4,405 research outputs found

    Automatic Code Placement Alternatives for Ad-Hoc And Sensor Networks

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    Developing applications for ad-hoc and sensor networks poses significant challenges. Many interesting applications in these domains entail collaboration between components distributed throughout an ad-hoc network. Defining these components, optimally placing them on nodes in the ad-hoc network and relocating them in response to changes is a fundamental problem faced by such applications. Manual approaches to code and data migration are not only platform-dependent and error-prone, but also needlessly complicate application development. Further, locally optimal decisions made by applications that share the same network can lead to globally unstable and energy inefficient behavior. In this paper we describe the design and implementation of a distributed operating system for ad-hoc and sensor networks whose goal is to enable power-aware, adaptive, and easy-to-develop ad-hoc networking applications. Our system achieves this goal by providing a single system image of a unified Java virtual machine to applications over an ad-hoc collection of heterogeneous nodes. It automatically and transparently partitions applications into components and dynamically finds a placement of these components on nodes within the ad-hoc network to reduce energy consumption and increase system longevity. This paper outlines the design of our system and evaluates two practical, power-aware, online algorithms for object placement that form the core of our system. We demonstrate that our algorithms can increase system longevity by a factor of four to five by effectively distributing energy consumption, and are suitable for use in an energy efficient operating system in which applications are distributed automatically and transparently

    Mobile Data Management

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    The management of data in the mobile computing environment offers new challenging problems. Existing software needs to be upgraded to accommodate this environment. To do so, the critical parameters need to be understood and defined. We have surveyed some problems and existing solution

    PERFORMANCE ANALYSIS AND OPTIMIZATION OF QUERY-BASED WIRELESS SENSOR NETWORKS

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    This dissertation is concerned with the modeling, analysis, and optimization of large-scale, query-based wireless sensor networks (WSNs). It addresses issues related to the time sensitivity of information retrieval and dissemination, network lifetime maximization, and optimal clustering of sensor nodes in mobile WSNs. First, a queueing-theoretic framework is proposed to evaluate the performance of such networks whose nodes detect and advertise significant events that are useful for only a limited time; queries generated by sensor nodes are also time-limited. The main performance parameter is the steady state proportion of generated queries that fail to be answered on time. A scalable approximation for this parameter is first derived assuming the transmission range of sensors is unlimited. Subsequently, the proportion of failed queries is approximated using a finite transmission range. The latter approximation is remarkably accurate, even when key model assumptions related to event and query lifetime distributions and network topology are violated. Second, optimization models are proposed to maximize the lifetime of a query-based WSN by selecting the transmission range for all of the sensor nodes, the resource replication level (or time-to-live counter) and the active/sleep schedule of nodes, subject to connectivity and quality-of-service constraints. An improved lower bound is provided for the minimum transmission range needed to ensure no network nodes are isolated with high probability. The optimization models select the optimal operating parameters in each period of a finite planning horizon, and computational results indicate that the maximum lifetime can be significantly extended by adjusting the key operating parameters as sensors fail over time due to energy depletion. Finally, optimization models are proposed to maximize the demand coverage and minimize the costs of locating, and relocating, cluster heads in mobile WSNs. In these models, the locations of mobile sensor nodes evolve randomly so that each sensor must be optimally assigned to a cluster head during each period of a finite planning horizon. Additionally, these models prescribe the optimal times at which to update the sensor locations to improve coverage. Computational experiments illustrate the usefulness of dynamically updating cluster head locations and sensor location information over time

    Extensions to the self protecting object model to facilitate integrity in stationary and mobile hosts

