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Energy-Efficient Communication Protocol for Wireless Microsensor Networks by Wendi Rabiner Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan. Presented by Neha Jain. Overview. Introduction Key Features of Microsensors Sensor Network Model Direct Communication Protocol
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Energy-Efficient Communication Protocol for Wireless Microsensor NetworksbyWendi Rabiner Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan Presented by Neha Jain
Overview • Introduction • Key Features of Microsensors • Sensor Network Model • Direct Communication Protocol • Minimum Energy Routing Protocol • LEACH (Low-Energy Adaptive Clustering Hierarchy) • Results • Conclusion • Future Work
INTRODUCTION • Nodes maybe mobile(though very low mobility) • Sensor networks are “data-centric” networks. • They are application specific • Adjacent nodes may have similar data.
Typical applications of Sensor Networks • Reliable environment monitoring for commercial and military applications • For a security system, acoustic, seismic and video sensors can be used to form an adhoc network to detect intrusion. • Monitor machines for fault detection and diagnosis
Assumptions for Our Sensor Network • The radio channel is symmetric, energy required to transmit a message from node A to B is same as energy required to transmit message from node B to A (symmetry among nodes) • All the nodes in the network are homogeneous, energy constrained and begin with the same initial energy.
Assumptions for Our Sensor Network(cont) • All sensors are sensing data at a fixed rate and always have data to send to the end –user. • Not event-driven • Fixed base station, away from the nodes, through which the end user can access data from the sensor network
Direct Communication Protocol • Requires large amount of transmit power from each node if the BS is far away from the nodes. This will quickly drain the battery of the nodes and reduce system lifetime. • The nodes furthest from the BS are the ones to die out first as they have the highest transmit energy .
Minimum Energy Routing Protocol BS Routing
Minimum Energy Routing Protocol • In these protocols nodes route data destined ultimately for the base station through intermediate nodes. Thus nodes act as routers for other nodes’ data in addition to sensing the environment. • Nodes die out quicker using MTE routing than DC • Nodes closest to the BS are the first to die out in MTE routing, as they are the ones most used as “routers” for other sensors’ data
Which is more Energy Efficient ? • When transmission distance is short / the radio electronics energy is high, direct transmission is more energy efficient on a global scale than MTE routing. Thus the most energy efficient protocol to use depends on the network topology and radio parameters of the system.
Clustering BS
Clustering • Here nodes are organized into clusters that communicate with a local BS and these local Base Stations transmit the data to the global BS, where it is accessed by the end user. • Reduced distance of data transmission as the local BS is typically close to all nodes in the Cluster but BS becomes energy constrained • As soon as cluster -head node dies, all nodes from that cluster effectively die since there is no way to get their data to the base station. • In Adaptive clustering, cluster heads change as nodes move in order to keep the network fully connected.
Optimal percentage of nodes, N that should be cluster heads • If it is less than N, some nodes have to transmit very far to reach the cluster head, large global energy. • If more than N, distance does not reduce substantially, more cluster heads have to transmit the long haul distances to the base station, hence compression is less. N= 5%, reduces energy consumption by a factor of 7.
Hierarchical Clustering • Cluster • To achieve node coordination • One cluster member is made the cluster head • Carries out assigned task depending on each application • Thus, each cluster head aggregates data & sends to the BS or higher level cluster head - After a fixed period(cluster period T) cluster heads are changed
Key Features of LEACH (Low-Energy Adaptive Clustering Hierarchy) • Localised coordination and control for cluster set-up and operation. • Randomised rotation of the cluster “base stations” or “ cluster heads” and the corresponding clusters. • Local compression to reduce global communication • Random Death of nodes : there is no one section of the environment that is not being “sensed” as nodes die, as occurs in the other protocols.
Randomised Rotation • The high energy cluster head position rotates among the various sensors in order not to drain the battery of a single sensor. • Sensors elect themselves to be the local cluster heads at any given time with a certain probability, and broadcast their status to other sensors, each sensor node determines to which cluster it wants to belong by choosing the cluster-head that requires the minimum communication energy. • Each node takes the decision independent of the other nodes to become cluster head. It is based on the suggested percentage determined a priori and number of times the node has been a cluster-head so far.
LEACH - Algorithm Details • The operation is broken up into rounds • Advertisement phase • use CSMA MAC protocol, and all cluster heads transmit with same energy • Set up phase : Cluster is organized • each node transmits to which cluster head it wants to belong to using a CSMA MAC • Steady State Phase: Data Transfer to Base Station occurs
LEACH • Uses TDMA with CDMA TDMA code3 code1 CDMA code2
LEACH uses TDMA with CDMA • Then cluster head creates a TDMA schedule for all nodes within its cluster telling each node when it can transmit. • Allows radio component of each non cluster head to be turned off at all times except during its transmit time, thus minimizing the energy dissipated in the individual sensors. They must keep their receivers on during set up phase to hear the advertisements of all cluster heads. • Transmission in one cluster will affect communication in a nearby cluster, hence each cluster communicates using different CDMA codes.
How is LEACH Energy Efficient ? • Energy requirement is distributed among all the sensors , local computation reduces amount of data to be transmitted to the base station (computation is cheaper than communication) . • Main energy saving is due to combining localised compression with the data routing . tradeoff between quality of output and amount of compression resulting in substantial reduction of overall energy dissipation.
Total system energy dissipated using direct communication, MTE routing and LEACH for a 100-node random network . Eelec = 50 nJ/bit, messages are 2000 bits
Compare System Lifetime System lifetime using direct transmission, MTE routing, static clustering, and LEACH with 0.5 J/node
Results • LEACH reduces communication energy by as much as 8 times compared to direct transmission and MTE routing • The first node death in LEACH occurs over 8 times later than the first node death and the last node death occurs over 3 times later than the first node death in Direct Communication, MTE routing and a static clustering protocol.
Conclusion • LEACH outperforms conventional routing protocols like direct transmission, minimum-transmission-energy, multihop routing and static clustering algorithms • LEACH is completely distributed , requiring no control information from the base station and the nodes do not require knowledge of the global network in order for LEACH to operate
Future Work • Developing distributed , low energy protocols like LEACH for future microsensor networks. • Scope to implement an “event -driven” simulation, where sensors only transmit if some event occurs in the environment for future versions of LEACH.