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Although Fog computing specifies a scalable architecture for computation, communication and storage, there is still a demand for better Quality of Service (QoS), especially for agile mobile services. Both industry and academia have been working on novel and efficient mechanisms for QoS provisioning in Fog computing. This paper presents a classification of services according to their QoS requirements...
This paper introduces a study of the fog computing suitability assessment as a solution for the increasing demand of the IoT devices. In particular, we focus on the energy consumption and the Quality of Service (QoS) as two important metrics of the performance of the fog. Therefore, we present a modeling of these two metrics in the fog. Then, we express the problem as constrained optimization and...
Internet of things, a trend of the following years, makes it possible to develop new applications and services as well as creates a huge amount of data to be processed. In order to support this new paradigm, an extension of cloud computing, named Fog Computing, has been developed. Fog computing improves the cloud security, availability and performance by providing a distributed and powerful communication...
The important construction paradigms, the technological and energy efficiency in Distributed Computing are examined within the paper. The most responsible parameters like performance, speedup, energy consumption, PUE, ERE etc. are discussed. The case studies which are dedicated to Fog Computing, VM migration and utilization of waste heat in the clouds are analyzed.
Deploying composite applications to Fog nodes in a QoS- and context-aware manner is challenging due to the heterogeneity, scale and dynamicity of Fog infrastructures.
More and more real-time IoT applications such as smart cities or autonomous vehicles require big data analytics with reduced latencies. However, data streams produced from distributed sensing devices may not suffice to be processed traditionally in the remote cloud due to: (i) longer Wide Area Network (WAN) latencies and (ii) limited resources held by a single Cloud. To solve this problem, a novel...
Edge data centers (EDCs) typically provide lower availability rates than Cloud counterparts since they lack expensive support systems such as air conditioning units and power generators. To avoid this limitation deteriorating response time which is critical for Edge applications, use of proactive optimization algorithms is essential. Such proactive algorithms, however, require an accurate method for...
Abstract-Internet of Things (IoT) is emerging as part ofthe infrastructures for advancing a large variety of applicationsinvolving connection of many intelligent devices, leadingto smart communities. Due to the severe limitation on thecomputing resources of IoT devices, it is common to offloadtasks of various applications requiring substantial computingresources to computing systems with sufficient...
This report contains a brief overview of the main concerns addressed by the authors of the Cloud-Based Collaborative Technologies in IoT Age track, held at WETICE 2017 conference. A presentation of the main topics is given and a summary of the papers accepted for this conference track is reported.
The evolution of the Internet of Things (IoT) is bringing Cloud services closer to the networks' edge. Thus, fog networking presents itself as an approach aiming to utilize more and more resources in network edge devices to provide various networking tasks. This work presents an optimization formulation that minimizes the cost of executing a set of services, taking into account the availability of...
Fog computing provides a decentralized approach to data processing and resource provisioning in the Internet of Things (IoT). Particular challenges of adopting fog-based computational resources are the adherence to geographical distribution of IoT data sources, the delay sensitivity of IoT services, and the potentially very large amounts of data emitted and consumed by IoT devices. Despite existing...
An increasing number of online services are hosted on public clouds. However, since a centralized cloud architecture imposes high network latency, researchers suggested moving latency sensitive applications, such as virtual and augmented reality ones, to the edge of the network. Nevertheless, little has been done for edge layer capacity estimation resulting in a great need towards practical tools...
A large number of modern applications and systemsare cloud-hosted, however, limitations in performance assurancesfrom the cloud, and the longer and often unpredictable endto-end network latencies between the end user and the cloudcan be detrimental to the response time requirements of theapplications, specifically those that have stringent Quality ofService (QoS) requirements. Although edge resources,...
This work develops a cloud-fog computing architecture for information-centric Internet-of-Things (IoT) applications with job classification and resource scheduling functions. The two designed functions support quality of service (QoS) by classifying IoT applications and scheduling computing resources. An innovative scheduling mechanism is developed to optimize the dispatch of cloud and fog resources...
Internet of Things (IoT) is now transitioning from theory to practice. This means that a lot of data will be generated and the management of this data is going to be a big challenge. To transform IoT into reality and build upon realistic and more useful services, better resource management is required at the perception layer. In this regard, Fog computing plays a very vital role. With the advent of...
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