Abstract

Opportunistic Routing (OR) scheme increases the transmission reliability despite the lossy wireless radio links by exploiting the broadcast nature of the wireless medium. However, OR schemes in low power Wireless Sensor Network (WSN) leads to energy drain in constrained sensor nodes due to constant overhearing, periodic beaconing for Neighbourhood Management (NM) and increase in packet header length to append priority wise sorted Forwarding Candidates Set (FCS) prior to data transmission. The timer-based coordination mechanism incurs the least overhead to coordinate among the FCS that has successfully received the data packet for relaying the data in a multi-hop manner. This timer-based mechanism suffers from duplicate transmissions if the FCS is either not carefully selected or coordinated. The focus of this work is to propose a hybrid opportunistic energy efficient routing design for large scale, low power and lossy WSN. This design avoids periodic 'hello' beacons for NM, limits constant overhearing and increase in packet header length. There are two modes of operation i) opportunistic ii) unicast mode. The sender node adopts opportunistic forwarding for its initial data packet transmission and instead of pre-computing the FCS, it is dynamically computed in a completely distributed manner. The eligible nodes to be part of FCS will be neighbour nodes at lower corona level than the sender with respect to the sink and remaining energy above the minimum threshold. The nodes part of FCS based on crosslayered multi-metrics and fuzzy decision logic determines its priority level to compute Dynamic Holding Delay (DHD) for effective timer coordination. The differentiated back off implementation along with DHD enables the higher priority candidate that had received data packet to forward the packet first and facilitates others to cancel its timer upon overhearing. The sender node switches to unicast mode of forwarding for successive transmissions by choosing the forwarding node with maximum trust value as it denotes the stability of the temporally varying link with respect to the forwarder. The sender node will revert to opportunistic mode to increase transmission reliability in case of link-level transmission error or no trustworthy forwarders. Simulation results in NS2 show significant increase in Packet Delivery Ratio (PDR),decrease in both average energy consumption per node and Normalized Energy Consumption (NEC) per packet in comparison with existing protocols.

Highlights

  • The low power, lossy WSN consists of tiny embedded resource-constrained sensor motes limited in energy, bandwidth, memory and computational power [1]

  • We proposed an Opportunistic Scalable and Energy-efficient Routing protocol (OPSER) algorithm for lossy WSN that uses a hybrid approach based on the trustworthiness of forwarding candidate to switch between opportunistic and unicast modes of operation

  • The proposed protocol is found suitable for large-scale deployment despite problems such as lossy links and constrained sensor nodes with limited available energy

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Summary

INTRODUCTION

The low power, lossy WSN consists of tiny embedded resource-constrained sensor motes limited in energy (battery-powered), bandwidth, memory and computational power [1]. The problem of time-varying channel characteristics in thewireless medium are because the radio signal propagation is subjected to large scale fading caused by reflection, scattering, diffraction and small scale fading caused by multi-path signals, Doppler effect or interferences. This results in fluctuations in signal strength and intermittent link connectivity [2]. The neighbouring nodes within communication range can overhear any transmission in wireless medium, since this medium is broadcast in nature This property is utilized in OR approach and it exploits the spatial and temporal characteristics of wireless networks.

RELATED WORK
PROBLEM STATEMENT
HYBRID OPSER DESIGN
19: Discard CID
2: NB: Number of Backoff 3: BE:Backoff Exponent 4: macMinBE
Forward Data Packet function
Metrics computation and Fuzzy Decision Logic for FCS
Link Quality Indicator Metric
Trust degree Metric
Network Model
Energy Cost Modelling of CID Algorithm
End to End delivery probability analysis
PERFORMANCE EVALUATION
Performance metrics
Impact of radio propagation modelling on packet reception probability
PDR vs Traffic Rate
Average Energy Consumed vs Traffic Rate
Findings
CONCLUSIONS
Full Text
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