Energetic trade-off between computing and communication resource in multimedia surveillance sensor network

In recent years, advances in microelectronics have allowed the development of low-power, low-cost, and small devices with sensing, computing, and wireless communication capabilities. An important criterion on the design and operation of these devices is their energy consumption. Two factors that affect the energy consumption of the sensor network are computation and communication. The simple strategy of locally processing the acquired data and transmitting it, is not optimal from the energy consumption point of view, relative to other strategies based on distributed processing and successive transmission of partially processed data. In this paper, we analyze the energy tradeoff between computation and communication resources in order to minimize the total energy consumption. We propose a heuristic solution to the stated sensor network problem for a multimedia application using Strong Arm RISC processors to perform a certain data compression algorithm.