Fog computing is an emerging paradigm that aims to improve the efficiency and QoS of cloud computing by extending the cloud to the edge of the network. This paper develops a comprehensive energy efficiency analysis framework based on mathematical modeling and heuristics to study the offloading of virtual machine (VM) services from the cloud to the fog. The analysis addresses the impact of different factors including the traffic between the VM and its users, the VM workload, the workload versus number of users profile and the proximity of fog nodes to users. Overall, the power consumption can be reduced if the VM users traffic is high and/or the VMs have a linear power profile. In such a linear profile case, the creation of multiple VM replicas does not increase the computing power consumption significantly (there may be a slight increase due to idle / baseline power consumption) if the number of users remains constant, however the VM replicas can be brought closer to the end users, thus reducing the transport network power consumption. In our scenario, the optimum placement of VMs over a cloud-fog architecture significantly decreased the total power consumption by 56% and 64% under high user data rates compared to optimized distributed clouds placement and placement in the existing AT&T network cloud locations, respectively.
This work evaluates three Fog Computing dataplacement algorithms via experiments carried out with theiFogSim simulator. The paper describes the three algorithms(Cloud-only, Mapping, Edge-ward) in the context of an Internetof Things scenario, which has been based on an e-Health systemwith variations in applications and network topology. Resultsachieved show that edge placement strategies are beneficial toassist cloud computing in lowering latency and cloud energyexpenditure.
The proliferation in data volume and processing requests calls for a new breed of on-demand computing. Fog computing is proposed to address the limitations of cloud computing by extending processing and storage resources to the edge of the network. Cloud and fog computing employ virtual machines (VMs) for efficient resource utilization. In order to optimize the virtual environment, VMs can be migrated or replicated over geo-distributed physical machines for load balancing and energy efficiency. In this work, we investigate the offloading of VM services from the cloud to the fog considering the…
Fog computing extends cloud computing technology to the edge of the infrastructure to let IoT applications access objects' data with reduced latency, location awareness and dynamic computation. By displacing workloads from the central cloud to the edge devices, fog computing overcomes communication bottlenecks avoiding raw data transfer to the central cloud, thus paving the way for the next generation IoT-based applications. In this paper we study scheduling and placement of applications in fog computing, which is key to ensure profitability for the involved stakeholders. We consider a scenari…
Applications are sets of interacting components that can be executed in sequence, in parallel, or by using more complex constructs such as selections and loops. They can, therefore, be modeled as structured graphs with sub-structures consisting of these constructs. Fog computing can reduce the latency induced by distant clouds by enabling the deployment of some components at the edge of the network (i.e., closer to end-devices) while keeping others in the cloud. Network Functions Virtualization (NFV) decouples software from hardware and enables an agile deployment of network services and appli…
The Function-as-a-Service (FaaS) paradigm has a lot of potential as a computing model for fog environments comprising both cloud and edge nodes. When the request rate exceeds capacity limits at the edge, some functions need to be offloaded from the edge towards the cloud. In this position paper, we propose an auction-based approach in which application developers bid on resources. This allows fog nodes to make a local decision about which functions to offload while maximizing revenue. For a first evaluation of our approach, we use simulation.
