The impact of timing in data aggregation for sensor networks

Solís, Ignacio; Obraczka, Katia

doi:10.1109/icc.2004.1313222

Cited by 134 publications

(85 citation statements)

References 7 publications

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“…Various aggregation protocols have been proposed for different applications, such as monitoring and periodic data collection [7,8,9], dynamic event detection [10], and target tracking [11]. This paper considers data aggregation in the context of sensor networks supporting realtime monitoring, specifically real-time monitoring systems where sensor data is sampled periodically and forwarded to a single sink node.…”

Section: Introductionmentioning

confidence: 99%

“…Aggregation protocols for sensor networks with periodic traffic transmit sensor values over a tree or cluster topology, rooted at the sink [12,7,8,9]. Previous work has advocated synchronous aggregation protocols, in which a sequence of time intervals are statically defined for each round (collection of one set of sensor values), with each interval dedicated to transmissions from particular sensor nodes.…”

Section: Introductionmentioning

confidence: 99%

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Asynchronous Data Aggregation for Real-Time Monitoring in Sensor Networks

Eager

Makaroff

2007

NETWORKING 2007. Ad Hoc and Sensor Networks, Wireless Networks, Next Generation Internet

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Abstract. Real-time monitoring applications for sensor networks can require high sampling rates and low-delay forwarding of the sensor values to a sink node at which the data is to be further processed. High data collection rates can be efficiently supported by aggregating data as it is being forwarded to the sink. Since aggregation requires that some sensor data be delayed at intermediate nodes, while waiting for other data to be received, a key issue in the context of real-time monitoring is how to achieve effective aggregation with minimal forwarding delay. Previous work has advocated synchronous aggregation, in which a node's position in the aggregation tree determines when it transmits to its parent. This paper shows that asynchronous aggregation, in which the time of each node's transmission is determined adaptively based on its local history of past packet receptions from its children, outperforms synchronous aggregation by providing lower delay for a given end-to-end loss rate.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Asynchronous Data Aggregation for Real-Time Monitoring in Sensor Networks

Eager

Makaroff

2007

NETWORKING 2007. Ad Hoc and Sensor Networks, Wireless Networks, Next Generation Internet

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“…The efficiency of data collection can be vastly improved by aggregating the sensor data received at intermediate nodes into fewer numbers of packets, as this data is being forwarded to the sink [1] [2][3] [4][5] [6]. By reducing the number of transmitted packets, aggregation can reduce energy usage, increase the achievable data collection rate, and (owing to reduced network contention) decrease the data collection delay.…”

Section: Introductionmentioning

confidence: 99%

“…Existing protocols for data collection using aggregation ("aggregation protocols") may be classified as either asynchronous or synchronous and according to whether they use unicast or broadcast communication [1] [2][3] [9][10] [11]. The former distinction concerns how a node determines when to wait for additional data from upstream nodes, and when to send downstream an aggregate packet containing whatever data it has received up until then.…”

Section: Introductionmentioning

confidence: 99%

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Aggregation Protocols for High Rate, Low Delay Data Collection in Sensor Networks

Eager

Makaroff

2009

Networking 2009

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Abstract. Sensor network applications commonly require sensor data to be periodically collected. Aggregation protocols can make this process considerably more efficient. This paper considers the problem of devising aggregation protocols for applications that must achieve as "real-time" a view of the monitored area as possible, entailing a high sampling rate and a low data collection delay, at the possible cost of some modest amount of data loss. We examine in particular broadcast-based protocols that minimize the number of packet transmissions, relying on multipath delivery rather than ARQ for reliability, and consider the question of whether such protocols can achieve lower collection delays and support higher sampling rates than conventional aggregation protocols. Our results suggest that broadcast-based protocols can yield significantly improved performance in some scenarios, when sensor data can be aggregated into packets of size that is independent (or largely independent) of the number of values being aggregated.

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