TY  - GEN
A1  - Aranda, Juan
A1  - Schölzel, Mario
A1  - Mendez, Diego
A1  - Carrillo, Henry
T1  - An energy consumption model for multiModal wireless sensor networks based on wake-up radio receivers
T2  - 2018 IEEE Colombian Conference on Communications and Computing (COLCOM)
N2  - Energy consumption is a major concern in Wireless Sensor Networks. A significant waste of energy occurs due to the idle listening and overhearing problems, which are typically avoided by turning off the radio, while no transmission is ongoing. The classical approach for allowing the reception of messages in such situations is to use a low-duty-cycle protocol, and to turn on the radio periodically, which reduces the idle listening problem, but requires timers and usually unnecessary wakeups. A better solution is to turn on the radio only on demand by using a Wake-up Radio Receiver (WuRx). In this paper, an energy model is presented to estimate the energy saving in various multi-hop network topologies under several use cases, when a WuRx is used instead of a classical low-duty-cycling protocol. The presented model also allows for estimating the benefit of various WuRx properties like using addressing or not.
KW  - Energy efficiency
KW  - multimodal wireless sensor network
KW  - low-duty-cycling
KW  - wake-up radio
Y1  - 2018
SN  - 978-1-5386-6820-7
U6  - https://doi.org/10.1109/ColComCon.2018.8466728
PB  - IEEE
CY  - New York
ER  - 
TY  - GEN
A1  - Diaz, Sergio
A1  - Mendez, Diego
A1  - Schölzel, Mario
T1  - Dynamic Gallager-Humblet-Spira Algorithm for Wireless Sensor Networks
T2  - 2018 IEEE Colombian Conference on Communications and Computing (COLCOM)
N2  - The problem of constructing and maintaining a tree topology in a distributed manner is a challenging task in WSNs. This is because the nodes have limited computational and memory resources and the network changes over time. We propose the Dynamic Gallager-Humblet-Spira (D-GHS) algorithm that builds and maintains a minimum spanning tree. To do so, we divide D-GHS into four phases, namely neighbor discovery, tree construction, data collection, and tree maintenance. In the neighbor discovery phase, the nodes collect information about their neighbors and the link quality. In the tree construction, D-GHS finds the minimum spanning tree by executing the Gallager-Humblet-Spira algorithm. In the data collection phase, the sink roots the minimum spanning tree at itself, and each node sends data packets. In the tree maintenance phase, the nodes repair the tree when communication failures occur. The emulation results show that D-GHS reduces the number of control messages and the energy consumption, at the cost of a slight increase in memory size and convergence time.
KW  - Minimum spanning tree
KW  - Tree maintenance
Y1  - 2018
SN  - 978-1-5386-6820-7
PB  - IEEE
CY  - New York
ER  -