Traditional load shedding algorithms for data stream systems calculate current operator selectivity over several run periods and use them to determine where to shed load during the next run period. In this paper, we show that the current selectivity may change due to the implementation of load shedding. Our algorithm, called RLS, determines the optimum drop location by these changed selectivity rather than those pre-calculated values. Simulation results demonstrate that RLS achieves higher accuracy than traditional algorithms.

The conventional successive adaptive loading algorithm, represented by Hughes-Hartogs algorithm, can be used to reduce the transmit power of orthogonal frequency division multiplexing (OFDM) system. However, two major disadvantages exist for this kind of algorithm: One is the long loading time delay caused by the bit-to-bit loading, i.e., only one bit is loaded in every iteration; the other is that there is no flexibility in freely pre-defining the candidate modulation set before the loading is finished. In order to solve these problems, we propose the low-loading-delay parallel adaptive loading algorithms aiming at reducing the transmit power under the condition that the data throughput and error rate are maintained to target values. Two improvements are achieved by the new algorithm. One is that it divides the successive adaptive loading into several independent small-scale loading (SS-Loading) procedures. "SS-Loading" can be performed in parallel mode. To support this, we propose two subband division methods (successive and sorted subband divisions). The simulation results show that for a large range of subband number (1-128), the loading time delay can be remarkably decreased (especially for the parallel adaptive loading based on sorted subband division, i.e., SRT parallel adaptive loading algorithm) with neglectable power efficiency loss, compared with Hughes-Hartogs algorithm. The second improvement is that the new algorithm allows us to pre-define the candidate modulation set, which provide flexibility for the system design, e.g. we can exclude those rarely used modulation modes. We also reveal that Hughes-Hartogs algorithm is actually a special case of the newly proposed algorithm.

A new method of cancellation of IM3 using current feedback has been proposed for a multi-stage RFIC amplifier. In order to cancel the IM3 present in an output signal of the amplifier, the IIP3 level and IM3 phase of the amplifier are adjusted by means of feedback circuit techniques, so that the target specification is satisfied. By estimating the IIP3 level and IM3 phase variations for two states in situations with and without feedback possessing linear factors, the parameters of a feedback circuit can be calculated. To confirm the validity of the method, we have investigated two approaches; one including an analytical approach to designing a two-stage feedback amplifier, achieving an IIP3 level improvement of 14.8 dB. The other method involves the fabrication of single-stage amplifiers with and without feedback, operating at 850 MHz, both of which were designed as an integrated circuit using a 0.18 µm SiGe BiCMOS process. The fabricated IC's were tested using a load-pull measurement system, and a good agreement between the estimated and measured IIP3 level and IM3 phase variations has been achieved. Further studies show that the error in these variations, as estimated by the method, has been found to be less than 1.5 dB and 15 degrees, respectively, when the load admittance at 1701 MHz was greater than 1/50 S.

In this paper, we propose an efficient resource discovery scheme for large-scale ubiquitous computing environments, which supports scalable semantic searches and load balancing among resource discovery resolvers. Here, the resources are described based on the concepts defined in the ontological hierarchy. To semantically search the resources in a scalable manner, we propose a semantic vector space and semantic resource discovery network in which the resources are organized based on their respective semantic distances. Most importantly, landmarks are introduced for the first time to reduce the dimensionality of the vector space. Computer simulation with CAN verifies the effectiveness of the proposed scheme.

Transmission schemes that gain content from multiple servers concurrently have been highlighted due to their ability to provide bandwidth aggregation, stability on dynamic server departure, and load balancing. Previous approaches employ parallel downloading in the transport layer to minimize the receiver buffer size and maximize bandwidth utilization. However, they only focus on the receiver operations and induce considerable overhead at the senders in contradiction to the main goal of a multi-provider environment, offloading popular servers through replication. In the present work, the authors propose MTCP, a novel transport layer protocol that focuses on reduction of the sender overhead through the elimination of unnecessary disk I/Os and efficient buffer cache utilization. MTCP also balances trade-off objectives to minimize buffering at receivers and maximize the request locality at senders.

