Recently, Yuan et al. (IEEE Infocom'13, pp.2652-2660) proposed an efficient secure nearest neighbor (SNN) search scheme on encrypted cloud database. Their scheme is claimed to be secure against the collusion attack of query clients and cloud server, because the colluding attackers cannot infer the encryption/decryption key. In this letter, we observe that the encrypted dataset in Yuan's scheme can be broken by the collusion attack without deducing the key, and present a simple but powerful attack to their scheme. Experiment results validate the high efficiency of our attacking approach. Additionally, we also indicate an upper bound of collusion-resistant ability of any accurate SNN query scheme.

This letter deals with a sparse signal recovery problem and proposes a new algorithm based on the iterative reweighted least squares (IRLS) algorithm. We assume that the non-zero values of a sparse signal is always greater than a given constant and modify the IRLS algorithm to satisfy this assumption. Numerical results show that the proposed algorithm recovers a sparse vector efficiently.

Formalizing requirements in formal specifications is an effective way to deepen the understanding of the envisioned system and reduce ambiguities in the original requirements. However, it requires mathematical sophistication and considerable experience in using formal notations, which remains a challenge to many practitioners. To handle this challenge, this paper describes a pattern-based approach to facilitate the formalization of requirements. In this approach, a pattern system is pre-defined to guide requirements formalization where each pattern provides a specific solution for formalizing one kind of function into a formal expression. All of the patterns are classified and organized into a hierarchical structure according to the functions they can be used to formalize. The distinct characteristic of our approach is that all of the patterns are stored on computer as knowledge for creating effective guidance to facilitate the developer in requirements formalization; they are “understood” only by the computer but transparent to the developer. We also describe a prototype tool that supports the approach. It adopts Hierarchical Finite State Machine (HFSM) to represent the pattern knowledge and implements an algorithm for applying it to assist requirements formalization. Two experiments on the tool are presented to demonstrate the effectiveness of the approach.

As a promising lamination-loss-free fabrication technique, diffusion bonding of etched thin metal plates is used to realize double-layer waveguide slot antennas. Alternating-phase feed is adopted in this paper to reduce the number of laminated plates to simplify fabrication as well as to reduce cost. A 20 × 20-element double-layer waveguide slot antenna with a bottom partially-corporate feed circuit is designed for 39GHz band operation as an example. The adjacent radiating waveguides as well as the 2 × 2 sub-arrays fed in an alternating-phase manner eliminate the need for complete electrical contact in the top layer. However, the feed circuit in the bottom layer has to be completely diffusion-bonded. These two layers are simply assembled by screws. An antenna laminated by only diffusion bonding is also fabricated and evaluated for comparison. The comparison proved that the simply fabricated antenna is comparable in performance to the fully diffusion-bonded one.

Outsourcing to a cloud storage brings forth new challenges for the efficient utilization of computing resources as well as simultaneously maintaining privacy and security for the outsourced data. Data deduplication refers to a technique that eliminates redundant data on the storage and the network, and is considered to be one of the most-promising technologies that offers efficient resource utilization in the cloud computing. In terms of data security, however, deduplication obstructs applying encryption on the outsourced data and even causes a side channel through which information can be leaked. Achieving both efficient resource utilization and data security still remains open. This paper addresses this challenging issue and proposes a novel solution that enables data deduplication while also providing the required data security and privacy. We achieve this goal by constructing and utilizing equality predicate encryption schemes which allow to know only equivalence relations between encrypted data. We also utilize a hybrid approach for data deduplication to prevent information leakage due to the side channel. The performance and security analyses indicate that the proposed scheme is efficient to securely manage the outsourced data in the cloud computing.

In this letter, advanced QRD-M detection using iterative scheme is proposed. This scheme has a higher diversity degree than conventional QRD-M detection. According to the simulation results, the performance of proposed QRD-M detection is 0.5dB to 5.5dB better than the performance of conventional QRD-M detection and average iteration time is approximately 1 in the value of M = 1, 2, 3. Therefore, the proposed QRD-M detection has better performance than conventional QRD-M detection, particularly in a high SNR environment and low modulation order.

In this paper, we study partial words in relation with pcodes, compatibility, and containment. First, we introduce C⊂(L), the set of all partial words contained by elements of L, and C⊃(L), the set of all partial words containing elements of L, for a set L of partial words. We discuss the relation between C(L), the set of all partial words compatible with elements of the set L, C⊂(L), and C⊃(L). Next, we consider the condition for C(L), C⊂(L), and C⊃(L) to be a pcode when L is a pcode. Furthermore, we introduce some classes of pcodes. An infix pcode and a comma-free pcode are defined, and the inclusion relation among these classes is established.

