In Network Processing and Data Aggregation in

y generating an output record. Also, a query optimizer generates an efficient query planfor in-network processing of query Q, in order to vastly reduce resource usage and thusextend the lifetime of the sensor network. Furthermore, a query plan specifies both thedata flow (between sensors) and an exact computation plan (at each sensor). Thecomputation plan determines the leader of the specific query, a designated node wherethe computation of the average temperature will take place. The leader could be either afixed sensor with more remaining power and energy, or a randomly selected node bysome distributed leader election algorithm. Two computation plans are produced, one forthe leader node, and a second plan for the remaining nodes in the query region. A queryoptimizer can also perform several techniques to improve the performance of the system.For example, it can merge a new query with existing similar queries. It is important tomention that in order to generate a good plan for a user query, the optimizer requiresmetadata about the status of the sensor network to evaluate the costs acid benefits(latency and accuracy) of different plans.Data Aggregation in COUGAR involves two important issues:a) from a computational point of view, the aggregation must take place at a "leader"node [leader election problem + dynamically maintain a leader + leader with physicallyadvantageous location], unless the final computation of the aggregate is delegated to agateway node or happens outside of the network.b) data records have to be delivered from source sensor nodes to the designated leadersimply by sending data records directly to the leader along multi-hop routes so as all thecomputation takes place directly at the leader or alternatively by pushing partialcomputation from the leader to internal nodes along the path in order to reduce data sizeon-the-fly. Synchronization between sensor nodes along the communication path is veryimportant, since a node has to "wait" to receive the results that are to be aggregated.TAG [10]In the TAG system, the connection of the users to the sensor network is achieved byusing a workstation or a base station which is directly connected to a sensor and has therole of the root node. The aggregation of queries over the data of the sensors isformulated using a simple SQL-like language. The in-network query evaluation consistsof two phases, the (smart) distribution and the collection phase. During the distributionphase, the query is flooded in the network and organizes the nodes into an Aggregation