An adaptive energy-efficient MAC protocol for wireless sensor networks (2003)

by T van Dam, K Langendoen
Venue:in Proc. of of the 1st ACM Conference on Embedded Network Sensor Systems (Sensys’03
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Versatile Low Power Media Access for Wireless Sensor Networks

by Joseph Polastre, Jason Hill, David Culler , 2004
"... We propose B-MAC, a carrier sense media access protocol for wireless sensor networks that provides a flexible interface to obtain ultra low power operation, effective collision avoidance, and high channel utilization. To achieve low power operation, B-MAC employs an adaptive preamble sampling scheme ..."
Abstract - Cited by 1077 (19 self) - Add to MetaCart
We propose B-MAC, a carrier sense media access protocol for wireless sensor networks that provides a flexible interface to obtain ultra low power operation, effective collision avoidance, and high channel utilization. To achieve low power operation, B-MAC employs an adaptive preamble sampling scheme to reduce duty cycle and minimize idle listening. B-MAC supports on-the-fly reconfiguration and provides bidirectional interfaces for system services to optimize performance, whether it be for throughput, latency, or power conservation. We build an analytical model of a class of sensor network applications. We use the model to show the effect of changing B-MAC’s parameters and predict the behavior of sensor network applications. By comparing B-MAC to conventional 802.11inspired protocols, specifically S-MAC, we develop an experimental characterization of B-MAC over a wide range of network conditions. We show that B-MAC’s flexibility results in better packet delivery rates, throughput, latency, and energy consumption than S-MAC. By deploying a real world monitoring application with multihop networking, we validate our protocol design and model. Our results illustrate the need for flexible protocols to effectively realize energy efficient sensor network applications.

X-mac: A short preamble mac protocol for duty-cycled wireless sensor networks

by Michael Buettner, Gary V. Yee, Eric Anderson, Richard Han - in SenSys , 2006
"... In this paper we present X-MAC, a low power MAC protocol for wireless sensor networks (WSNs). Standard MAC protocols developed for duty-cycled WSNs such as B-MAC, which is the default MAC protocol for TinyOS, employ an extended preamble and preamble sampling. While this “low power listening ” approa ..."
Abstract - Cited by 348 (0 self) - Add to MetaCart
In this paper we present X-MAC, a low power MAC protocol for wireless sensor networks (WSNs). Standard MAC protocols developed for duty-cycled WSNs such as B-MAC, which is the default MAC protocol for TinyOS, employ an extended preamble and preamble sampling. While this “low power listening ” approach is simple, asynchronous, and energy-efficient, the long preamble introduces excess latency at each hop, is suboptimal in terms of energy consumption, and suffers from excess energy consumption at nontarget receivers. X-MAC proposes solutions to each of these problems by employing a shortened preamble approach that retains the advantages of low power listening, namely low power communication, simplicity and a decoupling of transmitter and receiver sleep schedules. We demonstrate through implementation and evaluation in a wireless sensor testbed that X-MAC’s shortened preamble approach significantly reduces energy usage at both the transmitter and receiver, reduces per-hop latency, and offers additional advantages such as flexible adaptation to both bursty and periodic sensor data sources.
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Z-MAC: a Hybrid MAC for Wireless Sensor Networks

by Ajit Warrier, Jeongki Min, Injong Rhee , 2005
"... Z-MAC is a hybrid MAC protocol for wireless sensor networks. It combines the strengths of TDMA and CSMA while offsetting their weaknesses. Nodes are assigned time slots using a distributed implementation of RAND. Unlike TDMA where a node is allowed to transmit only during its own assigned slots, a n ..."
Abstract - Cited by 289 (7 self) - Add to MetaCart
Z-MAC is a hybrid MAC protocol for wireless sensor networks. It combines the strengths of TDMA and CSMA while offsetting their weaknesses. Nodes are assigned time slots using a distributed implementation of RAND. Unlike TDMA where a node is allowed to transmit only during its own assigned slots, a node can transmit in both its own time slots and slots assigned to other nodes. Owners of the current time slot always have priority in accessing the channel over non-owners. Therefore, under low contention where not all owners have data to send, non-owners can “steal ” time slots from owners. This has the effect of switching between CSMA and TDMA depending on contention. Z-MAC is robust to topology changes and clock synchronization errors; in the worst case its performance falls back to that of CSMA. We implemented Z-MAC in TinyOS and evaluated its channel utilization, energy, latency and fairness over single-hop, twohop and multi-hop sensor network topologies constructed using Mica2. The result shows that Z-MAC has remarkably better data throughput than existing sensor MAC protocols while consuming comparable energy (over three times better throughput under high contention).
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Habitat Monitoring with Sensor Networks