Recent years have witnessed a remarkable development in communication and computing systems, mainly driven by the increasing demands of data and processing intensive applications such as virtual reality, M2M, connected vehicles, IoT services, to name a few. Massive amounts of data will be collected by various mobile and fixed terminals that will need to be processed in order to extract knowledge from the data. Traditionally, a centralized approach is taken for processing the collected data using large data centers connected to a core network. However, due to the scale of the Internet-connected…
This paper introduces the Virtual Sensor Middleware (VSM), which facilitates distributed sensor data processing on multiple fog nodes. VSM uses a Virtual Sensor as the core component of the middleware. The virtual sensor concept is redesigned to support functionality beyond sensor/device virtualization, such as deploying a set of virtual sensors to represent an IoT application and distributed sensor data processing across multiple fog nodes. Furthermore, the virtual sensor deals with the heterogeneous nature of IoT devices and the various communication protocols using different adapters to com…
In Fog-assisted IoT systems, it is a common practice to cache popular content at the network edge to achieve high quality of service. Due to uncertainties in practice such as unknown file popularities, cache placement scheme design is still an open problem with unresolved challenges: 1) how to maintain time-averaged storage costs under budgets, 2) how to incorporate online learning to aid cache placement to minimize performance loss (a.k.a. regret), and 3) how to exploit offline historical information to further reduce regret. In this paper, we formulate the cache placement problem with unknow…
The advancements of cloud computing came as a radical transformation in the way Information and Communication Technology (ICT) services are deployed and maintained. Cloud computing provides ubiquitous on-demand access to an Internet-based pool of processing, storage, and communication resources offered to a large set of geographically distributed users. As the cloud computing infrastructure grows and demand increases, the need for a new breed of on-demand computing that can efficiently maintain Quality of Service (QoS) requirements has increased. Fog computing was proposed to address the limit…
Fog computing becomes a promising technology to process user's requests near the proximity of users to reduce response time for latency-sensitive requests. Despite its advantages, the properties such as resource heterogeneity and limitations, and its dynamic and unpredictable nature greatly reduce the efficiency of fog computing. Therefore, predicting the dynamic behavior of the fog and managing resources accordingly is of utmost importance. In this work, we provide a review of machine learning-based predictive resource management approaches in a fog environment. Resource management is classif…
We propose a fog computing simulator for analysing the design and deployment of applications through customized and dynamical strategies. We model the relationships among deployed applications, network connections and infrastructure characteristics through complex network theory, enabling the integration of topological measures in dynamic and customizable strategies such as the placement of application modules, workload location, and path routing and scheduling of services. We present a comparative analysis of the efficiency and the convergence of results of our simulator with the most referen…
The rapid growth of time-sensitive applications and services has driven enhancements to computing infrastructures. The main challenge that needs addressing for these applications is the optimal placement of the end-users demands to reduce the total power consumption and delay. One of the widely adopted paradigms to address such a challenge is fog computing. Placing fog units close to end-users at the edge of the network can help mitigate some of the latency and energy efficiency issues. Compared to the traditional hyperscale cloud data centres, fog computing units are constrained by computatio…
We study the benefits of adopting server disaggregation in the fog computing tier by evaluating energy efficient placement of interactive apps in a future fog 6G network. Using a mixed integer linear programming (MILP) model, we compare the adoption of traditional server (TS) and disaggregated server (DS) architectures in a fog network comprising of selected fog computing sites in the metro and access networks. Relative to the use of TSs, our results show that the adoption of DS improves the energy efficiency of the fog network and enables up to 18% reduction in total fog computing power consu…
Hardware accelerators are available on the Cloud for enhanced analytics. Next generation Clouds aim to bring enhanced analytics using accelerators closer to user devices at the edge of the network for improving Quality-of-Service by minimizing end-to-end latencies and response times. The collective computing model that utilizes resources at the Cloud-Edge continuum in a multi-tier hierarchy comprising the Cloud, the Edge and user devices is referred to as Fog computing. This article identifies challenges and opportunities in making accelerators accessible at the Edge. A holistic view of the Fo…
