Maintaining Approximate Minimum Steiner Tree and k-center for Mobile Agents in a Sensor Network

Zhou, Dengpan; Gao, Jie

doi:10.1109/infcom.2010.5462182

Cited by 13 publications

(12 citation statements)

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“…Constant-doubling networks have been widely used as an appropriate model of a sensor network metric, e.g. see [7,11,12,27,40]. We use a distributed maximal independent set algorithm due to Luby [24] to select the nodes of G to include in HS; some recent algorithms [15,29] can also be used to construct HS.…”

Section: Construction Of Overlay Structurementioning

confidence: 99%

“…MOT essentially maintains a data structure as we mentioned above for the tracking task. When applied to constant-doubling networks, which have been widely used as a model of a sensor network in the literature (e.g., [7,11,12,27,40]), MOT provides a cost ratio of O(min{log n, log D}) in maintaining the data structure for any arbitrary set of maintenance operations comparing its communication cost to the optimal cost, where n and D, respectively, are the number of nodes and the diameter of the network. This result assumes the case where each maintenance operation of an object arrives only after the previous maintenance operation for that object is finished.…”

Section: Introductionmentioning

confidence: 99%

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Near-Optimal Location Tracking Using Sensor Networks

Sharma

Krishnan

Busch

et al. 2015

IJNC

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We consider the problem of tracking mobile objects using a sensor network. We present a distributed tracking algorithm, called Mobile Object Tracking using Sensors (MOT), that scales well with the number of sensors and also with the number of mobile objects. MOT maintains a hierarchical structure of detection lists of objects that can efficiently track mobile objects and resolve object queries at any time. MOT guarantees that the cost to update (or maintain) its data structures will be at most O(min{log n, log D}) times the optimal update cost and query cost will be within O(1) of the optimal query cost in the constant-doubling graph model, where n and D, respectively, are the number of nodes and the diameter of the network. MOT achieves polylogarithmic approximations for both costs in the general graph model. MOT balances the object and bookkeeping information load at each node in the expense of only O(log n) increase in the update and query costs. The experimentation evaluation in both one by one and concurrent execution situations shows that MOT performs well in practical scenarios. To the best of our knowledge, MOT is the first algorithm for this problem in a distributed setting that is traffic-oblivious, i.e. agnostic to a priori knowledge of objects movement patterns, mobility and query rate, etc., and is load balanced. All previous solutions for this problem assumed traffic-consciousness in constructing the tracking data structure.

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Section: Construction Of Overlay Structurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Near-Optimal Location Tracking Using Sensor Networks

Sharma

Krishnan

Busch

et al. 2015

IJNC

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“…Mobile agents [4] are processes that can move throughout a computer network, either Local Area Network (LAN) or WAN (Wide Area Network), migrating or cloning its code and state from a computer server to another. These agents can interact with heterogeneous devices, gathering information and then return to its origin with the data obtained.…”

Section: Multi-agent Systems and Mobile Agentsmentioning

confidence: 99%

User-Centered Ubiquitous Multi-Agent Model for e-Health Web-Based Recommender Applications Development

Álvarez

Salazar

Ovalle

2013

Communications in Computer and Information Science

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Abstract. Despite recent progress in e-health system development, there are still significant problems in health service recommendation processes such as searching for healthcare specialists or medical appointments in hospitals and healthcare centers. Also, there are not so many e-health user-centered systems that provide assistance and good recommendations to users at any time in the location they are situated. The aim of this paper is to propose a model based on the integration of several approaches such as: ubiquitous computing, adaptive and recommender systems, web-based and user-centered multi-agent systems, and ontologies. In addition, an e-health web-based system prototype was built based on this model adopting mechanisms to search for information from anywhere and anytime, thus providing ubiquity characteristics. Finally, we present the validation of the U-MAS-HEALTH system by means of a case study.

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“…A few sensor network papers [24,29] consider a model when the growth rate is both upper and lower bounded, i.e., ρ − r k4 ≤ |B(p, r)| ≤ ρ + r k4 for a constant k 4 , where ρ − ≤ ρ + are two constants. We denote the family of metrics with constant expansion rate, constant doubling dimension, constant upper bounded growth rate, and constant upper and lower bounded growth rate as M expansion , M doubling , M + growth , M growth respectively.…”

Section: Preliminariesmentioning

confidence: 99%

Resilient and Low Stretch Routing through Embedding into Tree Metrics

Gao

Zhou

2011

Lecture Notes in Computer Science

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Abstract. Given a network, the simplest routing scheme is probably routing on a spanning tree. This method however does not provide good stretch -the route between two nodes can be much longer than their shortest distance, nor does it give good resilience -one node failure may disconnect quadratically many pairs. In this paper we use two trees to achieve both constant stretch and good resilience. Given a metric (e.g., as the shortest path metric of a given communication network), we build two hierarchical well-separated trees using randomization such that for any two nodes u, v, the shorter path of the two paths in the two respective trees gives a constant stretch of the metric distance of u, v, and the removal of any node only disconnect the routes between O(1/n) fraction of all pairs. Both bounds are in expectation and hold true as long as the metric follows certain geometric growth rate (the number of nodes within distance r is a polynomial function of r), which holds for many realistic network settings such as wireless ad hoc networks and Internet backbone graphs. The algorithms have been implemented and tested on real data.

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Maintaining Approximate Minimum Steiner Tree and k-center for Mobile Agents in a Sensor Network

Cited by 13 publications

References 13 publications

Near-Optimal Location Tracking Using Sensor Networks

Near-Optimal Location Tracking Using Sensor Networks

User-Centered Ubiquitous Multi-Agent Model for e-Health Web-Based Recommender Applications Development

Resilient and Low Stretch Routing through Embedding into Tree Metrics

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