TY - GEN
T1 - On the interplay between clustering and power control in multihop wireless networks
AU - Mir, Zeeshan Hameed
AU - Lim, Keun Woo
AU - Ko, Young Bae
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/1/1
Y1 - 2014/1/1
N2 - Topology control offers many advantages for wireless networks such as reduced energy cost, simplified communication graph and network-wide connectivity. There are mainly two methods for managing the network topology. In clustering, a hierarchy of backbone nodes is selected to improve on the systems scalability and network lifetime whereas in power control each node adjusts its transmission power to achieve certain desirable properties of the resulting topology. While the focus of the former approach is to find an ideal number of the backbone nodes, the main objective of the later approach is to estimate a minimal power level which can solve multi-objective design problem. There have been several topology control protocols proposed however they miss the potential of combining both approaches. In this paper we propose Two-Tiered Topology Control (TTTC) protocol, a generic framework which combines the clustering and power control approach towards topology control and evaluate different conditions under which it performs well. TTTC operation is divided into two phases. During the first phase, a parameterized clustering algorithm is executed to obtain clusters of varying properties. At the end of first phase, the network is organized into two tiers. The backhaul-tier consists of cluster-head nodes while the connectivity-tier contains the cluster-members. In the second phase, each cluster-head runs a local MST-based power control algorithm. Simulation results show that proposed framework achieves efficient trade-off in terms of energy cost, neighbor count and hop count while maintaining fully connected network. Moreover, the framework relies on local available information with lower communication overhead.
AB - Topology control offers many advantages for wireless networks such as reduced energy cost, simplified communication graph and network-wide connectivity. There are mainly two methods for managing the network topology. In clustering, a hierarchy of backbone nodes is selected to improve on the systems scalability and network lifetime whereas in power control each node adjusts its transmission power to achieve certain desirable properties of the resulting topology. While the focus of the former approach is to find an ideal number of the backbone nodes, the main objective of the later approach is to estimate a minimal power level which can solve multi-objective design problem. There have been several topology control protocols proposed however they miss the potential of combining both approaches. In this paper we propose Two-Tiered Topology Control (TTTC) protocol, a generic framework which combines the clustering and power control approach towards topology control and evaluate different conditions under which it performs well. TTTC operation is divided into two phases. During the first phase, a parameterized clustering algorithm is executed to obtain clusters of varying properties. At the end of first phase, the network is organized into two tiers. The backhaul-tier consists of cluster-head nodes while the connectivity-tier contains the cluster-members. In the second phase, each cluster-head runs a local MST-based power control algorithm. Simulation results show that proposed framework achieves efficient trade-off in terms of energy cost, neighbor count and hop count while maintaining fully connected network. Moreover, the framework relies on local available information with lower communication overhead.
U2 - 10.1109/AICCSA.2014.7073214
DO - 10.1109/AICCSA.2014.7073214
M3 - Conference contribution
AN - SCOPUS:84988220995
T3 - Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA
SP - 310
EP - 317
BT - 2014 IEEE/ACS 11th International Conference on Computer Systems and Applications, AICCSA 2014
PB - IEEE Computer Society
T2 - 2014 11th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2014
Y2 - 10 November 2014 through 13 November 2014
ER -