This study addresses the management of Heterogeneous Sensor Networks (HSNs) in an area of interest. The use of sensors in our day-to-day life has increased dramatically, and in ten to fifteen years the sensor nodes may cover the whole world, and could be accessed through the Internet. Currently, sensors are in use for such things as vehicular movement tracking, nuclear power plant monitoring, fire incident reporting, traffic controlling, and environmental monitoring. There is vast potential for various applications, such as entertainment, drug trafficking, border surveillance, crisis management, under water environment monitoring, and smart spaces. So this research area has a lot of potential. The sensors have limited resources and researchers have invented methods to deal with the related issues. But security and routing in sensor networks and clustering of sensors are handled separately by past researchers. Since route selection directly depends on the position of the nodes and sets of resources may change dynamically, so cumulative and coordinated activities are essential to maintain the organizational structure of laid out sensors. So for conserving the sensor network energy, it is better if we follow a holistic approach taking care of both clustering and secure routing. In this research, we have developed an efficient key management approach with an improved tree routing algorithm for clustered heterogeneous sensor networks. The simulation results show that this scheme offers good security and uses less computation with substantial savings in memory requirements, when compared with some of other key management, clustering and routing techniques. The low end nodes are simple and low cost, while the high end nodes are costly but provide significantly more processing power. In this type of sensor network, the low end nodes are clustered and report to a high end node, which in turn uses a network backbone to route data to a base station. Initially, we partition the given area into Voronoi clusters. Voronoi diagrams generate polygonal clusters using Euclidian distance. Since sensor networks routing is multi-hopped, we apply a tabu search to adjust some of the nodes in the Voronoi clusters. The Voronoi clusters then work with hop counts instead of distance. When some event occurs in the network, low end nodes gather and forward data to cluster heads using the Secure Improved Tree Routing approach. The routing amongst the low end nodes, high end nodes and the base station is made secure and efficient by applying a 2-way handshaking secure Improved Tree Routing (ITR) technique. The secure ITR data routing procedure improves the energy efficiency of the network by reducing the number of hops utilized to reach the Base Station. We gain robustness and energy efficiency by reducing the vulnerability points in the network by employing alternatives to shortest path tree routing. In this way a complete solution is provided to the travelling data in a two tier heterogeneous sensor network by reducing the hop count, making it secure and energy efficient. Empirical evaluations show how the described algorithm performs with respect to delivery ratio, end to end delays, and energy usage.