In order to find paths guaranteed by Quality of Service (QoS), the link state database (LSDB), containing QoS constraint information, and residing in routers, needs to be well managed. However, there is a trade-off between the exact reflection of the current link status and the update cost to calculate and maintain this data. In order to perfectly reflect the current link state, each router immediately notifies its neighbors whenever link state information changes. However, this may degrade the performance of the router. On the other hand, if current link state information is not updated routinely, route setup requests may be rejected because of the discrepancy between the current link state information and the previously updated link state information in the LSDB. Therefore, we need link state update (LSU) algorithms making it possible to appropriately update the LSDB. In addition, to facilitate implementation, they also should have low-complexity and must be adaptive under the variation of network conditions. In this paper, we propose an enhanced simple-adaptive (ESA) LSU algorithm, to reduce the generation of LSU messages while maintaining simplicity and adaptivity. The performance of this algorithm is compared with five existing algorithms by rigorous simulations. The comparision shows that the ESU algorithm can adapt to changes in network conditions and its performance is superior to existing LSU algorithms.

The recent progress in sensor and wireless communication technologies has enabled the design and implementation of new applications such as sensor telemetry which is the use of wireless sensors to gather fine-grained information from products, people and places. In this work, we consider a realistic telemetry application in which an area is periodically monitored by a sensor network which gathers data from equally spaced sample points. The objective is to maximize the lifetime of the network by jointly selecting the sensing nodes, the node transmission powers and the route to the base station from each sensing node. We develop an optimization-based algorithm OPT-RE and a low complexity algorithm SP-RE for this purpose and analyze their dynamics through extensive numerical studies. Our results indicate that SP-RE is a promising algorithm which has comparable performance to that of the more computationally intensive OPT-RE algorithm. The energy consumption is significantly affected by the channel access method, and in this paper, we also compare the effects of the collision free TDMA and contention based CSMA/CA methods. We propose practical enhancements to CSMA/CA so that the energy consumption due to collisions is reduced. Our simulation results indicate that with the proposed enhancements contention based channel access can provide comparable performance to that of the collision free methods.

We have been developing a secure and reliable distributed storage system, which uses a secret sharing scheme. In order to efficiently store data in the system, this paper introduces an optimal share transfer problem, and proves it to be, generally, NP-hard. It is also shown that the problem can be resolved into a Steiner tree problem. Finally, through computational experiments we perform the comparison of heuristic algorithms for the Steiner tree problem.

It is well known that Pisarenko's frequency estimate for a single real tone can be computed easily using the sample covariance with lags 1 and 2. In this Letter, we propose to use alternative covariance expressions, which are inspired from the modified covariance (MC) frequency estimator, in Pisarenko's algorithm. Computer simulations are included to corroborate the theoretical development of the variant and to demonstrate its superiority over the MC and Pisarenko's methods.

It has been shown that the output information produced by the soft output Viterbi algorithm (SOVA) is too optimistic. To compensate for this, the output information should be normalized. This letter proposes a simple normalization technique that extends the existing sign difference ratio (SDR) criterion. The new normalization technique counts the sign differences between the a-priori information and the extrinsic information, and then adaptively determines the corresponding normalization factor for each data block. Simulations comparing the new technique with other well-known normalization techniques show that the proposed normalization technique can achieve about 0.2 dB coding gain improvement on average while reducing up to about 1/2 iteration for decoding.

The Clonal Selection Algorithm (CSA) is employed by the natural immune system to define the basic features of an immune response to an antigenic stimulus. In the immune response, according to Burnet's clonal selection principle, the antigen imposes a selective pressure on the antibody population by allowing only those cells which specifically recognize the antigen to be selected for proliferation and differentiation. However ongoing investigations indicate that receptor editing, which refers to the process whereby antigen receptor engagement leads to a secondary somatic gene rearrangement event and alteration of the receptor specificity, is occasionally found in affinity maturation process. In this paper, we extend the traditional CSA approach by incorporating the receptor editing method, named RECSA, and applying it to the Traveling Salesman Problem. Thus, both somatic hypermutation (HM) of clonal selection theory and receptor editing (RE) are utilized to improve antibody affinity. Simulation results and comparisons with other general algorithms show that the RECSA algorithm can effectively enhance the searching efficiency and greatly improve the searching quality within reasonable number of generations.

