Microprocessor-based communication and multimedia applications face increasing data access bottlenecks in cache, system bus, and main memory, which significantly impact system power consumption. To address this, the paper explores architectural optimizations, system-level transformations, and compiler technologies for power reduction. Voltage reduction is the most effective method, but architectural and algorithmic transformations can mitigate performance loss. Architectural optimizations include module parameter tradeoffs, locality exploitation, power-down mechanisms, speculation reduction, and hardware-software interfaces. System-level power management involves dynamic power states for components, with standards like ACPI for general platforms. For embedded systems, tailored power management can be highly efficient. Compiler optimizations, such as data flow and loop transformations, reduce memory traffic and improve performance. System-level code transformations, like data transfer and storage exploration, minimize memory usage and transfers. Platform-specific compilers optimize memory hierarchy and data layout. Memory-aware compilation techniques enhance DRAM access efficiency. Compiler-controlled power management dynamically balances power and performance. The paper concludes that three main approaches—architectural optimizations, system-level transformations, and compiler technology—are essential for low-power embedded applications.Microprocessor-based communication and multimedia applications face increasing data access bottlenecks in cache, system bus, and main memory, which significantly impact system power consumption. To address this, the paper explores architectural optimizations, system-level transformations, and compiler technologies for power reduction. Voltage reduction is the most effective method, but architectural and algorithmic transformations can mitigate performance loss. Architectural optimizations include module parameter tradeoffs, locality exploitation, power-down mechanisms, speculation reduction, and hardware-software interfaces. System-level power management involves dynamic power states for components, with standards like ACPI for general platforms. For embedded systems, tailored power management can be highly efficient. Compiler optimizations, such as data flow and loop transformations, reduce memory traffic and improve performance. System-level code transformations, like data transfer and storage exploration, minimize memory usage and transfers. Platform-specific compilers optimize memory hierarchy and data layout. Memory-aware compilation techniques enhance DRAM access efficiency. Compiler-controlled power management dynamically balances power and performance. The paper concludes that three main approaches—architectural optimizations, system-level transformations, and compiler technology—are essential for low-power embedded applications.