Hierarchical Mobile IPv6 (HMIPv6) was designed to reduce the long handover time associated with MIPv6 by employing a hierarchy of Mobile Anchor Points (MAPs). However, the selection of MAP and its load status critically affect the system performance. Thus, in this paper, we introduce two novel dynamic MAP selection schemes for HMIPv6, that relieve overloaded MAPs as well as select a more suitable MAP according to each Mobile Node (MN)'s up-to-date mobility towards reducing inter-domain handover, resulting in saving the overall signaling cost. Further, we develop an analytical model of the average signaling cost for inter-domain handover to investigate the performance of another existing approach with its basis on IETF HMIPv6 as well as our schemes. We also perform simulations to evaluate the performance of our proposed schemes. It is shown via simulation and numerical results that the proposed dynamic MAP selection schemes can significantly reduce the number of inter-domain handovers and the average signaling cost as well as distribute load over multiple MAPs compared to the other existing approaches.

A lossless data embedding method that inserts data in images in the spatial domain is proposed in this paper. Though a lossless data embedding method once distorts an original image to embed data into the image, the method restores the original image as well as extracts hidden data from the image in which the data are embedded. To guarantee the losslessness of data embedding, all pixel values after embedding must be in the dynamic range of pixels. Because the proposed method modifies some pixels to embed data and leaves other pixels as their original values in the spatial domain, it can easily keep all pixel values after embedding in the dynamic range of pixels. Thus, both the capacity and the image quality of generated images are simultaneously improved. Moreover, the proposed method uses only one parameter based on the statistics of pixel blocks to embed and extract data. By using this parameter, this method does not require any reference images to extract embedded data nor any memorization of the positions of pixels in which data are hidden to extract embedded data. In addition, the proposed method can control the capacity for hidden data and the quality of images conveying hidden data by controlling the only one parameter. Simulation results show the effectiveness of the proposed method; in particular, it offers images with superior image quality to conventional methods.

Parallel downloading retrieves different pieces of a file from different servers simultaneously and so is expected to greatly shorten file fetch times. A key requirement is that the different servers must hold the same file. We have already proposed a proxy system that can ensure file freshness and concordance. In this paper, we combine parallel downloading with the proxy server technology in order to download a file quickly and ensure that it is the latest version. Our previous paper on parallel downloading took neither the downloading order of file fragments nor the buffer space requirements into account; this paper corrects those omissions. In order to provide the user with the required file in correct order as a byte stream, the proxy server must reorder the pieces fetched from multiple servers and shuffle in the delayed blocks as soon as possible. Thus, "substitution download" is newly introduced, which requests delayed blocks from other servers to complete downloading earlier. Experiments on substitution download across the Internet clarify the tradeoff between the buffering time and the redundant traffic generated by duplicate requests to multiple servers. As a result, the pseudo-optimum balance is discovered and our method is shown both not to increase downloading time and to limit the buffer space. This network software can be applied to download files smoothly absorbing the difference in performance characteristics among heterogeneous networks.

Multipath routing employs multiple parallel paths between the source and destination for a connection request to improve resource utilization of a network. In this paper, we present an integrated design of multipath routing with delay constraints and failure survivability in MPLS networks. By combining the failure survivability schemes into the multipath routing algorithms, path protection or restoration policies will enable the network to accommodate link failures and at the same time achieve significant improvement on network resource utilization. We propose a number of multipath routing algorithms, working-backup path selection and bandwidth allocation schemes. We evaluate the performance of the proposed schemes in terms of call blocking probability, network resource utilization and load balancing factor. Extensive simulation results validate the effectiveness of the proposed schemes. In particular, we compare these multipath schemes to the existing failure recovery schemes that mostly focus on single path routing. The results demonstrate that the proposed integrated design framework can provide effective network failure survivability, and also achieve better load balancing and/or higher network resource utilization.

