**1. Introduction**

Wireless sensor networks (WSNs) are composed of many homogeneous or heterogeneous sensor nodes with limited resources. Routing techniques are the most important issue for networks where resources are limited. WSNs technology's growth in the computation capacity requires these sensor nodes to be increasingly equipped to handle more complex functions. Each sensor is mostly limited in their energy level, processing power and sensing ability. Thus, a network of these sensors gives rise to a more robust, reliable and accurate network. Lots of studies on WSNs have been carried out showing that this technology is continuously finding new application in various areas, like remote and hostile regions as seen in the military for battle field surveillance, monitoring the enemy territory, detection of attacks and security etiquette. Other applications of these sensors are in the health sectors where patients can wear small sensors for physiological data and in deployment in disaster prone areas for environmental monitoring. It is noted that, to maintain a reliable information delivery, data aggregation and information fusion that is necessary for efficient and effective communication between these sensor nodes. Only processed and concise information should be delivered to the sinks to reduce communications energy, prolonging the effective network lifetime with optimal data delivery.

An inefficient use of the available energy leads to poor performance and short life cycle of the network. To this end, energy in these sensors is a scarce resource and must be managed in an efficient manner. In this chapter we propose Hierarchical Adaptive Balanced energy efficient Routing Protocol (HABRP) to decrease probability of failure nodes and to prolong the time interval before the death of the rst node (stability period) and increasing the lifetime in heterogeneous WSNs, which is crucial for many applications. We study the

© 2012 Alla et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2012 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

impact of heterogeneity of nodes, in terms of their energy, in wireless sensor networks that are hierarchically clustered. In these networks some high-energy nodes called NCG nodes (Normal node|Cluster Head| Gateway) are elected "cluster heads" to aggregate the data of their cluster members and transmit it to the chosen "Gateways" that requires the minimum communication energy to reduce the energy consumption of cluster head and decrease probability of failure nodes and properly balance energy dissipation. Simulation result shows an improvement in effective network lifetime and increased robustness of performance in the presence of energy heterogeneity.

Hierarchical Adaptive Balanced Routing Protocol

for Energy Efficiency in Heterogeneous Wireless Sensor Networks 315

Where ܲ is desired percentage of cluster head nodes in the sensor network, ݎ is current round number, and ܩ is the set of nodes that have not been cluster heads in the last ͳȀ rounds.

LEACH achieves over a factor of 7 reduction in energy dissipation compared to direct communication and a factor of 4–8 compared to the minimum transmission energy routing protocol (Akkaya & Younis, 2005). The nodes die randomly and dynamic clustering increases lifetime of the system. LEACH is completely distributed and requires no global knowledge of network. However, LEACH uses single-hop routing where each node can transmit directly to the cluster-head and the sink. Therefore, it is not applicable to networks deployed in large regions. Furthermore, the idea of dynamic clustering brings extra overhead, e.g. Head changes, advertisements etc., which may diminish the gain in energy

**2.2. Power-Efficient Gathering in Sensor Information Systems (PEGASIS)** 

greedy algorithm that starts from the farthest node from the base station.

**Figure 2.** Chain is constructed using the greedy algorithm

This is improved version from LEACH. The main idea of PEGASIS (Lindsey & Raghavendra, 2002) is that nodes are formed into a chain where each node receive from and transmit to closest neighbor only. The distance between sender and receiver is reduced as well as decreasing the amount of transmission energy. To construct a chain, PEGASIS uses a

**Figure 1.** Network model with clustering

consumption.

The organization of this chapter is as followings: We briefly review related work in section 2. Section 3 describes heterogeneous sensor network. Sensor network models is analysed in section 4. In section 5, we present our HABRP protocol. Simulation results of the proposed protocol are discussed in terms of energy consumption, Length of stable region for different values of heterogeneity, number of alive nodes per round, variation of the Base Station location, sensitivity to degree of heterogeneity in large scale networks, improvement of stability period in section 6. Finally, in section 7, we conclude the chapter.
