Fog over Virtualized IoT: New Opportunity for Context-Aware Networked Applications and a Case Study

Paola Naranjo, Zahra Pooranian, Shahaboddin Shamshirband, Jemal Abawajy, Mauro Conti
2017 Applied Sciences  
In this paper, we discuss the most significant application opportunities and outline the challenges in performing a real-time and energy-efficient management of the distributed resources available at mobile devices and Internet-to-Data Center. We also present an energy-efficient adaptive scheduler for Vehicular Fog Computing (VFC) that operates at the edge of a vehicular network, connected to the served Vehicular Clients (VCs) through an Infrastructure-to-Vehicular (I2V) over multiple Foglets
more » ... ls). The scheduler optimizes the energy by leveraging the heterogeneity of Fls, where the Fl provider shapes the system workload by maximizing the task admission rate over data transfer and computation. The presented scheduling algorithm demonstrates that the resulting adaptive scheduler allows scalable and distributed implementation. dynamic scaling of the CPU computing frequencies on the energy consumption experienced by the execution of MapReduce-type jobs. Fog Data Centers (FDCs) are dedicated to supervising the transmission, distribution and communication networks [10] . All these require a precisely manage grid infrastructure from generation points to consumption ones by using the communication of measured values and transmitted control information more accurately. The IoT applications (real-time requirements, as stream processing) are distributed in different geographical locations [11] , with numerous devices and emit data via gateways (FNs) for further processing and filtering. In addition, the FNs (gateways) are hosting application modules that connect sensors to the Internet. FNs include Cloud resources that are provisioned on-demand from geographically distributed FDC. FDC (Fog Data Center) services are mainly implemented in the Fog, that use a distributed architecture over moderate-bandwidth to provide high availability operations. The vehicles are attached to one of the (RSU) in the FN [12] with the heterogeneous type of devices consider a physical infrastructure, consisting each FN as a single server or a set of servers building heterogeneous FNs. FDC has a huge amount of computations and it is distributed and may be more energy-efficient than the centralized Cloud model of computation, being the reduction of energy consumption on FDC an important challenge. Also, this drastically reduces the traffic sent to the Cloud by allowing the placement of filtering operators close to the sources of data. FDC as a vital component over the IoT (vehicular )environmental, is capable of filtering and processing a considerable amount of incoming data on edge devices, by making the data processing architecture distributed and thereby scalable. Hence, it is an important task to give a neat simulated scenario or case study, in order to detail the analytic structure of the FDC and the traffic injected to the engaged servers to make the presented model more efficient and interesting. FDC, in each processing unit, executes the currently assigned task by self-managing own local virtualized storage/computing resources. When a request for a new job (i.e., it is transferred through data network) is submitted from the remote clients and transferred through the Internet to the FNs and FDC, the resource controller dynamically performs both admission control and allocation of the available virtual resources. FDC, roughly speaking, it is composed by i) an Access Control Server and Router (ACSRs or Adaptive load dispatcher); ii) a reconfigurable computing Cloud managed by the Virtual Machine Manager (VMM), called load balancer, the related switched Virtual LAN, and iii) an adaptive controller that dynamically manages all the available computing-communication resources and also performs the admission control of the input/output traffic flows out to the ACSRs and reaches the processed information to the FNs. As we know, many efforts have been made to curtail the energy consumption in data centers. Roughly speaking, FDC consolidation is a popular strategy to further reduce the energy consumption by turning OFF the underutilized VMs and grouping the VMs onto the smallest number of physical servers. The effectiveness of FDC consolidation in driving costs out of IT is shown by the popularity of this strategy. The recent consolidation technologies employed in data centers encompass server and storage virtualization, as well as deploying tools for process automation. In this case study, we use the server virtualization as a dynamic control to improve energy efficiency in FDC. The main contribution of the paper The technical contribution of this paper focuses on the design of Fog-based VFC architecture for the energy-efficient joint management of the networking and computing resources under hard constraints on the overall tolerated computing-plus-communication latency. The main contribution of the paper is : i) To the best of our knowledge, there is no related work that consider FDC across the VFC and presented resource allocation and scheduling for the considered real traffics. This is the first Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted:
doi:10.3390/app7121325 fatcat:4un5wox3dreehakzkq6yjuvsae