For a comprehensive list of our publications, in all areas, go here.


IoT.Pub.Fitzgerald IoT.Pub.Batalla
E. Fitzgerald, M. Pióro, A. Tomaszewski: “Energy-Optimal Data Aggregation and Dissemination for the Internet of Things”; IEEE Internet of Things Journal, 2018.

In this paper we consider the problem of optimising the dissemination of measurements in the wireless sensor network. It is assumed that the measurements are taken at multiple sensor nodes, routed through a set of transit nodes, and disseminated to multiple control nodes. At transit nodes the measurements can be aggregated in order to minimise the number of packet transmissions and the energy used at the nodes. The problem consists in optimising the routing of packets, the aggregation of measurements, and the scheduling of packet transmissions with the objective to minimise the usage of energy. We present a method of problem decomposition, mixed-integer programming formulations of the resulting subproblems – energy-optimal measurement aggregation and dissemination, and throughput-optimal scheduling of transmissions under the physical interference model – as well as algorithms that solve them. We show the results of numerical studies that have been carried out for networks of varying topologies and size.

C. X. Mavromoustakis, J. Mongay Batalla, G. Mastorakis, E. Markakis, E. Pallis: “Socially Oriented Edge Computing for Energy Awareness in IoT Architectures”; IEEE Communications Magazine, 2018.

The Internet of Things services provision plays a critical role in today’s ubiquitous systems. In many cases, there are secondary devices that are interconnected (glasses, set-top-boxes, home furniture, etc.), playing an active role in the level of QoS/QoE provided to end users. This is valid for any service demands, requested by end users on the move. The most important aspect of this kind of communication is to allow users to exploit continuous on-demand service provision. This is feasible to achieve by using schemes to support the edge devices. Considering the latter, this work presents the different ways to implement the edge computing paradigm in dense networked systems via social connectivity from two different perspectives: the offered reliability for delay-tolerant services and the energy conservation over reliability provision. The offloading social-based processing of selected applications to the edge devices, in terms of both time and energy, offers significant lifetime extensibility for each device as indicative results show.