Power efficient data gathering and aggregation in wireless sensor networks

Recent developments in processor, memory and radio technology have enabled wireless sensor networks which are deployed to collect useful information from an area of interest The sensed data must be gathered and transmitted to a base station where it is further processed for end-user queries. Since the network consists of low-cost nodes with limited battery power, power efficient methods must be employed for data gathering and aggregation in order to achieve long network lifetimes. In an environment where in a round of communication each of the sensor nodes has data to send to a base station, it is important to minimize the total energy consumed by the system in a round so that the system lifetime is maximized. With the use of data fusion and aggregation techniques, while minimizing the total energy per round, if power consumption per node can be balanced as well, a near optimal data gathering and routing scheme can be achieved in terms of network lifetime. So far, besides the conventional protocol of direct transmission, two elegant protocols called LEACH and PEGASIS have been proposed to maximize the lifetime of a sensor network. In this paper, we propose two new algorithms under name PEDAP (Power Efficient Data gathering and Aggregation Protocol), which are near optimal minimum spanning tree based routing schemes, where one of them is the power-aware version of the other. Our simulation results show that our algorithms perform well both in systems where base station is far away from and where it is in the center of the field. PEDAP achieves between 4x to 20x improvement in network lifetime compared with LEACH, and about three times improvement compared with PEGASIS

A distributed and dynamic data gathering protocol for sensor networks

In this paper we propose a distributed, self organizing, robust and energy efficient data gathering algorithm for sensor networks operating in environments where all the sensor nodes are not in direct communication range of each other and data aggregation is used while routing. Proposed algorithm is based on local minimum spanning tree (LMST) structure, which nodes can construct from the position of their 1-hop neighbors. Reporting tree is constructed from the sink by allowing only edges of LMST to join the tree, plus possibly some direct links to the sink. Each node selects as parent the LMST neighbor so that the total energy cost of route to the sink is minimal. We also describe route maintenance protocols to respond to predicted sensor failures and addition of new sensors. Our simulation results show that our algorithm prolongs the network lifetime significantly compared to some alternative schemes. © 2007 IEEE