We propose localized, self organizing, robust, and energy-efficient data aggregation tree approaches for sensor networks, which we call Localized Power-Efficient Data Aggregation Protocols (L-PEDAPs). They are based on topologies, such as LMST and RNG, that can approximate minimum spanning tree and can be efficiently computed using only position or distance information of one-hop neighbors. The actual routing tree is constructed over these topologies. We also consider different parent selection strategies while constructing a routing tree. We compare each topology and parent selection strategy and conclude that the best among them is the shortest path strategy over LMST structure. Our solution also involves route maintenance procedures that will be executed when a sensor node fails or a new node is added to the network. The proposed solution is also adapted to consider the remaining power levels of nodes in order to increase the network lifetime. Our simulation results show that by using our power-aware localized approach, we can almost have the same performance of a centralized solution in terms of network lifetime, and close to 90 percent of an upper bound derived here.

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.