TRUS: Towards the Real-Time Route Update Scheduling in SDN for Data Centers

Zhu, Jinqi; Hua, Jiwei; Liu, Ming; Li, Yabo; Cao, Ke

doi:10.1109/access.2020.2986226

Cited by 7 publications

(3 citation statements)

References 26 publications

(46 reference statements)

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“…Much research [2], [10], [13], [16]- [21] has investigated DCN traffic and related flow management challenges either in SDN or other networking paradigms. Most of the proposed solutions in the DCN context take advantage of leveraging the SDN centralized control and the path diversity typically available in such networks.…”

Section: Introductionmentioning

confidence: 99%

Flow-Aware Forwarding in SDN Datacenters Using a Knapsack-PSO-Based Solution

Abdollahi

Deldari

Asadi

et al. 2021

IEEE Trans. Netw. Serv. Manage.

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With the rapid growth of different massive applications and parallel flow requests in Data Center Networks (DCNs), today's providers are confronting challenges in flow forwarding decisions. Since Software Defined Networking (SDN) provides fine granular control, it can be intelligently programmed to distinguish between flow requirements. The present article proposes a knapsack model in which the link bandwidth and incoming flows are modeled as a knapsack capacity and items, respectively. Furthermore, each flow consists of two size and value aspects, acquired through flow size extraction and the type of service value assigned by the SDN controller decision. Indeed, the current work splits the incoming flow size range into Type of Service (ToS) decimal value numbers. The lower the flow size category, the higher the value dedicated to the flow. Particle Swarm Optimization (PSO) optimizes the knapsack problem and first forwards the selected-flows by KP-PSO, and the non-selectedflows second. To address the shortcomings of these methods in the event of dense parallel flow detection, the present study puts the link under the threshold of a 70% load by simultaneous requests. Experimental results indicate that the proposed method outperforms Sonum, Hedera, and ECMP in terms of flow completion time, packet loss rate, and goodput regarding flow size requirements.

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Section: Introductionmentioning

confidence: 99%

Flow-Aware Forwarding in SDN Datacenters Using a Knapsack-PSO-Based Solution

Abdollahi

Deldari

Asadi

et al. 2021

IEEE Trans. Netw. Serv. Manage.

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show abstract

“…The proposed scheme is different from existing works for two main reasons. First, numerous research studies address service assurance and resource optimization problems in different SDN-based environments, such as smart home, smart campus, and datacenter networks [23]- [25]. However, only a few research studies deal with the SD-IIoT network, especially the joining problem between the heterogeneous service assurance, resource optimization, and energy awareness aspects, which is still an open issue with many challenges for building sustainable and smart industrial networks.…”

Section: Introductionmentioning

confidence: 99%

Parallel Route Optimization and Service Assurance in Energy-Efficient Software-Defined Industrial IoT Networks

Njah

Cheriet

2021

IEEE Access

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In recent years, the Industrial world has been embracing new digital technology, including the internet of things (IoT) paradigm that promises revolutionizing-prospects in numerous industrial applications. However, many deployment challenges related to real-time big data analytics, service assurance, resource optimization, energy consumption, and security awareness are raised. In this work, we focus on service assurance and resource optimization, including energy consumption challenges over Industrial Internet of Things (IIoT)-based environments since the existing network routing algorithms cannot meet the strict heterogeneous quality of service (QoS) requirements of industrial communications while optimizing resources. We take advantage of the flexibility and programmability offered by the promising softwaredefined networking paradigm, and we propose a centralized route optimization and service assurance scheme, named ROSA, over a multi-layer programmable industrial architecture. The proposed solution supports a wide range of heterogeneous flows, such as ultra-reliable low-latency communications (URLLC) and bandwidth-sensitive services. The routing optimization problems are formulated as multi-constrained shortest path problems. The Lagrangian Relaxation approach is used to solve the NP-hard complexity. Hence, we deploy a pair of parallel routing algorithms run according to the flow type to ensure QoS requirements, efficiently allocate constrained resources, and enhance the overall network energy consumption. We conduct extensive simulations to validate the proposed ROSA scheme. The experimental results show promising performance in terms of reducing bandwidth utilization by up to 22%, end-to-end delay at least by 21%, packet loss by more than 19%, flow violation by about 16%, and energy consumption up to 14% as compared to well-known benchmarks in QoS provisioning and energy-aware routing problem.INDEX TERMS Industrial Internet of Things (IIoT), Software-Defined Networking (SDN), multiprogrammability, traffic engineering, Quality of Service (QoS), energy awareness, resource optimization.

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“…With the rise in the consumers and devices connected to the internet, the networking industry has gone through many challenges [1]. The commencement of new technologies such as internet-of-things (IoT) [2], Fog computing [3][4][5], Cloud computing [6,7], Bigdata [8][9][10], etc. welcome numerous numbers of applications.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficiency in Software Defined Networking: A Survey

Rout¹,

Sahoo

Patra

et al. 2021

SN COMPUT. SCI.

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Software defined networking has solved many challenging issues in the field of networking industry. It separates the control plane from the data forwarding plane. This makes SDN to be more powerful than traditional networking. However, energy cost enhances the overall network cost. Therefore, this issue needs to be addressed to improve design requirements and boost the networking performance. In this article, several energy efficiency techniques have been discussed. To represent it in more detail, a thematic taxonomy of energy efficiency techniques in SDN is given by considering several technical studies of the past research. These studies have been categorized into three sub categories of traffic aware model, end-host aware model and finally rule placement. These models are provided with detailed objective functions, parameters, constraints and detailed information. Furthermore, useful visions of each approach, its advantages and disadvantages and compressive analysis of energy efficiency techniques are also discussed. Finally, the paper is highlighted with the future directions for energy efficiency in SDN.

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TRUS: Towards the Real-Time Route Update Scheduling in SDN for Data Centers

Cited by 7 publications

References 26 publications

Flow-Aware Forwarding in SDN Datacenters Using a Knapsack-PSO-Based Solution

Flow-Aware Forwarding in SDN Datacenters Using a Knapsack-PSO-Based Solution

Parallel Route Optimization and Service Assurance in Energy-Efficient Software-Defined Industrial IoT Networks

Energy Efficiency in Software Defined Networking: A Survey

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