Fog computing extends the cloud to the edge of the network, close to the end-users enabling the deployment of some application component in the fog while others in the cloud. Network Functions Virtualization (NFV) decouples the network functions from the underlying hardware. In NFV settings, application components can be implemented as sets of Virtual Network Functions (VNFs) chained in specific order representing VNF-Forwarding Graphs (VNF-FG). Many studies have been carried out to map the VNF-FGs to cloud systems. However, in hybrid cloud/fog systems, an additional challenge arises. The mobi…
Live virtual machine migration aims at enabling the dynamic balanced use of the networking/computing physical resources of virtualized data-centers, so to lead to reduced energy consumption. Here, we analytically characterize, prototype in software and test an optimal bandwidth manager for live migration of VMs in wireless channel. In this paper we present the optimal tunable-complexity bandwidth manager (TCBM) for the QoS live migration of VMs under a wireless channel from smartphone to access point. The goal is the minimization of the migration-induced communication energy under service leve…
Cloud computing is a revolutionary process that has impacted the manner of using networks. It allows a high level of flexibility as Virtual Machines (VMs) run elastically workloads on physical machines in data centers. The issue of placing virtual machines (VMP) in cloud environments is an important challenge that has been thoroughly addressed, although not yet completely resolved. This article discusses the different problems that may disrupt the placement of VMs and Virtual Network Functions (VNFs), and classifies the existing solutions into five major objective functions based on multiple p…
To adapt to continuously changing workloads in networks, components of the running network services may need to be replicated (scaling the network service) and allocated to physical resources (placement) dynamically, also necessitating dynamic re-routing of flows between service components. In this paper, we propose JASPER, a fully automated approach to jointly optimizing scaling, placement, and routing for complex network services, consisting of multiple (virtualized) components. JASPER handles multiple network services that share the same substrate network; services can be dynamically added …
Data centers are critical to the commercial and social activities of modern society but are also major electricity consumers. To minimize their environmental impact, it is imperative to make data centers more energy efficient while maintaining a high quality of service (QoS). Bearing this consideration in mind, we develop an analytical model using queueing theory for evaluating the QoS of a data center. Furthermore, based on this model, we develop a domain-specific evolutionary optimization framework featuring a tailored solution representation and a constraint-aware initialization operator fo…
Traditional highly-centralized mobile core networks (e.g., Evolved Packet Core (EPC)) need to be constantly upgraded both in their network functions and backhaul links, to meet increasing traffic demands. Network Function Virtualization (NFV) is being investigated as a potential cost-effective solution for this upgrade. A virtual mobile core (here, virtual EPC, vEPC) provides deployment flexibility and scalability while reducing costs, network-resource consumption and application delay. Moreover, a distributed deployment of vEPC is essential for emerging paradigms like Multi-Access Edge Comput…
The emerging 5G paradigm will enable multi-radio smartphones to run high-rate stream applications. However, since current smartphones remain resource and battery-limited, the 5G era opens new challenges on how to actually support these applications. In principle, the service orchestration capability of the Fog and Cloud Computing paradigms could be an effective means of dynamically providing resource-augmentation to smartphones. Motivated by these considerations, the peculiar focus of this paper is on the joint and adaptive optimization of the resource and task allocations of mobile stream app…
With smart devices, particular smartphones, becoming our everyday companions, the ubiquitous mobile Internet and computing applications pervade people daily lives. With the surge demand on high-quality mobile services at anywhere, how to address the ubiquitous user demand and accommodate the explosive growth of mobile traffics is the key issue of the next generation mobile networks. The Fog computing is a promising solution towards this goal. Fog computing extends cloud computing by providing virtualized resources and engaged location-based services to the edge of the mobile networks so as to …
Virtual Network Functions as a Service (VNFaaS) is currently under attentive study by telecommunications and cloud stakeholders as a promising business and technical direction consisting of providing network functions as a service on a cloud (NFV Infrastructure), instead of delivering standalone network appliances, in order to provide higher scalability and reduce maintenance costs. However, the functioning of such NFVI hosting the VNFs is fundamental for all the services and applications running on top of it, forcing to guarantee a high availability level. Indeed the availability of an VNFaaS…
