An Efficient Scheduling Method Based on Pulse-coupled Oscillator Model for Heterogeneous Large-scale Wireless Sensor Networks
Author(s) -
Yamanaka Soichiro,
Masafumi Hashimoto,
Naoki Wakamiya
Publication year - 2016
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2016.04.271
Subject(s) - computer science , wireless sensor network , scheduling (production processes) , distributed computing , computer network , real time computing , economics , operations management
Wireless sensor networks (WSNs) have been common networking technologies for data gathering applications. In order to collect necessary data effectively, such applications require large-scale WSNs many sensor nodes are deployed widely. As its solution, IEEE 802.11ah is promising. However, it operates at sub 1GHz band that is license-free, which may result in that different service providers deploy WSNs for different purposes. This incurs serious collisions due to hidden nodes. Unfortunately, they often refuse cooperation among the others due to their service policies. Therefore, self-organized scheduling methods are needed without proactive cooperation. To this end, in this paper, we propose a self-organized scheduling method for large-scale WSNs, which is based on the pulse-coupled oscillator model. To avoid collisions effectively, the proposed method utilizes a phase response function that has attractors corresponding to time slots and a random mechanism for slot selection. Through simulation-based evaluation, we demonstrate that the proposed method can collect about 90% of data in a situation sensor nodes have different cycles of data gathering while achieving a reasonable convergence time. We also show its good flexibility for environmental changes
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom