Balancing Power Consumption in IoT Devices by Using Variable Packet Size

Currently, IoT devices are becoming more and more popular, being deployed in different scenarios such as monitoring the power consumption of a house or the state of an outdoor parking spot. These networks tend to be densely populated by a huge amount of sensors that send really short messages. Given these characteristics, their main problem is the great variability and unpredictability of battery lifetime, when they cannot be plugged to a power outlet. In this paper, we analyze the mote behaviour on a real IoT network and use the extracted data to propose a mechanism to distribute the power consumption more equally between all motes, regardless the number of messages each one sends. This new proposal decreases the numbers of interventions required to replace batteries, minimizing costs and increasing network lifetime.

[1]  Enrico Macii,et al.  Improving the efficiency of memory partitioning by address clustering , 2003, 2003 Design, Automation and Test in Europe Conference and Exhibition.

[2]  Mani Srivastava,et al.  Energy efficient routing in wireless sensor networks , 2001, 2001 MILCOM Proceedings Communications for Network-Centric Operations: Creating the Information Force (Cat. No.01CH37277).

[3]  Qin Wang,et al.  A Realistic Energy Consumption Model for TSCH Networks , 2014, IEEE Sensors Journal.

[4]  Michele Rossi,et al.  On the Performance of Lossy Compression Schemes for Energy Constrained Sensor Networking , 2014, TOSN.

[5]  Koen Langendoen,et al.  An adaptive energy-efficient MAC protocol for wireless sensor networks , 2003, SenSys '03.

[6]  David A. Huffman,et al.  A method for the construction of minimum-redundancy codes , 1952, Proceedings of the IRE.

[7]  Shahram Latifi,et al.  A survey on data compression in wireless sensor networks , 2005, International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II.

[8]  Kah Phooi Seng,et al.  A Simple Data Compression Algorithm for Wireless Sensor Networks , 2012, SOCO.