Energy Efficient Data Transmission Scheme for Internet of Things Applications

Recently, there is a rapid increase in the use of Internet of Things (IoT) technology, and it is envisaged that in the forthcoming days, billions of devices and things are going to be interconnected among themselves with the help of Internet. To make this technology self-sustainable, there is a need for an incessant energy supply that can be achieved through green energy harvesting. IoT has attracted the attention of researchers as well as practitioners all over the globe by serving as an important architecture for communication systems, but the terminal devices used in IoT are resource-constrained, which results in low energy storage capacity and low computing power. Among several tasks that need to be performed at the level of IoT node, the data transmission is the most energy intensive phase. To provide continuous power to nodes used in IoT systems, it is imperative that the available energy source should be used judiciously and in an optimized manner. In this paper, an energy efficient data transmission scheme for IoT devices has been proposed. The result obtained through extensive experiments depicts that there is a high potential for saving energy during the process of data transmission

MIFaaS: A Mobile-IoT-Federation-as-a-Service Model for dynamic cooperation of IoT Cloud Providers

In the Internet of Things (IoT) arena, a constant evolution is observed towards the deployment of integrated environments, wherein heterogeneous devices pool their capacities to match wide-ranging user requirements. Solutions for efficient and synergistic cooperation among objects are, therefore, required. This paper suggests a novel paradigm to support dynamic cooperation among private/public local clouds of IoT devices. Differently from . device-oriented approaches typical of Mobile Cloud Computing, the proposed paradigm envisages an . IoT Cloud Provider (ICP)-oriented cooperation, which allows all devices belonging to the same private/public owner to participate in the federation process. Expected result from dynamic federations among ICPs is a remarkable increase in the amount of service requests being satisfied. Different from the Fog Computing vision, the network edge provides only management support and supervision to the proposed Mobile-IoT-Federation-as-a-Service (MIFaaS), thus reducing the deployment cost of peripheral micro data centers. The paper proposes a coalition formation game to account for the interest of rational cooperative ICPs in their own payoff. A proof-of-concept performance evaluation confirms that obtained coalition structures not only guarantee the satisfaction of the players' requirements according to their utility function, but also these introduce significant benefits for the cooperating ICPs in terms of number of tasks being successfully assigned

Management in the era of Internet of Things. Part A: How to manage Internet of Things

Σημείωση: διατίθεται συμπληρωματικό υλικό σε ξεχωριστό αρχείο

A Cognitive Management Framework for Empowering the Internet of Things

This work presents a Cognitive Management framework for empowering the Internet of Things (IoT). This framework has the ability to dynamically adapt its behaviour, through self-management functionality, taking into account information and knowledge (obtained through machine learning) on the situation (e.g., internal status and status of environment), as well as policies (designating objectives, constraints, rules, etc.). Cognitive technologies constitute a unique and efficient approach for addressing the technological heterogeneity of the IoT and obtaining situation awareness, reliability and efficiency. The paper also presents a first indicative implementation of the proposed framework, comprising real sensors and actuators. The preliminary results of this work demonstrate high potential towards self-reconfigurable IoT

A cognitive management framework for empowering the internet of things

This work presents a Cognitive Management framework for empowering the Internet of Things (IoT). This framework has the ability to dynamically adapt its behaviour, through self-management functionality, taking into account information and knowledge (obtained through machine learning) on the situation (e.g., internal status and status of environment), as well as policies (designating objectives, constraints, rules, etc.). Cognitive technologies constitute a unique and efficient approach for addressing the technological heterogeneity of the IoT and obtaining situation awareness, reliability and efficiency. The paper also presents a first indicative implementation of the proposed framework, comprising real sensors and actuators. The preliminary results of this work demonstrate high potential towards self-reconfigurable IoT. © The Author(s)