49717519
A spreadsheet approach to programming and managing sensor networks
2193838
Scaling into ambient intelligence
Envision the situation that high quality information and entertainment is easily accessible to anyone, anywhere, at any time, and on any device. How realistic is this vision? And what does it require from the underlying technology? Ambient Intelligence (AmI) integrates concepts ranging from ubiquitous computing to autonomous and intelligent systems. An AmI environment will be highly dynamic in many aspects. Underlying technology must be very flexible to cope with this dynamism. The scalability of technology is only one crucial aspect. This paper explores scalability from the processing, the communication, and the software perspectives.
10851913
Taming heterogeneity - the Ptolemy approach
Modern embedded computing systems tend to be heterogeneous in the sense of being composed of subsystems with very different characteristics, which communicate and interact in a variety of ways-synchronous or asynchronous, buffered or unbuffered, etc. Obviously, when designing such systems, a modeling language needs to reflect this heterogeneity. Today's modeling environments usually offer a variant of what we call amorphous heterogeneity to address this problem. This paper argues that modeling systems in this manner leads to unexpected and hard-to-analyze interactions between the communication mechanisms and proposes a more structured approach to heterogeneity, called hierarchical heterogeneity, to solve this problem. It proposes a model structure and semantic framework that support this form of heterogeneity, and discusses the issues arising from heterogeneous component interaction and the desire for component reuse. It introduces the notion of domain polymorphism as a way to address these issues.
640793
A component-based approach to modeling and simulating mixed-signal and hybrid systems
Systems with both continuous and discrete behaviors can be modeled using a mixed-signal style or a hybrid systems style. This article presents a component-based modeling and simulation framework that supports both modeling styles. The component framework, based on an actor metamodel, takes a hierarchical approach to manage heterogeneity in modeling complex systems. We describe how ordinary differential equations, discrete event systems, and finite-state machines can be built under this metamodel. A mixed-signal system is a hierarchical composition of continuous-time and discrete event models, and a hybrid system is a hierarchical composition of continuous-time and finite-state-machine models. Hierarchical composition and information hiding help build clean models and efficient execution engines. Simulation technologies, in particular, the interaction between a continuous-time ODE solving engine and various discrete simulation engines are discussed. A signal type system is introduced to schedule hybrid components inside a continuous-time environment. Breakpoints are used to control the numerical integration step sizes so that discrete events are handled properly. A "refiring" mechanism and a "rollback" mechanism are designed to manage continuous components inside a discrete event environment. The technologies are implemented in the Ptolemy II software environment. Examples are given to show the applications of this framework in mixed-signal and hybrid systems.
986010
On the Causality of Mixed-Signal and Hybrid Models
This paper extends the application of the Cantor metric as a mathematical tool for defining causalities from pure discrete models to mixed-signal and hybrid models. Using the Cantor metric, which maps timed signals, continuous or discrete, into a metric space, we define causality as contractive properties of processes operating on these signals. Thus, the Banach fixed point theorem can be applies to establish conditions for the existence, uniqueness, and liveness of the behaviors for mixed-signal and hybrid systems. The results also provide theoretical foundations for the simulation technologies for such systems, including the time-marching strategy, evaluation of feedback loops, and the necessity of supporting rollback.
5682640
A dual-space approach to tracking and sensor management in wireless sensor networks
Wireless ad hoc sensor networks have the advantage of spanning a large geographical region and being able to collaboratively detect and track non-local spatio-temporal events. This paper presents a dual-space approach to event tracking and sensor resource management in sensor networks. The dual-space transformation maps a non-local phenomenon, e.g., the edge of a half-plane shadow, to a single point in the dual space, and maps locations of distributed sensor nodes to a set of lines that partitions the dual space. The detection problem becomes finding and tracking the cell that contains the point in the arrangement defined by these lines. This mechanism can be effectively used for power management of the sensor network - nodes that will not be immediately visited by an event can be turned off to save energy required for sensing, processing, and communication. The approach has been successfully demonstrated on a laboratory testbed built using the UC Berkeley motes sensors. An implemented application of detecting and tracking light shadow edges moving over a sensor field is described.
13909958
The Wisdom Web: New Challenges for Web Intelligence (WI)
The World Wide Web (WWW) has profoundly changed our ways of doing things, from business and communication to entertainment and learning. This impact is inevitable due to the facts that the Web connectivity rapidly increases and that the on-line information astronomically explodes. In order to not only live with such a change but also benefit from the information infrastructure that WWW has empowered, we have witnessed the fast development as well as application of various WWW technologies, which cover:
5692814
Mining associated implication networks: computational intermarket analysis
Current attempts to analyze international financial markets include the use of financial technical analysis and data mining techniques. In this paper, we propose a new approach that incorporates implication networks and association rules to form an associated network structure. The proposed approach explicitly addresses the issue of local vs. global influences between financial markets.
10636871
Agent-based load balancing on homogeneous minigrids: macroscopic modeling and characterization
In this paper, we present a macroscopic-characterization of agent-based load balancing in homogeneous minigrid environments. The agent-based load balancing is regarded as agent distribution from a macroscopic point of view. We study two quantities on minigrids: the number and size of teams where agents (tasks) queue. In macroscopic modeling, the load balancing mechanism is characterized using differential equations. We show that the load balancing we concern always converges to a steady state. Furthermore, we show that load balancing with different initial distributions converges to the same steady state gradually. Also, we prove that the steady state becomes an even distribution if and only if agents have complete knowledge about agent teams on minigrids. Utility gains and efficiency are introduced to measure the quality of load balancing. Through numerical simulations, we discuss the utility gains and efficiency of load balancing in different cases and give a series of analysis. In order to maximize the utility gain and the efficiency, we theoretically study the optimization of agents' strategies. Finally, in order to validate our proposed agent- based load balancing mechanism, we develop a computing platform, called simulation system for grid task distribution (SSGTD). Through experimentation, we note that our experimental results in general confirm our theoretical proofs and numerical simulation results from the proposed equation system. In addition, we find a very interesting phenomenon, that is, agent-based load balancing mechanism is topology-independent.
15797818
From Alife Agents to a Kingdom of N Queens
This paper presents a new approach to solving N-queen problems, which involves a model of distributed autonomous agents with artificial life (ALife) and a method of representing N-queen constraints in an agent environment. The distributed agents locally interact with their living environment, i.e., a chessboard, and execute their reactive behaviors by applying their behavioral rules for randomized motion, least-conflict position searching, and cooperating with other agents etc. The agent-based N-queen problem solving system evolves through selection and contest according to the rule of Survival of the Fittest, in which some agents will die or be eaten if their moving strategies are less efficient than others. The experimental results have shown that this system is capable of solving large-scale N-queen problems. This paper also provides a model of ALife agents for solving general CSPs.
46660401
Multi-agent Integer Programming
Many real-life optimization problems such as planning and scheduling require finding the best allocation of scarce resources among competing activities. These problems may be modeled and solved by means of mathematical programming. This paper explores a distributed multi-agent approach to mathematical programming, and demonstrates the approach in the case of integer programming. The important characteristics of the multi-agent approach consist in that the behavior-based computation performed by the agents is parallel and goal-driven in nature, and has low time complexity.