Analysing RPC and Testing the Performance of Solutions

Király, Sándor; Szekely, Szilveszter

doi:10.31449/inf.v42i4.1510

Cited by 5 publications

(8 citation statements)

References 3 publications

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“…Compared with other interprocess communications, such as file lock, semaphore and so on, RPC can transmit complex message structures more conveniently in an application, which is easy to maintain and expand. Especially when the media service needs to access multiple read intervals in a single request, the RPC based on protocol buffer (protobuf) can design the message body more conveniently 43 …”

Section: Prototype System Design and Implementationmentioning

confidence: 99%

TVSR‐OR: Tile‐based 360‐degree video streaming over real time streaming protocol with optimized read

Zeng

Yin

et al. 2023

Trans Emerging Tel Tech

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Among video application use cases and scenarios, 360-degree video applications gradually become significant. The state-of-the-art solution for 360-degree video streaming is field of view (FOV) transmission, whose quality of experience highly depends on system processing speed and network latency. The extant 360-degree video FOV transmission profiles transmit multiple video tile streams to the client over either Hypertext Transfer Protocol (HTTP) or Real Time Streaming Protocol (RTSP). The client needs to merge all different tile streams after receiving them, which may cause a data synchronization problem of waiting for each tile to sync in the presents of packet losses. Therefore, we propose a system to select and merge tile streams on the Content Delivery Network (CDN) server and transmit the merged stream to the client. During the streaming service, the client can send a viewport switch request through RTSP signaling, and the server will subsequently deliver the merged video stream of the new viewport to the client after receiving the request. Also, to reduce disk overhead from parallel reads, we optimize the system with a file prefetch strategy to reduce unorganized, random, and parallel reads into serialized reads of large data trunks. We evaluate its performance through user request simulation experiments. Compared with the extant transmission solution, our system provides slightly lower video transmission latency, lower central processing unit (CPU) usage, and better disk performance under heavy service load.

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Section: Prototype System Design and Implementationmentioning

confidence: 99%

TVSR‐OR: Tile‐based 360‐degree video streaming over real time streaming protocol with optimized read

Zeng

Yin

et al. 2023

Trans Emerging Tel Tech

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“…We utilized gRPC, a Google open-source request-response protocol framework that is cross-platform and language-independent. This RPC was used as an executor subroutines on several machines connected over a shared network [26]. Moreover, the gRPC was designed based on an HTTP/2 transport protocol, enabling bi-directional real-time data streaming.…”

Section: Client-server Communicationmentioning

confidence: 99%

“…Afterward, the gRPC Stub on the edge device requests service by sending this encoded data. The selection of Protobuf was based on a recent trade-off performed by [26], showing that Protobuf had a lower network load than JavaScript Object Notation (JSON) or Binary Javascript Object Notation (BSON) format. Moreover, the examination by [26] of the application layer's performance, messaging protocols, and binary serialization formats, concluded that although Protobuf's competitor, Constrained Application Protocol (CoAP), offers the lowest latency and overhead, it cannot ensure reliable transmission.…”

Section: Client-server Communicationmentioning

confidence: 99%

“…The selection of Protobuf was based on a recent trade-off performed by [26], showing that Protobuf had a lower network load than JavaScript Object Notation (JSON) or Binary Javascript Object Notation (BSON) format. Moreover, the examination by [26] of the application layer's performance, messaging protocols, and binary serialization formats, concluded that although Protobuf's competitor, Constrained Application Protocol (CoAP), offers the lowest latency and overhead, it cannot ensure reliable transmission. Meanwhile, Protobuf supported a faster serialization and three-fold reduction in serialized messages compared to other serialization libraries like Flatbuffers [27].…”

Section: Client-server Communicationmentioning

confidence: 99%

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Cloud-Based Architecture for YOLOv3 Object Detector using gRPC and Protobuf

Jamzuri

Mandala

Analia

et al. 2022

Jurnal Teknik Elektro

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The deep learning-based object detector accuracy has surpassed conventional detection methods. Although implementation is still limited to hardware capabilities, this problem can be overcome by combining edge devices with cloud computing. The recent study of cloud-based object detector architecture is generally based on representational state transfer (RESTful web services), which uses a pooling system method for data exchange. As a result, this system leads to a low detection speed and cannot support real-time data streaming. Therefore, this study aims to enhance the detection speed in cloud-based object recognition systems using gRPC and Protobuf to support real-time detection. The proposed architecture was deployed on the Virtual Machine Instance (VMI) equipped with a Graphics Processing Unit (GPU). The gRPC server and YOLOv3 deep learning object detector were executed on the cloud server to handle detection requests from edge devices. Furthermore, the captured images from the edge devices were encoded into Protobuf format to reduce the message size delivered to the cloud server. The results showed that the proposed architecture improved detection speed performance on the client-side in the range of 0.27 FPS to 1.72 FPS compared to the state-of-the-art method. It was also observed that it could support multiple edge devices connection with slight performance degradation in the range of 1.78 FPS to 1.83 FPS, depending on the network interface used.

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“…The RDF designed as a foundation for other languages functions as a standard. At the same time, the schemes forming its foundation can differ (Király-Szekely, 2018), and the RDF can even support the chronological development of the schemes.…”

Section: Subjectmentioning

confidence: 99%

Trend Analysis of Technologies Supporting the Availability of Online Content: From Keyword-Based Search to the Semantic Web

Molnár

2020

Acta Universitatis Sapientiae, Communicatio

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The era of Web 1.0 implied the connection of web-based documents via links, which enabled search engines to scan for information and guarantee the search and availability of webpages. Web 2.0 represented the next evolutionary stage. Known as the collaborative web, the emphasis in this case was on the establishment of services and content by the community. Search options were complemented with labelling and frequently undesirable clickstream analysis coupled with push technology-supported information provision. The semantic web is a revolutionary development, which, in addition to processing information by humans, assures the readability of datasets by machines and facilitates communication between devices. In order to promote data and information processing by machines, the semantic web relies on a special ontology allocating the respective meaning to the given data along with relying on the global indexing and naming schemes of the web. Several ontologies emerged with differing basic guidelines while displaying compatibility to the RDF standard ranging from the more semantic description of bibliographical data in libraries to the description of information gained from social networks and human conversations. While Web 3.0 is often used interchangeably with the semantic web, the former one with its intelligent server function exceeds the semantic web. We have to ask ourselves, however, whether we can rely on the accuracy of the obtained data, and we must explore what progress have libraries – expected to increase reliability – made regarding the implementation of semantic data storage.

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Analysing RPC and Testing the Performance of Solutions

Cited by 5 publications

References 3 publications

TVSR‐OR: Tile‐based 360‐degree video streaming over real time streaming protocol with optimized read

TVSR‐OR: Tile‐based 360‐degree video streaming over real time streaming protocol with optimized read

Cloud-Based Architecture for YOLOv3 Object Detector using gRPC and Protobuf

Trend Analysis of Technologies Supporting the Availability of Online Content: From Keyword-Based Search to the Semantic Web

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