Towards Optimal Network Planning for Software-Defined Networks

Lin, Shih‐Chun; Wang, Pu; Akyildiz, Ian F.; Luo, Ming‐Xing

doi:10.1109/tmc.2018.2815691

Cited by 31 publications

(16 citation statements)

References 27 publications

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“…The analysis leverages on the method of Upper Tail Chernoff bound [53] and Union Bound (Boole's inequality) [54,Chapter 4.7] -a technique often used in other works (see e.g., [55], [56]). For completeness, we first give a formal definition of the Upper Tail Chernoff bound and Union Bound inequality:…”

Section: Approximation Performance Analysismentioning

confidence: 99%

Delay-Aware Virtual Network Function Placement and Routing in Edge Clouds

Yang,

Li,

Trajanovski

et al. 2021

IEEE Trans. on Mobile Comput.

105

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Mobile Edge Computing (MEC) offers a way to shorten the cloud servicing delay by building the small-scale cloud infrastructures at the network edge, which are in close proximity to the end users. Moreover, Network Function Virtualization (NFV) has been an emerging technology that transforms from traditional dedicated hardware implementations to software instances running in a virtualized environment. In NFV, the requested service is implemented by a sequence of Virtual Network Functions (VNF) that can run on generic servers by leveraging the virtualization technology. Service Function Chaining (SFC) is defined as a chain-ordered set of placed VNFs that handles the traffic of the delivery and control of a specific application. NFV therefore allows to allocate network resources in a more scalable and elastic manner, offer a more efficient and agile management and operation mechanism for network functions and hence can largely reduce the overall costs in MEC. In this paper, we study the problem of how to place VNFs on edge and public clouds and route the traffic among adjacent VNF pairs, such that the maximum link load ratio is minimized and each user's requested delay is satisfied. We consider this problem for both totally ordered SFCs and partially ordered SFCs. We prove that this problem is NP-hard, even for the special case when only one VNF is requested. We subsequently propose an efficient randomized rounding approximation algorithm to solve this problem. Extensive simulation results show that the proposed approximation algorithm can achieve close-to-optimal performance in terms of acceptance ratio and maximum link load ratio.

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Section: Approximation Performance Analysismentioning

confidence: 99%

Delay-Aware Virtual Network Function Placement and Routing in Edge Clouds

Yang,

Li,

Trajanovski

et al. 2021

IEEE Trans. on Mobile Comput.

105

View full text Add to dashboard Cite

show abstract

“…It has two main planes; the 5G control and management plane and the 5G physical infrastructure plane. Centralized control in such a 5G network with many alternatives signaling paths in the congested network results in increased demand and a large amount of overhead [29]. This illustrates that using a centralized controller would adversely affect the entire network, rendering it insufficient for a single controller.…”

Section: B Multi-controller Architecture Based On 5gmentioning

confidence: 99%

Heuristic Resource Allocation Algorithm for Controller Placement in Multi-Control 5G Based on SDN/NFV Architecture

et al. 2021

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“…The frequency of the SDN controller being overloaded depends on traffic dynamics and the number of switches that the controller is responsible for, so estimating the exact frequency is difficult in the real world. However, from many previous literatures, 5–14 the overloaded controller is actually a problem and must be dealt with. Many previous studies tried to relieve the controller load, and they can be classified into three categories: packet scheduling, 15,16 multi‐controller architecture, 5–9,17–19 and frequency reduction 10–14,20,21 .…”

Section: Introductionmentioning

confidence: 99%

Buffering and prioritization in switches for fast processing table‐miss packets in software‐defined networks

Lai

Hailemariam

Chen

et al. 2021

Int J Communication

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Summary In software‐defined networks, the switch forwards incoming packets according to forwarding rules recorded in the flow entries. When a switch receives a table‐miss packet, meaning no match with any flow entry, it sends this packet as a Packet‐In message to the controller for its further processing. Many Packet‐In messages will cause large overhead and long packet delay. This paper proposes a novel method, Packet‐In Buffering and Prioritization (PIBP), which buffers Packet‐In messages and prioritizes these messages to reduce the number of Packet‐In messages and accelerate their processing, respectively. The concept of PIBP is sending only the first table‐miss packet of each flow to the controller. The other table‐miss packets belonging to the same flow are temporarily stored in the switch. Moreover, these messages have a higher priority. That is, after the packet sent from the controller has been forwarded from the switch, the buffered packets belonging to the same flow are also immediately forwarded. We formally analyze the performance of PIBP with queuing theory. The analytical and simulation results show that PIBP can decrease the average delay of table‐miss packets compared with two typical methods, Priority Queue and Mismatched Packets Table.

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Towards Optimal Network Planning for Software-Defined Networks

Cited by 31 publications

References 27 publications

Delay-Aware Virtual Network Function Placement and Routing in Edge Clouds

Delay-Aware Virtual Network Function Placement and Routing in Edge Clouds

Heuristic Resource Allocation Algorithm for Controller Placement in Multi-Control 5G Based on SDN/NFV Architecture

Buffering and prioritization in switches for fast processing table‐miss packets in software‐defined networks

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