41 research outputs found

    Improving Routing Efficiency through Intermediate Target Based Geographic Routing

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    The greedy strategy of geographical routing may cause the local minimum problem when there is a hole in the routing area. It depends on other strategies such as perimeter routing to find a detour path, which can be long and result in inefficiency of the routing protocol. In this paper, we propose a new approach called Intermediate Target based Geographic Routing (ITGR) to solve the long detour path problem. The basic idea is to use previous experience to determine the destination areas that are shaded by the holes. The novelty of the approach is that a single forwarding path can be used to determine a shaded area that may cover many destination nodes. We design an efficient method for the source to find out whether a destination node belongs to a shaded area. The source then selects an intermediate node as the tentative target and greedily forwards packets to it, which in turn forwards the packet to the final destination by greedy routing. ITGR can combine multiple shaded areas to improve the efficiency of representation and routing. We perform simulations and demonstrate that ITGR significantly reduces the routing path length, compared with existing geographic routing protocols

    Broadcasting with Prediction and Selective Forwarding in Vehicular Networks

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    Broadcasting in vehicular networks has attracted great interest in research community and industry. Broadcasting on disseminating information to individual vehicle beyond the transmission range is based on inter-vehicle communication systems. It is crucial to broadcast messages to other vehicles as fast as possible because the messages in vehicle communication systems are often emergency messages such as accident warning or alarm. In many current approaches, the message initiator or sender selects the node among its neighbors that is farthest away from it in the broadcasting direction and then assigns the node to rebroadcast the message once the node gets out of its range or after a particular time slot. However, this approach may select a nonoptimal candidate because it does not consider the moving status of vehicles including their moving directions and speeds. In this paper, we develop a new approach based on prediction of future velocity and selective forwarding. The current message sender selects the best candidate that will rebroadcast the message to other vehicles as fast as possible. Key to the decision making is to consider the candidates\u27 previous moving status and predict the future moving trends of the candidates so that the message is spread out faster. In addition, this approach generates very low overhead. Simulations demonstrate that our approach significantly decreases end-to-end delay and improves message delivery ratio

    Hole Detection and Shape-Free Representation and Double Landmarks Based Geographic Routing in Wireless Sensor Networks

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    In wireless sensor networks, an important issue of Geographic Routing is local minimum problem, which is caused by hole that blocks the greedy forwarding process. To avoid the long detour path, recent research focuses on detecting the hole in advance, then the nodes located on the boundary of the hole advertise the hole information to the nodes near the hole

    Scheduling Based on Interruption Analysis and PSO for Strictly Periodic and Preemptive Partitions in Integrated Modular Avionics

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    Integrated modular avionics introduces the concept of partition and has been widely used in avionics industry. Partitions share the computing resources together. Partition scheduling plays a key role in guaranteeing correct execution of partitions. In this paper, a strictly periodic and preemptive partition scheduling strategy is investigated. First, we propose a partition scheduling model that allows a partition to be interrupted by other partitions, but minimizes the number of interruptions. The model not only retains the execution reliability of the simple partition sets that can be scheduled without interruptions, but also enhances the schedulability of the complex partition sets that can only be scheduled with some interruptions. Based on the model, we propose an optimization framework. First, an interruption analysis method to decide whether a partition set can be scheduled without interruptions is developed. Then, based on the analysis of the scheduling problem, we use the number of interruptions and the sum of execution time for all partitions in a major time frame as the optimization objective functions and use particle swarm optimization (PSO) to solve the optimization problem when the partition sets cannot be scheduled without interruptions. We improve the update strategy for the particles beyond the search space and round all particles before calculating the fitness value in PSO. Finally, the experiments with different partitions are conducted and the results validate the partition scheduling model and illustrate the effectiveness of the optimization framework. In addition, other optimization algorithms, such as genetic algorithm and neural networks, can also be used to solve the partition problem based on our model and solution framework

    An Outlier Detection Algorithm Based on Cross-Correlation Analysis for Time Series Dataset

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    Outlier detection is a very essential problem in a variety of application areas. Many detection methods are deficient for high-dimensional time series data sets containing both isolated and assembled outliers. In this paper, we propose an Outlier Detection method based on Cross-correlation Analysis (ODCA). ODCA consists of three key parts. They are data preprocessing, outlier analysis, and outlier rank. First, we investigate a linear interpolation method to convert assembled outliers into isolated ones. Second, a detection mechanism based on the cross-correlation analysis is proposed for translating the high-dimensional data sets into 1-D cross-correlation function, according to which the isolated outlier is determined. Finally, a multilevel Otsu\u27s method is adopted to help us select the rank thresholds adaptively and output the abnormal samples at different levels. To illustrate the effectiveness of the ODCA algorithm, four experiments are performed using several high-dimensional time series data sets, which include two smallscale sets and two large-scale sets. Furthermore, we compare the proposed algorithm with the detection methods based on wavelet analysis, bilateral filtering, particle swarm optimization, auto-regression, and extreme learning machine. In addition, we discuss the robustness of the ODCA algorithm. The statistical results show that the ODCA algorithm is much better than existing mainstream methods in both effectiveness and time complexity

