Due to the excellent rendering capabilities, GPUs are mainstream accelerators in the Cloud-rendering industry. However, current Cloud-rendering systems suffer from a CPU-GPU workload imbalance that not only degrades application performance but also causes a significant waste of GPU resources. Recent proposals (such as API-forwarding and c-GPU) for improving CPU-GPU balance are promising but fail to solve system-resource redundancy issues (i.e., each instance tends to occupy all resources, exceeding its requirements). Such behavior will increase CPU load and lower effective GPU utilization. To demonstrate the severity of the issue, we evaluated real-world applications and results show that in most cases, nearly 50% of resources are useless. To solve this problem, we present CARE, the first framework intended to reduce the system-level redundancy by cloudifying the system from monolithic to Cloud-native. To allow users to configure required services, CARE puts forward a functional unit calledConfigurable Android (CA). To allow multiple instances to share certain types of resources, CARE innovatesSharing Resource (SR). To reduce the unused services, CARE introducesPruning Resources (PR). To further alleviate the CPU pressure and achieve CPU-GPU balance, we propose rShare, a system aiming at enhancing CPU effective utilization and increasing Android instance density of the Cloud-rendering platform. Based on Kubernetes, rShare divides all the CPUs into non-overlapping shared CPU pools, allocates instances to pools within milliseconds, and dynamically migrates them by tracking their QoS status. So far, CARE primarily focuses on Android systems and can handle 60 heavyweight instances (e.g., KOG (King of Glory)) on Intel SG1. rShare can apply instance allocation within milliseconds and increase the platform density by 39.4%.

Containerization is widely used for isolation in various applications because it is lightweight, scalable, and portable.In modern distributed systems, seamless inter-process communication (IPC) between multi-platform containers is essential for a range of applications and services, including microservices, cloud computing, and Internet of Things (IoT) devices.However, secure and efficient communication between containers on the same host is challenging, especially when different operating systems are involved.This paper introduces Bindox, a lightweight, efficient, and secure IPC mechanism that enables seamless communication across multiple platforms, including Android and Linux.Bindox uses shared memory for data transfer and implements a stable client-server architecture, ensuring high performance and ease of maintenance.Additionally, Bindox provides a robust security mechanism that guarantees confidentiality, integrity, and availability of the communication channel.Experimental results demonstrate that Bindox outperforms existing networking and IPC methods in terms of memory use, latency, and CPU usage, making it a promising solution for efficient and secure communication between multi-platform containers.