The recent progress of RISC technology has led to the feeling that a significant percentage of image processing applications, which in the past required the use of special purpose computer architectures or of "ad hoc" hardware, can now be implemented in software on low cost general purpose platforms. We decided to undertake the study described in this paper to understand the extent to which this feeling corresponds to reality . We selected a set of reference RISC based systems to represent RISC technology, and identified a set of basic image processing tasks to represent the image processing domain. We measured the performance and studied the behaviour of the reference systems in the execution of the basic image processing tasks by running a number of experiments based on different program organizations. The results of these experiments are summarized in a table, which can be used by image processing application designers to evaluate whether RISC based platforms are able to deliver the computing power required for a specific application.The study of the reference system behaviour led us to draw the following conclusions. First, unless special programming solutions are adopted, image processing programs turn out to be extremely inefficient on RISC based systems. This is due to the fact that present generation optimizing compilers are not able to compile image processing programs into efficient machine code.Second, while computer architecture has evolved from the original flat organization towards a more complex organization, based, for example, on memory hierarchy and instruction level parallelism, the programming model upon which high level languages (e.g., C, Pascal) are based has not evolved accordingly. As a consequence programmers are forced to adopt special programming solutions and tricks to bridge the gap between architecture and programming model to improve efficiency.Third, although processing speed has grown up much faster than memory access speed, in current generation single processor RISC systems image processing can still be considered computebound. As a consequence, improvements in processing speed (originated for example by a higher degree of parallelism) will yield improvements of an equal factor in applications.

One of the most challenging objectives of the Internet of Things (IoT) domain is the identification of interaction paradigms and communication standards to integrate smart objects (SOs), i.e., physical objects able to interact with the network. Such interaction paradigms and communication protocols belong to what can be called the IoT application layer, on which this paper focuses. This paper presents app execution platform (AEP), a platform that supports the design, deployment, execution, and management of IoT applications in the domain of smart home, smart car, and smart city. AEP was designed to coherently fulfill a set of requirements covered only partially or in a fragmented way by other IoT application platforms. AEP focuses on SO virtualization and on composite application (CA) orchestration and supports dynamic object availability

No abstract

No abstract

In this paper, we consider the evolution of telephone networks from time-division multiplexing circuit switching to packet switching and, in particular, to packet switching-based on Internet Protocol (IP-supported telephony