Showing papers by "Miroslaw Klinkowski published in 2023"
DOI•
TL;DR: In this article , the authors focus on the problem of planning a survivable 5G packet-optical xHaul access network, in which the remote sites are connected with the hub by means of disjoint primary-backup paths.
Abstract: Packet-optical xHaul transport networks are a promising solution for assuring low-cost connectivity between a large number of antennas, located at remote sites, and a central site (hub), in which traffic is gathered and baseband processing is performed, in dense 5G radio access networks (RANs). The demand for fiber connections in such networks can be reduced by means of optical add-drop multiplexers (OADMs), which allow to aggregate traffic from a number of remote sites onto a single optical transmission path. An important issue here is the protection of transmission paths since the failure of a single link may result in the loss of connectivity of a number of antennas. In this work, we focus on the problem of planning a survivable 5G packet-optical xHaul access network, in which the remote sites are connected with the hub by means of disjoint primary-backup paths. The network scenario is based on a passive wavelength division multiplexing (WDM) system in which the maximum transmission distance depends on the number of OADMs installed on the transmission path. In the solution proposed, network survivability is achieved using a dedicated path protection with wavelength aggregation (DPPWA) mechanism. The network planning problem is modeled and solved as an integer linear programming (ILP) problem. Numerical results indicate, among others, that cost savings of between 20%–40% can be achieved in lower traffic load scenarios due to the traffic aggregation by means of OADMs, and that the savings increase with the cost of dark fiber lease.
1 citations
TL;DR: In this article , the authors investigated the flexible use of optical add-drop multiplexers (OADMs) for the aggregation of traffic from a number of remote sites, where the type/capacity of optical devices was selected in accordance with the traffic demand.
Abstract: This work concentrates on the problem of optimizing the cost of a passive wavelength division multiplexing (WDM) optical network used as a transport network for carrying the xHaul packet traffic between a set of remote radio sites and a central hub in a 5G radio access network (RAN). In this scope, we investigate the flexible use of optical add-drop multiplexers (OADMs) for the aggregation of traffic from a number of remote sites, where the type/capacity of optical devices—OADMs and optical multiplexers (MUXs)—is selected in accordance with the traffic demand. The approach is referred to as Flex-O. To this end, we formulate the xHaul network planning problem consisting in the joint provisioning of transmission paths (TPs) between the remote sites and the hub with optimized selection and placement of OADMs on the paths and proper selection of MUXs at the ends of the TPs. The problem formulation takes into accounts the optical power budget that limits the maximum transmission distance in a function of the amount and type of optical devices installed on the TPs. The network planning problem is modeled and solved as a mixed-integer linear programming (MILP) optimization problem. Several network scenarios are analyzed to evaluate the cost savings from the flexible (optimized) use of OADMs. The scenarios differ in terms of the availability of OADMs and the capacity of the WDM devices applied on the TPs. The numerical experiments performed in three mesh networks of different size show that the cost savings of up to between 35 and 45% can be achieved if the selection of OADMs is optimized comparing to the networks in which either single-type OADMs are used or the OADMs are not applied.
1 citations
TL;DR: In this paper , the authors investigate two traffic prioritization policies, namely, flow-aware (FA) and latencyaware (LA), in a packet-switched xHaul network supporting slices of different latency requirements.
Abstract: —Packet-switched xHaul networks are a scalable solu- tion enabling convergent transport of diverse types of radio data flows, such as fronthaul / midhaul / backhaul (FH / MH / BH) flows, between remote sites and a central site (hub) in 5G radio access networks (RANs). Such networks can be realized using the cost-efficient Ethernet technology, which enhanced with time-sensitive networking (TSN) features allows for prioritized transmission of latency-sensitive fronthaul flows. Provisioning of multiple types of 5G services of different service requirements in a shared network, commonly referred to as network slicing, requires adequate handling of transported data flows in order to satisfy particular service / slice requirements. In this work, we investigate two traffic prioritization policies, namely, flow- aware (FA) and latency-aware (LA), in a packet-switched xHaul network supporting slices of different latency requirements. We evaluate the effectiveness of the policies in a network-planning case study, where virtualized radio processing resources allocated at the processing pool (PP) facilities, for two slices related to enhanced mobile broadband (eMBB) and ultra-reliable low latency communications (URLLC) services, are subject to optimization. Using numerical experiments, we analyze PP cost savings from applying the LA policy (vs. FA) in various network scenarios. The savings in active PPs reach up to 40% − 60% in ring scenarios and 30% in a mesh network, whereas the gains in overall PP cost are up to 20% for the cost values assumed in the analysis.
