BurstProbe: Debugging Time-Critical Data Delivery in Wireless Sensor Networks

Brown, James; McCarthy, Ben; Roedig, Utz; Voigt, Thiemo; Sreenan, Cormac J.

doi:10.1007/978-3-642-19186-2_13

Cited by 20 publications

(19 citation statements)

References 11 publications

(24 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since all of those protocols create a schedule for all network activity, in this subsection we describe, as an example, the scheduling mechanisms used by the GinMAC protocol [8]. The following description is based on [8,12].…”

Section: Scheduling Mechanisms Of Tdma Protocolmentioning

confidence: 99%

Scheduling of Wireless Sensor Networks

Cecílio

Furtado

2013

Computer Communications and Networks

View full text Add to dashboard Cite

This chapter discusses the state of the art related to scheduling and network planning within wireless sensor networks (WSN). It first provides some background information concerning medium access control (MAC), communication protocol approaches, and scheduling mechanisms used by time-division multiple access protocols (TDMA protocols). Planning mechanisms used to plan wireless sensor networks with precise timing are then examined. Wireless Medium Access Control (MAC)One key issue in WSNs that influences whether the deployed system will be able to provide timing guarantees is the MAC protocol and its configurations. The MAC protocols for wireless sensor networks can be classified broadly into two categories: contention-and schedule-based. The contention-based protocols can easily adjust to the topology changes as new nodes may join and others may die after deployment. These protocols are based on Carrier Sense Multiple Access (CSMA) mechanisms and have higher costs due to potential interference, message collisions, overhearing, and idle listening than the schedule-based counterparts. Schedulebased protocols can avoid those problems by defining precise schedules, but they have strict time synchronization requirements. Contention-Based MAC ProtocolsIn contention-based MAC protocols, potential message receivers wake up periodically for a short time to sample the medium. When a sender has data, it transmits a series of short preamble packets, each containing the ID of the target node, until it either receives an acknowledgment (ACK) packet from the receiver or a maximum sleep time is exceeded. Following the transmission of each preamble packet, the transmitter node waits for a timeout. If the receiver is not the target, it returns to sleep immediately. If the receiver is the target, it sends an ACK during the pause between the preamble packets. Upon reception of the ACK, the sender transmits the data packet to the destination.These protocols are implemented using units of time called backoff periods. The expected number of times random backoff is repeated is a function of the probability of sensing the channel busy, which depends on the channel traffic. Since these do not provide a precise schedule to send data and use random backoff, these protocols have higher costs for message collisions, overhearing, and idle listening than schedule-based counterparts, and they are typically not used for applications requiring strict operation timing guarantees. On the other hand, they can easily adjust to topology changes, such as when new nodes join and others leave after deployment.Some protocols frequently used in WSNs, such as S-MAC, B-MAC, WiseMAC, and X-MAC, are contention-based. S-MAC [1] defines periodic frame structure divided into two parts, with nodes being active in the first fraction of the frame and asleep for the remaining duration. The length of each of the frame parts is fixed, according to the desired duty cycle. Virtual clustering permits that nodes adopt and propagate time schedules, but it leads to the exist...

show abstract

Section: Scheduling Mechanisms Of Tdma Protocolmentioning

confidence: 99%

Scheduling of Wireless Sensor Networks

Cecílio

Furtado

2013

Computer Communications and Networks

View full text Add to dashboard Cite

show abstract

“…[7] [8] [9] utilize link burstiness to achieve better communication performance. [8] present a metric de noted (3 to measure this link burstiness.…”

Section: Related Workmentioning

confidence: 99%

Efficient information transmission under lossy WSNs link using compressive sensing

et al. 2014

2014 9th IEEE Conference on Industrial Electronics and Applications

View full text Add to dashboard Cite

Compressive sensing (CS) is applied to sparse signal transmission so that it can be transmitted efficiently over lossy wireless links. By exploiting the commonly sparse property of measured signal within wireless sensor networks (WSNs), we pro pose a CS-reconstruction based efficient information transmission framework. According to CS theory, if the sensed information has some sparsity, it can be reconstructed with only a few sensed data. In this case, we argue that, by using CS technique, information transmission can tolerate a certain degree of link lossy without requiring all of the data being successfnlly transmit ted, thus avoiding the expensive data retransmission. Moreover, CS-based information transmission framework is established,where the lossy link transmission is modeled as compressive sampling process. Data packets are directly transmitted after signal sampling, then the sensing matrix is obtained through the original sequence of received broken data and finally signal is reconstructed through optimization algorithm. Through experi mental verification, we first show the lossy link and sparsity of signal. Further, aiming at two distinct links, we make a couple of comparison tests, which shows our method achieves the same good reconstruction performance as conventional mnltiple data retransmission scheme does in good link. While in bad link our method outperforms conventional method even it adopts multiple retransmission. Results verify that during lossy link information transmission, the proposed CS-based method obtains high information transmission quality, also significantly reduces the energy cost and latency.

show abstract

“…The burstiness of a link can be measured using a mechanism called BurstProbe presented by Brown et al [19]. Essentially, a burst of unicast packets is sent to a neighbor and the Acknowledgment (ACK) responses are collected.…”

Section: A Relationship Between Receiver Signal Strength and Burstinessmentioning

confidence: 99%

“…The necessary amount of probe slots in each epoch depends on the burstiness a schedule can handle. For a typical schedule with a worst-case burstiness of 1/1, a reasonable number of probe slots is less or equal to 15 [19]. Those probe slots have All tuples R containing the burstiness for different P r values are kept in a ring buffer.…”

Section: B Determining the Receiver Signal Strength Target Based On mentioning

confidence: 99%

Probe-Based Transmission Power Control for Dependable Wireless Sensor Networks

Pöttner

Wolf

2013

2013 IEEE International Conference on Distributed Computing in Sensor Systems

View full text Add to dashboard Cite

Abstract-Dependable Wireless Sensor Networks for industrial process automation, monitoring and control applications have high demands regarding network reliability in terms of timely delivery and packet loss. In large industrial facilities, interference between neighboring networks is a major problem that can be mitigated by reducing the radio transmission power to the necessary minimum. However, reliability of the network should not be compromised even in spite of packet loss bursts.In this paper we aim at keeping the link within certain burstiness bounds while still minimizing the transmission power. We present evaluation results showing that the burstiness changes with the receiver signal strength. Based on this observation we present two mechanisms for dependable wireless sensor networks and study the performance in our testbed.

show abstract

BurstProbe: Debugging Time-Critical Data Delivery in Wireless Sensor Networks

Cited by 20 publications

References 11 publications

Scheduling of Wireless Sensor Networks

Scheduling of Wireless Sensor Networks

Efficient information transmission under lossy WSNs link using compressive sensing

Probe-Based Transmission Power Control for Dependable Wireless Sensor Networks

Contact Info

Product

Resources

About