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A smooth-turn mobility model for airborne networks
- in Proc. 1st ACM MobiHoc Workshop Airborne Netw. Commun
, 2012
"... Abstract—The design of effective routing protocols in airborne networks (ANs) relies on suitable mobility models that capture the movement patterns of airborne vehicles. As airborne vehicles can-not make sharp turns as easily as ground vehicles do, the widely used ground-based mobile ad hoc network ..."
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Cited by 7 (4 self)
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Abstract—The design of effective routing protocols in airborne networks (ANs) relies on suitable mobility models that capture the movement patterns of airborne vehicles. As airborne vehicles can-not make sharp turns as easily as ground vehicles do, the widely used ground-based mobile ad hoc network (MANET) mobility models are not appropriate to use as the analytical frameworks for airborne networking. In this paper, we introduce a novel mobility model, which is called the smooth-turn (ST) mobility model, that captures the correlation of acceleration of airborne vehicles across temporal and spatial coordinates. The proposed model is realistic in capturing the tendency of airborne vehicles toward making straight trajectories and STs with large radii, yet is tractable enough for analysis and design. We first describe the mathematics of this model and then prove that the stationary node distribution is uniform. Furthermore, we introduce a metric to quantify the degree of model randomness, and using this, we compare and classify several mobility models in the literature. We conclude this paper with several possible variations to the basic ST mobility model. Index Terms—Airborne networks, mobility models, randomness. I.
Online, Adaptive, and Distributed Multi-Robot Motion Planning for Collaborative Patrolling of Sparse Sensor Networks
"... Abstract-This paper presents an online, adaptive, distributive and collaborative path planning method for a team of autonomous mobile sensors that enables them to navigate through a sparse network of stationary sensors to search for events and improve the spatio-temporal coverage of the sensor fiel ..."
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Abstract-This paper presents an online, adaptive, distributive and collaborative path planning method for a team of autonomous mobile sensors that enables them to navigate through a sparse network of stationary sensors to search for events and improve the spatio-temporal coverage of the sensor field. The mobile sensor nodes have limited communication and sensing ranges and collaborate to autonomously plan their trajectories, adapt to the local region they monitor and enhance the area coverage over time under constrains like obstacles, collisions and limited communication. In this context, this paper addresses the trade off between area coverage and mobiles' travelled distance and proposes an adaptive speed model to minimize the distance the mobiles travelled and hence the energy needed for mobility. Finally, simulation results indicate the effectiveness of the proposed approach over a centralized partitioning approach under mobile sensors failures.
A Smooth-Turn Mobility Model for Airborne Networks
"... In this article, I introduce a novel airborne network mobility model, called the Smooth Turn Mobility Model, that captures the correlation of acceleration for airborne vehicles across time and spatial coordinates. Effective routing in airborne networks (ANs) relies on suitable mobility models that ..."
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In this article, I introduce a novel airborne network mobility model, called the Smooth Turn Mobility Model, that captures the correlation of acceleration for airborne vehicles across time and spatial coordinates. Effective routing in airborne networks (ANs) relies on suitable mobility models that capture the random movement pattern of airborne vehicles. As airborne vehicles cannot make sharp turns as easily as ground vehicles do, the widely used mobility models for Mobile Ad Hoc Networks such as Random Waypoint and Random Direction models fail. Our model is realistic in capturing the tendency of airborne vehicles toward making straight trajectory and smooth turns with large radius, and whereas is simple enough for tractable connectivity analysis and routing design.
Article A Trajectory-Based Coverage Assessment Approach for Universal Sensor Networks
, 2015
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3.1.6. Advances in Methodological Tools 3
"... Models for the performance analysis and the ..."
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Cost-minimizing Mobile Access Point Deployment in Workflow-based Mobile Sensor Networks
"... Abstract—In mission-based mobile environments such as airplane maintenance, workflow-based mobile sensor networks emerge, where mobile users (MUs) with sensing devices visit sequences of mission-driven locations defined by workflows, and demand the gathering of sensory data within mission durations. ..."
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Abstract—In mission-based mobile environments such as airplane maintenance, workflow-based mobile sensor networks emerge, where mobile users (MUs) with sensing devices visit sequences of mission-driven locations defined by workflows, and demand the gathering of sensory data within mission durations. To satisfy this demand in a cost-efficient manner, mobile access point (AP) deployment needs to be part of the overall solution. Therefore, we study the mobile AP deployment in workflow-based mobile sensor networks. We categorize MUs ’ workflows according to a priori knowledge of MUs ’ staying durations at mission locations into complete and incomplete information workflows. In both categories, we formulate the cost-minimizing mobile AP deployment problem into multiple (mixed) integer optimization problems, satisfying MUs ’ QoS constraints. We prove that the formulated optimization problems are NP-hard and design ap-proximation algorithms with guaranteed approximation ratios. We demonstrate using simulations that the AP deployment cost calculated using our algorithms is 50-60 % less than the stationary baseline approach and fairly close to the optimal AP deployment cost. In addition, the run times of our approximation algorithms are only 10-25 % of those of the branch-and-bound algorithm used to derive the optimal AP deployment cost. I.