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The β-factor: Measuring Wireless Link Burstiness
"... Measuring 802.15.4 reception in three testbeds, we find that most intermediate links are bursty: they shift between poor and good delivery. We present a metric to measure this link burstiness and name it β. We find that link burstiness affects protocol performance and that β can predict the effects. ..."
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Cited by 78 (2 self)
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Measuring 802.15.4 reception in three testbeds, we find that most intermediate links are bursty: they shift between poor and good delivery. We present a metric to measure this link burstiness and name it β. We find that link burstiness affects protocol performance and that β can predict the effects. We show that measuring β allows us to reason about how long a protocol should pause after encountering a packet failure to reduce its transmission cost. We find that using β as a guide to setting a single constant in a standard sensor network data collection protocol reduces its average transmission cost by 15%. In addition to data from 802.15.4 testbeds, we examine traces from 802.11b networks and find β has a broader relevance in the wireless domain. 1
Understanding the Causes of Packet Delivery Success and Failure in Dense Wireless Sensor Networks
- In Technical report SING-06-00
, 2006
"... We present empirical measurements of the packet delivery performance of the Telos and MicaZ sensor platforms. At a high level, their behavior is similar to that of earlier platforms. They exhibit link asymmetry, a reception “grey region, ” and temporal variations in packet loss. Looking more deeply, ..."
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Cited by 76 (5 self)
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We present empirical measurements of the packet delivery performance of the Telos and MicaZ sensor platforms. At a high level, their behavior is similar to that of earlier platforms. They exhibit link asymmetry, a reception “grey region, ” and temporal variations in packet loss. Looking more deeply, however, there are subtle differences, and looking deeper still, the patterns behind these complexities become clear. Packet losses are highly correlated over short time periods, but are independent over longer periods. Environmental noise (802.11b) has high spatial correlation. Packet loss occurs when a receiver operating near its noise floor experiences a small decrease in received signal strength, rather than an increase in environmental noise. These variations cause the reception “grey region. ” While short-term link asymmetries are not uncommon, long-term asymmetries are rare. Based on these findings, we suggest several ways in which current practices could be easily changed that would greatly improve the efficiency, performance, and lifetime of sensor networks. 1
RACNet: A High-Fidelity Data Center Sensing Network
"... RACNet is a sensor network for monitoring a data center’s environmental conditions. The high spatial and temporal fidelity measurements that RACNet provides can be used to improve the data center’s safety and energy efficiency. RACNet overcomes the network’s large scale and density and the data cent ..."
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Cited by 59 (8 self)
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RACNet is a sensor network for monitoring a data center’s environmental conditions. The high spatial and temporal fidelity measurements that RACNet provides can be used to improve the data center’s safety and energy efficiency. RACNet overcomes the network’s large scale and density and the data center’s harsh RF environment to achieve data yields of 99 % or higher over a wide range of network sizes and sampling frequencies. It does so through a novel Wireless Reliable Acquisition Protocol (WRAP). WRAP decouples topology control from data collection and implements a token passing mechanism to provide network-wide arbitration. This congestion avoidance philosophy is conceptually different from existing congestion control algorithms that retroactively respond to congestion. Furthermore, WRAP adaptively distributes nodes among multiple frequency channels to balance load and lower data latency. Results from two testbeds and an ongoing production data center deployment indicate that RACNet outperforms previous data collection systems, especially as network load increases.
An Empirical Study of Low-Power Wireless
, 2010
"... We present empirical measurements of the packet delivery performance of the latest sensor platforms: Micaz and Telos motes. In this article, we present observations that have implications to a set of common assumptions protocol designers make while designing sensornet protocols— specifically—the MAC ..."
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Cited by 51 (1 self)
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We present empirical measurements of the packet delivery performance of the latest sensor platforms: Micaz and Telos motes. In this article, we present observations that have implications to a set of common assumptions protocol designers make while designing sensornet protocols— specifically—the MAC and network layer protocols. We first distill these common assumptions in to a conceptual model and show how our observations support or dispute these assumptions. We also present case studies of protocols that do not make these assumptions. Understanding the implications of these observations to the conceptual model can improve future protocol designs.
Weighted centroid localization in Zigbee-based sensor networks.
- In Intelligent Signal Processing,
, 2007
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Radio link quality estimation in wireless sensor networks: a survey
- ACM Transactions on Sensor Networks (TOSN
"... Radio link quality estimation in Wireless Sensor Networks (WSNs) has a fundamental impact on the network performance and affects as well the design of higher layer protocols. Therefore, since about a decade, it has been attracting a vast array of research works. Reported works on link quality estima ..."
