Energy-Efficient Protocols for communication in Biosensor networks.

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Presentation transcript:

Energy-Efficient Protocols for communication in Biosensor networks

What are biosensors? Introduction These are microsensor devices placed in or on the body. A network of such biosensors can be used to monitor health or to act as prosthesis. Why do we need wireless communication? The data obtained by each sensor by itself is not important. It is the aggregation of data that is important. For this communication between sensors is necessary. However, a network may have 10s or even 100s of sensors and wiring them inside the body is not possible.

An example of the use of biosensor networks: Introduction Even though their nerve-endings are fine, a lot of people cannot see because the rods and cones in their retina have degenerated. We can induce a sensation of sight by artificially stimulating the nerve-endings. How do we do that? We place an array of biosensors in front of the nerve- endings at the back of the eye. An external processor compresses images it receives from a camera placed on the spectacles and transmits them to this array. We also need feedback from this array and hence reverse communication should also be possible.

The Retinal Prosthesis Project Transceiver External Processor Spectacles Sensor network Optic Nerve

1. Low but constant energy supply. 2. Low bandwidth. These sensors have to communicate in an error-prone environment with high path loss exponents. Increasing signal power is not an option as energy supply is scare. Characteristics of a Biosensor Network Since biosensors are typically implanted in the body, they cannot be powered by internal batteries that will run out of energy. To overcome this problem the battery packs are placed outside the body and the power is supplied to the sensor via infrared radiation.

3. Robustness and fault tolerance. 4. Size As these sensors have to be implanted into the body, they have to be as small and lightweight as possible. Characteristics of a biosensor network As biosensors are surgically implanted into the body, replacing failed sensors is difficult. Fault tolerance is also important because the failure of one node should not incapacitate the entire network. This calls for a dynamic, self-stabilizing network.

Observations: 1.Each sensor has to collect and transmit data every cycle. This suggests a TDMA approach to medium access. A TDMA approach will ensure contention-less access and hence no energy is wasted in collisions. 2.Neighboring sensors will collect more or less similar data. This suggests that we can use local data compression by removing redundant data. Doing this will reduce the number of bits to the transmitted and hence the transmission cost. Wireless Communications

Cluster-Based Approach: We can reduce the power consumption by limiting the long distance transmissions. We do this by organizing the network into clusters. Each cluster has one leader and several members. The members transmit their data to the leader. The leader compresses the data and transmits it to the the base station. The selection of leaders is done by the external processor. Several factors such as nodal density and transmission range will be taken into account during the selection process. Once the leaders are selected and the nodes have subscribed to a cluster, all communication follows TDMA. Our Approaches to the Problem

Cluster-based Approach

Tree-Based Approach: This is the tree-based routing that is common to today’s networks. The base station is at the root of the tree. Nodes that are reachable from it become its children. These children in turn have their own children and so on. Data from any node has to hop across several links to reach the base station. Our Approaches to the Problem.

Tree-based Approach

We observed that the power consumption depended on (a) Number of nodes (b) Percent of nodes that are cluster-heads (c) Propagation loss exponent (d) Distance between nodes. Results

Our analysis shows that the cluster-based approach provides better energy-efficiency than the tree-based approach. This is true for a wide range of path loss exponents, as long as we adjust the number of clusters in the network. For high path loss exponents, a smaller number of clusters is needed. Results

Results (contd.)

Explanation of Results: In the tree-based scheme, each data packet passes via several levels of the tree and transmission/reception costs are incurred at each level. The cost of such multi- hop routing then becomes greater than the cost of single-hop routing that is present in the cluster-based scheme.