Effect of Packet Loss and Reorder on Quality of Audio Streaming

Laghari, Asif Ali; Laghari, Rashid Ali; Wagan, Asif Ali; Umrani, Aamir Iqbal

doi:10.4108/eai.13-7-2018.160390

Cited by 15 publications

(6 citation statements)

References 32 publications

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“…The PLR constraint is 0.01. As shown in [41], the impairment is almost imperceptible for audio transmission with PLR 10 −2 . For all the scenarios, the energy consumption decreases with increasing average channel SNR because it is possible to use a high FEC code rate at high channel SNR to achieve the PLR constraint, and thus save energy.…”

Section: Performance Comparisonmentioning

confidence: 95%

Energy Optimization For Hybrid ARQ With Turbo Coding: Rate Adaptation and Allocation

Zhang

Milstein

Cosman

2020

IEEE Trans. Veh. Technol.

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We consider incremental redundancy (IR) hybrid automatic repeat request (HARQ) over independent block-fading channels with turbo coding. We consider different cases of channel state information (CSI) at the transmitter: the transmitter has no knowledge of any CSI, or knows the CSI in previous transmission rounds through a perfect feedback channel, or knows both current and previous CSI. The transmitter decides the forward error correction code rate based on the CSI it has. We minimize the energy consumption of turbo-coded HARQ, subject to a packet loss rate constraint. Numerical results show that the energy consumption of HARQ decreases when more CSI information is available at the transmitter. We also compare IR combining with Chase combining and the system without combining, and IR combining yields the least energy consumption.

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Section: Performance Comparisonmentioning

confidence: 95%

Energy Optimization For Hybrid ARQ With Turbo Coding: Rate Adaptation and Allocation

Zhang

Milstein

Cosman

2020

IEEE Trans. Veh. Technol.

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“…In contrast to the cloud, where all data is transmitted to and stored in a centralized way, edge computing provides additional resources to take the load from the cloud [48]. Especially low-latency application fields, like real-time analytics or video surveillance, can benefit from the increased bandwidth and reduced latency realized by edge computing [49,50]. Also, the geographically distributed nature of large IoT networks is prone to unstable network connections [51].…”

Section: Principles Of Edge Computingmentioning

confidence: 99%

Cloud-Edge Orchestration for Smart Cities: A Review of Kubernetes-based Orchestration Architectures

Böhm

Wirtz

2022

EAI Endorsed Trans Smart Cities

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Edge computing offers computational resources near data-generating devices to enable low-latency access. Especially for smart city contexts, edge computing becomes inevitable for providing real-time services, like air quality monitoring systems. Kubernetes, a popular container orchestration platform, is often used to efficiently manage containerized applications in smart cities. Although it misses essential requirements of edge computing, like network-related metrics for scheduling decisions, it is still considered. This paper analyzes custom cloud-edge architectures implemented with Kubernetes. Specifically, we analyze how essential requirements of edge orchestration in smart cities are solved. Also, shortcomings are identified in these architectures based on the fundamental requirements of edge orchestration. We conduct a literature review to obtain the general requirements of edge computing and edge orchestration for our analysis. We map these requirements to the capabilities of Kubernetes-based cloud-edge architectures to assess their level of achievement. Issues like using network-related metrics and the missing topology-awareness of networks are partially solved. However, requirements like real-time resource utilization, fault-tolerance, and the placement of container registries are in the early stages. We conclude that Kubernetes is an eligible candidate for cloudedge orchestration. When the formerly mentioned issues are solved, Kubernetes can successfully contribute latency-critical, large-scale, and multi-tenant application deployments for smart cities.

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“…Researchers have also indicated the emerging requirement of more research and development related to cloud event services present in cloud computing using real-world applications. Research is going on event services on cloud computing perspective of applications that how cloud computing support much better to multiple applications of organizations, and in this regard, many researchers are researching the analysis of cloud computing for applications [35]. A study has been carried out in demonstrating the fact that, by using patterns found in common cloud computing, mobile cloud computing can be optimized to use fewer resources.…”

Section: Previous Studiesmentioning

confidence: 99%

Highlight the Features of AWS, GCP and Microsoft Azure that Have an Impact when Choosing a Cloud Service Provider

Kamal¹,

Raza²,

Alam³

et al. 2020

IJRTE

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Picking up public cloud service providers is now becoming a harder task in an enterprise organization. This paper will help in reducing more hesitation to choose a public cloud service provider. This paper is highlighting computation, storage, and infrastructure is important to service features that have an impact when choosing cloud service providers. Compare these three (AWS, Microsoft Azure, GCP) CSPs concerning service, price, advantages, and highlight significant service features. Studies discuss the primary reason to choose a CSP that normally enhance features, familiarity with the brand, suitable for organization and security parameters considered when choosing CSP. Amazon Web Services proved its leadership by maintaining about 33% share in the market throughout for several quarters irrespective of the market size increased by a factor of 3. Microsoft has shown prominent performance in SaaS. Since 2008, after introducing PaaS in the form of Google App Engine, Google is continuously enhancing its cloud computing services of Google Cloud Platform.

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Effect of Packet Loss and Reorder on Quality of Audio Streaming

Cited by 15 publications

References 32 publications

Energy Optimization For Hybrid ARQ With Turbo Coding: Rate Adaptation and Allocation

Energy Optimization For Hybrid ARQ With Turbo Coding: Rate Adaptation and Allocation

Cloud-Edge Orchestration for Smart Cities: A Review of Kubernetes-based Orchestration Architectures

Highlight the Features of AWS, GCP and Microsoft Azure that Have an Impact when Choosing a Cloud Service Provider

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