Optical network-on-chip (ONoC) is an emerging chip-scale optical interconnection technology to realize high-performance and power-efficient intercore communication for many-core processors. Multicast communication is popularly used in parallel applications on chip. However, existing researches for multicast in ONoC mainly focus on the optimization of one multicast. This limits the practical applications of the research outcomes because we often face the dynamic formation of multiple multicast groups in real network systems. In this article, we define the problem of routing and wavelength assignment for multiple multicasts in ONoC with the objective of minimizing the number of wavelengths required. To solve the problem, we first formulate it as an integer programming model for general topologies. Then we design routing policies for special instances that optimally use only one wavelength on mesh topology. For general instances, we design a group-partitioning routing algorithm for multiple multicasts (GPRMM). GPRMM decouples a group of multicasts into a number of subgroups, each of which matching one of the special instances. Theoretical results show that the number of wavelengths required by GPRMM is no more than the Destination Density $\sigma _{d}$ , i.e., the maximum number of multicasts with destinations in the same row or column. Moreover, we find the upper bound and the lower bound on the number of wavelengths required for GPRMM. The wavelength requirement is also upper bounded by the network size $n$ for an $n\times n$ mesh network. Simulation results show that GPRMM can reduce the number of wavelengths by 26.7% compared with previous methods. GPRMM has the advantages of low routing complexity, low wavelength requirement, low power consumption, and good scalability.

Manycore processor becomes the mainstream platform for cloud computing applications. However, the design of highperformance and sustainable inter-core communication network is still a challenging problem. Optical Network on Chip (ONoC) is a promising chip-scale optical communication technology with high bandwidth capacity and energy efficiency. In this paper, we present a Wavelength Reused Hierarchical ONoC architecture, WRH-ONoC. It leverages the nonblocking wavelength-routed $\lambda$-router and the hierarchical networking to reuse the limited number of available wavelengths. In WRH-ONoC, all the cores are grouped to multiple subsystems, and the cores in the same subsystem are directly interconnected using a single $\lambda$-router for nonblocking communication. For inter-subsystem communication, all subsystems are further connected through multiple $\lambda$-routers and gateways in a hierarchical manner. Thus, the available wavelengths can be reused in different $\lambda$-routers. Furthermore, WRHm-ONoC, an efficient extension with multicast ability is also proposed. Given the numbers of cores and available wavelengths, we derive the minimum hardware requirement, the expected endto- end delay, and the maximum data rate. Theoretical analysis and simulation results indicate WRH-ONoC achieves prominent improvement on communication performance and sustainability, e.g., 46:0% of reduction on zero-load delay and 72:7% of improvement on throughput for 400 cores with modest hardware cost and energy overhead.

Downlink mobile edge computing (MEC) networks are requiblack to serve increasing large number of Internet of Things (IoT) devices with limited battery capacity. In order to serve massive user equipments with low power consumption requirements, in this paper, we propose an energy-efficient multi-carrier non-orthogonal multiple access (MC-NOMA) design which allows more than two IoT devices to multiplex and access the same subcarrier band. With the aim to minimize the total transmit energy while meeting the demands of each IoT device such as the low latency, in our design, we first derive the optimal successive interference cancellation (SIC) policy and minimum power allocated to every IoT device. Then we propose an optimal greedy algorithm to allocate the frequency blocks, and formulate the optimization of the computational resource allocation as a min-max problem. Subsequently, we characterize the MC-NOMA network with the potential game model, and present a scheduling scheme to manage massive IoT devices. Simulation results demonstrate that our proposed scheme can consume 3-10 dB less energy in a MEC network deployed with 256 IoT devices compablack with the conventional orthogonal multiple access (OMA) scheme and non-orthogonal multiple access (NOMA) scheme.