TY  - JOUR
AU  - Zhu, Qijin 
AU  - Liu, Shuyi 
AU  - Akhtar, Zahid 
AU  - Siddique, Kamran 
PY  - 2023
TI  - Segment-Aware Dynamic Partitioning PCM-DRAM: A Solution to IoT Devices Development Constraints
JF  - Journal of Computer Science
VL  - 19
IS  - 10
DO  - 10.3844/jcssp.2023.1212.1221
UR  - https://thescipub.com/abstract/jcssp.2023.1212.1221
AB  - The Internet of Things(IoT) furnishes a visual blueprint for the future internet. It serves upsensors, actuators, and distal devices on the edge of the network, creating agiant interconnected network. The IoT era refers to the future where all theconceivable data streams are integrated into the IoT, granting human-barrierfree access to physical entities on the internet. Along with the rapid progressof IoT, pressing issues have emerged. Energy dissipation, limited processingefficiency, and confined memory have become severe constraints for the IoT era.Phase Change Memory with Dynamic Random-Access Memory (PCM-DRAM) is ahybrid memory system that has been proven to reduce energy dissipation. It isknown to have a great capacity, higher endurance, and low latency. In thisstudy, we first analyze the significant constraints faced in the IoTdevelopment. We then analyze how these constraints can be solved by PCM-DRAMmemory. To this end, we propose a PCM-DRAM hybrid memory system called“Segment-Aware and Dynamic Partitioning PCM-DRAM” (SADP PCM-DRAM). Our proposalis grounded in a meticulous evaluation of the specific requirements posed byIoT applications. Furthermore, we also proposed two essential equations forquantifying energy consumption and the overall performance in terms ofaverage memory hit time.