by Robert Szewczyk, Eric Osterweil, Joseph Polastre, Michael Hamilton, Alan Mainwaring, Deborah Estrin - Communications of the ACM , 2004
"... of observations, showing how they fit into a unified architecture, deriving our data and conclusions from several case studies (see the sidebar "Sensing the Natural Environment"). Few themes permeate basic and applied ecological research to such an extent as the relationship of micro ..."
Abstract - Cited by 203 (5 self) - Add to MetaCart
of observations, showing how they fit into a unified architecture, deriving our data and conclusions from several case studies (see the sidebar "Sensing the Natural Environment"). Few themes permeate basic and applied ecological research to such an extent as the relationship of microclimate and ecological patterns, processes, physiology, and biological diversity. Microclimate can be defined as the climate close to surfaces, upon and beneath soils, under snow, or in water, on living things (such as trees), or even on individual animals. Individuals may disperse across broad areas, but persistence, growth, and reproduction depend on the existence of narrow ranges of key environmental conditions that vary over narrow spatial gradients. For example, we see only the stand of trees that reached the right microclimate as seeds but not the tens of thousands of seeds that perished or simply failed to take root because they germinated in areas outside the range of their tolera
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Ultra-Low Duty Cycle MAC with Scheduled Channel Polling

by Wei Ye, Fabio Silva, John Heidemann - In Proceedings of the Fourth International Conference On Embedded Networked Sensor Systems (SenSys 2006 , 2006
"... Energy is a critical resource in sensor networks. MAC protocols such as S-MAC and T-MAC coordinate sleep schedules to reduce energy consumption. Recently, lowpower listening (LPL) approaches such as WiseMAC and B-MAC exploit very brief polling of channel activity combined with long preambles before ..."
Abstract - Cited by 189 (3 self) - Add to MetaCart
Energy is a critical resource in sensor networks. MAC protocols such as S-MAC and T-MAC coordinate sleep schedules to reduce energy consumption. Recently, lowpower listening (LPL) approaches such as WiseMAC and B-MAC exploit very brief polling of channel activity combined with long preambles before each transmission, saving energy particularly during low network utilization. Synchronization cost, either explicitly in scheduling, or implicitly in long preambles, limits all these protocols to duty cycles of 1–2%. We demonstrate that ultra-low duty cycles of 0.1% and below are possible with a new MAC protocol called scheduled channel polling (SCP). This work prompts three new contributions: First, we establish optimal configurations for both LPL and SCP under fixed conditions, developing a lower bound of energy consumption. Under these conditions, SCP can extend lifetime of a network by a factor of 3–6 times over LPL. Second, SCP is designed to adapt well to variable traffic. LPL is optimized for known, periodic traffic, and long preambles become very costly when traffic varies. In one experiment, SCP reduces energy consumption by a factor of 10 under bursty traffic. We also show how SCP adapts to heavy traffic and streams data in multi-hop networks, reducing latency by 85 % and energy by 95 % at 9 hops. Finally, we show that SCP can operate effectively on recent hardware such as 802.15.4 radios. In fact, power consumption of SCP decreases with faster radios, but that of LPL increases.
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Mitigating congestion in wireless sensor networks

by Bret Hull, Kyle Jamieson, Hari Balakrishnan - in SenSys , 2004
"... Network congestion occurs when offered traffic load exceeds available capacity at any point in a network. In wireless sensor networks, congestion causes overall channel quality to degrade and loss rates to rise, leads to buffer drops and increased delays (as in wired networks), and tends to be gross ..."
Abstract - Cited by 189 (3 self) - Add to MetaCart
Network congestion occurs when offered traffic load exceeds available capacity at any point in a network. In wireless sensor networks, congestion causes overall channel quality to degrade and loss rates to rise, leads to buffer drops and increased delays (as in wired networks), and tends to be grossly unfair toward nodes whose data has to traverse a larger number of radio hops. Congestion control in wired networks is usually done using end-to-end and network-layer mechanisms acting in concert. However, this approach does not solve the problem in wireless networks because concurrent radio transmissions on different “links ” interact with and affect each other, and because radio channel quality shows high variability over multiple time-scales. We examine three techniques that span different layers of the traditional protocol stack: hop-by-hop flow control, rate limiting source traffic when transit traffic is present, and a prioritized medium access control (MAC) protocol. We implement these techniques and present experimental results from a 55-node in-building wireless sensor network. We demonstrate that the combination of these techniques, Fusion, can improve network efficiency by a factor of three under realistic workloads.
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A unifying link abstraction for wireless sensor networks

