Gathering correlated data in sensor networks

Rickenbach, Pascal von; Wattenhofer, Rogert

doi:10.1145/1022630.1022640

Cited by 120 publications

(94 citation statements)

References 23 publications

(37 reference statements)

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“…We divide existed strategies into two categories. In single-input coding each node can consider data from only one other source during data compression (P. V. Rickenbach et al, 2004;R. Cristescu et al, 2005).…”

Section: *Corresponding Author: Anand Nayyarmentioning

confidence: 99%

Performance Comparison of Distance and Density based Clustering Algorithm (DDCSA) V/s Normal Technique to analyze Power Consumption and Network Lifetime of Wireless Sensor Networks

Sharma¹

2011

International Journal of Current Engineering and Technology

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Section: *Corresponding Author: Anand Nayyarmentioning

confidence: 99%

Performance Comparison of Distance and Density based Clustering Algorithm (DDCSA) V/s Normal Technique to analyze Power Consumption and Network Lifetime of Wireless Sensor Networks

Sharma¹

2011

International Journal of Current Engineering and Technology

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“…Elkin et al [6] gave an Ω( 1/ log n )-approximation for the discrete version of Multiple Topology Convergecast problem. Regarding the case without aggregation, some partial results were given in [25], [1] and [14]. The paper [25] considered the conditional aggregation where data from one node can be compressed in the presence of data from other nodes.…”

Section: Previous Workmentioning

confidence: 99%

“…Regarding the case without aggregation, some partial results were given in [25], [1] and [14]. The paper [25] considered the conditional aggregation where data from one node can be compressed in the presence of data from other nodes. Liang and Liu [14] present a number of heuristics for different types of aggregation problems.…”

Section: Previous Workmentioning

confidence: 99%

Improved Approximation Algorithms for Maximum Lifetime Problems in Wireless Networks

Nutov

Segal

2009

Algorithmic Aspects of Wireless Sensor Networks

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A wireless ad-hoc network is a collection of transceivers positioned in the plane. Each transceiver is equipped with a limited battery charge. The battery charge is then reduced after each transmission, depending on the transmission distance. One of the major problems in wireless network design is to route network traffic efficiently so as to maximize the network lifetime, i.e., the number of successful transmissions. In this paper we consider Rooted Maximum Lifetime Broadcast/Convergecast problems in wireless settings. The instance consists of a directed graph G = (V, E) with edge-weights {w(e) : e ∈ E}, node capacities {b(v) : v ∈ V }, and a root r. The goal is to find a maximum size collection {T 1 , . . . , T k } of Broadcast/Convergecast trees rooted at r so that, where δ T (v) is the set of edges leaving v in T . In the Single Topology version all the Broadcast/Convergecast trees T i are identical. We present a number of polynomial time algorithms giving constant ratio approximation for various broadcast and convergecast problems, improving previously known result of Ω( 1/ log n )-approximation by [6]. We also consider a generalized Rooted Maximum Lifetime Mixedcast problem, where we are also given an integer γ ≥ 0, and the goal is to find the maximum integer k so that k Broadcast and γk Convergecast rounds can be performed.

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“…Most of current data gathering researches have been conducted towards this goal [3], [4], [5], [6]. Some works also use data aggregation techniques [7], [8], [9] to reduce the number of radio transmissions, which is the main drain of the battery of sensor nodes. Data aggregation is especially appropriate when sensor networks have high density and as a result, data sensed at neighboring nodes are either highly correlated or simply redundant.…”

Section: Motivationmentioning

confidence: 99%

Delay Efficient Data Gathering in Sensor Networks

Zhu

Tang

Gupta

2005

Lecture Notes in Computer Science

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Abstract. Data gathering is a very important functionality in sensor networks. Most of current data gathering researches have been emphasized on issues such as energy efficiency and network lifetime maximization; and the technique of data aggregation is usually used to reduce the number of radio transmissions. However, there are many emerging sensor network applications with different requirements and constraints. Rather, they are time critical, i.e., delivering sensed information of each individual sensor node back to a central base station quickly becomes most important. In this paper, we consider collision-free delay efficient data gathering problem in sensor networks, assuming that no data aggregation happens in intermediate nodes. We formally formulate this problem and propose optimal and near-optimal algorithms for different topologies. Particularly, in general topology, we present two approximation algorithms with performance ratio of 2 and 1+1/(k+1), respectively.

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Gathering correlated data in sensor networks

Cited by 120 publications

References 23 publications

Performance Comparison of Distance and Density based Clustering Algorithm (DDCSA) V/s Normal Technique to analyze Power Consumption and Network Lifetime of Wireless Sensor Networks

Performance Comparison of Distance and Density based Clustering Algorithm (DDCSA) V/s Normal Technique to analyze Power Consumption and Network Lifetime of Wireless Sensor Networks

Improved Approximation Algorithms for Maximum Lifetime Problems in Wireless Networks

Delay Efficient Data Gathering in Sensor Networks

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