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    M.Sc. (Computer Science)In this dissertation we propose extensions to the Self Protecting Object (SPO) model to facilitate the sharing of information in a more effective manner. We see the sharing ofinformation as the sharing of objects that provide services. Sharing objects effectively is allowing the objects to be used in a secure environment, independent of their location, in a manner usage was intended. The SPO model proposed by Olivier [32] allows for objects in a federated database to be moved from one site to another and ensures that the security policy of the object will always be respected and implemented, regardless of its location. Although the SPO model does indeed allow for objects (information) to be shared effectively, it fails to address issues of maintaining integrity within objects. We therefore define the notion of maintaining integrity within the spa model and propose a model to achieve it. We argue that ensuring an SPO is only used in a way usage was intended does not suffice to ensure integrity. The model we propose is based on ensuring that modifications to an SPO are only executed if the modification does not violate the constraints defined for the Sf'O, The model" allows for an spa to maintain its unique identity in addition to maintaining its integrity. The SPO model is designed to be used in a federated database on sites that are stationary. Therefore, having addressed the issue of maintaining integrity within SPOs on stationary sites in the federated database, we then introduce the notion of a mobile site: a site that will eventually disconnect from the federated database and become unreachable for some time. Introducing the mobile site into the federated database allows us to propose the Mobile Self Protecting Object (MSPO) and its associated architecture. Because of the nature of mobile sites, the original model for maintaining integrity can not be applied to the MSPO architecture. We therefore propose a mechanism (to be implemented in unison with the original model) to ensure the integrity of MSPOs on mobile sites. We then discuss the JASPO prototype. The aim of the prototype was to determine if the Self Protecting Object model was feasible using current development technologies. We examine the requirements identified in order for the prototype to be successful and discuss how these were satisfied. Several modifications were made to the original spa model, including the addition of a new module and the exclusion of others, we discuss these modifications and examine why they were necessary

    Probabilistic approaches to the design of wireless ad hoc and sensor networks

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    The emerging wireless technologies has made ubiquitous wireless access a reality and enabled wireless systems to support a large variety of applications. Since the wireless self-configuring networks do not require infrastructure and promise greater flexibility and better coverage, wireless ad hoc and sensor networks have been under intensive research. It is believed that wireless ad hoc and sensor networks can become as important as the Internet. Just as the Internet allows access to digital information anywhere, ad hoc and sensor networks will provide remote interaction with the physical world. Dynamics of the object distribution is one of the most important features of the wireless ad hoc and sensor networks. This dissertation deals with several interesting estimation and optimization problems on the dynamical features of ad hoc and sensor networks. Many demands in application, such as reliability, power efficiency and sensor deployment, of wireless ad hoc and sensor network can be improved by mobility estimation and/or prediction. In this dissertation, we study several random mobility models, present a mobility prediction methodology, which relies on the analysis of the moving patterns of the mobile objects. Through estimating the future movement of objects and analyzing the tradeoff between the estimation cost and the quality of reliability, the optimization of tracking interval for sensor networks is presented. Based on the observation on the location and movement of objects, an optimal sensor placement algorithm is proposed by adaptively learn the dynamical object distribution. Moreover, dynamical boundary of mass objects monitored in a sensor network can be estimated based on the unsupervised learning of the distribution density of objects. In order to provide an accurate estimation of mobile objects, we first study several popular mobility models. Based on these models, we present some mobility prediction algorithms accordingly, which are capable of predicting the moving trajectory of objects in the future. In wireless self-configuring networks, an accurate estimation algorithm allows for improving the link reliability, power efficiency, reducing the traffic delay and optimizing the sensor deployment. The effects of estimation accuracy on the reliability and the power consumption have been studied and analyzed. A new methodology is proposed to optimize the reliability and power efficiency by balancing the trade-off between the quality of performance and estimation cost. By estimating and predicting the mass objects\u27 location and movement, the proposed sensor placement algorithm demonstrates a siguificant improvement on the detection of mass objects with nearmaximal detection accuracy. Quantitative analysis on the effects of mobility estimation and prediction on the accuracy of detection by sensor networks can be conducted with recursive EM algorithms. The future work includes the deployment of the proposed concepts and algorithms into real-world ad hoc and sensor networks

    Adaptive sampling-based profiling techniques for optimizing the distributed JVM runtime