TL;DR: In this article , a joint placement of DUs and routing of flows with the goal to minimize the overall cost of PPs activation and processing in the network is considered, which is referred to as the PPC-DUP-FR problem.
Abstract: Packet-switched xHaul networks based on Ethernet technology are considered a promising solution for assuring convergent, cost-effective transport of diverse radio data traffic flows in dense 5G radio access networks (RANs). A challenging optimization problem in such networks is the placement of distributed processing units (DUs), which realize a subset of virtualized baseband processing functions on general-purpose processors at selected processing pool (PP) facilities. The DU placement involves the problem of routing of related fronthaul and midhaul data flows between network nodes. In this work, we focus on developing optimization methods for joint placement of DUs and routing of flows with the goal to minimize the overall cost of PPs activation and processing in the network, which we refer to as the PPC-DUP-FR problem. We account for limited processing and transmission resources as well as for stringent latency requirements of data flows in 5G RAN. The latency constraint makes the problem particularly difficult in a packet-switched xHaul network since it involves the non-linear and dynamic estimation of the latencies caused by buffering of packets in the switches. The latency model that we apply in this work is based on worst-case calculations with improved latency estimations that skip from processing the co-routed, but non-affecting flows. We use a mixed-integer programming (MIP) approach to formulate and solve the PPC-DUP-FR optimization problem. Moreover, we develop a heuristic method that provides optimized solutions to larger PPC-DUP-FR problem instances, which are too complex for the MIP method. Numerical experiments performed in different network scenarios indicate on the effectiveness of the heuristic in solving the PPC-DUP-FR problem. In particular, the heuristic achieves up to 63% better results than MIP (at the MIP optimality gap equal to 76%) in a medium-size mesh network, in which the MIP problem is unsolvable for higher traffic demands within reasonable runtime limits. In larger networks, MIP is able to provide some results only for the PPC-DUP-FR problem instances with very low traffic demands, whereas the solutions generated by the heuristic are at least 83% better than the ones achieved with MIP. Also, the analysis performed shows a significant impact of the PP cost factors considered and of the level of cost differentiation of PP nodes on the overall PP cost in the network. Finally, simulation results of a case-study packet xHaul network confirm the correctness of the latency model used.
TL;DR: In this article , the authors presented extended versions of selected papers presented at the 26th International Conference on Optical Network Design and Modeling (ONDM 2022), which took place 16-19 May 2022 at Warsaw University of Technology, Warsaw, Poland.
Abstract: This JOCN special issue contains extended versions of selected papers presented at the 26th International Conference on Optical Network Design and Modeling (ONDM 2022), which took place 16–19 May 2022 at Warsaw University of Technology, Warsaw, Poland. The topics covered by the papers represent trends in optical networking research: application of machine learning to network management, cross-layer network performance optimization, visible light communication as well as coherent metro networks.
TL;DR: In this paper , the authors address a network planning problem that concerns the joint latency-aware placement of DUs/CUs and routing of data flows (LADCPR) for a set of RUs in a 5G RAN connected using a PXN.
Abstract: Packet-switched Xhaul networks (PXNs) have been proposed as a cost-effective and scalable solution for provisioning of connectivity between densely located radio antenna (remote) units (RU) and distributed (DU) / central (CU) processing units in 5G Radio Access Networks (RANs). A PXN enables statistical multiplexing of different data flows, such as fronthaul, midhaul, and backhaul flows, and their routing over a commonly shared packet transport network, thus increasing network flexibility and decreasing bandwidth requirements. The decisions concerning the placement of virtualized DU and CU entities at selected processing nodes and the selection of paths for routing of data flows between these nodes have a direct impact on flow latencies. In addition, buffering of packets in switches introduces dynamic, flow-dependent latencies, which as well have to be accounted for in latency-sensitive 5G RANs. In this work, we address a network planning problem that concerns the joint latency-aware placement of DUs/CUs and routing of data flows (LADCPR) for a set of RUs in a 5G RAN connected using a PXN. We model the LADCPR problem as a Mixed-Integer Linear Programming (MILP) optimization problem and propose two reformulations of the model that facilitate its solving. Since the MILPs have limited scalability, we develop two heuristic algorithms, based on problem decomposition and an iterative search approach. Numerical experiments performed in different network scenarios show that the algorithms are capable of generating good-quality solutions to the LADCPR problem. Also, they can optimize larger network instances – consisting of tens of switches, a number of routing paths, and comprising some hundreds of demands – within relatively low algorithm run times.