1336005
Supporting concurrent applications in wireless sensor networks
It is vital to support concurrent applications sharing a wireless sensor network in order to reduce the deployment and administrative costs, thus increasing the usability and efficiency of the network. We describe Melete 1 , a system that supports concurrent applications with efficiency, reliability, flexibility, programmability, and scalability. Our work is based on the Maté virtual machine [1] with significant modifications and enhancements. Melete enables reliable storage and execution of concurrent applications on a single sensor node. Dynamic grouping is used for flexible, on-the-fly deployment of applications based on contemporary status of the sensor nodes. The grouping procedure itself is programmed with the TinyScript language. A group-keyed code dissemination mechanism is also developed for reliable and efficient code distribution among sensor nodes. Both analytical and simulation results are presented to study the impact of several key parameters and optimization techniques on the code dissemination mechanism. Simulation results indicate satisfactory scalability of our techniques to both application code size and node density. The usefulness and effectiveness of Melete is also validated by empirical study.
6083994
On communication models for algorithm design in networked sensor systems: A case study,
Towards building a systematic methodology of algorithm design for applications of networked sensor systems, we formally define two link-wise communication models, the Collision Free Model (CFM) and the Collision Aware Model (CAM). While CFM provides ease of programming and analysis for high level application functionality, CAM enables more accurate performance analysis and hence more efficient algorithms through cross-layer optimization, at the expense of increased programming and analysis complexity. These communication models are part of an abstract network model, above which algorithm design and performance optimization is performed. We use the example of optimizing a probability based broadcasting scheme under CAM to illustrate algorithm optimization based on the defined models. Specifically, we present an analytical framework that facilitates an accurate modeling and analysis for the probability based broadcasting in CAM (PB_CAM). Our analytical results indicate that (1) the optimal broadcast probability for either maximizing the reachability within a given latency constraint or minimizing the latency for a given reachability constraint decreases rapidly with node density, and (2) the optimal probability for either maximizing the reachability with a given energy constraint or minimizing the energy cost for a given reachability constraint varies slowly between 0 and 0.1 over the entire range of the variations in node density. Our analysis is also confirmed by extensive simulation results.
39238334
Information Processing and Routing in Wireless Sensor Networks
Introduction of Wireless Sensor Networks Background Energy Models Information Processing within a Collocated Cluster Information Transportation over a Tree Substrate Information Routing with Tunable Compression.
2701730
Data Gathering with Tunable Compression in Sensor Networks
We study the problem of constructing a data gathering tree over a wireless sensor network in order to minimize the total energy for compressing and transporting information from a set of source nodes to the sink. This problem is crucial for advanced computationally intensive applications, where traditional "maximum" in-network compression may result in significant computation energy. We investigate a tunable data compression technique that enables effective trade-offs between the computation and communication costs. We derive the optimal compression strategy for a given data gathering tree and then investigate the performance of different tree structures for networks deployed on a grid topology, as well as general graphs. Our analytical results pertaining to the grid topology and simulation results pertaining to the general graphs indicate that the performance of a simple greedy approximation to the Minimal Steiner Tree (MST) provides a constant-factor approximation for the grid topology and good average performance on the general graphs. Although, theoretically, a more complicated randomized algorithm offers a polylogarithmic performance bound, the simple greedy approximation of MST is attractive for practical implementation.
14893914
Energy-balanced task allocation for collaborative processing in networked embedded systems
In this paper, we study the problem of allocating a real-time application onto a set of homogeneous processing elements connected by a single-hop wireless network. A periodic application consisting of a set of communicating tasks is considered. Each element is equipped with discrete dynamic voltage scaling for exploring the energy-latency tradeoffs. The time and energy costs of both computation and communication activities are considered. The goal is to balance the energy dissipation of the elements during each period of the application with respect to the remaining energy of elements, such that the system lifetime is maximized. An Integer Linear Programming (ILP) formulation is first developed, which can be solved to obtain the optimal solution. We then propose an efficient 3-phase heuristic. Experimental results show that for small scale problems, the performance of the heuristic achieves up to 85% of the system lifetime obtained by the ILP-based approach. For large scale problems, the performance of the heuristic shows an improvement of 120-250\% in the system lifetime compared with the case where no voltage scaling is used. Further, we present two extensions of our approaches that consider multiple communication channels and techniques for exploring the energy-latency tradeoffs of the communication activities.
