Versatile low power media access for wireless sensor networks

Polastre, Joseph; Hill, Jason; Culler, David

doi:10.1145/1031495.1031508

Cited by 2,742 publications

(2,105 citation statements)

References 21 publications

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“…Therefore, we opted for a software-based power profiler based on the following assumptions: 1) radio communication occurs only through MUSTER; 2) MUSTER runs atop a CSMA-like MAC protocol providing some form of low-power listening [41]; 3) the current draw due to processing and sensing is roughly the same on all the nodes. Under these assumptions, Iavg can be computed by tracking send and receive operations at the MAC layer, based on the quantities in Figure 9.…”

Section: Estimating the Expected Lifetimementioning

confidence: 99%

MUSTER: Adaptive Energy-Aware Multisink Routing in Wireless Sensor Networks

Mottola

Picco

2011

IEEE Trans. on Mobile Comput.

102

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Abstract-Wireless sensor networks (WSNs) are increasingly proposed for applications characterized by many-to-many communication, where multiple sources report their data to multiple sinks. Unfortunately, mainstream WSN collection protocols are generally designed to account for a single sink and, dually, WSN multicast protocols optimize communication from a single source.In this paper we present MUSTER, a routing protocol expressly designed for many-to-many communication. First, we devise an analytical model to compute, in a centralized manner, the optimal solution to the problem of simultaneously routing from multiple sources to multiple sinks. Next, we illustrate heuristics approximating the optimal solution in a distributed setting, and their implementation in MUSTER. To increase network lifetime, MUSTER minimizes the number of nodes involved in many-tomany routing and balances their forwarding load. We evaluate MUSTER in emulation and in a real WSN testbed. Results indicate that our protocol builds near-optimal routing paths, doubles the WSN lifetime, and overall delivers to the user 2.5 times the amount of raw data w.r.t. mainstream protocols. Moreover, MUSTER is intrinsically amenable to in-network aggregation, pushing the improvements up to a 180% increase in lifetime and a 4-time increase in data yield.

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Section: Estimating the Expected Lifetimementioning

confidence: 99%

MUSTER: Adaptive Energy-Aware Multisink Routing in Wireless Sensor Networks

Mottola

Picco

2011

IEEE Trans. on Mobile Comput.

102

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“…Typically, CCA involves having wireless devices monitoring the received signal and comparing the average received signal strength with a threshold Υ . Studies [8] have shown that adaptive-CCA, which adjusts the threshold Υ based on the ambient noise floor, can achieve better throughput and latency than using a pre-determined threshold Υ . Therefore, we assume that each node employs an adaptive-CCA mechanism in our study.…”

Section: Network Model and Assumptionsmentioning

confidence: 99%

Wireless Jamming Localization by Exploiting Nodes’ Hearing Ranges

Liu

et al. 2010

Distributed Computing in Sensor Systems

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Abstract. Jamming attacks are especially harmful when ensuring the dependability of wireless communication. Finding the position of a jammer will enable the network to actively exploit a wide range of defense strategies. Thus, in this paper, we focus on developing mechanisms to localize a jammer. We first conduct jamming effect analysis to examine how a hearing range, e.g., the area from which a node can successfully receive and decode the packet, alters with the jammer's location and transmission power. Then, we show that the affected hearing range can be estimated purely by examining the network topology changes caused by jamming attacks. As such, we solve the jammer location estimation by constructing a least-squares problem, which exploits the changes of the hearing ranges. Compared with our previous iterativesearch-based virtual force algorithm, our proposed hearing-range-based algorithm exhibits lower computational cost (i.e., one-step instead of iterative searches) and higher localization accuracy.

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“…B-MAC [8] is a modular and flexible channel access method. The objective of B-MAC is to reduce the idle time of the sensors.…”

Section: Related Workmentioning

confidence: 99%

A Low Latency MAC Scheme for Event-Driven Wireless Sensor Networks

Guyennet

Felea

et al. 2007

Mobile Ad-Hoc and Sensor Networks

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Abstract. In this paper, we present a low latency media access control scheme which we call LLMAC (Low Latency MAC) for event-driven wireless sensor networks (WSN). In this kind of WSN, sensors do not regularly send data to the sink. They send a burst data only when there is an event in the monitoring area. It takes time for this burst data to arrive to the sink. Normally, these events are critical and we hope to obtain the information on the event in the shortest delay. Hence, the latency is considered to be a crucial requirement in event-driven WSN contrary to the traditional wireless networks where the fairness is the most important requirement. Our proposal LLMAC makes a trade-off between fairness and latency in order to offer a shorter latency transmission when certain events happen. The performance evaluation shows that our proposal reduces the latency in comparison to existing MAC protocols.

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Versatile low power media access for wireless sensor networks

Cited by 2,742 publications

References 21 publications

MUSTER: Adaptive Energy-Aware Multisink Routing in Wireless Sensor Networks

MUSTER: Adaptive Energy-Aware Multisink Routing in Wireless Sensor Networks

Wireless Jamming Localization by Exploiting Nodes’ Hearing Ranges

A Low Latency MAC Scheme for Event-Driven Wireless Sensor Networks

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