Cloud-Link: IoT and Cloud
Internt of Things and Cloud ComIputing are tightly related. Cloud Computing has made IOT possible. In this issue of Cloud Link we have gathered articles related to IOT. The articles reflect the growth in Cloud Computing support and managment options that support IOT. For example, you can now provision virtual serves loaded with tools that can be used specifically with IOT applications. Storage will always be a challenge. Cloud computing today in some ways makes it appear as if we have an infinite amount of data storage available. But people in the cloud computing field that I speak with say that, eventually, we may “fall off a cliff.” And they suspect that, possibly, IoT represents that cliff. I’m not an expert on IoT by any means, but the projections for big data in an age of IoT that I’ve seen certainly suggest that we’ll need to adapt existing strategies and technologies and develop new ones to meet that challenge.
One potential solution is to process data at the edge of the network, at or near the sensor level, and only return a portion of it for central storage and processing. Another strategy might divide up the data into manageable portions so that it’s logically partitioned (LPAR). Dividing a problem into smaller micro-portions will decrease the size of the data needed to draw meaningful insights and would be less taxing on the storage and processing side. These are known strategies that could be adapted to handle the big data generated by IoT.
Another concept that may come into play is inter-cloud computing, which belongs in that cut-the-problem-down-to-size category. If a single problem exhausted the physical limitations of a single cloud service and its infrastructure, separate clouds might handle parts of the problem, reducing the challenge to storage and processing. But a lot of issues in inter-cloud computing remain to be worked out, including interoperability and security, among others. Obviously we’re talking at a very high level and the necessary strategies and technical means to meet the big data challenge now or in an IoT-enabled world become very complex. I’d like to point readers to IEEE’s Cloud Computing magazine for more in-depth treatment of this topic. It has and continues to publish numerous insightful articles on this very issue.
Published at Datamation, February 2018
AWS Cloud: A Leader's Approach Big Data, IoT and AI
Published at Datamation, February 2018
"Technology tandems aren’t very common but occasionally you do find two techs that can’t live without each other. The relationship between operating systems and CPUs is entirely co-dependent because they both need each other. Another example of that is the simultaneous growth of edge computing, sometimes called fog computing by people trying to be clever, and the Internet of Things (IoT)..."
Published at ZDNet, February 2018
Google has generally released its Cloud IoT Core service after public beta release in 2017
Mobility-Aware Application Scheduling in Fog Computing: Luiz F. Bittencourt, Javier Diaz-Montes, Rajkumar Buyya, Omer F. Rana, Manish Parashar
Published in IEEE Cloud Computing, April 2017
With the advancement of IoT, the number of smart and connected devices is increasing. These geographically distributed devices produce and consume a huge amount of heterogeneous and dynamic data known as ‘Big Data’ at the network edge that is close to the end users. Therefore, a new requirement of data management and computing capacity at the network edge has been evolved with respect to user mobility and diverse requirements of applications. Since the traditional cloud data-centers are not capable of handling such extensive data as well as user mobility, it has become indispensable to rethink about the resource allocation and management in the cloud infrastructure. In this case, distributed computing models such as fog computing, mobile clouds and vehicular networks come into play.
The article, ‘Mobility-aware application scheduling in fog computing’ by Luiz F. Bittencourt et al., discusses the advantageous aspects of fog computing in the context of faster data processing and computing at the edges of the network for the applications dependent on users’ geographical location. It gives an overview of the hierarchical fog computing infrastructure and illustrates the possible development of user access point called ‘cloudlets’ with the utilization of computation and storage facility. Applications can be classified into different categories based on the user mobility and Quality of Service (QoS) requirements of the applications. These classes can influence the design of scheduling strategies for fog computing infrastructure.
The article depicts that by putting application classes and fog computing scheduling policies together while considering user mobility can reduce network delay which makes the applications perform better. To find out more detailed information, please follow the link,
Principles for Engineering IoT Cloud SystemsHong-Linh Truong and Schahram Dustdar
Published in IEEE Cloud Computing, June 2015
This article outlines ways in which Cloud Computing providers can suport IOT infrastructure. In the past year, some of these ideas has been implemented but this article gives other ideas for the future.
IoT Remote Group Experiments in the Cyber Laboratory: A FPGA-based Remote Laboratory in the Hybrid Cloud: Norihiro Fujii and Nobuhiko Koike
Presented at International Conference on Cyberworlds 2017
This paper uses cloud technology to enable remote IoT experiments. IoT experiments can be time consuming to set-up, particularly if they require multiple modifications to the experiment infrastructure. The authors propose a system using FPGA and a hybrid cloud to allow IoT infrastructure simulation to be determined by code rather than physical reconfiguration. The proposed “Cyber Laboratory” allows researchers to conduct experiments using different IoT configurations remotely and simultaneously.