Abstract
Internet of Things (IoT) is the next big step in evolution of Internet. IoT is a gradual upgrade of wireless sensor networks of embedded devices. Embedded sensor nodes can be directly addressed (IPv6) through the Internet owing to the 6LoWPAN adaptation layer. IETF working group Routing Over Low Power and Lossy Networks (ROLL) in 2012 introduced RPL–IPv6 Routing Protocol for low-power and lossy networks to provide efficient routing solution for 6LoWPAN abstraction layer running over IEEE 802.15.4 providing PHY and MAC for Low-Rate Wireless Personal Area Network. All the protocols including RPL insure minimal energy utilization of the sensors. RPL builds destination oriented directed acyclic graph (DODAG) using the objective function (OF). This objective function is responsible for fixation of rank of node and selection of best DAG and best parent. Large network of sensor nodes can be seen as a colony of ants. The Ant Colony Optimization is an important Swarm Intelligence technique under the paradigm of Computational Intelligence. It is inspired by collective intelligence of large number of homogeneous agents (ants). This optimization can be implemented toward selection of most efficient route and hence the preparation of DODAG. In this paper, we implement Ant Colony Optimization in RPL and present the results based on simulation using COOJA simulator in Contiki operating system.
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Thapar, P., Batra, U. (2018). Implementation of Ant Colony Optimization in Routing Protocol for Internet of Things. In: Panda, B., Sharma, S., Batra, U. (eds) Innovations in Computational Intelligence . Studies in Computational Intelligence, vol 713. Springer, Singapore. https://doi.org/10.1007/978-981-10-4555-4_10
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DOI: https://doi.org/10.1007/978-981-10-4555-4_10
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