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Due to the limited computation resources and lifetime of user equipment, we study the energy minimization problem for computation offloading in cognitive radio networks (CRNs). This work proposes a device-to-device (D2D)-assisted computation offloading scheme for non-orthogonal multiple access (NOMA)-enabled CRNs. Specifically, the secondary user (SU) can provide computation resources for the primary user (PU) to access the spectrum owned by the PU. With the constraints of task deadline and maximum transmit power, offloading decision and power control of PU and SU are optimized to minimize the energy consumption of CRNs. The solution is obtained by deploying the block coordinate descent method and successive convex approximation. Simulation results show the improvement of the proposed scheme in terms of energy consumption and computing performance compared with other methods. [ABSTRACT FROM AUTHOR]

Virtualization technology enables multiple virtual machines (VMs) to share a single physical server. Commercial servers increasingly use the nonuniform memory access (NUMA) architecture due to its scalable memory performance. However, multiple VMs running on a NUMA physical server will cause performance overheads such as remote memory access latency and shared microarchitectural resource contention, which makes the VM performance less efficient and stable. These performance overheads are mainly caused by memory traffic from data-intensive workloads. In this paper, we propose a traffic-aware VM optimization (TAVO) scheme on NUMA systems. Based on the performance monitoring of the data traffic and CPU/memory resource usages in the system, TAVO addresses VM memory access locality and shared resource contention problems via automatic VM initial placement and NUMA-aware VM online scheduling. Our experimental results show that TAVO improves VM performance in terms of benchmark runtime by up to 22.6% compared with the default KVM CFS scheduler. TAVO also achieves a much stable performance with benchmark's average runtime variation under 3%. [ABSTRACT FROM PUBLISHER]