Path Selection with Joint Latency and Packet Loss for Edge Computing in SDN

Hu, Chih‐Lin; Hsu, Chao-Yu; Khuukhenbaatar, Sod-Erdene; Yamkhin, Dashdorj; Dong, Yun

doi:10.23919/apnoms.2019.8892916

Cited by 4 publications

(8 citation statements)

References 11 publications

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“…However, it requires statistical history data which may be ineffective in SDN due to memory constraints [9]. Hu et al [15] considered latency and packet loss to design path selection. Delaysensitive flows are routed through a path with minimal delay, other flows are routed via a path with lower packet loss.…”

Section: Related Workmentioning

confidence: 99%

“…Similarly, Alnajim and Salehi [27] presented a QoS-aware path selection algorithm to speed up rerouting of time-sensitive flows for real-time applications, which spare the bottleneck links causing the infeasible scheduling. However, the work in [15,27] did not consider the switch load during the path selection decision. Link latency and the ratio of the link delivery should also be considered to guarantee the quality of the link selected.…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, the study obtains the summation ∑ N Ψ, f lag in each list of k paths, which in turn served as critical switch frequency score (CWF score ). In this way, for each switch Si the value of C SCBR (N ) and C load are retrieved and append the corresponding S i flag as shown in Algorithm 2 line (12)(13)(14)(15)(16). Similarly, for each P i in P, such that P i ∈ P, the summation of S i value is appended to the corresponded P i .…”

Section: Critical Switch Detection and Expected Loadmentioning

confidence: 99%

“…shown in Algorithm 2 line (12)(13)(14)(15)(16). Similarly, for each Pi in P, such that Pi ∈ P, the summa tion of Si value is appended to the corresponded Pi.…”

Section: Critical Switch Detection and Expected Loadmentioning

confidence: 99%

“…The existing route path selection considers a single metric during path selection but does not optimize the switch update operation mainly caused by poor link quality and higher update operation in the switch flow table. Several path selection works have been proposed but they focus on the shortest distance [12], link latency [14,15], link bandwidth [16] as routing metrics for route path selection. These types of metrics are insufficient and not appropriate to meet the challenging Service-Level Agreement (SLA) of delaysensitive applications.…”

Section: Introductionmentioning

confidence: 99%

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Route Path Selection Optimization Scheme Based Link Quality Estimation and Critical Switch Awareness for Software Defined Networks

et al. 2021

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Software-defined network (SDN) is a new paradigm that decouples the control plane and data plane. This offered a more flexible way to efficiently manage the network. However, the increasing number of traffics due to the proliferation of the Internet of Things (IoT) devices also increase the number of flow arrival which in turn causes flow rules to change more often, and similarly, path setup requests increased. These events required route path computation activities to take place immediately to cope with the new network changes. Searching for an optimal route might be costly in terms of the time required to calculate a new path and update the corresponding switches. However, the current path selection schemes considered only single routing metrics either link or switch operation. Incorporating link quality and switch’s role during path selection decisions have not been considered. This paper proposed Route Path Selection Optimization (RPSO) with multi-constraint. RPSO introduced joint parameters based on link and switches such as Link Latency (LL), Link Delivery Ratio (LDR), and Critical Switch Frequency Score (CWFscore). These metrics encourage path selection with better link quality and a minimal number of critical switches. The experimental results show that the proposed scheme reduced path stretch by 37%, path setup latency by 73% thereby improving throughput by 55.73%, and packet delivery ratio by 12.5% compared to the baseline work.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Critical Switch Detection and Expected Loadmentioning

confidence: 99%

“…shown in Algorithm 2 line (12)(13)(14)(15)(16). Similarly, for each Pi in P, such that Pi ∈ P, the summa tion of Si value is appended to the corresponded Pi.…”

Section: Critical Switch Detection and Expected Loadmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Route Path Selection Optimization Scheme Based Link Quality Estimation and Critical Switch Awareness for Software Defined Networks

et al. 2021

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FitPath: QoS-Based Path Selection With Fittingness Measure in Integrated Edge Computing and Software-Defined Networks

Hsu

Sung

2022

IEEE Access

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Integrating Software-Defined Networking (SDN) and Edge Computing (EC) technologies becomes a promising approach to harness enormous data traffic in the Internet. Recent studies examined the Quality of Service (QoS) based routing paradigms for different data applications such as IoT, heterogeneous networks, and 5G network slicing in such integrated networks. In this paper, our study formulates the QoS-specific routing optimization as a minimum-cost resource allocation problem, while multi-dimensional factors of bandwidth cost, latency, and packet los are jointly considered. Since we use the fittingness factor to help the problem solving, we propose a path selection scheme based on the measure of fittingness factor, briefly named as FitPath. The FitPath scheme can appropriately adjust network resources to maintain delivery time against various service requirements of user demands. Simulation results show that the FitPath scheme can perform better than the Open Shortest Path First (OSPF) and Greedy heuristic schemes in terms of the total of link costs, delivery latency, and packet loss rate under both of normal and heavy data traffic experiments. The effects by the FitPath scheme can be further enhanced with the top-B% path selection policy in integrated network environments.INDEX TERMS Routing, data delivery, path selection, quality of service (QoS), edge computing, (EC) and software-defined networking (SDN).

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