LAUSR

As an open integrated environment deployed with wired and wireless infrastructures, the smart city heavily relies on the wireless-optical broadband access network. Smart home data are usually sent to neighbor optical network units (ONUs) through front-end wireless mesh networks (WMNs) and finally reach the optical line terminal (OLT) for decision making via the passive optical network (PON) backhaul. To reduce backhaul bandwidth saturated by this conventional approach, smart edge devices (EDs) should be deployed at sensors and ONUs so that collaborative edge computing can be performed in front-end WMNs. Moreover, the cooperation of EDs at different ONUs is also promising for computing tasks that cannot be handled within front-end WMNs due to the local bottleneck, leading to collaborative edge computing in the PON backhaul. In this paper, network virtualization is utilized to support the coordination of computing and network resources. We also describe the relationship between virtual networks and requirements of computing tasks for substrate resources. First, a graph-cutting algorithm is employed to embed as many virtual networks as possible onto the common network infrastructure in front-end WMNs, aiming at minimizing the total transmitting power. Next, we transform impossibly embedded virtual networks into new ones that must be processed through the PON backhaul where the wavelength consumption will be optimized. Simulations results demonstrate that 1) the total transmitting power assigned for nodes is effectively reduced using the graph-cutting algorithm if all computing tasks can be solved by front-end WMNs; 2) otherwise, our method accepts more virtual networks with the improvement ratio of 77%, through the PON backhaul. In addition, there is a good match between the algorithm result and the optimal number of consumed wavelengths per optical fiber cable.