Marcello Mura

Virtual Power Plant As a Bridge between Distributed Energy Resources and Smart Grid

The liberalization of energy markets, especially in correlation with the Smart Grid concept development, requires adjusted legislation, new business models, energy stock exchanges establishment and many other advanced instruments. Realization of these features necessitates novel concepts to support such changes in the power system while granting security and reliability of supply. Such evolution poses new challenges to ICT (Information and Communication Technologies) to bridge the gap between increased complexity of deregulated market and on the other side expected rapid growth of number of players in power systems. Increasing presence of Distributed Energy Resources (DER) implementations constitutes a further source of complexity.Bearing in mind ongoing and possible scenarios we aim to determinate the place and role of the novel Virtual Power Plants (VPP) concept, related to the Smart Grid structure. At the same time we introduce an innovative modeling approach as an instrument to determine actors and highlight their actual roles and interactions from different point of view, trying to pave the way for development of a common understanding platform for variety of stakeholders. The effectiveness of the proposed modeling concept is shown through a number of UML models representing system level description of VPP at different levels of abstraction.

Model-based Design Space Exploration for RTES with SysML and MARTE

The features of the emerging modeling languages for system design allow designers to build models of almost any kind of heterogeneous hardware-software systems, including real time embedded systems (RTES). An important goal to achieve is the implementation and use of these models in all the steps of a common design flow. One of these steps is the design space exploration (DSE), which helps designers in discovering the optimal solutions among all possible combinations after mapping functional to architectural specifications; for RTES this step is particularly hard as it should include scheduling analysis in order to proof the time validity after the mapping. This paper presents some guidelines on how to use SysML and MARTE profiles to identify design points fulfilling the timing constraints of an RTES, and thus allowing to automate DSE analysis within the system design phase.

Code Generation from Statecharts: Simulation of Wireless Sensor Networks

Automatic generation of code starting from lightweight modeling languages such as UML is by now a widely adopted approach. In particular generation of executable SystemC models starting from StateCharts and other UML diagrams represents a promising research field. While RTL SystemC appears better suited for matching the StateCharts formalism (being intrinsically clocked), performances of the generated code suffer from the heavy overhead induced by time management, specially when the number of concurrent processes is high. In this paper we present a methodology that allows applying a solution mixing event based and clock-driven approach. More specifically, clock-driven simulation is activated only when the configuration of the system is identified to be evolving. When no events are present this fact is also detected (together with the interval of absence of events) so that no simulation is performed although the clock runs on. This solution is particularly suited for low duty cycle systems, as, e.g. when simulating Wireless Sensor Networks (WSN); in such instances, speedup of the generated code has been found to be well over two orders of magnitude. Application of the technique to the generation of a power simulator for the IEEE 802.15.4 networking protocol is used as a test case.

StateCharts to systemc: a high level hardware simulation approach

In this paper we present a tool that converts specifications written with a subset of StateCharts into SystemC behavioral models. The main advantages of such an approachare rapidity of use, simplicity and reusability. Various systems can be modeled at different levels of abstraction andaccuracy through StateCharts and different peculiar aspects (e.g. energy, performances) can be taken into consideration. Moreover different parts of the design can be identified at different detail levels. The kernel of the simulator is fully discussed together with its mapping to the semantics of our StateCharts diagrams. As a case study we present here a model of the IBM PowerPC 750 Cache system and the respective SystemC simulator automatically generated by our tool.

Power Modeling and Power Analysis for IEEE 802.15.4: a Concurrent State Machine Approach

is a recent low-rate/low-power standard for wireless personal area and sensor networks. Its simple infrastructure, intermediate range and good power performance make it a candidate for applications that require a reasonably low throughput but a very high device lifetime and power efficiency. An experimental power analysis of an 802.15.4 implementation is carried out, providing a detailed power model of the protocol based on concurrent state machines; resulting power model is then used to generate a customized simulator. The model has been validated through a set of experiments and provides good accuracy; results are discussed, considering in particular use of the model as a basis for subsequent optimizations on 802.15.4 networks.

SC2 StateCharts to SystemC: Automatic Executable Models Generation

The recent development of embedded systems calls for the necessity of a complete framework for design and simulation of applications that span through all levels of system design. Desirable characteristics of such a framework are rapidity of use, simplicity and reusability. For this purpose we already introduced a generator that converts specifications written with a subset of StateCharts to behavioral SystemC [16, 17]. We present here the new version of our tool: most of the limitations of the previous versions have been overcome, the considered subset of the StateCharts formalism has been extended and the target has been changed from behavioral to Register Transfer Level (RTL) SystemC. A major enhancement of this new version is the possibility of obtaining various module instances starting from a single specification, which is vital in some contexts (e.g. Wireless Sensors Networks simulation). The semantics chosen for our StateCharts diagrams is clearly described. The generation of executable models, as well as the kernel template of the generated code, are discussed in detail.

Modelling the power cost of security in Wireless Sensor Networks : The case of 802.15.4

Pervasive applications and in particular Wireless Sensors Networks have very strict requirements in terms of power consumption. It is well known that radio activity is very expensive in terms of energy; we show here that intensive processing activities (as security) represent a major contribution to power budget. In this paper we extend our methodology for analyzing the impact of security related operations on power consumption and optimizing it. The analysis is based on experimental data and was validated with measurements on a real platform.

ADSC: application-driven storage control for energy efficiency

While performance and quality of service are the main criteria for application data management on storage units, energy efficiency is increasingly being stated as an additional criterion for evaluation. Due to the increasing energy consumption of storage subsystems, improving their energy efficiency is an important issue. In this paper we present a novel approach to storage management whereby both mid-level (file placement) and low level (disk mode) aspects are controlled, in a tiered storage architecture. The proposed mechanism is based on policies, and it is implemented via fuzzy logic rules, in contrast to attempting to build a model of the storage subsystem. The inputs to the storage management system are high level (application), mid level (file system) and low level (disk access patterns) information. The effectiveness of our approach has been validated by means of a case study using a TPC-C benchmark modified to access file level data. Results from this simulation are presented.

MDE Support for HW/SW Codesign: A UML-based Design Flow

The spread of technology is mostly possible thanks to the growing presence of Embedded Systems in our everyday lives. Embedded Systems are information processing devices enclosed in a variety of products such as cars, telecommunication or fabrication equipment. These devices must accomplish a large set of requirements and constraints to meet the computational demands of modern applications. As a matter of fact, Embedded Systems are very complex and heterogeneous systems, and this implies very difficult, expensive and time consuming design processes. Although MDE and Hw/Sw codesign are widely used to address the design complexity problem, the lack of design procedures and methodologies joining both concepts restrains their usage as complementary techniques, thus preventing the implementation of faster and more robust design cycles. In this chapter we present a practical semi-automated design flow where both methodologies are merged and exploited to enable a fast design process targeting highly complex Real-Time Embedded Systems, executing several tasks on SoC and MPSoC devices, while allowing the usage of Design Space Exploration, Schedulability Analysis and Estimation techniques.

Dynamic Adaptation of Security and QoS in Energy-Harvesting Sensors Nodes

Pervasive computing applications have, in many cases, hard requirements in terms of security. In particular when deploying a Wireless Sensor Network (WSN), security and privacy exigences must be accommodated with the small computational power and especially with the limited energy of the nodes. In some applications nodes may be equipped with energy harvesting devices, especially solar cells, to keep their small batteries charged. The presence of an harvesting device, while enabling the use of WSN in more application fields, represents an additional challenge in the design phase. Given the stochastic nature of most energy harvesting sources, optimizing system performance requires the capability to evaluate the current system conditions runtime.