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ردیف | عنوان | نوع |
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1 |
Publish–Subscribe approaches for the IoT and the cloud: Functional and performance evaluation of open-source systems
رویکردهای انتشار – اشتراک برای اینترنت اشیا و ابر: ارزیابی عملکرد و کارایی سیستمهای منبع باز-2022 Publish–Subscribe systems facilitate the communication between services or applications. A
typical system comprises the publisher, the subscriber, and the broker but, may also feature
message queues, databases, clusters, or federations of brokers, apply message delivery policies,
communication protocols, security services, and a streaming API. Not all these features are
supported by all systems or, others may be optional. As a result, there is no common ground
for the comparison of Publish–Subscribe systems. This paper presents a critical survey and
taxonomy of Publish–Subscribe systems, of their design features and technologies. The concepts
of message queuing, publish–subscribe systems, and publish–subscribe protocols for the cloud
and the IoT are discussed and clarified. The respective evaluation is about seven state-of-the-art
open-source systems namely, Apache Kafka, RabbitMQ, Orion-LD, Scorpio, Stellio, Pushpin, and
Faye. For the sake of fair comparison, a minimum set of common features is identified in all
systems. All systems are evaluated and compared in terms of functionality and performance
under real-case scenarios.
keywords: صف پیام | انتشار – اشتراک | معیارها | ارزیابی | Message queue | Publish–subscribe | Benchmarks | Evaluation |
مقاله انگلیسی |
2 |
MISS-D: A fast and scalable framework of medical image storage service based on distributed file system
MISS-D: یک چارچوب سریع و مقیاس پذیر از خدمات ذخیره سازی تصویر پزشکی بر اساس سیستم فایل توزیع شده-2020 Background and Objective Processing of medical imaging big data is deeply challenging due to the size of
data, computational complexity, security storage and inherent privacy issues. Traditional picture archiving
and communication system, which is an imaging technology used in the healthcare industry, generally
uses centralized high performance disk storage arrays in the practical solutions. The existing storage solutions
are not suitable for the diverse range of medical imaging big data that needs to be stored reliably
and accessed in a timely manner. The economical solution is emerging as the cloud computing which
provides scalability, elasticity, performance and better managing cost. Cloud based storage architecture
for medical imaging big data has attracted more and more attention in industry and academia.
Methods This study presents a novel, fast and scalable framework of medical image storage service based
on distributed file system. Two innovations of the framework are introduced in this paper. An integrated
medical imaging content indexing file model for large-scale image sequence is designed to adapt to the
high performance storage efficiency on distributed file system. A virtual file pooling technology is proposed,
which uses the memory-mapped file method to achieve an efficient data reading process and
provides the data swapping strategy in the pool.
Result The experiments show that the framework not only has comparable performance of reading and
writing files which meets requirements in real-time application domain, but also bings greater convenience
for clinical system developers by multiple client accessing types. The framework supports different
user client types through the unified micro-service interfaces which basically meet the needs of
clinical system development especially for online applications. The experimental results demonstrate the
framework can meet the needs of real-time data access as well as traditional picture archiving and communication
system.
Conclusions This framework aims to allow rapid data accessing for massive medical images, which can be
demonstrated by the online web client for MISS-D framework implemented in this paper for real-time
data interaction. The framework also provides a substantial subset of features to existing open-source and
commercial alternatives, which has a wide range of potential applications. Keywords: Hadoop distributed file system | Data packing | Memory mapping file | Message queue | Micro-service | Medical imaging |
مقاله انگلیسی |