16580627
Handling Safety-Related Feature Interaction in Safety-Critical Product Lines
The variation management of software product lines is currently handled without adequately taking safety or other system-level properties into account. This is largely due to (1) the fact that the available product-line variation-management techniques lack sufficient support for representing the combined effect of different features, and (2) the existing feature interaction techniques do not suffice for handling one-to-many feature interactions typical of many safety-critical product lines. The challenge is that we need to track the safety-related feature interactions while still promoting reuse. The expected contribution of this work is to demonstrate how safety-related feature interactions can be better investigated and managed by the safety-analysis guided, model-based approach described in this paper.
10834714
Safety analysis of software product lines using state-based modeling
The analysis and management of variations (such as optional features) are central to the development of safety-critical, software product lines. However, the difficulty of managing variations, and the potential interactions among them, across an entire product line currently hinders safety analysis in such systems. The work described here contributes to a solution by integrating safety analysis of a product line with model-based development. This approach provides a structured way to construct a state-based model of a product line having significant, safety-related variations. The process described here uses and extends previous work on product-line software fault tree analysis to explore hazard-prone variation points. The process then uses scenario-guided executions to exercise the state model over the variations as a means of validating the product-line safety properties. Using an available tool, relationships between behavioral variations and potentially hazardous states are systematically explored and mitigation steps are identified. The paper uses a product line of embedded medical devices to demonstrate and evaluate the process and results
894781
A constraint-based application model and scheduling techniques for power-aware systems
New embedded systems must be power-aware, not just low-power. That is, they must track their power sources and the changing power and performance constraints imposed by the environment. Moreover, they must fully explore and integrate many novel power management techniques. Unfortunately, these techniques are often incompatible with each other due to overspecialized formulations or they fail to consider system-wide issues. This paper proposes a new graph-based model to integrate novel power management techniques and facilitate design-space exploration of power-aware embedded systems. It captures min/max timing and min/max power constraints on computation and non-computation tasks through a new constraint classification and enables derivation of flexible system-level schedules. We demonstrate the effectiveness of this model with a power-aware scheduler on real mission-critical applications. Experimental results show that our automated techniques can improve performance and reduce energy cost simultaneously. The application model and scheduling tool presented in this paper form the basis of the IMPACCT system-level framework that will enable designers to aggressively explore many power-performance trade-offs with confidence.
15656771
On optimal communication cost for gathering correlated data through wireless sensor networks
In many energy-constrained wireless sensor networks, nodes cooperatively forward correlated sensed data to data sinks. In order to reduce the communication cost (e.g.overall energy) used for data collection, previous works have focused on specific coding schemes, such as Slepian-Wolf Code or Explicit Entropy Code. However, the minimum communication cost under arbitrary coding/routing schemes has not yet been characterized. In this paper, we consider the problem of minimizing the total communication cost of a wireless sensor network with a single sink. We prove that the minimum communication cost can be achieved using Slepian-Wolf Code and Commodity Flow Routing when the link communication cost is a convex function of link data rate. Furthermore, we find it useful to introduce a new metric distance entropy, a generalization of entropy, to characterize the data collection limit of networked sources. When the energy consumption is proportional to the link data rate (e.g.normally in 802.11), we show that distance entropy provides a lower bound of the communication cost and can be achieved by using a specific rate SWC and shortest path routing. Theoretically, achieving optimality may require global knowledge of the data correlation structure, which may not be available in practice. Therefore, we propose a simple, hierarchical scheme that primarily exploits data correlation between local neighboring nodes. We show that for several correlation structures and topologies, the communication cost achieved by this scheme is within a constant factor of the distance entropy, i.e., it is asymptotically optimal. Finally, we simulate our algorithm using radar reffectivity data as well as traces from Gaussian Markov Fields (GMF). As the network size goes large, for the radar data, we find our algorithm saves two thirds of the communication cost compared to a non-coding approach; as for the GMF data, our algorithm converges to a constant factor (1 .5_1.8) the distance entropy.
18067929
Multiagent SAT (MASSAT): Autonomous Pattern Search in Constrained Domains
In this paper, we present an autonomous pattern search approachto solving Satisfiability Problems (SATs). Our approach is essentially a multiagent system. To solve a SAT problem, we first divide variables into groups, and represent each variable group with an agent. Then, we randomly place each agent onto a position in the correspoding local space which is composed of the domains of the variables that are represented by this agent. Thereafter, all agents will autonomously make searchdecisions guided by some reactive rules in their local spaces until a special pattern (i.e., solution) is found or a time step threshold is reached. Experimental results on some benchmark SAT test-sets have shown that by employing the MASSAT approach, we can obtain performances comparable to those of other popular algorithms.
7025134
Communication speed selection for embedded systems with networked voltage-scalable processors
High-speed serial network interfaces are gaining wide use in connecting multiple processors and peripherals in modern embedded systems, thanks to their size advantage and power efficiency. Many such interfaces also support multiple data rates, and this ability is opening a new dimension in the power/performance trade-offs between communication and computation on voltage scalable embedded processors. To minimize energy consumption in these networked architectures, designers must not only perform functional partitioning but also carefully balance the speeds between communication and computation, which compete for time and energy. Minimizing communication power without considering computation may actually lead to higher energy consumption at the system level due to elongated on-time as well as lost opportunities for dynamic voltage scaling on the processors. We propose a speed selection methodology for globally optimizing the energy consumption in embedded networked architectures. We formulate a multi-dimensional optimization problem by modeling communication dependencies between processors and their timing budgets. This enables engineers to systematically solve the problem of optimal speed selection for global energy reduction. We demonstrate the effectiveness of our speed selection approach with an image processing application mapped onto a multi-processor architecture with a multi-speed Ethernet.
6371621
3D object reconstruction from a single 2D line drawing without hidden lines
The human vision system can interpret a single 2D line drawing as a 3D object without much difficulty even if the hidden lines of the object are invisible. Several reconstruction approaches have tried to emulate this ability, but they cannot recover the complete object if the hidden lines of the object are not shown. This paper proposes a novel approach for reconstructing complete 3D objects from line drawings without hidden lines. First, we develop some constraints and properties for the inference of the topology of the invisible edges and vertices of an object. Then we present a reconstruction method based on perceptual symmetry and planarity of the object. We give a number of examples to demonstrate the ability of our approach.