What question did this study set out to answer?

To develop an optimized and secure routing framework for SDN-enabled Internet of Things sensor networks by integrating a Markov Chain Model with reinforcement learning.

August 20, 2026International Journal of Communication Systems

Modeling a Software‐Defined Network for Analyzing Route and Energy With Sensor Nodes

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Authors

MDM. Meenakshi DhanalakshmiBannari Amman Institute of Technology MKM. KarthigaSaveetha University

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Implication

Network modeling study demonstrates optimized routing and energy efficiency in SDN-enabled sensor networks, indicating improved wireless IoT network lifetime.

Key Points

To develop an optimized and secure routing framework for SDN-enabled Internet of Things sensor networks by integrating a Markov Chain Model with reinforcement learning.
Designed a routing algorithm (MCM-RLA) combining Markov Chain modeling with reinforcement learning within an SDN controller architecture.
Formulated reward functions aligned with Quality of Service (QoS) metrics to select successive optimal routing paths dynamically.
Evaluated performance against prevailing routing approaches across packet delivery rate (PDR), network lifetime, routing overhead, energy efficiency, and latency.
Enhanced packet delivery rate and energy efficiency compared to conventional wireless sensor routing protocols.
Extended overall network lifetime while reducing routing overhead and transmission delay across sensor nodes.

Cite This Study

Dhanalakshmi et al. (2026) studied this question.

synapsesocial.com/papers/6a86b5da8a91293e6a1cd709 https://doi.org/10.1002/dac.70556

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Implication

Network modeling study demonstrates optimized routing and energy efficiency in SDN-enabled sensor networks, indicating improved wireless IoT network lifetime.

Modeling a Software‐Defined Network for Analyzing Route and Energy With Sensor Nodes

Discussion

Member takes

Implication

Key Points

Cite This Study

Modeling a Software‐Defined Network for Analyzing Route and Energy With Sensor Nodes

Discussion

Member takes

Implication

Key Points

Cite This Study

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