15352374
Network-Aware State Update For Large Scale Mobile Games
In large scale mobile gaming environments, efficient mechanisms for state update is crucial to allow graceful real-time interaction of a large number of players, under limited wireless network bandwidth. By using the state updating threshold as a key parameter that bridges the resulting state inconsistency (or distortion) and the network traffic, we are able to model the fundamental traffic-distortion tradeoffs. Given the tradeoffs for all users, an optimal bandwidth allocation can be derived using well-known convex programming techniques. By exploring the temporal locality of gaming behavior, we also propose a prediction method to realize on-line bandwidth adaptation. Using real data trace from a multi-player driving game, the proposed network aware bandwidth allocation method, NABA, is able to achieve significant reduction in state distortion compared to two baselines: Uniform and Proportional policies. NABA is also adaptable to variations in system parameters, including bandwidth constraint and network delay.
15993806
A Workflow Model with Temporal Logic Constraints and Its Automated Verification
Traditional workflow models are weak in describing the temporal properties and constraints between activities, while some high-level extensions based on time or temporal logic have another problem that the soundness verification of the model requires high academic knowledge. In order to solve these problems, a new workflow model LTL-WF based on WF-net and linear temporal logic is proposed in this paper. Besides introducing the new model, we also bring forward a method for automated verification of LTL-WF. The method proposed here provides the verification of workflow model with a convenient environment for model checking.
8755762
FEM Based Numerical Analysis on the Temperature Field in Grind-hardening
The grind-hardening is a new type of surface modification technology, which utilizes the dissipated grinding heat for hardening the surface layer of the workpiece. Currently, most of the researchers studying the grind-hardening have used Design of Experiments approach, by varying grind-hardening processes parameters with a great deal of experiments which has significant degree of uncertainty of the results. In this paper, temporal and spatial temperature distributions of the workpiece are simulated based on the FEM (finite element method). The simulated hardness penetration depth is deduced from the local temperature distribution and the time history of workpiece and its martensitic phase transformation conditions. The numerical simulation results were validated with experimental data. The results of this research indicate that the finite element method can be used in temperature field simulation in the grind-hardening technology. Thus the experiment cost and time in grind-hardening can be reduced by FEM simulation of the grind-hardening temperature field.
33694964
Workflow scheduling in grids: an ant colony optimization approach
Grid applications in virtue of open service grid architecture (OGSA) are promising next-generation computation techniques. One of the most important and challenging problems about grid application is the workflow scheduling problem to achieve the users' QoS (quality of service) requirements as well as to minimize the cost. This paper proposes an ant colony optimization (ACO) algorithm to tackle this problem. Several new features are introduced to the algorithm. First, we define two kinds of pheromone and three kinds of heuristic information to guide the search direction of ants for this bi-criteria problem. Each ant uses either one from these heuristic types and pheromone types in each iteration based on the probabilities controlled by two parameters. These two parameters are adaptively adjusted in the process of the algorithm. Second, we use the information of partial solutions to modify the bias of ants so that inferior choices will be ignored. Moreover, the experimental results in 3 workflow applications under different deadline constraints show that the performance of our algorithm is very promising, for it outperforms the Deadline-MDP algorithm in most cases.
6882751
Applications of a feather-weight virtual machine
A Feather-weight Virtual Machine (FVM) is an OS-level virtualization technology that enables multiple isolated execution environments to exist on a single Windows kernel. The key design goal of FVM is efficient resource sharing among VMs so as to minimize VM startup/shutdown cost and scale to a larger number of concurrent VM instances. As a result, FVM provides an effective platform for fault-tolerant and intrusion-tolerant applications that require frequent invocation and termination of dispensable VMs. This paper presents three complete applications of the FVM technology: scalable web site testing; shared binary service for application deployment and distributed Display-Only File Server (DOFS). To identify malicious web sites that exploit browser vulnerabilities, we use a web crawler to access untrusted sites, render their pages in multiple browsers each running in a separate VM, and monitor their execution behaviors. To allow Windows-based end user machines to share binaries that are stored, managed and patched on a central location, we run shared binaries in a special VM on the end user machine whose runtime environment is imported from the central binary server. To protect confidential files in a file server against information theft by insiders, we ensure that file viewing/editing programs run in a VM, which grants file content display but prevents file content from being saved on the host machine. In this paper, we show how to customize the generic FVM framework to accommodate the needs of the three applications, and present experimental results that demonstrate their performance and effectiveness.
14798479
Learning the Semantic Meaning of a Concept from the Web
Many researchers have used text classification method in solving the ontology mapping problem. Their mapping results heavily depend on the availability of quality exemplars used as training data. However, manual preparation of exemplars is costly. In this work, we propose to automatically extract text from web pages returned by a search engine. Search queries are formed according to the semantic information given in the ontology. We have implemented a prototype system that automates the entire process (from search query formation to conditional probability calculation) and conducted a series of experiments. We assessed the effectiveness of our approach by comparing the obtained conditional probabilities with human expectations. Our main contribution is that we explored the possibilities of utilizing web information for text classification based ontology mapping and made several valuable discoveries on its usefulness for future research.