Coordination Models for Internet of Things

In constrained environments, there is a variety of devices like sensors and actuators with limited computation power or energy that form an Internet of Things (IoT) system. When processing complex tasks is required, those devices send the data to the cloud and obtain the result later. However, the IoT system could process complex task if more devices work together, sharing computational resources and cooperating. This cooperation can be achieved using a coordination model that distributes the load among the different devices based on a set of parameters, laws and defined entities. This research implements and evaluates a data-oriented coordination model with three variations for Internet of Things (IoT). It also presents, implements and evaluates a new process-oriented coordination model that can make constrained environments much more effective and allow the processing of more complex tasks closer to the network. The development of all the coordination models was focused on using the system’s computational resources effectively. As IoT is a heterogeneous field, devices with more power can process more complex tasks, creating an uneven but adequate load distribution. Various experiments were conducted to evaluate the performance of each model using one and two workers. The results showed that every coordination model works effectively when distributing the load among more workers. For the process-oriented model, implementing some CoAP features allowed the system to perform better when repetitive tasks are required

A perspective on service orchestration

Service-oriented computing is an emerging paradigm with increasing impact on the way modern software systems are designed and developed. Services are autonomous, loosely coupled and heterogeneous computational entities able to cooperate to achieve common goals. This paper introduces a model for service orchestration, which combines a exogenous coordination model, with services’ interfaces annotated with behavioural patterns specified in a process algebra which is parametric on the interaction discipline. The coordination model is a variant of Reo for which a new semantic model is proposed

Role of defects in the electronic properties of amorphous/crystalline Si interface

The mechanism determining the band alignment of the amorphous/crystalline Si heterostructures is addressed with direct atomistic simulations of the interface performed using a hierarchical combination of various computational schemes ranging from classical model-potential molecular dynamics to ab-initio methods. We found that in coordination defect-free samples the band alignment is almost vanishing and independent on interface details. In defect-rich samples, instead, the band alignment is sizeably different with respect to the defect-free case, but, remarkably, almost independent on the concentration of defects. We rationalize these findings within the theory of semiconductor interfaces.Comment: 4 pages in two-column format, 2 postscript figures include

A macroscopic analytical model of collaboration in distributed robotic systems

In this article, we present a macroscopic analytical model of collaboration in a group of reactive robots. The model consists of a series of coupled differential equations that describe the dynamics of group behavior. After presenting the general model, we analyze in detail a case study of collaboration, the stick-pulling experiment, studied experimentally and in simulation by Ijspeert et al. [Autonomous Robots, 11, 149-171]. The robots' task is to pull sticks out of their holes, and it can be successfully achieved only through the collaboration of two robots. There is no explicit communication or coordination between the robots. Unlike microscopic simulations (sensor-based or using a probabilistic numerical model), in which computational time scales with the robot group size, the macroscopic model is computationally efficient, because its solutions are independent of robot group size. Analysis reproduces several qualitative conclusions of Ijspeert et al.: namely, the different dynamical regimes for different values of the ratio of robots to sticks, the existence of optimal control parameters that maximize system performance as a function of group size, and the transition from superlinear to sublinear performance as the number of robots is increased