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Benchmarking Distributed Stream Processing Platforms for IoT Applications [chapter]

Anshu Shukla, Yogesh Simmhan
2017 Lecture Notes in Computer Science  
Here, we develop a benchmark suite and per- formance metrics to evaluate DSPS for streaming IoT applications.  ...  Distributed Stream Processing Systems (DSPS) are becoming es- sential components of any IoT stack, but the efficacy and performance of contemporary DSPS have not been rigorously studied for IoT data streams  ...  We propose categories of tasks that are essential for IoT applications and the key features that are present in their input data streams. 2.  ... 
doi:10.1007/978-3-319-54334-5_7 fatcat:ri6vg6aig5gujjm2t6ejfcsdcq

RIoTBench: An IoT benchmark for distributed stream processing systems

Anshu Shukla, Shilpa Chaturvedi, Yogesh Simmhan
2017 Concurrency and Computation  
The inherent closedloop responsiveness and decision making of IoT applications make them ideal candidates for using low latency and scalable stream processing platforms.  ...  Distributed Stream Processing Systems (DSPS) hosted on Cloud data-centers are becoming the vital engine for real-time data processing and analytics in any IoT software architecture.  ...  We thank the reviewers of the Technology Conference on Performance Evaluation & Benchmarking (TPCTC), 2016, for their valuable comments to improve the benchmark suite.  ... 
doi:10.1002/cpe.4257 fatcat:rivgwd7jqbdr5gu7lc6rkshzne

Towards a High-Level Description for Generating Stream Processing Benchmark Applications

Alessio Pagliari, Fabrice Huet, Guillaume Urvoy-Keller
2019 2019 IEEE International Conference on Big Data (Big Data)  
A considerable amount of work has been dedicated to improve performance and features of DSP platforms. Thus, benchmark application are necessary for comparison and evaluation.  ...  The relevance of Data Stream Processing (DSP) is nowadays established, thanks to its capability to analyze continuous streams and provide statistics in real-time.  ...  The research leading to these results has received funding from the European Commission's Horizon 2020 Framework Programme for Research and Innovation (H2020), under grant agreement #732339: PrEstoCloud  ... 
doi:10.1109/bigdata47090.2019.9006278 dblp:conf/bigdataconf/PagliariHU19 fatcat:tojenujl3vg5hjphpuonmrgaty

Analytics-as-a-Service in a Multi-Cloud Environment through Semantically enabled Hierarchical Data Processing [article]

Prem Prakash Jayaraman, Charith Perera, Dimitrios Georgakopoulos, Schahram Dustdar, Dhavalkumar Thakker, Rajiv Ranjan
2016 arXiv   pre-print
A large number of cloud middleware platforms and tools are deployed to support a variety of Internet of Things (IoT) data analytics tasks.  ...  In this paper, we have outlined an innovative hierarchical data processing architecture that utilises semantics at all the levels of IoT stack in multicloud environments.  ...  Specially, there is no consensus on available performance benchmarking for executing large-scale IoT applications across distributed data centers.  ... 
arXiv:1606.07935v1 fatcat:fiuhjbrqivcq7lsvqnydfze4ra

A Survey on IoT Big Data Analytic Systems: Current and Future

Yuya Sasaki
2021 IEEE Internet of Things Journal  
We explore Hadoop-and Spark-based batch processing systems for spatio-temporal and trajectory data. We also review fog-and edge-aware stream processing systems.  ...  The generation of IoT big data means that efficient analytic systems are needed for many application scenarios, for example, to optimize urban planning, solve air pollution problems, and improve business  ...  Frontier [76] is a distributed and resilient edge-processing platform for IoT devices.  ... 
doi:10.1109/jiot.2021.3131724 fatcat:cgvglkxiavdg3a6uv2zljl4ofm

Evaluation of distributed stream processing frameworks for IoT applications in Smart Cities

Hamid Nasiri, Saeed Nasehi, Maziar Goudarzi
2019 Journal of Big Data  
Distributed stream processing frameworks (DSPFs) have the capacity to handle real-time data processing for Smart Cities.  ...  In this paper, we examine the applicability of employing distributed stream processing frameworks at the data processing layer of Smart City and appraising the current state of their adoption and maturity  ...  Abbreviations IoT: Internet of Things; DSPF: distributed stream processing framework; RFID: Radio Frequency IDentification; HDFS: Hadoop Distributed File System; API: application programming interface;  ... 
doi:10.1186/s40537-019-0215-2 fatcat:ijkn7pbgybfz5d2md2xgkmsh2a

JANUS: Benchmarking Commercial and Open-Source Cloud and Edge Platforms for Object and Anomaly Detection Workloads [article]

Karthick Shankar, Pengcheng Wang, Ran Xu, Ashraf Mahgoub, Somali Chaterji
2020 arXiv   pre-print
We find that AWS IoT Greengrass delivers at least 2X lower latency and 1.25X lower cost compared to all other cloud platforms for the compute-light outlier detection workload.  ...  In our paper, JANUS, we profile the performance/and the compute versus communication cost for a compute-light IoT workload and a compute-intensive IoT workload.  ...  We perform benchmarking experiments with these applications on two different platform types-edge computing and cloud computing platforms [31] .  ... 
arXiv:2012.04880v1 fatcat:6poo6wjgszf3fbg5qbu3mofajm

Sensor observation streams within cloud-based IoT platforms: Challenges and directions

