Affiliations: [a] Department of Computer Science and Engineering, Nirma University, Gujarat, India | [b] Space Application Centre (SAC), Indian Space Research Organization (ISRO), Ahmedabad, India | [c] Indian Institute of Space Science and Technology, Kerala, India
Correspondence:
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Corresponding author: Sachin Gajjar, Department of Computer Science and Engineering, Nirma University, Gujarat, India. E-mail:[email protected]
Abstract: This paper introduces Fuzzy-Cross, a decision making and
information-sharing architecture for wireless sensor networks (WSN) that
enables the protocols to achieve energy efficiency, reliability, and low
data latency. FUCR retains a layered structure with each layer matching to a
communication function to provide a practical and simple design. The
administrative plane provided by FUCR collects residual energy from physical
layer, data delivery, and channel assessment records from data link layer,
packet dispatch rate from network layer and sensitivity of sensing unit from
application layer. The information collected is used as input descriptors
for running fuzzy logic. Output of the fuzzy logic assists physical layer
protocol to decide node's transmit power; data link layer protocol to decide
retransmission time out, back off time and duty cycle; network layer to
determine chance of the node to become a relay node and application layer to
determine chance of node to become a reporting node. To investigate the
extent to which Fuzzy-Cross meets its goals, it is implemented on top of
ZigBee standard. Simulation results demonstrated that Fuzzy-Cross with
ZigBee outperforms both (i) ADaptive Access Parameters Tuning (ADAPT) with
Zigbee and (ii) standard ZigBee without any modifcations. For a single hop
network Fuzzy-Cross is up to 12% more energy efficient compared to
ADAPT. Delivery ratio of Fuzzy-Cross is up to 12% more and data latency
is up to 19% less compared to ADAPT. Similar trend is seen for multi-hop
network and for a wide range of operating conditions.
Keywords: Wireless sensor network, fuzzy logic, cross layer, energy efficiency, data latency, ZigBee