Properties of random direction models

Nain, Philippe; Towsley, Don; Liu, Benyuan; Liu, Zhen

doi:10.1109/infcom.2005.1498468

Cited by 275 publications

(193 citation statements)

References 8 publications

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“…The stationary distributions of the location and direction have been shown to be uniform [11] for arbitrary direction, speed and travel time distributions, irrespective of the boundaries being reflecting or wrap around. This is in contrast with the random waypoint mobility model where nodes are more likely to be concentrated near the center of the area.…”

Section: Random Direction Mobility Modelmentioning

confidence: 99%

The message delay in mobile ad hoc networks

Groenevelt

Nain

Koole

2005

Performance Evaluation

551

554

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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. Closed-form 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 closed-form 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 two-hop 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).

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Section: Random Direction Mobility Modelmentioning

confidence: 99%

The message delay in mobile ad hoc networks

Groenevelt

Nain

Koole

2005

Performance Evaluation

551

554

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“…It moves to the chosen destination with the chosen speed, and then waits there for a fixed pause time, before choosing a new destination and speed. RWP has very different statistical properties compared to the earlier used random direction model [42], [43]. E.g., it lets robots make longer straight movements (since robots can choose any location in the area to move to), it leads to a nonuniform stationary distribution of robots over the area, etc.…”

Section: Tests With Different Movement Patternsmentioning

confidence: 99%

Cooperative navigation in robotic swarms

Ducatelle

Förster

et al. 2013

Swarm Intell

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Abstract-We present a cooperative navigation algorithm for robotic swarms. Its purpose is to let a robot find a given target robot, while being guided by the other robots of the swarm. The system is based on wireless communication: the robots forward messages containing navigation information over the ad hoc network among them, and the searching robot uses this information to find its target. We study the algorithm in two different scenarios. In the first scenario, a single searching robot needs to find a single target, while all other robots are involved in tasks of their own. We show that the communication based navigation system allows the robots of the swarm to guide the searching robot without the need to adapt their own movements. In the second scenario, we study collective navigation: all robots of the swarm need to navigate back and forth between two targets. We show that in this case, the proposed navigation algorithm gives rise to synergies in robot navigation, and lets the swarm self-organize into a robust dynamic structure. This selforganization improves navigation efficiency, and lets the swarm find shortest paths in cluttered environments. We test our system both in simulation and on real robots.

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“…The stationary probability density function under the Random Direction mobility model is uniform [15], i.e.,…”

Section: A One Dimensionmentioning

confidence: 99%

“…A detailed analysis involving second-order moments of contact times between mobile nodes is necessary to obtain a full picture. We perform such an analysis for the Random Direction model [15] inside a square in addition to the random walk model over a circle derived in [2]. 4) We then show numerically that the average relay buffer size at cycle times derived in [2, Sec.…”

Section: Introductionmentioning

confidence: 99%

Impact of mobility on the performance of relaying in ad hoc networks – Extended version

Hanbali

Kherani

Groenevelt³

et al. 2007

Computer Networks

Self Cite

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Abstract-We consider a mobile ad hoc network consisting of three types of nodes: source, destination, and relay nodes. All the nodes are moving over a bounded region with possibly different mobility patterns. We introduce and study the notion of relay throughput, i.e. the maximum rate at which a node can relay data from the source to the destination. Our findings include the results that a) the relay throughput depends on the node mobility pattern only via its (stationary) node position distribution, and b) that a node mobility pattern that results in a uniform steady-state distribution for all nodes achieves the lowest relay throughput. Random Waypoint and Random Direction mobility models in both one and in two dimensions are studied and approximate simple expressions for the relay throughput are provided. Finally, the behavior of the relay buffer occupancy is examined for the Random Walk and Random Direction mobility models. For both models, the explicit form of the mean buffer are provided in the heavy-traffic case.

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Properties of random direction models

Cited by 275 publications

References 8 publications

The message delay in mobile ad hoc networks

The message delay in mobile ad hoc networks

Cooperative navigation in robotic swarms

Impact of mobility on the performance of relaying in ad hoc networks – Extended version

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