The fifth-generation mobile evolution enables transformations on Next-Generation Radio Access Networks (NG-RAN). The RAN protocol stack is split into eight disaggregated options combined in three network units, i.e., Central, Distributed, and Radio. Besides that, further advances allow the RAN functions to be virtualized on top of general-purpose hardware, using the concept of virtualized RAN (vRAN). The Combination of NG-RAN and vRAN results in vNG-RAN, which enables the management of the disaggregated units and protocols as a set of radio functions. However, the orchestration-based placement…
The virtualization of Radio Access Networks (RANs) has been proposed as one of the important use cases of Network Function Virtualization (NFV). In Virtualized Radio Access Networks (VRANs), some functions from a Base Station (BS), such as those which make up the Base Band Unit (BBU), may be implemented in a shared infrastructure located at either a data center or distributed in network nodes. For the latter option, one challenge is in deciding which subset of the available network nodes can be used to host the physical BBU servers (the placement problem), and then to which of the available ph…
Software Defined Networking and Network Function Virtualization are two paradigms that offer flexible software-based network management. Service providers are instantiating Virtualized Network Functions - e.g., firewalls, DPIs, gateways - to highly facilitate the deployment and reconfiguration of network services with reduced time-to-value. They employ Service Function Chaining technologies to dynamically reconfigure network paths traversing physical and virtual network functions. Providing a cost-efficient virtual function deployment over the network for a set of service chains is a key techn…
Network Function Virtualization (NFV) carries the potential for on-demand deployment of network algorithms in virtual machines (VMs). In large clouds, however, VM resource allocation incurs delays that hinder the dynamic scaling of such NFV deployment. Parallel resource management is a promising direction for boosting performance, but it may significantly increase the communication overhead and the decline ratio of deployment attempts. Our work analyzes the performance of various placement algorithms and provides empirical evidence that state-of-the-art parallel resource management dramaticall…
With smart devices, particular smartphones, becoming our everyday companions, the ubiquitous mobile Internet and computing applications pervade people's daily lives. With the surge demand on high-quality mobile services at anywhere, how to address the ubiquitous user demand and accommodate the explosive growth of mobile traffics is the key issue of the next generation mobile networks. The Fog computing is a promising solution towards this goal. Fog computing extends cloud computing by providing virtualized resources and engaged location-based services to the edge of the mobile networks so as t…
Deep Neural Networks (DNNs) have served as a catalyst in introducing a plethora of next-generation services in the era of Internet of Things (IoT), thanks to the availability of massive amounts of data collected by the objects on the edge. Currently, DNN models are used to deliver many Artificial Intelligence (AI) services that include image and natural language processing, speech recognition, and robotics. Accordingly, such services utilize various DNN models that make it computationally intensive for deployment on the edge devices alone. Thus, most AI models are offloaded to distant cloud da…
The new generation of 5G mobile services places stringent requirements for cellular network operators in terms of latency and costs. The latest trend in radio access networks (RANs) is to pool the baseband units (BBUs) of multiple radio base stations and to install them in a centralized infrastructure, such as a cloud, for statistical multiplexing gains. The technology is known as Cloud Radio Access Network (CRAN). Since cloud computing is gaining significant traction and virtualized data centers are becoming popular as a cost-effective infrastructure in the telecommunication industry, CRAN is…
The shift towards a completely virtualized networking environment is triggered by the emergence of software defined networking and network function virtualization (NFV). Network service providers have unlocked immense capabilities by these technologies, which have enabled them to dynamically adapt to user needs by deploying their network services in real-time through generating Service Function Chain (SFCs). However, NFV still faces challenges that hinder its full potentials, including availability guarantees, network security, and other performance requirements. For this reason, the deploymen…
Network softwarization is one of the major paradigm shifts in the next generation of networks. It enables programmable and flexible management and deployment of the network. Network function virtualization (NFV) is referred to the deployment of software functions running on commodity servers instead of traditional hardware-based middle-boxes. It is an example of network softwarization. In NFV, a service is defined as a chain of software functions named service chain function (SFC). The process of allocating the resources of servers to the services, called service placement, is the most challen…
