Improving Energy Adaptivity of Constructive Interference-Based Flooding for WSN-AF

Constructive interference (CI) is a synchronous transmission technique for multiple senders transmitting the same packet simultaneously in wireless sensor networks (WSNs). CI enables fast and reliable network flooding in order to reduce the scheduling overhead of MAC protocols, to achieve accurate time synchronization, to improve link quality of lossy links, and to realize efficient data collection. By achieving microsecond level time synchronization, Glossy realizes millisecond level CI-based flooding and 99% reliability. However, Glossy produces substantial unnecessary data forwarding, which significantly reduces the network lifetime. This is a very critical problem, especially in energy-limited large-scale wireless sensor networks for agriculture and forestry (WSN-AF) system. In this paper, we present an energy adaptive CI-based flooding protocol (EACIF) by exploiting CI in WSN-AF. EACIF proposes a distributed active nodes selection algorithm (ANSA) to reduce redundant transmissions, thereby significantly reducing energy consumption and flooding latency. We estimate the performance of EACIF both with real data traces and with uniformly distributed topology. Simulation results show that EACIF achieves almost the same packet reception ratio (PRR) as Glossy (e.g., 99%), while reducing 63.96% energy consumption. EACIF also reduces 25% flooding latency. When the packet interval is 30 seconds, EACIF achieves 0.11% duty cycle.

[1]  Xiangyang Li,et al.  TriggerCast : Enabling Wireless Constructive Collisions , 2013 .

[2]  Andreas Terzis,et al.  Wireless ACK Collisions Not Considered Harmful , 2008, HotNets.

[3]  Hiroyuki Morikawa,et al.  Low-Power, End-to-End Reliable Collection Using Glossy for Wireless Sensor Networks , 2013, 2013 IEEE 77th Vehicular Technology Conference (VTC Spring).

[4]  Marcus Chang,et al.  Forwarder Selection in Multi-transmitter Networks , 2013, 2013 IEEE International Conference on Distributed Computing in Sensor Systems.

[5]  Kamin Whitehouse,et al.  Flash Flooding: Exploiting the Capture Effect for Rapid Flooding in Wireless Sensor Networks , 2009, IEEE INFOCOM 2009.

[6]  Yunhao Liu,et al.  QoF: Towards Comprehensive Path Quality Measurement in Wireless Sensor Networks , 2014, IEEE Transactions on Parallel and Distributed Systems.

[7]  David E. Culler,et al.  Design of an application-cooperative management system for wireless sensor networks , 2005, Proceeedings of the Second European Workshop on Wireless Sensor Networks, 2005..

[8]  Wei Xi,et al.  GenePrint: Generic and Accurate Physical-Layer Identification for UHF RFID Tags , 2016, IEEE/ACM Transactions on Networking.

[9]  Yunhao Liu,et al.  Beyond Trilateration: On the Localizability of Wireless Ad-Hoc Networks , 2009, INFOCOM 2009.

[10]  Gyula Simon,et al.  The flooding time synchronization protocol , 2004, SenSys '04.

[11]  Lothar Thiele,et al.  Low-power wireless bus , 2012, SenSys '12.

[12]  John S. Heidemann,et al.  RBP: robust broadcast propagation in wireless networks , 2006, SenSys '06.

[13]  Xiang-Yang Li,et al.  Geometric spanners for wireless ad hoc networks , 2002, Proceedings 22nd International Conference on Distributed Computing Systems.

[14]  Lothar Thiele,et al.  Efficient network flooding and time synchronization with Glossy , 2011, Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks.

[15]  Yunhao Liu,et al.  L2: Lazy forwarding in low duty cycle wireless sensor networks , 2012, 2012 Proceedings IEEE INFOCOM.

[16]  Bo Jiang,et al.  Opportunistic Flooding in Low-Duty-Cycle Wireless Sensor Networks with Unreliable Links , 2009, IEEE Transactions on Computers.

[17]  K. Leentvaar,et al.  The Capture Effect in FM Receivers , 1976, IEEE Trans. Commun..

[18]  Federico Ferrari,et al.  Chaos: versatile and efficient all-to-all data sharing and in-network processing at scale , 2013, SenSys '13.

[19]  Ting Zhu,et al.  Exploring Link Correlation for Efficient Flooding in Wireless Sensor Networks , 2010, NSDI.

[20]  Shaojie Tang,et al.  Canopy closure estimates with GreenOrbs: sustainable sensing in the forest , 2009, SenSys '09.

[21]  Yunhao Liu,et al.  Exploiting Constructive Interference for Scalable Flooding in Wireless Networks , 2013, IEEE/ACM Transactions on Networking.

[22]  Yunhao Liu,et al.  CitySee: Urban CO2 monitoring with sensors , 2012, 2012 Proceedings IEEE INFOCOM.

[23]  Peng-Jun Wan,et al.  Distributed Construction of Connected Dominating Set in Wireless Ad Hoc Networks , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[24]  Andreas Terzis,et al.  Design and evaluation of a versatile and efficient receiver-initiated link layer for low-power wireless , 2010, SenSys '10.

[25]  Kamesh Munagala,et al.  Message in Message (MIM): A Case for Shuffling Transmissions in Wireless Networks , 2008, HotNets.

[26]  Mun Choon Chan,et al.  Splash : Fast Data Dissemination with Constructive Interference in Wireless Sensor Networks , 2013 .