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    Extending the standard Java virtual machine (JVM) for cluster-awareness is a transparent approach to scaling out multithreaded Java applications. While this clustering solution is gaining momentum in recent years, efficient runtime support for fine-grained object sharing over the distributed JVM remains a challenge. The system efficiency is strongly connected to the global object sharing profile that determines the overall communication cost. Once the sharing or correlation between threads is known, access locality can be optimized by collocating highly correlated threads via dynamic thread migrations. Although correlation tracking techniques have been studied in some page-based sof Tware DSM systems, they would entail prohibitively high overheads and low accuracy when ported to fine-grained object-based systems. In this paper, we propose a lightweight sampling-based profiling technique for tracking inter-thread sharing. To preserve locality across migrations, we also propose a stack sampling mechanism for profiling the set of objects which are tightly coupled with a migrant thread. Sampling rates in both techniques can vary adaptively to strike a balance between preciseness and overhead. Such adaptive techniques are particularly useful for applications whose sharing patterns could change dynamically. The profiling results can be exploited for effective thread-to-core placement and dynamic load balancing in a distributed object sharing environment. We present the design and preliminary performance result of our distributed JVM with the profiling implemented. Experimental results show that the profiling is able to obtain over 95% accurate global sharing profiles at a cost of only a few percents of execution time increase for fine- to medium- grained applications. © 2010 IEEE.published_or_final_versionThe 24th IEEE International Symposium on Parallel & Distributed Processing (IPDPS 2010), Atlanta, GA., 19-23 April 2010. In Proceedings of the 24th IPDPS, 2010, p. 1-1

    Investigation on the mobile robot navigation in an unknown environment

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    Mobile robots could be used to search, find, and relocate objects in many types of manufacturing operations and environments. In this scenario, the target objects might reside with equal probability at any location in the environment and, therefore, the robot must navigate and search the whole area autonomously, and be equipped with specific sensors to detect objects. Novel challenges exist in developing a control system, which helps a mobile robot achieve such tasks, including constructing enhanced systems for navigation, and vision-based object recognition. The latter is important for undertaking the exploration task that requires an optimal object recognition technique. In this thesis, these challenges, for an indoor environment, were divided into three sub-problems. In the first, the navigation task involved discovering an appropriate exploration path for the entire environment, with minimal sensing requirements. The Bug algorithm strategies were adapted for modelling the environment and implementing the exploration path. The second was a visual-search process, which consisted of employing appropriate image-processing techniques, and choosing a suitable viewpoint field for the camera. This study placed more emphasis on colour segmentation, template matching and Speeded-Up Robust Features (SURF) for object detection. The third problem was the relocating process, which involved using a robot’s gripper to grasp the detected, desired object and then move it to the assigned, final location. This also included approaching both the target and the delivery site, using a visual tracking technique. All codes were developed using C++ and C programming, and some libraries that included OpenCV and OpenSURF were utilized for image processing. Each control system function was tested both separately, and then in combination as a whole control program. The system performance was evaluated using two types of mobile robots: legged and wheeled. In this study, it was necessary to develop a wheeled search robot with a high performance processor. The experimental results demonstrated that the methodology used for the search robots was highly efficient provided the processor was adequate. It was concluded that it is possible to implement a navigation system within a minimum number of sensors if they are located and used effectively on the robot’s body. The main challenge within a visual-search process is that the environmental conditions are difficult to control, because the search robot executes its tasks in dynamic environments. The additional challenges of scaling these small robots up to useful industrial capabilities were also explored

    Relocating sensor nodes to maximize cumulative connected coverage in wireless sensor networks

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    PubMed ID: 27879850In order to extend the availability of the wireless sensor network and to extract maximum possible information from the surveillance area, proper usage of the power capacity of the sensor nodes is important. Our work describes a dynamic relocation algorithm called MaxNetLife, which is mainly based on utilizing the remaining power of individual sensor nodes as well as properly relocating sensor nodes so that all sensor nodes can transmit the data they sense to the sink. Hence, the algorithm maximizes total collected information from the surveillance area before the possible death of the sensor network by increasing cumulative connected coverage parameter of the network. A deterministic approach is used to deploy sensor nodes into the sensor field where Hexagonal Grid positioning is used to address and locate each sensor node. Sensor nodes those are not planned to be actively used in the close future in a specific cell are preemptively relocated to the cells those will be in need of additional sensor nodes to improve cumulative connected coverage of the network. MaxNetLife algorithm also includes the details of the relocation activities, which include preemptive migration of the redundant nodes to the cells before any coverage hole occurs because of death of a sensor node. Relocation Model, Data Aggregation Model, and Energy model of the algorithm are studied in detail. MaxNetLife algorithm is proved to be effective, scalable, and applicable through simulations.Publisher's Versio
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