Cloud Computing (CC) serves to be a key driver for fulfilling the store and compute requirements of a modern Smart Grid (SG). However, since the datacenters are deployed in concentrated and far remote areas, it fails to guarantee the quality of experience (QoE) attributes for the SG services, viz. latency, bandwidth, energy consumption, and network cost. Fog Computing (FC) extends the processing capabilities into the edge of the network, offering location-awareness, low latency, and latency-sensitive analytics for mission critical requirements of SG. In this work, we first examine the current …
Virtual machine (VM) placement is very important for cloud platforms. While techniques, such as live virtual machine migration, are very useful to balance the load in the data centers, they are expensive operations. In this position paper, we propose to minimize the chance of the load hot spots in the data center by applying the workload patterns of the VMs in the virtual machine placement algorithms - place VMs that require a lot of same type of resource across different physical servers. In this way, the resource competition of VMs on the same physical server is significantly mitigated. Mean…
The virtualization of Radio Access Networks (RANs) has been proposed as one of the important use cases of Network Function Virtualization (NFV). In VRAN!s (VRAN!s), some functions from a Base Station (BS), such as those which make up the Base Band Unit (BBU), may be implemented in a shared infrastructure located at either a data center or distributed in network nodes. For the latter option, one challenge is in deciding which subset of the available network nodes can be used to host the physical BBU servers (the placement problem), and then to which of the available physical BBUs each Remote Ra…
With the growing demand for openness, scalability, and granularity, mobile network function virtualization (NFV) has emerged as a key enabler for most mobile network operators. NFV decouples network functions from hardware devices. This decoupling allows network services, referred to as Virtualized Network Functions (VNFs), to be hosted on commodity hardware which simplifies and enhances service deployment and management for providers, improves flexibility, and leads to efficient and scalable resource usage, and lower costs. The proper placement of VNFs in the hosting infrastructures is one of…
Edge caching via the placement of distributed storages throughout the network is a promising solution to reduce latency and network costs of content delivery. With the advent of the upcoming 5G future, billions of F-RAN (Fog-Radio Access Network) nodes will created and used for for the purpose of Edge Caching. Hence, the total amount of memory deployed at the edge is expected to increase 100 times. Currently, used DRAM-based caches in CDN (Content Delivery Networks) are extremely power-hungry and costly. Our purpose is to reduce the cost of ownership and recurring costs (of power consumption) …
Network Functions Virtualization (NFV) allows implantation of network functions to be independent of dedicated hardware devices. Any series of services can be represented by a service function chain which contains a set of virtualized network functions in a specified order. From the perspective of network performance optimization, the challenges of deploying service chain in network is twofold: 1) the location of placing virtualized network functions and resources allocation scheme; and 2) routing policy for traffic flow among different instances of network function. This article introduces se…
The fifth-generation mobile evolution enables several transformations on Next Generation Radio Access Networks (NG-RAN). The RAN protocol stack is splitting into eight possible disaggregated options combined into three network units, i.e., Central, Distributed, and Radio. Besides that, further advances allow the RAN software to be virtualized on top of general-purpose vendor-neutral hardware, dealing with the concept of virtualized RAN (vRAN). The disaggregated network units initiatives reach full interoperability based on the Open RAN (O-RAN). The combination of NG-RAN and vRAN results in vNG…
Fog radio access network (F-RAN) and virtualisation are promising technologies for 5G networks. In F-RAN, the fog and cloud computing are integrated where the conventional C-RAN functions are diverged to the edge devices of radio access networks. F-RAN is adopted to mitigate the burden of front-haul and improve the end to end (E2E) latency. On other hand, virtualization and network function virtualization (NFV) are IT techniques that aim to convert the functions from hardware to software based functions. Many merits could be brought by the employment of NFV in mobile networks including a high …
