Flow processing-aware controller placement in wireless DenseNets

Auroux, Sebastien; Karl, Holger

doi:10.1109/pimrc.2014.7136368

Cited by 13 publications

(16 citation statements)

References 7 publications

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“…Unlike deployment of radio access networks (access points), strengthening the backhaul network will require massive deployment of network equipment. Auroux et al [11, 12] formulate the problem of optimizing latency in densenets, taking into consideration the stringent constraints of cellular networks. The problem is formulated as a mixed integer program and is shown to be NP‐Hard.…”

Section: Cpp Solution Methodsmentioning

confidence: 99%

“…The problem is formulated as a mixed integer program and is shown to be NP‐Hard. In [11], the authors present an exact solution using Gurobi [48]. Next, the authors propose a heuristic solution [12], where nodes are greedily assigned to regional controllers depending on the number of unassigned neighbor nodes or the number of unsatisfied flows.…”

Section: Cpp Solution Methodsmentioning

confidence: 99%

“…The algorithms differ in the way they rank the nodes (controllers). The nodes are ranked according to their degree, that is, the number of switches managed [17, 26, 134], contribution to southbound reliability [114], switch failure rate [59], delay requirement [66], capacity or flow processing rate [11, 16, 105], switch to controller latency or distance [116, 145], and the total number of controllers required [163].…”

Section: Cpp Optimization Strategiesmentioning

confidence: 99%

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Controller placement problem in software‐defined networking: A survey

Kumari

Sairam

2021

Networks

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A distinctive feature of software‐defined networking (SDN) is a logically centralized control plane realized using multiple physical controllers. The placement of the controllers, the so‐called controller placement problem (CPP), is a crucial design issue. It influences network performance parameters such as latency, flow setup time, network availability, load balance of the controllers, and energy consumption. In this article, we illustrate the formulation of these CPP objectives. We categorize the CPP design solutions as either static or adaptive. In adaptive CPP, the solutions proposed dynamically adapt to the number of controllers required and the switch to controller mapping to varying network traffic. We further differentiate adaptive CPP as wired or wireless. The optimization strategies adopted by the papers are analyzed and grouped into five categories: exact, heuristic, meta‐heuristic, clustering, and game theory. The merits and demerits of each approach are discussed. In conclusion, we outline the research challenges worth investigating.

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Section: Cpp Solution Methodsmentioning

confidence: 99%

Section: Cpp Solution Methodsmentioning

confidence: 99%

Section: Cpp Optimization Strategiesmentioning

confidence: 99%

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Controller placement problem in software‐defined networking: A survey

Kumari

Sairam

2021

Networks

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“…To address these issues introduced by densenets, the authors proposed a dynamic two-tier SDN controller hierarchy. In [200], [201], the authors formulate the problem of optimizing the flow setup time in densenets, taking into consideration the stringent constraints of cellular networks. The problem is formulated as a mixed integer program and is shown to be NPhard.…”

Section: Cpp Solutions For Wireless Networkmentioning

confidence: 99%

A Survey of Controller Placement Problem in Software Defined Networks

Kumari¹,

Sairam²

2019

Preprint

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“…The works [14,15,16,17,18,19,20,21,22] target fault tolerance, whereas [23,24,25] aim at balancing the loads on the controllers. [26] strives for network resource minimization in mobile cellular networks. [27] addresses the energy-efficient controller placement problem.…”

Section: Related Workmentioning

confidence: 99%