City of things : enabling resource provisioning in smart cities

In the last few years, traffic over wireless networks has been increasing exponentially due to the impact of IoT. IoT is transforming a wide range of services in different domains of urban life, such as environmental monitoring, home automation, and public transportation. The so-called smart city applications will introduce a set of stringent requirements, such as low latency and high mobility, since services must be allocated and instantiated on demand, simultaneously, close to multiple devices at different locations. Efficient resource provisioning functionalities are needed to address these demanding constraints introduced by smart city applications while minimizing resource costs and maximizing QoS. In this article, the CoT framework is presented, which provides not only data collection and analysis functionalities but also automated resource provisioning mechanisms for future smart city applications. CoT is deployed as a smart city test-bed in Antwerp, Belgium, which allows researchers and developers to easily set up and validate IoT experiments. A smart city use case of air quality monitoring through the deployment of air quality sensors in moving cars is presented showing the full applicability of the CoT framework for a flexible and scalable resource provisioning in the smart city ecosystem

Trading of cloud of things resources

Cloud Computing and Internet of Things (IoT) continue to emerge as revolutionary paradigms to support wide range of real world scenarios. They promise benefits for increasing number of applications, including health, smart cities, smart homes, smart logistics, video surveillance, energy and environmental monitoring. Independent deployments of each technology have issues that can be resolved partially or fully by integrating Cloud and IoT. This integration forms a new paradigm that is called Cloud of Things (CoT)supporting Everything as a Service (XaaS) service model. Despite the issues integration resolves, the integrated services will suffer from issues that Cloud and IoT offerings previously encountered. This includes interoperability, ambiguous SLAs, QoS, elasticity and reliability concerns. This paper argues that commoditising CoT resources will help resolving these issues. This paper aims to; 1) review the state-of-the-art in CoT literature 2) propose a conceptual model for CoT marketplace and its basic trading processes

Framework for Virtualized Network Functions (VNFs) in Cloud of Things Based on Network Traffic Services

The cloud of things (CoT), which combines the Internet of Things (IoT) and cloud computing, may offer Virtualized Network Functions (VNFs) for IoT devices on a dynamic basis based on service-specific requirements. Although the provisioning of VNFs in CoT is described as an online decision-making problem, most widely used techniques primarily focus on defining the environment using simple models in order to discover the optimum solution. This leads to inefficient and coarse-grained provisioning since the Quality of Service (QoS) requirements for different types of CoT services are not considered, and important historical experience on how to provide for the best long-term benefits is disregarded. This paper suggests a methodology for providing VNFs intelligently in order to schedule adaptive CoT resources in line with the detection of traffic from diverse network services. The system makes decisions based on Deep Reinforcement Learning (DRL) based models that take into account the complexity of network configurations and traffic changes. To obtain stable performance in this model, a special surrogate objective function and a policy gradient DRL method known as Policy Optimisation using Kronecker-Factored Trust Region (POKTR) are utilised. The assertion that our strategy improves CoT QoS through real-time VNF provisioning is supported by experimental results. The POKTR algorithm-based DRL-based model maximises throughput while minimising network congestion compared to earlier DRL algorithms

Dynamic Power Provisioning System for Fog Computing in IoT Environments

Large amounts of data are created from sensors in Internet of Things (IoT) services and applications. These data create a challenge in directing these data to the cloud, which needs extreme network bandwidth. Fog computing appears as a modern solution to overcome these challenges, where it can expand the cloud computing model to the boundary of the network, consequently adding a new class of services and applications with high-speed responses compared to the cloud. Cloud and fog computing propose huge amounts of resources for their clients and devices, especially in IoT environments. However, inactive resources and large number of applications and servers in cloud and fog computing data centers waste a huge amount of electricity. This paper will propose a Dynamic Power Provisioning (DPP) system in fog data centers, which consists of a multi-agent system that manages the power consumption for the fog resources in local data centers. The suggested DPP system will be tested by using the CloudSim and iFogsim tools. The outputs show that employing the DPP system in local fog data centers reduced the power consumption for fog resource providers