Optimizing Power and Buffer Congestion on Wireless Sensor Nodes Using Cap (coordinated Adaptive Power) Management Technique

Limited hardware capabilities and very limited battery power supply are the two main constraints that arise because of small size and low cost of the wireless sensor nodes. Power optimization is highly desired at all the levels in order to have a long lived Wireless Sensor Network (WSN). Prolonging the life span of the network is the prime focus in highly energy constrained wireless sensor networks. Sufficient number of active nodes can only ensure proper coverage of the sensing field and connectivity of the network. If large number of wireless sensor nodes get their batteries depleted over a short time span then it is not possible to maintain the network. In order to have long lived network it is mandatory to have long lived sensor nodes and hence power optimization at node level becomes equally important as power optimization at network level. In this paper need for a dynamically adaptive sensor node is signified in order to optimize power at individual nodes along with the reduction in data loss due to buffer congestion. We have analyzed a sensor node with fixed service rate (processing rate and transmission rate) and a sensor node with variable service rates for its power consumption and data loss in small sized buffers under varying traffic (workload) conditions. For variable processing rate Dynamic Voltage Frequency Scaling (DVFS) technique is considered and for variable transmission rate Dynamic Modulation Scaling (DMS) technique is considered. Comparing the results of a dynamically adaptive sensor node with that of a fixed service rate sensor node shows improvement in the lifetime of node as well as reduction in the data loss due to buffer congestion. Further we have tried to coordinate the service rates of computation unit and communication unit on a sensor node which give rise to Coordinated Adaptive Power (CAP) management. The main objective of CAP Management is to save the power during normal periods and reduce the data loss due to buffer congestion (overflow) during catastrophic periods. With CAP management we are trying to adaptively change the power consumption of sensor nodes. Power consumption of processing unit and communication unit are coordinated together and changed adaptively with respect to the workload. Coordination between processing and communication subunits results in better energy optimization as well as possible data loss before transmission because of limited buffer sizes can be avoided.