Digital Twin systems are designed as two interconnected mirrored spaces, one real and one virtual, each reflecting the other, sharing information, and making predictions based on analysis and simulations. The correct behavior of a real-time Digital Twin depends not only on the logical results of computation but also on the timing constraints. To cope with the large amounts of data that need to be stored and analyzed, modern large scale Digital Twin deployments often rely on cloud-based architectures. A significant portion of the overall response time of a Digital Twin is spent on moving data f…
Traditionally, Network Function Virtualization (NFV) has been implemented to run on Virtual Machines (VMs) in form of Virtual Network Functions (VNFs). More recently, the so-called Serverless Computing has gained traction in cloud computing, offering Function-as-a-Service (FaaS) platforms that make use of containerization techniques to deploy services. In contrast to VM-based VNFs, where resources are usually reserved and continuously running, FaaS can just be subsets of code implementing small functions allowing for event-driven, on-demand instantiations. Thus, a hybrid VM-Container based Ser…
Network Function Virtualization (NFV) is enabling the softwarization of traditional network services, commonly deployed in dedicated hardware, into generic hardware in form of Virtual Network Functions (VNFs), which can be located flexibly in the network. However, network load balancing can be critical for an ordered sequence of VNFs, also known as Service Function Chains (SFCs), a common cloud and network service approach today. The placement of these chained functions increases the ping-pong traffic between VNFs, directly affecting to the efficiency of bandwidth utilization. The optimization…
The deployment of edge computing infrastructure requires a careful placement of the edge servers, with an aim to improve application latencies and reduce data transfer load in opportunistic Internet of Things systems. In the edge server placement, it is important to consider computing capacity, available deployment budget, and hardware requirements for the edge servers and the underlying backbone network topology. In this paper, we thoroughly survey the existing literature in edge server placement, identify gaps and present an extensive set of parameters to be considered. We then develop a nov…
University of Jeddah（吉达大学）；Umm Al-Qura University（乌姆·库拉大学）；Western Michigan University（西密歇根大学）
With the rapid development of virtualization techniques, cloud data centers allow for cost effective, flexible, and customizable deployments of applications on virtualized infrastructure. Virtual machine (VM) placement aims to assign each virtual machine to a server in the cloud environment. VM Placement is of paramount importance to the design of cloud data centers. Typically, VM placement involves complex relations and multiple design factors as well as local policies that govern the assignment decisions. It also involves different constituents including cloud administrators and customers th…
Network Function Virtualization (NFV) has the potential to significantly reduce the capital and operating expenses, shorten product release cycle, and improve service agility. In this paper, we focus on minimizing the total number of Virtual Network Function (VNF) instances to provide a specific service (possibly at different locations) to all the flows in a network. Certain network security and analytics applications may allow fractional processing of a flow at different nodes (corresponding to datacenters), giving an opportunity for greater optimization of resources. Through a reduction from…
The University of Western Ontario（西安大略大学）；York University（约克大学）
With the constant increase in demand for data connectivity, network service providers are faced with the task of reducing their capital and operational expenses while ensuring continual improvements to network performance. Although Network Function Virtualization (NFV) has been identified as a solution, several challenges must be addressed to ensure its feasibility. In this paper, we present a machine learning-based solution to the Virtual Network Function (VNF) placement problem. This paper proposes the Depth-Optimized Delay-Aware Tree (DO-DAT) model by using the particle swarm optimization t…
Network Function Virtualization (NFV) provides higher flexibility for network operators and reduces the complexity in network service deployment. Using NFV, Virtual Network Functions (VNF) can be located in various network nodes and chained together in a Service Function Chain (SFC) to provide a specific service. Consolidating multiple VNFs in a smaller number of locations would allow decreasing capital expenditures. However, excessive consolidation of VNFs might cause additional latency penalties due to processing-resource sharing, and this is undesirable, as SFCs are bounded by service-speci…
Network Function Virtualization (NFV) is a new paradigm, enabling service innovation through virtualization of traditional network functions located flexibly in the network in form of Virtual Network Functions (VNFs). Since VNFs can only be placed onto servers located in networked data centers, which is the NFV's salient feature, the traffic directed to these data center areas has significant impact on network load balancing. Network load balancing can be even more critical for an ordered sequence of VNFs, also known as Service Function Chains (SFCs), a common cloud and network service approac…
