Design methodologies and algorithms for survivable C-RAN

Khorsandi, Bahare Masood; Tonini, Federico; Raffaelli, Carla

doi:10.23919/ondm.2018.8396115

Cited by 13 publications

(13 citation statements)

References 5 publications

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“…However, widespread deployment of these nodes may be costly; therefore, intelligent nodes hosting BBU hotels and edge computing resources need to be identified in relation to latency and processing constraints. Moreover, the problem of BBU hotel placement in C-RAN has been shown to be NP-hard [10], requiring novel strategies to make optimal approaches more scalable.…”

Section: Introductionmentioning

confidence: 99%

“…Deployment strategies for C-RAN have been proposed recently for Wavelenght Division Multiplexing (WDM) networks based on ILP and heuristic strategies [24,25]. Reliability aspects for C-RAN deployment are analyzed in detail in References [10,26,27]. In References [28], the authors propose a fog computing framework for C-RAN in vehicular networks.…”

Section: Introductionmentioning

confidence: 99%

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Scalable Edge Computing Deployment for Reliable Service Provisioning in Vehicular Networks

Tonini

Khorsandi

Amato

et al. 2019

JSAN

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The global connected cars market is growing rapidly. Novel services will be offered to vehicles, many of them requiring low-latency and high-reliability networking solutions. The Cloud Radio Access Network (C-RAN) paradigm, thanks to the centralization and virtualization of baseband functions, offers numerous advantages in terms of costs and mobile radio performance. C-RAN can be deployed in conjunction with a Multi-access Edge Computing (MEC) infrastructure, bringing services close to vehicles supporting time-critical applications. However, a massive deployment of computational resources at the edge may be costly, especially when reliability requirements demand deployment of redundant resources. In this context, cost optimization based on integer linear programming may result in being too complex when the number of involved nodes is more than a few tens. This paper proposes a scalable approach for C-RAN and MEC computational resource deployment with protection against single-edge node failure. A two-step hybrid model is proposed to alleviate the computational complexity of the integer programming model when edge computing resources are located in physical nodes. Results show the effectiveness of the proposed hybrid strategy in finding optimal or near-optimal solutions with different network sizes and with affordable computational effort.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Scalable Edge Computing Deployment for Reliable Service Provisioning in Vehicular Networks

Tonini

Khorsandi

Amato

et al. 2019

JSAN

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“…In this work, we consider two different aggregation network topologies with different levels of node connectivity degree, as in [18] (i.e., ratio between the total number of edges and the total number of nodes in the network) as shown in Fig. 4.…”

Section: Evaluation Settingsmentioning

confidence: 99%

“…[17] proposes a heuristic algorithm to connect each RRH to two BBU pools, primary and backup, while reducing the number of the backup BBU ports among the RRHs. Then in [18], the authors extend the work and formulate the problem as an ILP algorithm and compare it to the aforementioned heuristic algorithm. Ref.…”

Section: Introductionmentioning

confidence: 99%

Resilient BBU placement in 5G C-RAN over optical aggregation networks

2019

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The huge data demand envisioned for the 5G requires radically changes in the mobile network architecture and technology. Centralized Radio Access Network (C-RAN) is introduced as a novel mobile network architecture, designed to effectively support the challenging requirements of the future 5G mobile networks. In C-RAN, BaseBand Units (BBUs) are physically separated from their corresponding Radio Remote Heads (RRHs) and located in a central single physical location called BBU pool. The RRHs are connected to the BBU pool via the socalled fronthaul network. The "centralization" demonstrates remarkable benefits in terms of computational resources as well as power savings. Following this centralization, designing a survivable C-RAN becomes crucial as BBU pool and link failures might cause service outage for large number of users. In this paper, we propose three different approaches for the survivable BBU pool placement problem and traffic routing in C-RAN deployment over a 5G optical aggregation network. Namely we define the following protection scenarios: i) Dedicated Path protection, ii) Dedicated BBU protection and iii) Dedicated BBU and path protection. The three approaches are formalized as Integer Linear Programming (ILP) problems. The ILPs objectives are to minimize the number of BBU pools, the number of used wavelengths and the baseband processing computational resources, in terms of Giga operations Per Second (GOPS). We provide numerical results to compare the aforementioned protection strategies considering different network topologies. The results show the effect of the latency and the transport-network capacity on the BBU placement. We show the trade-off between the centralization degree and the tight latency requirements. Moreover, we discuss important insights about considering the different objective functions for each protection approach.

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“…Survivability in C-RAN and resiliency in 5G networks have been investigated in literature (see [3,[9][10][11]). Existing models tend to include this notion into the consideration of other problems, such as: (i) a BBU placement problem; or (ii) a control function split problem.…”

Section: Survivability and Resilience In C-ran Backhaul Networkmentioning

confidence: 99%

Optimizing C-RAN Backhaul Topologies: A Resilience-Oriented Approach Using Graph Invariants

et al. 2019

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At the verge of the launch of the first commercial fifth generation (5G) system, trends in wireless and optical networks are proceeding toward increasingly dense deployments, supporting resilient interconnection for applications that carry higher and higher capacity and tighter latency requirements. These developments put increasing pressure on network backhaul and drive the need for a re-examination of traditional backhaul topologies. Challenges of impending networks cannot be tackled by star and ring approaches due to their lack of intrinsic survivability and resilience properties, respectively. In support of this re-examination, we propose a backhaul topology design method that formulates the topology optimization as a graph optimization problem by capturing both the objective and constraints of optimization in graph invariants. Our graph theoretic approach leverages well studied mathematical techniques to provide a more systematic alternative to traditional approaches to backhaul design. Specifically, herein, we optimize over some known graph invariants, such as maximum node degree, topology diameter, average distance, and edge betweenness, as well as over a new invariant called node Wiener impact, to achieve baseline backhaul topologies that match the needs for resilient future wireless and optical networks.

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Design methodologies and algorithms for survivable C-RAN

Cited by 13 publications

References 5 publications

Scalable Edge Computing Deployment for Reliable Service Provisioning in Vehicular Networks

Scalable Edge Computing Deployment for Reliable Service Provisioning in Vehicular Networks

Resilient BBU placement in 5G C-RAN over optical aggregation networks

Optimizing C-RAN Backhaul Topologies: A Resilience-Oriented Approach Using Graph Invariants

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