12314143
Combs, needles, haystacks: balancing push and pull for discovery in large-scale sensor networks
In this paper we investigate efficient strategies for supporting on-demand information dissemination and gathering in large-scale vwireless sensor networks. In particular, we propose a "comb-needle" discovery support model resembling an ancient method: use a comb to help find a needle in sands or a haystack. The model combines push and pull for information dissemination and gathering. The push component features data duplication in a linear neighborhood of each node. The pull component features a dynamic formation of an on-demand routing structure resembling a comb. The comb-needle model enables us to investigate the cost of a spectrum of push and pull combinations for supporting discovery and query in large scale sensor networks. Our result shows that the optimal routing structure depends on the frequency of query occurrence and the spatial-temporal frequency of related events in the network. The benefit of balancing push and pull for discovery in large scale geometric networks are demonstrated. We also raise the issue of query coverage in unreliable networks and investigate how redundancy can improve the coverage via both theoretical analysis and simulation. Last, we study adaptive strategies for the case where the frequencies of query and events are unknown a priori and time-varying.
368408
A framework for opportunistic scheduling in wireless networks
Abstract We present a method, called opportunistic scheduling, for exploiting the time-varying nature of the radio environment to increase the overall performance of the system under certain quality of service/fairness requirements of users. We first introduce a general framework for opportunistic scheduling, and then identify three general categories of scheduling problems under this framework. We provide optimal solutions for each of these scheduling problems. All the proposed scheduling policies are implementable online; we provide parameter estimation algorithms and implementation procedures for them. We also show how previous work by us and others directly fits into or is related to this framework. We demonstrate via simulation that opportunistic scheduling schemes result in significant performance improvement compared with non-opportunistic alternatives.
5642431
Sensing-based opportunistic channel access
Enabled by regulatory initiatives and advanced radio technologies, more flexible opportunistic spectrum access has great potential to alleviate the spectrum scarcity. In this paper, we study the channel selection issue of secondary users in spectrum-agile communication systems. We focus on the sensing-based approach because it is simple and has low infrastructure requirements. We propose a two-step approach for channel selection. The first step is to determine whether or not a channel is idle and thus accessible to secondary users. We propose three algorithms to perform the accessibility check based on measurements of primary signals. Then we address the question whether an accessible channel is a good opportunity for a secondary user.
44693659
Global exponential stability of generalized recurrent neural networks with discrete and distributed delays
This paper is concerned with analysis problem for the global exponential stability of a class of recurrent neural networks (RNNs) with mixed discrete and distributed delays. We first prove the existence and uniqueness of the equilibrium point under mild conditions, assuming neither differentiability nor strict monotonicity for the activation function. Then, by employing a new Lyapunov-Krasovskii functional, a linear matrix inequality (LMI) approach is developed to establish sufficient conditions for the RNNs to be globally exponentially stable. Therefore, the global exponential stability of the delayed RNNs can be easily checked by utilizing the numerically efficient Matlab LMI toolbox, and no tuning of parameters is required. A simulation example is exploited to show the usefulness of the derived LMI-based stability conditions.
5760140
Reliable control design of fuzzy dynamic systems with time-varying delay
This paper focuses on the reliable fuzzy control design problem for fuzzy control systems with time delay. Based on linear matrix inequality (LMI) approach, a method for designing a reliable fuzzy controller is presented. The resulting fuzzy control systems are reliable in the sense that asymptotic stability is achieved not only when all control components are operating well, but also in the presence of some component failures. A reliable fuzzy control design scheme via state feedback is proposed in terms of LMIs. The result is extended to the case of observer-based reliable fuzzy control. Two illustrative examples are given to illustrate the validity of the proposed design procedures.
5155570
Low-power repeater insertion with both delay and slew rate constraints
In this paper, a novel repeater insertion algorithm is presented to minimize the power dissipation of interconnect trees under given timing budgets and slew rate constraints. In contrast to traditional bottom-up dynamic programming approaches, the proposed algorithm combines a Lagrangian relaxation framework and a graph-based search method to derive possible solutions in a top-down fashion. As a result, it is capable of analyzing repeater slew rates efficiently. In addition, our scheme incorporates accurate circuit models and is therefore able to capture the precise delay and slew rate information, leading to high-quality interconnect designs. We have applied our scheme to interconnects of different topologies and various timing and slew rate constraints. Experimental results demonstrate the effectiveness of our approach in comparison with previous low-power repeater insertion schemes. Under tight timing constraints, our scheme can always derive repeater insertion solutions that meet both delay and slew rate requirements, whereas other schemes often fail. Under loose timing constraints, our algorithm achieves up to a 23% average power dissipation reduction for different interconnects specifications with shorter runtimes
9790968
Fuzzy approximate disturbance decoupling of MIMO nonlinear systems by backstepping and application to chemical processes
Fuzzy approximate disturbance decoupling concept is introduced for a class of multiple-input-multiple-output (MIMO) nonlinear systems with completely unknown nonlinearities. Based on backstepping technique, a fuzzy almost disturbance decoupling control scheme is proposed. The fuzzy controllers guarantee internal uniform ultimate boundedness of the closed-loop adaptive systems and render a bounded approximate L/sub 2/ gain from the disturbance input to the output. The developed design scheme is applied to control a two continuous stirred tank reactor process. The simulation results illustrate the effectiveness of the method proposed in this paper.
204983610
Pyramidic Clustering of Large-Scale Microarray Images
With ongoing research and development of imaging techniques such as those involved in brain MRIs, cDNA microarrays and satellite reconnaissance, the need for tools that can intelligently parse larger images is ever increasing. One group of such techniques often used is that of segmentation, an example of which is that of clustering algorithms. In order to deal with large data sets, current approaches require the data to be sampled or summarized before true analysis can take place. In this paper we propose a novel image analysis technique using pyramidic type grouping, namely copasetic clustering, which focuses on the problem of applying traditional clustering techniques to these large-scale image data sets with limited resources. A further benefit of the technique is the transparency of its intermediate clustering steps; when applied to spatial data sets this allows the capture and incorporation of contextual information to improve result accuracy. The algorithm achieves an ∼1--3 dB w-to-noise ratio when compared with the conventional techniques described.