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Abstract
The world is witnessing an unprecedented growth of cyber-physical systems (CPS), which are foreseen to revolutionize our world via creating new services and applications in a variety of sectors, such as environmental monitoring, mobile-health systems, intelligent transportation systems, and so on. The information and communication technology sector is experiencing a significant growth in data traffic, driven by the widespread usage of smartphones, tablets, and video streaming, along with the significant growth of sensors deployments that are anticipated in the near future. It is expected to outstandingly increase the growth rate of raw sensed data. In this paper, we present the CPS taxonomy via providing a broad overview of data collection, storage, access, processing, and analysis. Compared with other survey papers, this is the first panoramic survey on big data for CPS, where our objective is to provide a panoramic summary of different CPS aspects. Furthermore, CPS requires cybersecurity to protect them against malicious attacks and unauthorized intrusion, which become a challenge with the enormous amount of data that are continuously being generated in the network. Thus, we also provide an overview of the different security solutions proposed for CPS big data storage, access, and analytics. We also discuss big data meeting green challenges in the contexts of CPS.
Highlights
T HE growing number of “things”, such as embedded devices, sensors, radio-frequency identification (RFID), and actuators have revolutionized the world through their integrated communication and tight interactions to create pervasive and global cyber-physical systems (CPS)
We provide a broader summary of security solutions proposed for big data CPS in data collection, storage, and access, as well as in data processing and analytics; unlike previous survey papers such as [15], [27], [28] that only focused on security of a particular component or element of big data
The orchestrator’s main components are: i) a green lesser to establish a per-job service-level agreements (SLA) that takes into account the available power, the power consumption statistics of jobs, the network and server states; ii) a preexecution analyzer that executes jobs based on their power consumption statistics; iii) a network and server states predictors; iv) a network traffic analyzer which helps eliminate redundant traffic using traffic engineering techniques; v) a VMizer that intelligently places virtual machines (VMs) such that some nodes are put to sleep; (vi) a pizer that schedules and places processes to a subset of clusters such that system resources are efficiently utilized; and (vii) a post-execution analyzer to analyze the energy profile of completed jobs
Summary
T HE growing number of “things”, such as embedded devices, sensors, radio-frequency identification (RFID), and actuators have revolutionized the world through their integrated communication and tight interactions to create pervasive and global cyber-physical systems (CPS). It is expected that over 50 billion sensors will be connected to
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