EYES – Energy Efficient Sensor Networks

Havinga, Paul J.M.; Etalle, Sandro; Karl, Holger; Petrioli, Chiara; Zorzi, Michele; Kip, Harry J.; Lentsch, Thomas

doi:10.1007/978-3-540-39867-7_20

Cited by 14 publications

(5 citation statements)

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“…Each node has communication range of 30m. Power consumption for transmission is set to 24mW and that for reception is set to 14.4mW, as in the EYES sensor prototypes [10]. The sensors that perform a look-up operation and then send a message to the server are uniformly chosen between the deployed sensors.…”

Section: Resultsmentioning

confidence: 99%

Fault-Tolerant and Load Balancing Localization of Services in Wireless Sensor Networks

Nidito

Battelli

Basagni

2007

2007 IEEE 66th Vehicular Technology Conference

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Heterogeneous wireless sensor networks are made up of different kinds of nodes. Some nodes, the sensors, are used as an interface to the physical environment. Other nodes act instead as servers, providing various services to the sensors. In this paper we define an architecture to enable the sensors to efficiently localize the services, and hence the servers. Our is a two-tier server architecture. The first tier is made up of the actual servers. The second tier is formed by nodes that are basically standard nodes (like the sensors). These nodes know the current position of the servers (they are called server locators). Sensors needing service query the server locators to find the corresponding service. The service locator sends a service position to the sensor. Finally, once got ahold of a server location, a sensor uses the service directly. Our server architecture provides load balancing (of queries to the servers) and is tolerant to server faults. Sensor nodes are endowed with caches to maintain the location of popular services. Experiments demonstrate the effectiveness of using caches at the sensor nodes.

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Section: Resultsmentioning

confidence: 99%

Fault-Tolerant and Load Balancing Localization of Services in Wireless Sensor Networks

Nidito

Battelli

Basagni

2007

2007 IEEE 66th Vehicular Technology Conference

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“…It can be concluded that time-outs are an effective way to resolve the idle listening issue under variable load of traffic. The implementation of T-MAC has shown energy conservation both in simulation in OMNET++ [55] and on real hardware (EYES nodes) [56]. It is shown that during a high load, nodes communicate without sleeping however, during low traffic load the nodes will use their radios as little as 2.5% of the time, resulting in 96% of energy conservation compared to a traditional MAC protocol.…”

Section: • Expiration Of Periodic Frame • Message Reception • Collisimentioning

confidence: 99%

Reinforcement Learning Based Adaptive Duty Cycling in LR-WPANs

et al. 2020

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For conserving energy, duty cycle is defined by setting up the active and sleep periods of network nodes. In beacon enabled networks, to provide support for duty cycle, the IEEE 802.15.4 standard uses optional super-frame structure. This duty cycle is usually fixed and does not consider the topology changes that often occur in dynamic sensor networks. In this paper, existing energy conserving duty cycling approaches for 802.15.4 networks especially the adaptive duty cycling techniques for wireless sensor networks are summed up. Also, this paper highlights the shortcomings of the proposals in the literature, such as induced additional latency, so that they may not support the practical scenarios of Internet of Things (IoT). Further, this study highlights a gross shortcoming that relative performance comparison of RL-based proposals cannot be performed without using a benchmarking framework and real test-bed environment. In this paper, we have presented the future research directions that would lay the foundation for successful development of energy efficient RL-based duty-cycling techniques.

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“…SensorSimulator is developed on the discrete event simulator OMNeT++ 39, mainly intended to support sensor network simulations. The simulator contains a model of the EYES wireless sensor node 40. Furthermore, the simulator has the same limits as the EYES nodes.…”

Section: Performance Analysismentioning

confidence: 99%

Energy efficient and QoS aware medium access control for wireless sensor networks

Yahya

Ben‐Othman

2010

Concurrency and Computation

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SUMMARYEnabling quality of service (QoS) applications over battery-constrained wireless sensor networks (WSNs) poses significant challenges, because of the special characteristics of such networks. Developing real-time applications for WSNs necessitates the development of new communication protocols capable of achieving application-specific QoS and at the same time save energy. In this paper, we continue our previous work on developing and improving our EQ-MAC protocol, which is designed specifically for WSNs to reduce energy consumption and provides QoS guarantees through the use of the service differentiation concept. The proposed protocol consists of two subprotocols: Classifier MAC (C-MAC) and Channel Access MAC (CA-MAC). C-MAC is responsible of classifying gathered data at sensor nodes based on its importance. The CA-MAC is an energy conserving medium access mechanism which uses a hybrid scheduling technique. CA-MAC saves energy by differentiating between control and data messages. Data messages are assigned scheduled slots with no contention (here we have to emphasize that slots are assigned only to those nodes that have data to send, this allows an efficient energy use of the Time Division Multiple Access (TDMA) slots), whereas short periodic control messages are assigned random access slots. To study the performance of the EQ-MAC protocol, we have conducted several simulation experiments on Network Simulator (NS-2) to evaluate and compare the performance of our protocol against S-MAC and Q-MAC protocols. Simulation results demonstrate that EQ-MAC outperforms the other two protocols and achieves a significant improvement in terms of the energy expenditure and delivery ratio. Under prioritized traffic, EQ-MAC is comparable to Q-MAC in average latency, while achieving less energy consumption. Copyright

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EYES – Energy Efficient Sensor Networks

Cited by 14 publications

References 0 publications

Fault-Tolerant and Load Balancing Localization of Services in Wireless Sensor Networks

Fault-Tolerant and Load Balancing Localization of Services in Wireless Sensor Networks

Reinforcement Learning Based Adaptive Duty Cycling in LR-WPANs

Energy efficient and QoS aware medium access control for wireless sensor networks

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