Data aggregation in wireless sensor network is implemented to reduce the communication overhead and to reduce bandwidth utilization. Data confidentiality requires the sensor node to transmit the data in a secure manner so that the adversary is unable to read the data or transmit false data even if it compromises some of the sensor nodes or aggregation node. In this paper a distributed aggregation protocol using homomorphic trapdoor permutation is proposed. This protocol distributes the responsibility of key generation , aggregation and verification to different nodes to reduce the overall power consumption of the sensor network. The peer verification scheme is also proposed as a part of the protocol. Peer verification ensures the authentication of the data and sender node in the network, by at least k peer nodes. Security of the proposed protocol is analyzed against passive and active adversary model.

In this paper, we describe the Oracle Large User Population Demonstration and highlight the scalability mechanisms in the Oracle8 Universal Data Server which make it possible to support as many as 50,000 concurrent users on a single Oracle8 database without any middle-tier TP-monitor software. Supporting such large user populations requires many mechanisms for high concurrency and throughput. Algorithms in all areas of the server ranging from process and buffer management to SQL compilation and execution must be designed to be highly scalable. Efficient resource sharing mechanisms are required to prevent server-side resource requirements from growing unboundedly with the number of users. Parallel execution across multiple systems is necessary to allow user-population and throughput to scale beyond the restrictions of a single system. In addition to scalability, mechanisms for high availability, ease-of-use, and rich functionality are necessary for supporting complex user applications typical of realistic workloads. All mechanisms must be portable to a wide variety of installations ranging from desk-top systems to large scale enterprise servers and to a wide variety of operating systems.