摘要：This paper investigates data processing schemes that define the distribution of decision making that affects system accuracy and energy consumption. There exist two typical schemes, namely: centralized and distributed schemes. In a centralized scheme, nodes collect samples and send them to a “fusion center.” This scheme provides optimal decision accuracy; however, it consumes considerable energy. In contrast, distributed schemes allow nodes to make local 1-bit decisions, which are sent to the fusion center to make the final decision. In a hybrid scheme, the network specifies the level of accuracy required for the whole system. This can be achieved by manipulating the scheme to work interchangeably as centralized or distributed. Most of the energy consumed is in the transmission process; therefore, this paper proposes an energy-saving hybrid scheme that focuses on optimizing transmission energy. In this proposed scheme, each node is able to alternate between centralized and decentralized scheme according to its location and path length. To validate the proposed approach, it is simulated and the results are compared with the hybrid scheme.
