyze the effect of mobility patterns on the intermeeting time distribution. We first identify the critical timescale in the intermeeting distribution, at which the transition from powerlaw to exponential takes place, in terms of the domain size and the statistics of the mobility pattern. We then prove that stronger correlations in mobility patterns lead to heavier (nonexponential) ‘head ’ of the intermeeting time distribution. We also prove that there exists an invariance property for several contactbased metrics such as intermeeting, contact, interanycontact time under both distancebased (Boolean) and physical interference (SINR) based models, in that the averages of those contactbased metrics do not depend on the degree of correlations in the mobility patterns. Our results collectively suggest a convex ordering relationship among intermeeting times of various mobility models indexed by their degrees of correlation, which is in good agreement with the ordering of network performance under a set of mobility patterns whose intermeeting time distributions have powerlaw ‘head ’ followed by exponential ‘tail’.
Distributed Storage Management of Evolving Files in Delay Tolerant Ad Hoc Networks
"... Abstract — This work focuses on a class of distributed storage systems whose content may evolve over time. Each component or node of the storage system is mobile and the set of all nodes forms a delay tolerant (ad hoc) network (DTN). The goal of the paper is to study efficient ways for distributing ..."
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Cited by 20 (0 self)
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Abstract — This work focuses on a class of distributed storage systems whose content may evolve over time. Each component or node of the storage system is mobile and the set of all nodes forms a delay tolerant (ad hoc) network (DTN). The goal of the paper is to study efficient ways for distributing evolving files within DTNs and for managing dynamically their content. We specify to dynamic files where not only the latest version is useful but also previous ones; we restrict however to files where a file has no use if another more recent version is available. The DTN is composed of fixed number of nodes including a single source. At some points in time the source makes available a new version of a single file F. We consider both the cases when (a) nodes do not cooperate and (b) nodes cooperate. In case (a) only the source may transmit a copy of F to a node that it meets, while in case (b) any node may transmit a copy of F to a node that