TY - GEN
T1 - Dynamic multi-hop routing protocol for unbalanced sized clusters in wireless sensor networks
AU - Misbahuddin,
AU - Ratna, Anak Agung Putri
AU - Sari, Riri Fitri
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - Wireless sensor networks is a rapidly emerging technology implemented in various applications for several domains. One of the important considerations in wireless sensor networks is the network lifetime because the sensor nodes are battery powered and difficult to replace or recharge when they are deployed in dangerous or inaccessible environments. Various node clustering approaches have been implemented to achieve energy efficiency in order to prolong the network lifetime. However, the approaches are only suitable for a certain application scope. The data similarity aware node clustering is a specific application that does not consider load balancing of clusters, so that it also requires a proper routing protocol. The main challenge in such clustering approach is that some nodes are far apart from other nodes and the network structure change dynamically. Therefore, it is required a dynamic multi hop routing protocol to address the problem. In this work, we propose a dynamic multi-hop routing protocol based on the rules incorporating fuzzy system and particle swarm optimization to obtain the priority factor of cluster head election. Our proposed Dynamic Multi-Hop Routing for Unbalanced Sized Cluster (DMHR-USC) protocol was compared against the K-hop Clustering Algorithm (KHOPCA) protocol to justify the performance. The DMHR-USC can reach the network lifetime longer than the KHOPCA in all terms of the First Node Dies (FND), Half of Nodes have Dead (HND), and the Last Node Dies (LND). Therefore, the DMHR-USC can prolong the network lifetime in a relative significant manner.
AB - Wireless sensor networks is a rapidly emerging technology implemented in various applications for several domains. One of the important considerations in wireless sensor networks is the network lifetime because the sensor nodes are battery powered and difficult to replace or recharge when they are deployed in dangerous or inaccessible environments. Various node clustering approaches have been implemented to achieve energy efficiency in order to prolong the network lifetime. However, the approaches are only suitable for a certain application scope. The data similarity aware node clustering is a specific application that does not consider load balancing of clusters, so that it also requires a proper routing protocol. The main challenge in such clustering approach is that some nodes are far apart from other nodes and the network structure change dynamically. Therefore, it is required a dynamic multi hop routing protocol to address the problem. In this work, we propose a dynamic multi-hop routing protocol based on the rules incorporating fuzzy system and particle swarm optimization to obtain the priority factor of cluster head election. Our proposed Dynamic Multi-Hop Routing for Unbalanced Sized Cluster (DMHR-USC) protocol was compared against the K-hop Clustering Algorithm (KHOPCA) protocol to justify the performance. The DMHR-USC can reach the network lifetime longer than the KHOPCA in all terms of the First Node Dies (FND), Half of Nodes have Dead (HND), and the Last Node Dies (LND). Therefore, the DMHR-USC can prolong the network lifetime in a relative significant manner.
KW - Fuzzy system
KW - Multi-hop
KW - Particle swarm optimization
KW - Routing
KW - Unbalanced sized cluster
UR - http://www.scopus.com/inward/record.url?scp=85045940449&partnerID=8YFLogxK
U2 - 10.1109/WPMC.2017.8301834
DO - 10.1109/WPMC.2017.8301834
M3 - Conference contribution
AN - SCOPUS:85045940449
T3 - International Symposium on Wireless Personal Multimedia Communications, WPMC
SP - 337
EP - 343
BT - Proceedings - 20th International Symposium on Wireless Personal Multimedia Communications, WPMC 2017
PB - IEEE Computer Society
T2 - 20th International Symposium on Wireless Personal Multimedia Communications, WPMC 2017
Y2 - 17 December 2017 through 20 December 2017
ER -