QoS-aware software-defined routing in smart community network

Attia, Maroua Ben; Nguyen, Kim Khoa; Cheriet, Mohamed

doi:10.1016/j.comnet.2018.10.015

Cited by 10 publications

(6 citation statements)

References 25 publications

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“…Ben Attia et al 23 proposed a LARAC‐based algorithm for smart community networks where a large number of smart device pairs need QoS‐aware communication. Since large pairs are communicating, LARAC needs to be executed repeatedly for each.…”

Section: Related Workmentioning

confidence: 99%

“…However, the computation of λ and the stop condition left the same as in the original LARAC. Similar to Ben Attia et al, 23 Varyani et al 26,27 try to reduce the computation time by using destination‐based routing in overlay networks. For every destination and QoS policy combination, they generate a Direct Acyclic Graph (DAG).…”

Section: Related Workmentioning

confidence: 99%

“…To cope with the constraints while building DAG, they utilized LARAC similar search. For other constraints (i.e., delay, jitter, and loss), similar to Ben Attia et al, 23 a vector of lambda values is repeatedly computed. The algorithm stops if the difference between the feasible path QoS metric value and the constraint reached zero (i.e., stop loop).…”

Section: Related Workmentioning

confidence: 99%

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Bootstrapped LARAC algorithm for fast delay‐sensitive QoS provisioning in SDN networks

BinSahaq

Sheltami

Mahmoud

2021

Int J Communication

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In today's networks, QoS provisioning becomes a major concern for service providers due to the massive increase in connected devices (e.g., mobile devices, servers, and Things), traffic in between, and the diverse service requirements (e.g., delay and bandwidth). Software-Defined Networking (SDN) promises solution for such issues with its central network control flexibility compared to traditional networking; nonetheless, a design of a fast and QoS guaranteeing routing algorithm is still needed. Delay Constrained Least Cost (DCLC) is a well-known NP-hard problem. LAgrange Relaxation-based Aggregated Cost (LARAC) algorithm is a Dijkstra-based QoS-aware algorithm and one of many heuristic algorithms proposed in the literature to solve the DCLC problem.Despite its outstanding performance over other algorithms in SDN, it still needs improvement. In this article, we present a modified version of LARAC, called MODLARAC, to improve the solution feasibility search state by exploiting LAR-AC's lower-bound paths before the approximation process start. Also, we modify its stop condition to avoid extra non-useful Dijkstra calls. We implement and evaluate MODLARAC using a realistic ISP network topology using Mininet and controlled by Floodlight SDN controller. We then compare MODLARAC against the original LARAC and BiLAD algorithms. The obtained results showed improvement up to 20% reduction in Dijkstra calls count compared to original LARAC and BiLAD algorithms without a significant increase in path's cost or delay metrics. It reached only 3% increase in path cost and 7% in path delay in its worst case with a safe distance of 11% lower than the delay demand.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Bootstrapped LARAC algorithm for fast delay‐sensitive QoS provisioning in SDN networks

BinSahaq

Sheltami

Mahmoud

2021

Int J Communication

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“…The traffic of big data generated from various smart things is mixed into the type of several classes with different priorities and requirements. Moreover, a large number of devices in the existing infrastructure generate a huge volume of data, which deteriorates network QoS in terms of latency and packet loss [10]. To provide quality access to the variety of services hosted on datacentres and maximise performance, it is necessary to use datacentre networks efficiently.…”

Section: Related Workmentioning

confidence: 99%

IntelliTC : intelligent inter‐DC traffic controller for the Internet of everything service based on fog computing

et al. 2020

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“…We assume that the main queue of the system has an unlimited size (storage area) as long as the service module can process up to c packets per service time using its parallel servers. In fact, given the limited number of smart home applications, where each home may have 10 devices, and the processing capacity of the smart home gateway, which can process up to 100 000 flows in the network [26], we can assume that the main queue has unlimited size.…”

Section: Related Workmentioning

confidence: 99%

Dynamic QoE/QoS-Aware Queuing for Heterogeneous Traffic in Smart Home

2019

Self Cite

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Smart home gateways have to forward multi-sourced network traffic generated with different distributions and with different quality-of-service (QoS) requirements. The state-of-the-art QoS-aware scheduling methods consider only the conventional priority metrics based on the IP type of service (ToS) field to make a decision for bandwidth allocation. Such priority-based scheduling methods are not optimal to provide both QoS and quality of experience (QoE), since higher priority traffic may not require lower delay than lower priority traffic (for example, traffic generated from medical sensors has a higher priority than traffic from streaming devices, but the latter one requires lower maximum delay). To solve the gaps between QoS and QoE, we propose a new queuing model for QoS-level Pair traffic with mixed arrival distributions in the smart home network (QP-SH) to make dynamic QoS-aware scheduling decisions meeting delay requirements of all traffic while preserving their degrees of criticality. A new metric that combines the ToS field and the maximum number of packets that can be processed by the system's service during the maximum required delay is defined. Our experiments show that the proposed solution increases 15% of packets that meet their priorities and 40% of packets that meet their maximum delays as well as 25% of the total number of packets in the system. INDEX TERMS Quality of service, quality of experience, smart home, traffic scheduling optimization.

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QoS-aware software-defined routing in smart community network

Cited by 10 publications

References 25 publications

Bootstrapped LARAC algorithm for fast delay‐sensitive QoS provisioning in SDN networks

Bootstrapped LARAC algorithm for fast delay‐sensitive QoS provisioning in SDN networks

IntelliTC : intelligent inter‐DC traffic controller for the Internet of everything service based on fog computing

Dynamic QoE/QoS-Aware Queuing for Heterogeneous Traffic in Smart Home

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