In peer-to-peer (P2P) networks, reputation is used to estimate the trustworthiness of servents and to help prevent untrustworthy resources from spreading by malicious servents. However, in dynamic scenarios with arrivals and departures of servents and resources, servent reputation is not enough to reduce the impacts of malicious behaviors such as lying, whitewashing, etc. In this paper, we propose a new reputation management model using both servent and resource reputation and demonstrate detail protocols to implement our model in structured P2P networks. Simulation results show that our model can reduce the rate of downloading untrustworthy resources more rapidly than the previous models even in dynamic scenarios where servents can rejoin with new identities, introduce new untrustworthy resources, and send wrong feedbacks. Also, we show that the proposed model and protocol can effectively share the load between servents.

To make the best use of the resources in a shared grid environment, an application scheduler must make a prediction of available performance on each resource. In this paper, we examine the problem of predicting available CPU performance in time-shared grid system. We present and evaluate a new and innovative method to predict the one-step-ahead CPU load in a grid. Our prediction strategy forecasts the future CPU load based on the variety tendency in several past steps and in previous similar patterns, and uses a polynomial fitting method. Our experimental results on large load traces collected from four different kinds of machines demonstrate that this new prediction strategy achieves average prediction errors which are between 22% and 86% less than those incurred by four previous methods.

For broadband wireless networks based on OFDM (Orthogonal Frequency Division Multiplexing), an FRF (Frequency Reuse Factor) of 1 has been highly desirable for more improved channel throughput. However, due to the limited power budget of MSs (Mobile Stations) or the increase in ICI (Inter-Cell Interference), a required QoS (Quality of Service) may not be maintained. This paper addresses an optimal LCRTD (Loading Control based on Region-Time Division) over multi-cell environments for an efficient uplink QoS control. In the LCRTD scheme, a cell is divided into several regions by utilizing an optimization approach under QoS constraints, and users in each region are allowed to send their data at the allocated time slots. In the simulation, it is demonstrated that a decrease of 26% in the transmit power can be obtained.

The multi-step prediction model based on partial least squares (PLS) is established to predict short-term load series with high embedding dimension in this paper, which refrains from cumulative error with local single-step linear model, and can cope with the multi-collinearity in the reconstructed phase space. In the model, PLS is used to model the dynamic evolution between the phase points and the corresponding future points. With research on the PLS theory, the model algorithm is put forward. Finally, the actual load series are used to test this model, and the results show that the model plays well in chaotic time series prediction, even if the embedding dimension is selected a big value.

To give comprehensive and consecutive understanding about load line regulation in the previous companion paper [1], more generalized expansion and theoretical derivation will be proposed in this paper. The paper provides an alternative current control approach to control the bias voltage compensation for full-color LED display based on the load-line approach. Modeling and formulation of the driver circuit system will be discussed in detail. Bias voltage compensation based on three load-lines regulation will keep the operating point fixed for the three color cells. Many properties can be observed based on the proposed model. Parasite effect such as the stray resistor and the stray capacitor will be considered in this paper. The associated standard RGB color testing for color cells and white color testing will be illustrated to verify the proposed compensation for the display driver circuit. The objectives of the luminance uniformity and the gray scale control can be achieved by using circuit approach. It is believed that this paper will be helpful to the driver circuit technology for the full-color LED display.

Resource performance prediction is known to be useful in resource scheduling in the Grid. The disk I/O workload is another important factor that influences the performance of the CPU and the network which are commonly used in resource scheduling. In the case of disk I/O workload time-series, the adaptation of a prediction algorithm to new time-series should be rapid. Further, the prediction should ensure that the prediction error is minimum in the heterogeneous environment. The storage workload (i.e., the disk I/O load) is a dynamic variable. A prediction parameter based on the characteristics of the current workload must be prepared for prediction purposes. In this paper, we propose and implement the OPHB (On-Line Parameter History Bank). This is a method that stabilizes the incoming disk I/O workload time-series fairly quickly with the help of accurately determined ESM (Exponential Smoothing Method) parameters. The parameters are drawn from a history database. In the case of forecasting with ESM, a smoothing parameter must be specified in advance. If the parameter is statically estimated from observed data found in previous executions, the forecasts would be inaccurate because they do not capture the actual I/O behavior. The smoothing parameter has to be adjusted in accordance with the shape of the new disk I/O workload. The ESM algorithms utilise one of the accumulated parameter histories chronicled by OPHB's Deposit operation. When a new time-series is started, an appropriate parameter value is looked up in the Bank by OPHB's Lookup operation. This is used for the time-series. This process is fully adaptive. We evaluate the proposed method with SES (Single Exponential Smoothing) and ARRSES (Auto-Responsive SES) methods.

