Wireless Sensor Nodes’ Energy Model and Cluster Head Rotation

Một phần của tài liệu Analysis, design and optimization of energy efficient protocols for wireless sensor networks (Trang 76 - 81)

3.2.1 Energy Model of the Wireless Sensor Node

In a WSN, sensor nodes consume energy to receive data from other nodes, process or aggregate these data and transmit to the other nodes. Sensor node components and associated energy consumption for communication are shown in Fig. 3.1where ET x and ERx are transmitting and receiving energy consumption. When data

aggregation mechanism is applied, the node’s energy consumption that is used to fulfill data aggregation task is denoted as Eda. Both the free space and multipath

Figure 3.1: Sensor Node Components and Energy Consumption for Data Aggregation and Communication Task

fading channel models in [47] are used to compute energy dissipated during the process of transmitting and receiving information. The energy consumption for transmitting a l-bit message over a distance d, in m, is

ET x = Eelec∗l+Ef s∗l∗d2, d < d0 (3.1) ET x = Eelec∗l+Emp∗l∗d4, d ≥d0 (3.2) and for receiving this message respectively is:

ERx=Eelec∗l (3.3)

where Eelec is the energy spent to operate the transceiver circuit, i.e. transmitter and receiver, Ef s and Emp are the energy consumption of transmitting one bit data to achieve an acceptable bit error rate and is dependent on the distance of transmission in the case of free space model and multipath fading model. If the transmission distance is less than a threshold d0, the free space model is applied;

otherwise, we use the multipath model. The threshold d0 is calculated as d0 =

q

Ef s/Emp (3.4)

3.2.2 Cluster Head Rotation for Balancing Energy in Wire- less Sensor Nodes

Considering a small scale WSN such as a WBAN with n nodes, these n nodes are organized in one group or cluster that is deployed on a human body in the case of WBAN and is stationary on the body during the operation. One of the nodes is chosen as the gateway or CH that gathers data from all other nodes and sends the concise data to a BS. The energy consumption of each node to transmit l-bit messages to this gateway is given by using Equation (3.1)

Enode =ET x(l, d) = Eelec∗l+Ef s∗l∗d2 (3.5)

where d is the distance between the node and the gateway. The energy consumption of the gateway to receive data from all nodes and send to a base station is as follows

Egateway = ET x(n∗l, d) +ERx((n−1)∗l) (3.6)

= Eelec∗n∗l+Ef s∗n∗l∗d2 +Eelec∗(n−1)∗l (3.7)

= l∗[(2n−1)Eelec+n∗Ef s∗d2] (3.8)

To solve the problem of just relying on one energy hungry gateway to commu- nicate with the BS, a selective gateway method to select among the sensor nodes based on their residual energy as the local gateway can be utilized to balance energy consumption of the network. Whenever the residual energy of the gateway reduces below a threshold value, Eth, another node among the rest in the WBAN with higher energy level than Eth is chosen as the current gateway. After one round of

threshold value is adjusted lower. It is required to make sure that at least one of the sensor nodes has enough energy supply to become the gateway. The selection process is repeated again as mentioned above until the residual energy stored in all the sensor nodes are used up. The information about residual energy of each individual node is added to the sending data, and is compared at the gateway at each round of data gathering. Decision of changing gateway made by the current gateway is sent to all the other nodes through the acknowledge messages of received data in the next round.

The simulation result shown in Fig. 3.2 illustrates the residual energy of the gateway based on the conventional fixed gateway case and the last node running out of energy when using proposed selective gateway method with 10 nodes deployed in an area of 0.4 m × 1.7 m, a 200-bit message (i.e. header, payload, metadata, etc.) is transferred from the sensor node to the gateway every round. Assuming that the distance between the gateway and the base station is within 200 m and all nodes have the same initial energy 0.5 J, the gateway in the first method spends all of its energy after 200 rounds of receiving and transmitting data, meanwhile in the second method, every node runs out of energy after an average number of 1700 rounds.

Fig. 3.3 shows the comparison between the lifetime of the single unique gateway and that of the last node which runs out of energy in the selective gateway method with respect to the number of nodes deployed in the WBAN. When the gateway is fixed, increasing number of nodes causes a short life of the gateway and thus shortens the network lifetime. In another case, where the gateway is selected based on the residual energy of the sensor nodes, the average lifetime of each node

Figure 3.2: Residual energy levels of the conventional fixed gateway and the selective gateway

in the network is much longer and its performance is independent of the number of sensor nodes. Therefore, the network lifetime, which does not depend on a unique local gateway, is much more improved.

Figure 3.3: Gateway life time with different number of nodes in the network

By changing the gateway based on residual energy, the energy among all

it guarantees the connection with the base station. Furthermore, when an energy harvesting source is added, the proposed method provides a benefit of utilizing energy scavenged from all of the nodes as well as let the gateway have enough time to recharge and restore its energy capacity and therefore prolong the network lifetime much more.

Một phần của tài liệu Analysis, design and optimization of energy efficient protocols for wireless sensor networks (Trang 76 - 81)

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