Sensor nodes are deployed over sensing fields for the purpose of monitoring certain phenomena of interest. The sensor nodes perform specific measurements, process the sensed data, and send the data to a base station over a wireless channel. The base station collects data from the sensor nodes, analyses this data, and reports it to the users. Wireless sensor networks are different from traditional networks, because of the following constraints. Typically, a large number of sensor nodes need to be randomly deployed and, in most cases, they are deployed in unreachable environments; however, the sensor nodes may fail, and they are subject to power constraints. Energy is one of the most important design constraints of wireless sensor networks. Energy consumption, in a sensor node, occurs due to many factors, such as: sensing the environment, transmitting and receiving data, processing data, and communication overheads. Since the sensor nodes behave as router nodes for data propagation, of the other sensor nodes to the base station, network connectivity decreases gradually. This may result in disconnected sub networks of sensor nodes. In order to prolong the network's lifetime, energy efficient protocols should be designed for the characteristics of the wireless sensor network. Sensor nodes in different regions of the sensing field can collaborate to aggregate the data that they gathered. Data aggregation is defined as the process of aggregating the data from sensor nodes to reduce redundant transmissions. It reduces a large amount of the data traffic on the network, it requires less energy, and it avoids information overheads by not sending all of the unprocessed data throughout the sensor network. Grouping sensor nodes into clusters is useful because it reduces the energy consumption. The clustering technique can be used to perform data aggregation. The clustering procedure involves the selection of cluster heads in each of the cluster, in order to coordinate the member nodes. The cluster head is responsible for: gathering the sensed data from its cluster's nodes, aggregating the data, and then sending the aggregated data to the base station. An adaptive clustering protocol was introduced to select the heads in the wireless sensor network. The proposed clustering protocol will dynamically change the cluster heads to obtain the best possible performance, based on the remaining energy level of sensor nodes and the average energy of clusters. The OMNET simulator will be used to present the design and implementation of the adaptive clustering protocol and then to evaluate it. This research has conducted extensive simulation experiments, in order to fully study and analyse the proposed energy efficient clustering protocol. It is necessary for all of the sensor nodes to remain alive for as long as possible, since network quality decreases as soon as a set of sensor nodes die. The goal of the energy efficient clustering protocol is to increase the lifetime and stability period of the sensor network. This research also introduces a new bidirectional data gathering protocol. This protocol aims to form a bidirectional ring structure among the sensor nodes, within the cluster, in order to reduce the overall energy consumption and enhance the network's lifetime. A bidirectional data gathering protocol uses a source node to transmit data to the base station, via one or more multiple intermediate cluster heads. It sends data through energy efficient paths to ensure the total energy, needed to route the data, is kept to a minimum. Performance results reveal that the proposed protocol is better in terms of: its network lifetime, energy dissipation, and communication overheads.

Sensor nodes are deployed over sensing fields for the purpose of monitoring certain phenomena of interest. The sensor nodes perform specific measurements, process the sensed data, and send the data to a base station over a wireless channel. The base station collects data from the sensor nodes, analyses this data, and reports it to the users. Wireless sensor networks are different from traditional networks, because of the following constraints. Typically, a large number of sensor nodes need to be randomly deployed and, in most cases, they are deployed in unreachable environments; however, the sensor nodes may fail, and they are subject to power constraints. Energy is one of the most important design constraints of wireless sensor networks. Energy consumption, in a sensor node, occurs due to many factors, such as: sensing the environment, transmitting and receiving data, processing data, and communication overheads. Since the sensor nodes behave as router nodes for data propagation, of the other sensor nodes to the base station, network connectivity decreases gradually. This may result in disconnected sub networks of sensor nodes. In order to prolong the network¿s lifetime, energy efficient protocols should be designed for the characteristics of the wireless sensor network. Sensor nodes in different regions of the sensing field can collaborate to aggregate the data that they gathered. Data aggregation is defined as the process of aggregating the data from sensor nodes to reduce redundant transmissions. It reduces a large amount of the data traffic on the network, it requires less energy, and it avoids information overheads by not sending all of the unprocessed data throughout the sensor network. Grouping sensor nodes into clusters is useful because it reduces the energy consumption. The clustering technique can be used to perform data aggregation. The clustering procedure involves the selection of cluster heads in each of the cluster, in order to coordinate the member nodes. The cluster head is responsible for: gathering the sensed data from its cluster¿s nodes, aggregating the data, and then sending the aggregated data to the base station. An adaptive clustering protocol was introduced to select the heads in the wireless sensor network. The proposed clustering protocol will dynamically change the cluster heads to obtain the best possible performance, based on the remaining energy level of sensor nodes and the average energy of clusters. The OMNET simulator will be used to present the design and implementation of the adaptive clustering protocol and then to evaluate it. This research has conducted extensive simulation experiments, in order to fully study and analyse the proposed energy efficient clustering protocol. It is necessary for all of the sensor nodes to remain alive for as long as possible, since network quality decreases as soon as a set of sensor nodes die. The goal of the energy efficient clustering protocol is to increase the lifetime and stability period of the sensor network. This research also introduces a new bidirectional data gathering protocol. This protocol aims to form a bidirectional ring structure among the sensor nodes, within the cluster, in order to reduce the overall energy consumption and enhance the network¿s lifetime. A bidirectional data gathering protocol uses a source node to transmit data to the base station, via one or more multiple intermediate cluster heads. It sends data through energy efficient paths to ensure the total energy, needed to route the data, is kept to a minimum. Performance results reveal that the proposed protocol is better in terms of: its network lifetime, energy dissipation, and communication overheads.