In this paper, we present a method to automatically acquire a large-scale vocabulary of evaluative expressions from a large corpus of blogs. For the purpose, this paper presents a semi-supervised method for classifying evaluative expressions, that is, tuples of subjects, their attributes, and evaluative words, that indicate either favorable or unfavorable opinions towards a specific subject. Due to its characteristics, our semi-supervised method can classify evaluative expressions in a corpus by their polarities, starting from a very small set of seed training examples and using contextual information in the sentences the expressions belong to. Our experimental results with real Weblog data as our corpus show that this bootstrapping approach can improve the accuracy of methods for classifying favorable and unfavorable opinions. We also show that a reasonable amount of evaluative expressions can be really acquired.

Content delivery network improves end-user performance by replicating Web contents on a group of geographically distributed sites interconnected over the Internet. However, with the development whereby content distribution systems can manage dynamically changing files, an important issue to be resolved is consistency management, which means the cached replicas on different sites must be updated if the originals change. In this paper, based on the analytical formulation of object freshness, web access distribution and network topology, we derive a novel algorithm as follows: (1) For a given content which has been changed on its original server, only a limited number of its replicas instead of all replicas are updated. (2) After a replica has been selected for update, the latest version will be sent from an algorithm-decided site instead of from its original server. Simulation results verify that the proposed algorithm provides better consistency management than conventional methods with the reduced the old hit ratio and network traffic.

This study introduces the fuzzy Lyapunov function to the fuzzy PID control systems, modified fuzzy systems, with an optimized robust tracking performance. We propose a compound search strategy called conditional linear matrix inequality (CLMI) approach which was composed of the proposed improved random optimal algorithm (IROA) concatenated with the simplex method to solve the linear matrix inequality (LMI) problem. If solutions of a specific system exist, the scheme finds more than one solutions at a time, and these fixed potential solutions and variable PID gains are ready for tracking performance optimization. The effectiveness of the proposed control scheme is demonstrated by the numerical example of a cart-pole system.

Named entities play an important role in many Natural Language Processing applications. Currently, most named entity recognition systems rely on a small set of general named entity (NE) types. Though some efforts have been proposed to expand the hierarchy of NE types, there are still a fixed number of NE types. In real applications, such as question answering or semantic search systems, users may be interested in more diverse specific NE types. This paper proposes a method to extract categories of person named entities from text documents. Based on Dual Iterative Pattern Relation Extraction method, we develop a more suitable model for solving our problem, and explore the generation of different pattern types. A method for validating whether a category is valid or not is proposed to improve the performance, and experiments on Wall Street Journal corpus give promising results.

In this paper, a computationally efficient stack-based iterative detection algorithm is proposed for V-BLAST systems. To minimize the receiver's efforts as much as possible, the proposed scheme employs iterative tree search for complexity reduction and storage saving. After an M-ary tree structure by QR decomposition of channel matrix is constructed, the full tree depth is divided into the first depth and the remaining ones. At tree depth of one, the proposed algorithm finds M candidate symbols. Based on these symbols, it iteratively searches the remaining symbols at second-to-last depth, until finding an optimal symbol sequence. Simulation results demonstrate that the proposed algorithm yields the performance close to that of sphere detection (SD) with significant saving in complexity and storage.

In this paper we introduce an area and power efficient fully-parallel LDPC decoder design, which keeps the BER performance while consuming less hardware resources and lower power compared with conventional decoders. For this decoder, we firstly propose two improved simplified min-sum algorithms, which enable the decoder to reduce the hardware implementation complexity and area: hardware consumption of check operation module is reduced by 40%, while achieving a negligible performance loss compared with the general min-sum algorithm. To reduce the power dissipation of the decoder, we also proposed a power-saved strategy, according to which the message evolution halts as the parity-check condition is satisfied. This strategy reduces more than 50% power under good channel condition. The synthesis result in 0.18 µm CMOS technology shows our decoder based on (648,540) irregular LDPC code of WLAN (802.11n) protocol achieves 810 [Mbps] throughput with 283 [mW] power consumption.

This letter presents an adaptive H∞ array beamforming scheme based on a generalized sidelobe canceller with lower computational load. It is shown that the adaptive H∞-based beamformer offers the advantages of faster convergence speed, insensitivity to dynamic estimation modeling error, and less sensitivity to pointing error over the conventional adaptive H∞ algorithm. Simulations confirm that the proposed technique achieves similar array performance of the adaptive H∞-based algorithm [4].