A novel approach of robust adaptive beamforming (RABF) is presented in this paper, aiming at robustness against both finite-sample effects and steering vector mismatches. It belongs to the class of diagonal loading approaches with the loading level determined based on worst-case performance optimization. The proposed approach, however, is distinguished by two points. (1) It takes finite-sample effects into account and applies worst-case performance optimization to not only the constraints, but also the objective of the constrained quadratic equation, for which it is referred to as joint worst-case RABF (JW-RABF). (2) It suggests a simple closed-form solution to the optimal loading after some approximations, revealing how different factors affect the loading. Compared with many existing methods in this field, the proposed one achieves better robustness in the case of small sample data size as well as steering vector mismatches. Moreover, it is less computationally demanding for presenting a simple closed-form solution to the optimal loading. Numerical examples confirm the effectiveness of the proposed approach.

IEEE 802.11 MAC is the most commonly used MAC layer protocol in multi-hop ad hoc networks. When the network load becomes heavy, the throughput performance of IEEE 802.11 MAC is decreased because of the high collision rates and the low spatial reuse of the channel. In this letter, we analyze the throughput of multi-hop ad hoc networks and propose a supervisory control framework to maximize the throughput.

This paper analytically studies performance improvement achieved by packet dispersion. Contrary to the previous work on packet dispersion, we consider the tail distribution of queue length and that of packet delay as performance measures, and we model a packet network as multiple parallel queues where the arrival processes from sources are not renewal but highly bursty. To appropriately evaluate the performance improvement achieved by packet dispersion, we develop approximate formulas to estimate the tail distributions. Our approximate formulas yield more accurate estimations than the standard approximate formulas. In the numerical results, we observe that packet dispersion can greatly improve the delay performance of packets. We also see that packet-level load balancing is superior to flow-level load balancing for any distribution ratio.

A self-organizing wireless network has to deal with reliability and congestion problems when the network size increases. In order to alleviate such problems, we designed and analyzed protocols and algorithms for a reliable and efficient multiple-layer self-organizing wireless network architecture. Each layer uses a high-power root node to supervise the self-organizing functions, to capture and maintain the physical topology, and to serve as the root of the hierarchical routing topology of the layer. We consider the problem of adding a new root with its own rooted spanning tree to the network. Based on minimum-depth and minimum-load metrics, we present efficient algorithms that achieve optimum selection of root(s). We then exploit layer scheduling algorithms that adapt to network load fluctuations in order to optimize the performance. For optimality we consider a load balancing objective and a minimum delay objective respectively. The former attempts to optimize the overall network performance while the latter strives to optimize the per-message performance. Four algorithms are presented and simulations were used to evaluate and compare their performance. We show that the presented algorithms have superior performance in terms of data throughput and/or message delay, compared to a heuristic approach that does not account for network load fluctuations.

In this paper, we propose Split Multi-path Routing protocol with Load Balancing policy (SMR-LB) to improve TCP performance in mobile ad hoc networks. In SMR-LB, each intermediate node records how many primary paths are attempted to construct as well as which source nodes attempt to construct the primary path. Each intermediate node decides which primary path should be constructed by using the primary path and the source node ID information. As a result, SMR-LB can balance the loads and so reduce the probability of congestion and avoid the continuous link breakage time between the specific source and destination pair. Computer simulation results show that SMR-LB can improve TCP performance compared with the conventional protocols.