A Wireless Sensor Network (WSN) deployed for detection applications has the distinguishing feature that sensors cooperate to perform the detection task. Therefore, the decoupled design approach that is typically used ...
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A Wireless Sensor Network (WSN) deployed for detection applications has the distinguishing feature that sensors cooperate to perform the detection task. Therefore, the decoupled design approach that is typically used to design communication networks, where each network layer is designed independently, does not lead to the desired optimal detection performance. Cross-layer design has been recently explored for the design of MAC protocols for parallel topology (single hop) networks, but little work has been done on the integration of communication and information fusion for tree networks. In this work, we design the optimal Transmission Control Policy (TCP) that coordinates the communication between sensor nodes connected in a tree configuration, in order to optimize the detection performance. We integrate the Quality of Information (QoI), Channel State Information (CSI), and Residual Energy Information (REI) for each sensor into the system model. We formulate a constrained nonlinear optimization problem to find the optimal TCP design variables. We solve the optimization problem using a hierarchical approach where smaller local optimization problems are solved by each parent node to find the optimal TCP design variables for its child nodes. We compare our design with the max throughput and decoupled design approaches.
An advisor autonomously improves the efficiency of self-organizing emergent multi-agent systems at runtime. It identifies tasks that the system has to perform recurringly. If the system performs these tasks inefficien...
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An advisor autonomously improves the efficiency of self-organizing emergent multi-agent systems at runtime. It identifies tasks that the system has to perform recurringly. If the system performs these tasks inefficiently, the advisor will create so-called exception rules for the agents that enable them to perform these tasks more efficiently in the future. In contrast to the previously presented concept of ignore rules, a type of exception rule which only keeps the agents from doing certain tasks, in this paper we present the concept of pro-active rules. This type of exception rule allows the advised agents to already prepare for tasks before they are even announced to the system. Our experimental evaluation shows that a combination of these two rule types for the domain of dynamic pickup and delivery problems utilizes the advantages of both, improves previously badly handled problem instances, and additionally offers slight improvements for randomly created instances.
Over the past decade, wireless sensor networks have advanced in terms of hardware design, communication protocols, resource efficiency, and other aspects. Recently, there has been growing interest in mobile wireless s...
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Over the past decade, wireless sensor networks have advanced in terms of hardware design, communication protocols, resource efficiency, and other aspects. Recently, there has been growing interest in mobile wireless sensor networks, and several small-profile sensing devices that are able to control their own movement have already been developed. Unfortunately, resource constraints inhibit the use of traditional navigation methods, because these typically require bulky, expensive, and sophisticated sensors, substantial memory and processor allocation, and a generous power supply. Therefore, alternative navigation techniques are required. In this paper we present TripNav, a localization and navigation system that is implemented entirely on resource-constrained wireless sensor nodes. Localization is realized using radio interferometric angle of arrival estimation, in which bearings to a mobile node from a small number of infrastructure nodes are estimated based on the observed phase differences of an RF interference signal. The position of the mobile node is then determined using triangulation. A digital compass is also employed to keep the mobile node from deviating from the desired trajectory. We demonstrate using a real-world implementation that a resource-constrained mobile sensor node can accurately perform waypoint navigation with an average position error of 0.95 m.
A Wireless Sensor Network (WSN) deployed for detection applications has the distinguishing feature that sensors cooperate to perform the detection task. Therefore, the decoupled design approach typically used to desig...
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A Wireless Sensor Network (WSN) deployed for detection applications has the distinguishing feature that sensors cooperate to perform the detection task. Therefore, the decoupled design approach typically used to design communication networks, where each network layer is designed independently, does not lead to the desired optimal detection performance. Recent work on decentralized detection has addressed the design of MAC and routing protocols for detection applications by considering independently the Quality of Information (QoI), Channel State Information (CSI), and Residual Energy Information (REI) for each sensor. However, little attention has been given to integrate the three quality measures (QoI, CSI, REI) in the complete system design. In this work, we pursue a cross-layer approach to design a QoI, CSI, and REI-aware Transmission Control Policy (TCP) that coordinates communication between local sensors and the fusion center, in order to maximize the detection performance. We formulate and solve a constrained nonlinear optimization problem to find the optimal TCP design variables. We compare our design with the decoupled approach, where each layer is designed separately, in terms of the delay for detection and WSN lifetime.
The rapidly increasing use of information technology in constructing real-world systems has led to the urgent need for a sound systematic approach in designing networked control systems. Communication delays and other...
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The rapidly increasing use of information technology in constructing real-world systems has led to the urgent need for a sound systematic approach in designing networked control systems. Communication delays and other uncertainties complicate the development and analysis of these systems. This paper describes a prototype modeling language for the design of networked control systems using passivity to decouple control design from network uncertainties. The modeling language includes an integrated analysis tool to check for passivity and code generators for simulation in MATLAB/Simulink using the TrueTime platform modeling toolbox and for running actual experiments. The resulting designs are by construction robust to platform effects and implementation uncertainties.