    The Effects of Using Chaotic Map on Improving the Performance of Multiobjective Evolutionary Algorithms

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    Chaotic maps play an important role in improving evolutionary algorithms (EAs) for avoiding the local optima and speeding up the convergence. However, different chaotic maps in different phases have different effects on EAs. This paper focuses on exploring the effects of chaotic maps and giving comprehensive guidance for improving multiobjective evolutionary algorithms (MOEAs) by series of experiments. NSGA-II algorithm, a representative of MOEAs using the nondominated sorting and elitist strategy, is taken as the framework to study the effect of chaotic maps. Ten chaotic maps are applied in MOEAs in three phases, that is, initial population, crossover, and mutation operator. Multiobjective problems (MOPs) adopted are ZDT series problems to show the generality. Since the scale of some sequences generated by chaotic maps is changed to fit for MOPs, the correctness of scaling transformation of chaotic sequences is proved by measuring the largest Lyapunov exponent. The convergence metric γ and diversity metric Δ are chosen to evaluate the performance of new algorithms with chaos. The results of experiments demonstrate that chaotic maps can improve the performance of MOEAs, especially in solving problems with convex and piecewise Pareto front. In addition, cat map has the best performance in solving problems with local optima

    An active buffer management technique for providing interactive functions in broadcast video-on-demand systems

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    Multicast delivery is an efficient approach to the provision of a video-on-demand (VoD) service. Interacting with the video stream is a desirable feature for users. However, it is a challenging task to provide the functionality in the multicast environment because a lot of users share multicast delivery channels. In this paper, we propose an active buffer management technique to provide interactive functions in broadcast VoD systems. In our scheme, the client can selectively prefetch segments from broadcast channels based on the observation of the play point in its local buffer. The content of the buffer is adjusted in such a way that the relative position of the play point is kept in the middle part of the buffer. Our simulations show that the active buffer management scheme can implement interactive actions through buffering with a high probability in a wide range of user interaction levels. © 2005 IEEE

    Location Aided Energy Balancing Strategy in Green Cellular Networks

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    Most cellular network communication strategies are focused on data traffic scenarios rather than energy balance and efficient utilization. Thus mobile users in hot cells may suffer from low throughput due to energy loading imbalance problem. In state of art cellular network technologies, relay stations extend cell coverage and enhance signal strength for mobile users. However, busy traffic makes the relay stations in hot area run out of energy quickly. In this paper, we propose an energy balancing strategy in which the mobile nodes are able to dynamically select and hand over to the relay station with the highest potential energy capacity to resume communication. Key to the strategy is that each relay station merely maintains two parameters that contains the trend of its previous energy consumption and then predicts its future quantity of energy, which is defined as the relay station potential energy capacity. Then each mobile node can select the relay station with the highest potential energy capacity. Simulations demonstrate that our approach significantly increase the aggregate throughput and the average life time of relay stations in cellular network environment.Comment: 6 pages, 5 figures. arXiv admin note: text overlap with arXiv:1108.5493 by other author

    A Multi-Institutional Approach to Delivering Shared Curricula for Developing a Next-Generation Energy Workforce

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    In this paper, we consider collaborative power systems education through the FEEDER consortium. To increase students\u27 access to power engineering educational content, the consortium of seven universities was formed. A framework is presented to characterize different collaborative education activities among the universities. Three of these approaches of collaborative educational activities are presented and discussed. These include 1) cross-institutional blended courses (“MS-MD”); 2) cross-institutional distance courses (“SS-MD”); and 3) single-site special experiential courses and concentrated on-site programs available to students across consortium institutions (“MS-SD”). This paper presents the advantages and disadvantages of each approach

    Proceedings of the Sixth International Workshop on Web Caching and Content Distribution

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    OVERVIEW The International Web Content Caching and Distribution Workshop (WCW) is a premiere technical meeting for researchers and practitioners interested in all aspects of content caching, distribution and delivery on the Internet. The 2001 WCW meeting was held on the Boston University Campus. Building on the successes of the five previous WCW meetings, WCW01 featured a strong technical program and record participation from leading researchers and practitioners in the field. This report includes all the technical papers presented at WCW'01. Note: Proceedings of WCW'01 are published by Elsevier. Hardcopies of these proceedings can be purchased through the workshop organizers. As a service to the community, electronic copies of all WCW'01 papers are accessible through Technical Report BUCS‐TR‐2001‐017, available from the Boston University Computer Science Technical Report Archives at http://www.cs.bu.edu/techreps. [Ed.note: URL outdated. Use http://www.bu.edu/cs/research/technical-reports/ or http://hdl.handle.net/2144/1455 in this repository to access the reports.]Cisco Systems; InfoLibria; Measurement Factory Inc; Voler
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