Two-Tiered Wireless Sensor Network (TT-WSN) is a kind of heterogeneous network typically proposed to improve the lifetime longevity of the network. In TT-WSN the lower tier consists of sensor nodes (SN), which are mainly responsible for sensing the environment and forwarding the data to its one hop neighbor relay node (RN). While the upper tier is constituent of more power affluent relay nodes (RNs), which deliver the data to the base station through potentially multiple connected relay nodes in a multi-hop fashion. As relay nodes are more expensive, it is therefore desirable to deploy a minimum number of such nodes so that every sensor node has at least one relay node as its one-hop neighbor and all the relay nodes form a connected network. Unfortunately the problem of finding such a minimum set of relay nodes is NP-Hard. Thus, an approximation based algorithm is required to solve the problem in polynomial time with good approximation ratio. This study presents a fast and efficient approximation algorithm to solve the problem in polynomial
time with a polynomial time worst-case time complexity of O(N^3), where N is the number of sensor nodes in the deployment region. The proposed algorithm is proved here to be a 3-approximation algorithm and the performance of the algorithm is compared with the existing algorithms through simulations. The extensive simulation results show that our algorithm outperforms the existing algorithms in terms of number of relay nodes deployed.
Moreover, this study also proposes an energy efficient broadcast scheme for Two-Tiered Wireless Sensor Network (TT-WSN) that exploits cooperative communication. Cooperative communication allows nodes in the network to cooperate with each other and form a
virtual MIMO system by sharing their antennas. Cooperative communication can provide significant energy savings for the broadcast process in (TT-WSN). The proposed scheme selects a smaller subset of relay nodes for forwarding broadcast messages by exploiting coop-
erative communication. Extensive simulation study reveals significant reduction in energy consumption is achieved by reducing the redundant transmissions of the same message.