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Cited by 44 (4 self)
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Radio link quality estimation in Wireless Sensor Networks (WSNs) has a fundamental impact on the network performance and affects as well the design of higher layer protocols. Therefore, since about a decade, it has been attracting a vast array of research works. Reported works on link quality estimation are typically based on different assumptions, consider different scenarios, and provide radically different (and sometimes contradictory) results. This paper provides a comprehensive survey on related literature, covering the characteristics of low-power links, the fundamental concepts of link quality estimation in WSNs, a taxonomy of existing link quality estimators, and their performance analysis. To the best of our knowledge, this is the first survey tackling in detail link quality estimation in WSNs. We believe our efforts will serve as a
Does Wireless Sensor Network Scale? A Measurement Study on GreenOrbs
"... Abstract—In spite of the remarkable efforts the community put to build the sensor systems, an essential question still remains unclear at the system level, motivating us to explore the answer from a point of real-world deployment view. Does the wireless sensor network really scale? We present findin ..."
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Cited by 40 (8 self)
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Abstract—In spite of the remarkable efforts the community put to build the sensor systems, an essential question still remains unclear at the system level, motivating us to explore the answer from a point of real-world deployment view. Does the wireless sensor network really scale? We present findings from a large scale operating sensor network system, GreenOrbs, with up to 330 nodes deployed in the forest. We instrument such an operating network throughout the protocol stack and present observations across layers in the network. Based on our findings from the system measurement, we propose and make initial efforts to validate three conjectures that give potential guidelines for future designs of large scale sensor networks. (1) A small portion of nodes bottlenecks the entire network, and most of the existing network indicators may not accurately capture them. (2) The network dynamics mainly come from the inherent concurrency of network operations instead of environment changes. (3) The environment, although the dynamics are not as significant as we assumed, has an unpredictable impact on the sensor network. We suggest that an event-based routing structure can be trained optimal and thus better adapt to the wild environment when building a large scale sensor network. I.
Air-dropped Sensor Network for Real-time High-fidelity Volcano Monitoring
, 2009
"... This paper presents the design and deployment experience of an air-dropped wireless sensor network for volcano hazard monitoring. The deployment of five stations into the rugged crater of Mount St. Helens only took one hour with a helicopter. The stations communicate with each other through an ampli ..."
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Cited by 40 (15 self)
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This paper presents the design and deployment experience of an air-dropped wireless sensor network for volcano hazard monitoring. The deployment of five stations into the rugged crater of Mount St. Helens only took one hour with a helicopter. The stations communicate with each other through an amplified 802.15.4 radio and establish a self-forming and self-healing multi-hop wireless network. The distance between stations is up to 2 km. Each sensor station collects and delivers real-time continuous seismic, infrasonic, lightning, GPS raw data to a gateway. The main contribution of this paper is the design and evaluation of a robust sensor network to replace data loggers and provide real-time long-term volcano monitoring. The system supports UTCtime synchronized data acquisition with 1ms accuracy, and is online configurable. It has been tested in the lab environment, the outdoor campus and the volcano crater. Despite the heavy rain, snow, and ice as well as gusts exceeding 120 miles per hour, the sensor network has achieved a remarkable packet delivery ratio above 99 % with an overall system uptime of about 93.8 % over the 1.5 months evaluation period after deployment. Our initial deployment experiences with the system have alleviated the doubts of domain scientists and prove to them that a low-cost sensor network system can support real-time monitoring in extremely harsh environments.
Bursty traffic over bursty links.
- In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (SenSys’09)
, 2009
"... Abstract Accurate estimation of link quality is the key to enable efficient routing in wireless sensor networks. Current link estimators focus mainly on identifying long-term stable links for routing. They leave out a potentially large set of intermediate links offering significant routing progress ..."
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Cited by 33 (5 self)
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Abstract Accurate estimation of link quality is the key to enable efficient routing in wireless sensor networks. Current link estimators focus mainly on identifying long-term stable links for routing. They leave out a potentially large set of intermediate links offering significant routing progress. Fine-grained analysis of link qualities reveals that such intermediate links are bursty, i.e., stable in the short term. In this paper, we use short-term estimation of wireless links to accurately identify short-term stable periods of transmission on bursty links. Our approach allows a routing protocol to forward packets over bursty links if they offer better routing progress than long-term stable links. We integrate a Short Term Link Estimator and its associated routing strategy with a standard routing protocol for sensor networks. Our evaluation reveals an average of 19% and a maximum of 42% reduction in the overall transmissions when routing over long-range bursty links. Our approach is not tied to any specific routing protocol and integrates seamlessly with existing routing protocols and link estimators.