This letter proposes a fast intra prediction method to reduce encoding time for the high-efficiency video coding (HEVC) standard, which involves an increase in the number of intra-modes. The proposed intra-mode coding method uses correlation between intra-modes and adjacent pixels. The proposed method skips half of the intra-modes in certain blocks, specifically those that satisfy predetermined conditions. Using the half of intra-modes reduces number of bits for intra-mode coding and offsets a decline of coding performance caused by mode skipping. The experimental results show that the proposed method achieved 5.87% reduction in encoding time compared to the HEVC test model 7.1 encoder with almost no loss in coding performance.

In this letter, an estimation technique for multiple CFOs is proposed that uses the properties of the Zadoff-Chu (ZC) sequence. After initial estimation of multiple CFOs by using the properties of the ZC sequence, accurate estimates are obtained in the proposed technique by an iterative procedure. The proposed technique can be applied to LTE-based CoMP systems where ZC sequences are used to generate synchronization signals in downlink and random access preambles in uplink.

Remote data possession checking for cloud storage is very important, since data owners can check the integrity of outsourced data without downloading a copy to their local computers. In a previous work, Chen proposed a remote data possession checking protocol using algebraic signature and showed that it can resist against various known attacks. In this paper, we find serious security flaws in Chen's protocol, and shows that it is vulnerable to replay attack by a malicious cloud server. Finally, we propose an improved version of the protocol to guarantee secure data storage for data owners.

Multiple access (MA) technology is of most importance for beyond long term evolution (LTE) system. Non-orthogonal multiple access (NOMA) utilizing power domain and advanced receiver has been considered as a candidate MA technology recently. In this paper, power assignment method, which plays a key role in performance of NOMA, is investigated. The power assignment on the basis of maximizing geometric mean user throughput requires exhaustive search and thus has an unacceptable computational complexity for practical systems. To solve this problem, a novel power assignment method is proposed by exploiting tree search and characteristic of serial interference cancellation (SIC) receiver. The proposed method achieves the same performance as the exhaustive search while greatly reduces the computational complexity. On the basis of the proposed power assignment method, the performance of NOMA is investigated by link-level and system-level simulations in order to provide insight into suitability of using NOMA for future MA. Simulation results verify effectiveness of the proposed power assignment method and show NOMA is a very promising MA technology for beyond LTE system.

As businesses are increasingly relying on the cloud to host their services, cloud providers are striving to offer guaranteed and highly-available resources. To achieve this goal, recent proposals have advocated to offer both computing and networking resources in the form of Virtual Data Centers (VDCs). Subsequently, several attempts have been made to improve the availability of VDCs through reliability-aware resource allocation schemes and redundancy provisioning techniques. However, the research to date has not considered the heterogeneity of the underlying physical components. Specifically, it does not consider recent findings showing that failure rates and availability of data center equipments can vary significantly depending on various parameters including their types and ages. To address this limitation, in this paper we propose a High-availability Virtual Infrastructure management framework (Hi-VI) that takes into account the heterogeneity of cloud data center equipments to dynamically provision backup resources in order to ensure required VDC availability. Specifically, we propose a technique to compute the availability of a VDC that considers both (1) the heterogeneity of data center networking and computing equipments in terms of failure rates and availability, and (2) the number of redundant virtual nodes and links provisioned as backups. We then leverage this technique to propose an allocation scheme that jointly provisions resources for VDCs and backups of virtual components with the goal of achieving the required VDC availability while minimizing energy costs. Through simulations, we demonstrate the effectiveness of our framework compared to heterogeneity-oblivious solutions.

Many subjective assessment methods for video quality are provided by ITU-T and ITU-R recommendations, but the differences among these methods have not been sufficiently studied. We compare five subjective assessment methods using four quantitative performance indices for both HD and QVGA resolution video. We compare the Double-Stimulus Continuous Quality-Scale (DSCQS), Double-Stimulus Impairment Scale (DSIS), Absolute Category Rating method (ACR), and ACR with Hidden Reference (ACR-HR) as common subjective assessment methods for HD and QVGA resolution videos. Furthermore, we added ACR with an 11-grade scale (ACR11) for the HD test and Subjective Assessment of Multimedia Video Quality (SAMVIQ) for the QVGA test for quality scale variations. The performance indices are correlation coefficients, rank correlation coefficients, statistical reliability, and assessment time. For statistical reliability, we propose a performance index for comparing different quality scale tests. The results of the performance comparison showed that the correlation coefficients and rank correlation coefficients of the mean opinion scores between pairs of methods were high for both HD and QVGA tests. As for statistical reliability provided by the proposed index, DSIS of HD and ACR of QVGA outperformed the other methods. Moreover, ACR, ACR-HR, and ACR11 were the most efficient subjective quality assessment methods from the viewpoint of assessment time.