by Joseph Polastre, Jonathan Hui, Philip Levis, Jerry Zhao, David Culler, Scott Shenker, Ion Stoica - in Proceedings of the 3rd ACM Conference on Embedded Networked Sensor Systems (SenSys , 2005
"... Recent technological advances and the continuing quest for greater efficiency have led to an explosion of link and network protocols for wireless sensor networks. These protocols embody very different assumptions about network stack composition and, as such, have limited interoperability. It has bee ..."
Abstract - Cited by 163 (16 self) - Add to MetaCart
Recent technological advances and the continuing quest for greater efficiency have led to an explosion of link and network protocols for wireless sensor networks. These protocols embody very different assumptions about network stack composition and, as such, have limited interoperability. It has been suggested [3] that, in principle, wireless sensor networks would benefit from a unifying abstraction (or “narrow waist ” in architectural terms), and that this abstraction should be closer to the link level than the network level. This paper takes that vague principle and turns it into practice, by proposing a specific unifying sensornet protocol (SP) that provides shared neighbor management and a message pool. The two goals of a unifying abstraction are generality and efficiency: it should be capable of running over a broad range of link-layer technologies and supporting a wide variety of network protocols, and doing so should not lead to a significant loss of efficiency. To investigate the extent to which SP meets these goals, we implemented SP (in TinyOS) on top of two very different radio technologies: B-MAC on mica2 and IEEE 802.15.4 on Telos. We also built a variety of network protocols on SP, including examples of collection routing [53], dissemination [26], and aggregation [33]. Measurements show that these protocols do not sacrifice performance through the use of our SP abstraction.
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Research Challenges and Applications for Underwater Sensor Networking

by John Heidemann, Wei Ye, Jack Wills, Affan Syed, Yuan Li - In Proceedings of the IEEE Wireless Communications and Networking Conference , 2006
"... This paper explores applications and challenges for underwater sensor networks. We highlight potential applications to off-shore oilfields for seismic monitoring, equipment monitoring, and underwater robotics. We identify research directions in shortrange acoustic communications, MAC, time synchroni ..."
Abstract - Cited by 157 (11 self) - Add to MetaCart
This paper explores applications and challenges for underwater sensor networks. We highlight potential applications to off-shore oilfields for seismic monitoring, equipment monitoring, and underwater robotics. We identify research directions in shortrange acoustic communications, MAC, time synchronization, and localization protocols for high-latency acoustic networks, longduration network sleeping, and application-level data scheduling. We describe our preliminary design on short-range acoustic communication hardware, and summarize results of high-latency time synchronization.
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Real-time QoS support in wireless sensor networks: a survey

by Yanjun Li, Chung Shue Chen, Ye-qiong Song, Zhi Wang - In: 7th IFAC International Conference on Fieldbuses & Networks in Industrial & Embedded Systems - FeT’2007 , 2007
"... Abstract: Real-time wireless sensor networks are becoming more and more important by the requirement of message delivery timeliness in emerging new applications. Supporting real-time QoS in sensor networks faces severe challenges due to the wireless nature, limited resource, low node reliability, di ..."
Abstract - Cited by 122 (6 self) - Add to MetaCart
Abstract: Real-time wireless sensor networks are becoming more and more important by the requirement of message delivery timeliness in emerging new applications. Supporting real-time QoS in sensor networks faces severe challenges due to the wireless nature, limited resource, low node reliability, distributed architecture and dynamic network topology. There are tradeoffs between different application requirements including energy efficiency and delay performance. This paper studies the state of the art of current real-time solutions including MAC protocols, routing protocols, data processing strategies and cross-layer designs. Some research challenges and future design favors are also identified and discussed. Keywords: Real-time, wireless sensor networks, MAC, routing, cross-layer. 1.

Protothreads: Simplifying event-driven programming of memory-constrained embedded systems

by Adam Dunkels, Oliver Schmidt, Thiemo Voigt, Muneeb Ali - In Proc. 2006 SenSys , 2006
"... Event-driven programming is a popular model for writing programs for tiny embedded systems and sensor network nodes. While event-driven programming can keep the memory overhead down, it enforces a state machine programming style which makes many programs difficult to write, maintain, and debug. We p ..."
Abstract - Cited by 119 (12 self) - Add to MetaCart
Event-driven programming is a popular model for writing programs for tiny embedded systems and sensor network nodes. While event-driven programming can keep the memory overhead down, it enforces a state machine programming style which makes many programs difficult to write, maintain, and debug. We present a novel programming abstraction called protothreads that makes it possible to write eventdriven programs in a thread-like style, with a memory overhead of only two bytes per protothread. We show that protothreads significantly reduce the complexity of a number of widely used programs previously written with event-driven state machines. For the examined programs the majority of the state machines could be entirely removed. In the other cases the number of states and transitions was drastically decreased. With protothreads the number of lines of code was reduced by one third. The execution time overhead of protothreads is on the order of a few processor cycles.
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