20735579
Kinetically stable task assignment for networks of microservers
• Job titles for all employees • Most recent payroll data (wages, hours, job codes, and dates of hire) • Union contracts • Employee handbooks or benefit descriptions • Summary plan descriptions for health and retirement plans • Benefit costs summaries or insurance bills For a detailed listing of information that BLS economists typically request, please visit the National Compensation Survey Web site at http://www.bls.gov/ncs/collection.htm. What is the National Compensation Survey (NCS)?
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.
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.
1787760
Greedy is Good: On Service Tree Placement for In-Network Stream Processing
This paper is concerned with reducing communication costs when executing distributed user tasks in a sensor network. We take a service-oriented abstraction of sensor networks, where a user task is composed of a set of data processing modules (called services) with dependencies. Communications in sensor networks consume significant energy and introduce uncertainty in data fidelity due to high bit error rate. These constraints are abstracted as costs on the communication graph. The goal is to place the services within the sensor network so that the communication cost in performing the task is minimized. In addition, since the lifetime of a node, the quality of network links, and the composition of the service graph may change over time, the quality of the placement must be maintained in the face of these dynamics. In this paper, we take a fresh look at what is generally considered a simple but poor performance approach for service placement, namely the greedy algorithm. We prove that a modified greedy algorithm is guaranteed to have cost at most 8 times the optimum placement. In fact, the guarantee is even stronger if there is a high degree of data reduction in the service graph. The advantage of the greedy placement strategy is that when there are local changes in the service graph or when a hosting node fails, the repair only affects the placement of services that depend on the changes. Simulations suggest that in practice the greedy algorithm finds a low cost placement. Furthermore, the cost of repairing a greedy placement decreases rapidly as a function of the proximity of the services to be aggregated.
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.
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.
17801993
Efficiency of emergent constraint satisfaction in small-world and random agent networks
In this paper, we study the efficiency of emergent constraint satisfaction in small-world and random agent networks. We find that emergent constraint satisfaction in a small-world network is less efficient than in some other networks (e.g., regular networks). Further, we find that this finding holds in almost all random networks. Based on these observations, we study the relationship between the efficiency of emergent constraint satisfaction and the randomness of the corresponding network from which the constraint satisfaction problem is generated.
14115714
Energy-efficient compressed address transmission
To realize energy-efficient buses in current nanometer-scale technologies, techniques like compression or encoding that exploit information redundancy have been explored. However, available compression techniques for buses do not always ensure energy-efficient transmission of compressed information. In this work, we present various techniques that can be used with compression schemes for buses to ensure high energy efficiency. Our best scheme, applied to a stream of 38-bit addresses issued in a typical microprocessor, yields about 14.7% energy reduction on the average across a wide range of compressed bus widths ranging and over many SPEC CPU2000 benchmarks. Our proposed techniques especially perform better - up to 28.8% energy reduction is obtained - for narrower bus widths in the range 8-16 bits.
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:
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.
20773612
QoS-aware service location in mobile ad hoc networks
The advent of light-weight terminals (e.g., PDA) with integrated communication capabilities facilitates service access and hosting anytime, anywhere. However, effective service access requires dealing with the service's QoS, including related resource consumption. This paper introduces a comprehensive framework for QoS-aware service location in ad hoc networks. Our framework divides into: (i) QoS specification that is expressive enough to capture most significant QoS-related properties, and concise enough to have minimal computation cost associated with QoS management; and (ii) a benefit function for evaluating the overall benefit of service instances available in the network from the standpoint of QoS regarding both the user's perspective and resource consumption on hosts. Application of the proposed QoS framework is addressed in the context of the mobile ADHoc WS system, which supports QoS-aware location of Web services deployed in mobile ad hoc networks.