@article{verma_edge-cloud_2020,
	title = {Edge-cloud computing performance benchmarking for {IoT} based machinery vibration monitoring},
	issn = {2213-8463},
	url = {http://www.sciencedirect.com/science/article/pii/S2213846320301759},
	doi = {10.1016/j.mfglet.2020.12.004},
	abstract = {Advances in low cost and reliable sensing, connectivity (Internet of Things), computational power, and advanced analytics, are leading to a new wave of innovation in machinery status sensing and condition monitoring. Significant research efforts are directed towards cloud computing architectures. However, given the latency, bandwidth, cost, security, and privacy concerns, further supported by the ever-increasing capabilities of edge computing devices, there is a need to consider both edge and cloud computing together to make informed decisions based upon context and performance. We present an edge-cloud performance evaluation for IoT based machinery vibration monitoring, to foster deployment for the contexts considered},
	language = {en},
	urldate = {2020-12-15},
	journal = {Manufacturing Letters},
	author = {Verma, Ankur and Goyal, Ayush and Kumara, Soundar and Kurfess, Thomas},
	month = dec,
	year = {2020},
	keywords = {Edge computing, Internet of Things, machinery vibration monitoring, smart manufacturing},
}

{"_id":"urcuCwBF2DTsZ3sR4","bibbaseid":"verma-goyal-kumara-kurfess-edgecloudcomputingperformancebenchmarkingforiotbasedmachineryvibrationmonitoring-2020","author_short":["Verma, A.","Goyal, A.","Kumara, S.","Kurfess, T."],"bibdata":{"bibtype":"article","type":"article","title":"Edge-cloud computing performance benchmarking for IoT based machinery vibration monitoring","issn":"2213-8463","url":"http://www.sciencedirect.com/science/article/pii/S2213846320301759","doi":"10.1016/j.mfglet.2020.12.004","abstract":"Advances in low cost and reliable sensing, connectivity (Internet of Things), computational power, and advanced analytics, are leading to a new wave of innovation in machinery status sensing and condition monitoring. Significant research efforts are directed towards cloud computing architectures. However, given the latency, bandwidth, cost, security, and privacy concerns, further supported by the ever-increasing capabilities of edge computing devices, there is a need to consider both edge and cloud computing together to make informed decisions based upon context and performance. We present an edge-cloud performance evaluation for IoT based machinery vibration monitoring, to foster deployment for the contexts considered","language":"en","urldate":"2020-12-15","journal":"Manufacturing Letters","author":[{"propositions":[],"lastnames":["Verma"],"firstnames":["Ankur"],"suffixes":[]},{"propositions":[],"lastnames":["Goyal"],"firstnames":["Ayush"],"suffixes":[]},{"propositions":[],"lastnames":["Kumara"],"firstnames":["Soundar"],"suffixes":[]},{"propositions":[],"lastnames":["Kurfess"],"firstnames":["Thomas"],"suffixes":[]}],"month":"December","year":"2020","keywords":"Edge computing, Internet of Things, machinery vibration monitoring, smart manufacturing","bibtex":"@article{verma_edge-cloud_2020,\n\ttitle = {Edge-cloud computing performance benchmarking for {IoT} based machinery vibration monitoring},\n\tissn = {2213-8463},\n\turl = {http://www.sciencedirect.com/science/article/pii/S2213846320301759},\n\tdoi = {10.1016/j.mfglet.2020.12.004},\n\tabstract = {Advances in low cost and reliable sensing, connectivity (Internet of Things), computational power, and advanced analytics, are leading to a new wave of innovation in machinery status sensing and condition monitoring. Significant research efforts are directed towards cloud computing architectures. However, given the latency, bandwidth, cost, security, and privacy concerns, further supported by the ever-increasing capabilities of edge computing devices, there is a need to consider both edge and cloud computing together to make informed decisions based upon context and performance. We present an edge-cloud performance evaluation for IoT based machinery vibration monitoring, to foster deployment for the contexts considered},\n\tlanguage = {en},\n\turldate = {2020-12-15},\n\tjournal = {Manufacturing Letters},\n\tauthor = {Verma, Ankur and Goyal, Ayush and Kumara, Soundar and Kurfess, Thomas},\n\tmonth = dec,\n\tyear = {2020},\n\tkeywords = {Edge computing, Internet of Things, machinery vibration monitoring, smart manufacturing},\n}\n\n\n\n","author_short":["Verma, A.","Goyal, A.","Kumara, S.","Kurfess, T."],"key":"verma_edge-cloud_2020","id":"verma_edge-cloud_2020","bibbaseid":"verma-goyal-kumara-kurfess-edgecloudcomputingperformancebenchmarkingforiotbasedmachineryvibrationmonitoring-2020","role":"author","urls":{"Paper":"http://www.sciencedirect.com/science/article/pii/S2213846320301759"},"keyword":["Edge computing","Internet of Things","machinery vibration monitoring","smart manufacturing"],"metadata":{"authorlinks":{}},"html":""},"bibtype":"article","biburl":"https://bibbase.org/zotero/mh_lenguyen","dataSources":["yanwtMpCcFaHzRwWb","iwKepCrWBps7ojhDx"],"keywords":["edge computing","internet of things","machinery vibration monitoring","smart manufacturing"],"search_terms":["edge","cloud","computing","performance","benchmarking","iot","based","machinery","vibration","monitoring","verma","goyal","kumara","kurfess"],"title":"Edge-cloud computing performance benchmarking for IoT based machinery vibration monitoring","year":2020}