ABSTRACT The emerging optical circuit technology, which can establish circuit connections among switches, has been proposed as a promising paradigm for data center networks. This paper investigates the problem of minimizing the completion time of multicast coflows in optical circuit switches (OCSs)‐based data center networks. The existing works either only focused on multicast coflow scheduling or focused solely on circuit scheduling in OCS‐based networks, which greatly limits their performance. Hence, in this paper, we study how to reduce the completion time of multicast coflows by considering circuit scheduling and coflow scheduling simultaneously. First, the problem of multicast coflow scheduling is formulated and proved to be NP‐hard. Then, a Delay‐efficient Multicast Coflow Scheduling (DMCS) algorithm is proposed by integrating multicast coflow scheduling with circuit scheduling. The proposed DMCS algorithm is proved to have an approximation ratio of at most , where represents the number of OCS. Through extensive simulations, it is shown that the proposed DMCS algorithm can achieve high performance compared to state‐of‐the‐art methods.

Summary Data broadcast is a fundamental communication pattern in wireless IoT networks, in which the messages are disseminated from a source node to the entire network. The problem of minimum latency broadcast scheduling (MLBS) which is aimed to generate a quick and conflict‐free broadcast schedule has not been extensively explored in duty‐cycled networks. The existing works either work in a centralized scheme or rely on a fixed tree for broadcasting. Additionally, they all employ a strict premise that each node can only utilize one channel for both transmitting and receiving messages. Thus, to address the issues mentioned above, we examine the first distributed broadcasting algorithm in multi‐channel duty‐cycled wireless IoT networks, without relying on a predetermined tree. First, the MLBS problem in such networks is defined and proved to be NP‐hard. Then, in order to avoid transmission conflicts between different links locally, two efficient data structures are designed to help compute the earliest time and channel of receiving messages without conflicts. Based on the above data structures, we introduce an efficient distributed broadcasting algorithm, which can generate a latency‐sensitive broadcast tree while calculating a collision‐free broadcast schedule, simultaneously. Finally, the theoretical analysis and simulations demonstrate the efficiency of the proposed algorithm.

Multicast is a fundamental function in network traffic engineering, allowing data traffic to be delivered from the source node to multiple destinations efficiently. To ensure the reliability and security of data traffic, NFV-enabled multicast (Network Function Virtualization) has emerged as a promising technology to reduce deployment and maintenance costs in mobile edge clouds, and has drawn extensive researching interests recently. However, existing works all assume that the Service Function Chain (SFC) follows a fixed-order, which greatly limits its application. Therefore, in this paper, we propose the first work to address the sequential SFC embedding problem without a fixed order for NFV-enabled multicasting in mobile edge clouds. Firstly, we formulate such a minimum cost SFC embedding problem and prove it to be NP-hard. Secondly, we propose a min-path breadth-first based progressive embedding algorithm (MBPE) for NFV-enabled multicasting, which achieves an approximation ratio of 1+K, where K represents the approximation ratio of the Steiner tree problem. Finally, the experiments demonstrate the high efficiency of the proposed method compared to the state-of-the-art algorithms.