The main target of compressed sensing is recovery of one-dimensional signals, because signals more than two-dimension can also be treated as one-dimensional ones by raster scan, which makes the sensing matrix huge. This is unavoidable for general sensing processes. In separable cases like discrete Fourier transform (DFT) or standard wavelet transforms, however, the corresponding sensing process can be formulated using two matrices which are multiplied from both sides of the target two-dimensional signals. We propose an approximate message passing (AMP) algorithm for the separable sensing process. Typically, we suppose DFT for the sensing process, in which the measurements are complex numbers. Therefore, the formulation includes cases in which both target signal and measurements are complex. We show the effectiveness of the proposed algorithm by computer simulations.

The throughput rate of Viterbi decoding (VD) is not limited by the speed of functional units when look-ahead computation techniques are used. The disadvantages of the look-ahead computation in VD are the hardware complexity and the decode latency. In this paper, implementation methods of the look-ahead ACS computation are proposed to improve the hardware efficiency and reduce the latency where the hardware efficiency and the latency can be balanced with a single parameter.

Temporal Decorrelation source SEParation (TDSEP) is a blind separation scheme that utilizes the time structure of the source signals, typically, their periodicities. The advantage of TDSEP over non-Gaussianity based methods is that it can separate Gaussian signals as long as they are periodic. However, its shortcoming is that separation performance (SEP) heavily depends upon the values of the time shift parameters (TSPs). This paper proposes a method to automatically and blindly estimate a set of TSPs that achieves optimal SEP against periodic Gaussian signals. It is also shown that, selecting the same number of TSPs as that of the source signals, is sufficient to obtain optimal SEP, and adding more TSPs does not improve SEP, but only increases the computational complexity. The simulation example showed that the SEP is higher by approximately 20dB, compared with the ordinary method. It is also shown that the proposed method successfully selects just the same number of TSPs as that of incoming signals.

This letter presents a scheme to improve the running time of exemplar-based image inpainting, first proposed by Criminisi et al. In the exemplar-based image inpainting, a patch that contains unknown pixels is compared to all the patches in the known region in order to find the best match. This is very time-consuming and hinders the practicality of Criminisi's method to be used in real time. We show that a simple bounding algorithm can significantly reduce number of distance calculations, and thus the running time. Performance of the bounding algorithm is affected by the order of patches that are compared, as well as the order of pixels in a patch. We present pixel and patch ordering schemes that improve the performance of bounding algorithms. Experiments with well-known images used in inpainting literature show that the proposed reordering scheme can reduce running time of the bounding algorithm up to 50%.

Heterogeneous multi-core architectures with CPUs and accelerators attract many attentions since they can achieve power-efficient computing in various areas from low-power embedded processing to high-performance computing. Since the optimal architecture is different from application to application, finding the most suitable accelerator is very important. In this paper, we propose an FPGA-based heterogeneous multi-core platform with custom accelerators for power-efficient computing. Using the proposed platform, we evaluate several applications and accelerators to identify many key requirements of the applications and properties of the accelerators. Such an evaluation is very important to select and optimize the most suitable accelerator according to the requirements of an application to achieve the best performance.

The main contribution of this paper is to show optimal parallel algorithms to compute the sum, the prefix-sums, and the summed area table on two memory machine models, the Discrete Memory Machine (DMM) and the Unified Memory Machine (UMM). The DMM and the UMM are theoretical parallel computing models that capture the essence of the shared memory and the global memory of GPUs. These models have three parameters, the number p of threads, and the width w of the memory, and the memory access latency l. We first show that the sum of n numbers can be computed in $O({nover w}+{nlover p}+llog n)$ time units on the DMM and the UMM. We then go on to show that $Omega({nover w}+{nlover p}+llog n)$ time units are necessary to compute the sum. We also present a parallel algorithm that computes the prefix-sums of n numbers in $O({nover w}+{nlover p}+llog n)$ time units on the DMM and the UMM. Finally, we show that the summed area table of size $sqrt{n} imessqrt{n}$ can be computed in $O({nover w}+{nlover p}+llog n)$ time units on the DMM and the UMM. Since the computation of the prefix-sums and the summed area table is at least as hard as the sum computation, these parallel algorithms are also optimal.

Scheduling plays a key role in MapReduce systems. In this paper, we explore the efficiency of an MapReduce cluster running lots of independent and continuously arriving MapReduce jobs. Data locality and load balancing are two important factors to improve computation efficiency in MapReduce systems for data-intensive computations. Traditional cluster scheduling technologies are not well suitable for MapReduce environment, there are some in-used schedulers for the popular open-source Hadoop MapReduce implementation, however, they can not well optimize both factors. Our main objective is to minimize total flowtime of all jobs, given it's a strong NP-hard problem, we adopt some effective heuristics to seek satisfied solution. In this paper, we formalize the scheduling problem as job selection problem, a load balance aware job selection algorithm is proposed, in task level we design a strict data locality tasks scheduling algorithm for map tasks on map machines and a load balance aware scheduling algorithm for reduce tasks on reduce machines. Comprehensive experiments have been conducted to compare our scheduling strategy with well-known Hadoop scheduling strategies. The experimental results validate the efficiency of our proposed scheduling strategy.