Antoine Auger, Ernesto Exposito, Emmanuel Lochin
2017 2017 20th Conference on Innovations in Clouds, Internet and Networks (ICIN)  
Unlike existing surveys, this paper is intended for developers that would like to design and implement a Cloud-based IoT platform capable of handling sensor observation streams.  ...  With the growth of the Internet of Things (IoT), more and more connected sensors will produce unbounded observation streams.  ...  To ingest and process large data streams coming from sensors, we have witnessed the deployment of many Cloud-based IoT platforms.  ... 
doi:10.1109/icin.2017.7899407 dblp:conf/icin/AugerEL17 fatcat:njchl5tl25dxznsgtr3bf5spfq

NAMB: A Quick and Flexible Stream Processing Application Prototype Generator

Alessio Pagliari, Fabrice Huet, Guillaume Urvoy-Keller
2020 2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID)  
Data Stream Processing (DSP) is a popular approach to deal with this constraint in many fields, from social networks to IoT.  ...  Benchmark Applications The first benchmark application appositely developed to benchmark streaming data is Linear Road [7] .  ... 
doi:10.1109/ccgrid49817.2020.00-87 dblp:conf/ccgrid/PagliariHU20 fatcat:ep226jzmzjavdk7v6avx74vh4u

On the use of IoT and Big Data Technologies for Real-time Monitoring and Data Processing

Y. Nait Malek, A. Kharbouch, H. El Khoukhi, M. Bakhouya, V. De Florio, D. El Ouadghiri, S. Latre, C. Blondia
2017 Procedia Computer Science  
In this paper, we propose to combine IoT techniques with Big data technologies into a holistic platform for continuous and real-time data monitoring and processing.  ...  Big data and IoT technologies have been recently proposed for timely analysing information (i.e., data, events) streams.  ...  Several IoT platforms have been proposed for easy deployment of context-aware applications.  ... 
doi:10.1016/j.procs.2017.08.281 fatcat:7tu7zlaz2fgxzp6jgozpohorkm

VIoLET: A Large-Scale Virtual Environment for Internet of Things [chapter]

Shreyas Badiger, Shrey Baheti, Yogesh Simmhan
2018 Lecture Notes in Computer Science  
Simulation environments that allow analytical modeling are a poor substitute for evaluating software platforms or application workloads in realistic computing environments.  ...  Here, we propose VIoLET, a virtual environment for defining and launching large-scale IoT deployments within cloud VMs.  ...  Other have proposed IoT data stream and application workloads for evaluating big data platforms, particularly stream processing ones.  ... 
doi:10.1007/978-3-319-96983-1_22 fatcat:bxgzvxxssjeeppbxd4c3tybp7u

Big Data Streaming Platforms: A Review

Harish Kumar, Ping Jack Soh, Mohd Arfian Ismail
2022 Iraqi Journal for Computer Science and Mathematics  
This article provides an overview of big data architecture and platforms, tools for data stream processing, and examples of implementations.  ...  Owing to this study, the feasibility of large-scale data processing for distributed, real-time computing is improved even when the systems are overwhelmed.  ...  Customers are only billed when data are processed if platform distribution can be achieved on an infrastructureas-a-service cloud platform, according to the company.  ... 
doi:10.52866/ijcsm.2022.02.01.010 fatcat:lbgm4mnn4rgiflfqxhsezm5j2u

A Survey on Edge Performance Benchmarking

Blesson Varghese, Nan Wang, David Bermbach, Cheol-Ho Hong, Eyal De Lara, Weisong Shi, Christopher Stewart
2021 ACM Computing Surveys  
In this context, the performance characteristics of such systems will need to be captured rapidly, which is referred to as performance benchmarking, for application deployment, resource orchestration,  ...  Therefore, it is envisioned that a large-scale, geographically dispersed, and resource-rich distributed system will emerge and play a key role in the future Internet.  ...  The latter facilitates benchmarking by combining distributed stream applications using modular IoT tasks.  ... 
doi:10.1145/3444692 fatcat:75kmnweazzeppefekfyrxmemze

A Survey on Edge Performance Benchmarking [article]

Blesson Varghese and Nan Wang and David Bermbach and Cheol-Ho Hong and Eyal de Lara and Weisong Shi and Christopher Stewart
2020 arXiv   pre-print
In this context, the performance characteristics of such systems will need to be captured rapidly, which is referred to as performance benchmarking, for application deployment, resource orchestration,  ...  Therefore, it is envisioned that a large-scale, geographically dispersed, and resource-rich distributed system will emerge and play a key role in the future Internet.  ...  The latter facilitates benchmarking by combining distributed stream applications using modular IoT tasks.  ... 
arXiv:2004.11725v2 fatcat:gyqqgfqf5fe2jk2ntlnd2itmli

PATH2iot: A Holistic, Distributed Stream Processing System

Peter Michalak, Paul Watson
2017 2017 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)  
Abstract-The PATH2iot open-source platform presents a new approach to stream processing for Internet of Things applications by automatically partitioning and deploying the computation over the available  ...  PATH2iot: A Holistic, Distributed Stream Processing System.  ...  Matthew Forshaw for his expert advice on energy modelling, Dr. Sarah Heaps for statistics and Prof. Mike Trenell for the healthcare application.  ... 
doi:10.1109/cloudcom.2017.35 dblp:conf/cloudcom/MichalakW17 fatcat:bd7lrl5hdnarzcajhnmi5oxcyy
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