Energy-aware routing for software-defined networks with discrete link rates: A benders decomposition-based heuristic approach

Awad, Mohamad Khattar; Rafique, Yousef; M’Hallah, Rym

doi:10.1016/j.suscom.2016.11.003

Cited by 16 publications

(12 citation statements)

References 13 publications

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“…Numerous works address the switch energy efficiency and energy-aware routing strategies in SDNs/NFVs [29,30,31,32,33]. In detail, the authors in [29] present a network-wide energy-aware routing method using OF maximizing aggregate network utilization and optimized load balancing in SDN.…”

Section: Energy-aware Fog-supported Solutions In Sdns/nfvsmentioning

confidence: 99%

“…In other words, it estimates neither the failure prevention nor the fault tolerance per SDN-enabled switch. To cover the limitation of the previous work, the authors in [33] present an energy-efficient routing solution in SDN by targeting the integral routing and discrete link rates as traffic characteristics. They solve the optimal MILP solution using two sub-optimal heuristics and validate it by single or multiple flows in a dynamic network.…”

Section: Energy-aware Fog-supported Solutions In Sdns/nfvsmentioning

confidence: 99%

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Joint failure recovery, fault prevention, and energy-efficient resource management for real-time SFC in fog-supported SDN

et al. 2019

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Middleboxes have become a vital part of modern networks by providing services such as load balancing, optimization of network traffic, and content filtering. A sequence of middleboxes comprising a logical service is called a Service Function Chain (SFC). In this context, the main issues are to maintain an acceptable level of network path survivability and a fair allocation of the resource between different demands in the event of faults or failures. In this paper, we focus on the problems of traffic engineering, failure recovery, fault prevention, and SFC with reliability and energy consumption constraints in Software Defined Networks (SDN). These types of deployments use Fog computing as an emerging paradigm to manage the distributed small-size traffic flows passing through the SDN-enabled switches (possibly Fog Nodes). The main aim of this integration is to support service delivery in real-time, failure recovery, and fault-awareness in an SFC context. Firstly, we present an architecture for Failure Recovery and Fault Prevention called FRFP; this is a multi-tier structure in which the real-time traffic flows pass through SDN-enabled switches to jointly decrease the network side-effects of flow rerouting and energy consumption of the Fog Nodes. We then mathematically formulate an optimization problem called the Optimal Fog-Supported Energy-Aware SFC rerouting algorithm (OFES) and propose a near-optimal heuristic called Heuristic OFES (HFES) to solve the corresponding problem in polynomial time. In this way, the energy consumption and the reliability of the selected paths are optimized, while the Quality of Service (QoS) constraints are met and the network congestion is minimized. In a reliability context, the focus of this work is on fault prevention; however, since we use a reallocation technique, the proposed scheme can be used as a failure recovery scheme. We compare the performance of HFES and OFES in terms of power consumption, average path length, fault probability, network side-effects, link utilization, and Fog Node utilization. Additionally, we analyze the computational complexity of HFES. We use a real-world network topology to evaluate our algorithm. The simulation results show that the heuristic algorithm is applicable to large-scale networks.

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Section: Energy-aware Fog-supported Solutions In Sdns/nfvsmentioning

confidence: 99%

Section: Energy-aware Fog-supported Solutions In Sdns/nfvsmentioning

confidence: 99%

Joint failure recovery, fault prevention, and energy-efficient resource management for real-time SFC in fog-supported SDN

et al. 2019

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“…We consider a software‐defined network consisting of a single CC and N FEs. We extend our model presented in Awad et al to consider the limited size of flow tables. The set of FEs is denoted by

scriptN = false{1, ⋯, n, ⋯, N false}

, and the set of links connecting them is denoted by

scriptL = false{1, ⋯, l, ⋯, L false}

.…”

Section: Network Model and Problem Formulationmentioning

confidence: 99%

“…Furthermore, algorithms designed for power‐aware routing in data centers generally exploit the symmetry of the data center topologies and are not applicable in regular networks that do not exhibit similar properties. In a previous study, we presented a Benders‐based routing algorithm for networks with discrete link rates; however, the limited flow table size was not considered. In another study, Tang et al presented a flow allocation algorithm in which the flows are allocated on a set of precomputed paths through links with discrete link rates.…”

Section: Introductionmentioning

confidence: 99%

Power‐efficient routing for SDN with discrete link rates and size‐limited flow tables: A tree‐based particle swarm optimization approach

et al. 2017

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Summary Software‐defined networking is a promising networking paradigm for achieving programmability and centralized control in communication networks. These features simplify network management and enable innovation in network applications and services such as routing, virtual machine migration, load balancing, security, access control, and traffic engineering. The routing application can be optimized for power efficiency by routing flows and coalescing them such that the least number of links is activated with the lowest link rates. However, in practice, flow coalescing can generally overflow the flow tables, which are implemented in a size‐limited and power‐hungry ternary content addressable memory (TCAM). In this paper, a set of practical constraints is imposed to the software‐defined networking routing problem, namely, size‐limited flow table and discrete link rate constraints, to ensure applicability in real networks. Because the problem is NP‐hard and difficult to approximate, a low‐complexity particle swarm optimization–based and power‐efficient routing (PSOPR) heuristic is proposed. Performance evaluation results revealed that PSOPR achieves more than 90% of the optimal network power consumption while requiring only 0.0045% to 0.9% of the optimal computation time in real‐network topologies. In addition, PSOPR generates shorter routes than the optimal routes generated by CPLEX.

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“…This report accounts increase in mobile subscriptions by 7 fold growth, from 6.5% to 43% in between 2000 and 2015. The proportion of households with internet access growth rate is 46% in 2015 whereas in 2005 it was 18% [2]. These growing numbers of users have led to tremendous growth in energy consumption globally.…”

Section: Introductionmentioning

confidence: 99%

Saving energy and improving performance in SDN using rate adaptation technique

Rout¹,

Patra²,

Sahoo³

2018

IJET

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Energy efficiency in wired networks has received considerable attention over the past few years for its heavy economic impact. Energy consumption in such network is becoming a challenging issue. Among all these wired networks Software Defined Networking (SDN) is considered as an intelligent network in which use of programmability provides the best solution for network operation. The logical separation of data plane and control plane enhances its network functionality. Despite of all these mechanisms, energy consumption is also an alarming issue in SDN. Various researchers propose many approaches in order to utilize the energy in its best way. Herein we consider the normal scenario of a data center network, and propose a new energy efficient routing algorithms to improve the performance in SDN, called SERAT. In this work, we focus on discrete of data rate of the link in order to minimize energy consumption in the network. In wired network the underutilized links are even operated in high data rate, increasing energy consumption. In order to reduce energy consumption of the network the links must be operated as per their utilization factor. We have used an output buffer queue with two levels of threshold values in order to monitor the performance of the network. Simulation result shows that the proposed technique leads to major amount of energy savings without mush affecting the throughput.

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Energy-aware routing for software-defined networks with discrete link rates: A benders decomposition-based heuristic approach

Cited by 16 publications

References 13 publications

Joint failure recovery, fault prevention, and energy-efficient resource management for real-time SFC in fog-supported SDN

Joint failure recovery, fault prevention, and energy-efficient resource management for real-time SFC in fog-supported SDN

Power‐efficient routing for SDN with discrete link rates and size‐limited flow tables: A tree‐based particle swarm optimization approach

Saving energy and improving performance in SDN using rate adaptation technique

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