Quantum-walk search in motion

In quantum computing, the quantum walk search algorithm is designed for locating fixed marked nodes within a graph. However, when multiple marked nodes exist, the conventional search algorithm lacks the capacity to simultaneously amplify the marked nodes as well as identify the correct chronological ordering between the marked nodes, if any. To address this limitation, we explore a potential extension of the algorithm by introducing additional quantum states to label the marked nodes. The labels resolve the ambiguity of simultaneous amplification of the marked nodes. Additionally, by associating the label states with a chronological ordering, we can extend the algorithm to track a moving particle on a two-dimensional surface. Our algorithm efficiently searches for the trajectory of the particle and is supported by a proposed quantum circuit. This concept holds promise for a range of applications, from real-time object tracking to network management and routing.

SDN-Based Traffic Monitoring in Data Center Network Using Floodlight Controller

Data center networks are the backbone of IT infrastructure and cloud services. According to traffic pattern research, a small group of flows transport the vast majority of the bytes and are referred to as elephant flows. Proper management of such traffic flows can enhance overall performance and energy efficiency. Software-defined network (SDN) is a fresh networking model that provides a centralized control plane (i.e., controller). The controller can be utilized for traffic monitoring by collecting the network flows at the controller. In this research, a new mechanism has been provided to detect such flows, which requires continuous polling of all switches. The proposed method depends on passive querying so it does not require additional traffic. The result shows the successful detection of elephant flow and cheetah flow that can be rerouted to improve the quality of service (QoS).