The share measure has been proposed as an important measure for mining association rules. The value of share itemsets provides useful information such as total profits and total customer purchased quantities associate...
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The share measure has been proposed as an important measure for mining association rules. The value of share itemsets provides useful information such as total profits and total customer purchased quantities associated with itemsets in database. The share-frequent itemsets mining problems become a very important research issue in data mining. Existing share-frequent itemsets mining algorithms are based on static database so knowledge must be rebuilded when the minimum share threshold is changed or database is modified either appended or updated. This paper proposes a novel BitTable knowledge for incremental and interactive share-frequent itemsets mining in multiple minimum share thresholds without rebuilding BitTable knowledge. It is effective for incremental and interactive mining to take advantage of the previous BitTable knowledge and the previous mining results.
Current research efforts are being directed to commit with the long-term view of self-management properties for wireless telecommunications. Technology has transformed the cell phone from being a mere phone to becomin...
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Current research efforts are being directed to commit with the long-term view of self-management properties for wireless telecommunications. Technology has transformed the cell phone from being a mere phone to becoming an indispensable medium for contact, information and entertainment. The new paradigm in mobile services lies in providing a location-based user experience and here lies the tremendous scope for expansion of location-based services (LBS). One of the key approaches that have been recognized as an enabler of such a view is policy-based management, which has been mostly acknowledged as a methodology that provides adaptability and support to automatically assign network resources, control Quality of Service and security, by considering administratively specified rules. The hype of policy-based management was to commit with these features in run-time as a result of changeable network conditions resulting from the interactions of users, applications and existing resources. This paper proposes an adaptive architectural framework which deals with the critical nature of addressing the policy conflict problem. In this framework, policies are used as a mechanism to direct and adapt the behavior of self-adaptive systems. This policy-based framework consists of a set of processes, the self-coordinator process represents as the main process; which coordinates all the framework activities. Furthermore, the paper provides a guideline to avoid static and dynamic policy conflicts of different applications.
In this study, we introduces a classification approach using Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm and a feature selection algorithm along with biomedical test values to diagnose heart d...
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In this study, we introduces a classification approach using Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm and a feature selection algorithm along with biomedical test values to diagnose heart disease. Clinical diagnosis is done mostly by doctor's expertise and experience. But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis. In many cases, not all the tests contribute towards effective diagnosis of a disease. Our work is to classify the presence of heart disease with reduced number of attributes. Original, 13 attributes are involved in classify the heart disease. We use Information Gain to determine the attributes which reduces the number of attributes which is need to be taken from patients. The Artificial neural networks is used to classify the diagnosis of patients. Thirteen attributes are reduced to 8 attributes. The accuracy differs between 13 features and 8 features in training data set is 1.1% and in the validation data set is 0.82%.
Consider a backoff algorithm for medium access in wireless networks where a node chooses with probability 1-q to transmit right away and with probability q to transmit after CW slots, where CW is the maximum value of ...
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Consider a backoff algorithm for medium access in wireless networks where a node chooses with probability 1-q to transmit right away and with probability q to transmit after CW slots, where CW is the maximum value of the contention window. We study a variation of the 802.11 protocol called XVBEB which uses the above backoff scheme and give a theoretical analysis of its saturation throughput. Simulation results show that the throughput of XVBEB is better than that of 802.11 for saturated CBR traffic. Furthermore, XVBEB also exhibits lower packet loss, delay and delay variation than 802.11 for both VBR and VoIP traffic for a variety of load conditions.
Cloud computing paradigm allows on-demand access to computing and storages services over the Internet. To solve the complexity of application deployment in Cloud infrastructure, virtual appliances, pre-configured, rea...
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Cloud computing paradigm allows on-demand access to computing and storages services over the Internet. To solve the complexity of application deployment in Cloud infrastructure, virtual appliances, pre-configured, ready-to-run applications are emerging as a breakthrough technology. However, an automated approach for deploying network of appliances is required to guarantee minimum deployment cost, low latency, and high reliability. In this paper, we propose and compare two different deployment approaches: Forward-checking-based backtracking (FCBB) and genetic-based. They take into account Quality of Service (QoS) criteria such as reliability, data communication cost, and latency between multiple Clouds to choose the most appropriate combination of virtual machines and appliances. We evaluate our approach using a real case study and different request types. Experimental results show both algorithms reach near optimal solution. Further, we investigate effects of factors such as latency requirements, and data communication between appliances on the performance of the algorithms and placement of appliances across multiple Clouds.
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