Energy-Aware Placement of Device-to-Device Mediation Services in IoT Systems

Abstract

Internet-of-Things (IoT) systems are becoming increasingly complex, heterogeneous and pervasive, integrating a variety of physical devices, virtual services, and communication protocols. Such heterogeneity presents an obstacle especially for interactions between devices of different systems that encounter each other at run time. Mediation services have been proposed to facilitate such direct communication by translating between messaging protocols, interfacing different middlewares, etc. However, the decision of where to place a mediation service within an IoT topology has repercussions and is in some cases critical for satisfying system objectives. In this paper, we propose an integer linear programming solution to optimize the placement decision specifically in terms of energy consumption. Our solution takes into account the energy consumed by each interaction at each device along the data transfer paths. Through simulations that use topologies of real-world IoT systems, we show the effect of our approach on energy consumption, messaging delay, and placement decision time. Our algorithm outperforms a state-of-theart solution in terms of reducing energy consumption by almost a third in large-scale typologies. We also demonstrate the feasibility of our approach in terms of overhead.

A Middleware for Automatic Composition and Mediation in IoT Systems

“…Mismatch discovery takes place at runtime and is attainable by having the messaging protocols specified in the constituent system descriptions. Note that the placement of a mediator is an optimization problem in its own right, but it has been tackled by others, e.g., [11]. Knowledge base is a data repository that stores real time information about the different constituent systems involved in the system such as vehicle fuel level and available parking slots.…”