Reliability-based hybrid ARQ (RB-HARQ) is a kind of incremental-redundancy ARQ recently introduced. In the RB-HARQ, the receiver returns both NAK signal and set of unreliable bit indices if the received sequence is not accepted. Since each unreliable bit index is determined by the bitwise posterior probability, better approximation of that probability becomes crucial as the number of retransmissions increases. Assuming the systematic code for the initial transmission, the proposed RB-HARQ scheme has the following two features: (a) the sender retransmits newly encoded and interleaved parity bits corresponding to the unreliable information bits; (b) the retransmitted parity bits as well as the initial received sequence are put all together to perform the message passing decoding i.e. the suboptimal MAP decoding. Finally, simulation results are shown to evaluate the above two features.

This paper proposes a new type of compact waveguide directional coupler, which is constructed from two crossed E-plane rectangular waveguide with two metallic posts in the square junction and one metallic post at each port. The metallic posts in the square junction are set symmetrically along a diagonal line to obtain the directivity properties. The metallic post inserted at each input/output waveguide port can realize a matched state. Tight-coupling properties 0.79-6 dB are realized by optimizing the dimension of the junction and the positions/radii of the posts. The design results are verified by an em-simulator (Ansoft HFSS) and experiments.

We introduce a novel configuration for a multi-user Multiple-Input Multiple-Output (MIMO) system in mobile communication over fast fading channels using space-time block coding (STBC) and adaptive array. The proposed scheme adopts the simultaneous transmission of data and pilot signals which reduces control errors caused by delay of obtaining channel state information (CSI). Data and pilot signals are then encoded using a space-time block code and are transmitted from two transmit antennas. In order to overcome the fast fading problem, implementation of adaptive array using recursive least squares (RLS) algorithms is considered at the base station. Through computer simulation, it is shown that the proposed scheme in this way can overcome Doppler spread in higher frequencies and suppress co-channel interference up to N-1 users for N receiving antennas.

Electromagnetic scattering properties of metamaterial cylinders due to a line source are studied by a multilayer algorithm based on eigenfunctional expansion. Closed forms of electric and magnetic fields are formulated. Both the fields inside the cylinder and field in outer space are plotted for different sizes of the cylinder. The focusing phenomena and the wave propagation in the presence of metamaterial cylinders are investigated and shown. Electromagnetic field distributions are presented for subwavelength metamaterial cylinders and cylinders fabricated by magnetoelectric materials, and resonant scattering and focusing properties are reported. Special designs of scatterer cloaking are proposed and calculated by multilayer algorithm which can reduce scattering cross sections.

The size-dependent array problem is a problem with systolic arrays such that the size of systolic arrays limits the size of calculations, which in a do-loop structure controls how many times it is repeated and how deep the nesting loops are. A systolic array cannot deal with larger calculations. For the size-dependent array problem, a spiral systolic array has been studied so far. It has non-adjacent connections between PEs, such as loop paths for sending data back so that data flows over the array independently of its own size. This paper takes an approach to the problem without non-adjacent connections. This paper discusses systolic messy arrays for infinite iterative algorithms so that they are independent from the size of calculations. First a systolic messy array called two-square shape is introduced then the properties of two-square shape are summarized: memory function, cyclic addition, and cyclic multiplication. Finally a way of building systolic messy arrays that calculate infinite iterative algorithms is illustrated with concrete examples such as an arithmetic progression, a geometric progression, N factorial, and Fibonacci numbers.

SAL is a toolkit for analyzing transition systems, providing several different tools. Among the tools are a BDD-based symbolic model checker (SMC) and an SMT-based infinite bounded model checker (infBMC). The unique functionality provided by SAL is k-induction, which is supported by infBMC. Given appropriate lemmas, infBMC can prove automatically by k-induction that an infinite-state transition system satisfies invariant properties. Maude is a specification language and system based on membership equational logic and rewriting logic. Maude is equipped with an on-the-fly explicit state model checker. The unique functionality provided by the Maude model checker supports inductive data types. We make a comparison of SAL (especially SMC and infBMC) and the Maude model checker by conducting case studies in which the Suzuki-Kasami distributed mutual exclusion algorithm is analyzed. The purpose of the comparison is to clarify some of the two tools' functionalities, especially the unique ones, through the case studies.

A novel high-speed and area-efficient Reed-Solomon decoder is proposed, which employs pipelining architecture of minimized modified Euclid (ME) algorithm. The logic synthesis and simulation results of its VLSI implementation show that it not only can operate at a higher clock frequency, but also consumes fewer hardware resources.