Context awareness is one of the ultimate goals of ubiquitous computing, and spatial information plays an important role in building context awareness. In this paper, we propose a new interoperable spatial information model, which is based on ucode relation (ucR) and Place Identifier (PI), for realizing ubiquitous spatial infrastructure. In addition, we propose a design environment for spatial information database using our model. Our model is based on ucode and its relation. ucode is 128 bits number and the number itself has no meaning. Hence, it is difficult to manage the relation between ucodes without using a tool. Our design environment provides to describe connection between each ucode visually and is able to manipulate data using the target space map interactively. To evaluate the proposed model and environment, we designed three spaces using our tool. In addition, we developed a web application using our spatial model. From evaluation, we have been showed that our model is effective and our design environment is useful to develop our spatial information model.

To improve Last-Level Cache (LLC) management, numerous approaches have been proposed requiring additional hardware budget and increased overhead. A number of these approaches even change the organization of the existing cache design. In this letter, we propose Adaptive Insertion and Promotion (AIP) policies based on Least Recently Used (LRU) replacement. AIP dynamically inserts a missed line in the middle of the cache list and promotes a reused line several steps left, realizing the combination of LRU and LFU policies deliberately under a single unified scheme. As a result, it benefits workloads with high locality as well as with many frequently reused lines. Most importantly, AIP requires no additional hardware other than a typical LRU list, thus it can be easily integrated into the existing hardware with minimal changes. Other issues around LLC such as scans, thrashing and dead lines are all explored in our study. Experimental results on the gem5 simulator with SPEC CUP2006 benchmarks indicate that AIP outperforms LRU replacement policy by an average of 5.8% on the misses per thousand instructions metric.

The present paper introduces a prototype design and experimental results for a multi-user MIMO linear precoding system. A base station and two mobile stations are implemented by taking full advantage of the software-defined radio. The base station consists of general purpose signal analyzers and signal generators controlled by a personal computer. Universal software radio peripherals are used as mobile stations. Linear spatial precoding and a simple two-way channel estimation technique are adopted in this experimental system. In-lab and field transmission experiments are carried out, and the bit error rate performance is evaluated. The impact of the channel estimation error under average channel gain discrepancy between two mobile stations is analyzed through computer simulations. Channel estimation error is shown to have a greater influence on the mobile station with the greater average channel gain.

This letter proposes a multiuser switched scheduling scheme with per-user threshold and post user selection and provides a generic analytical framework for determining the optimal feedback thresholds. The proposed scheme applies an individual feedback threshold for each user rather than a single common threshold for all users to achieve some capacity gain due to the flexibility of threshold selection as well as a lower scheduling outage probability. In addition, since scheduling outage may occur with a non-negligible probability, the proposed scheme employs post user selection in order to further improve the ergodic capacity, where the user with the highest potential for a higher channel quality than other users is selected. Numerical and simulation results show that the capacity gain by post user selection is significant when random sequence is used.

This paper introduces new FPGA design of user-monitoring system for power management of PC display. From the camera readings the system detects whether the user looks at the screen or not and produces signals to control the display backlight. The system provides over 88% eye detection accuracy at 8f/s image processing rate. We describe new eye-tracking algorithm and hardware and present the results of its experimental evaluation in prototype display power management system.

This paper presents an algorithmic approach to acquiring the influencing relationships among users by discovering implicit influencing group structure from smartphone usage. The method assumes that a time series of users' application downloads and activations can be represented by individual inter-personal influence factors. To achieve better predictive performance and also to avoid over-fitting, a latent feature model is employed. The method tries to extract the latent structures by monitoring cross validating predictive performances on approximated influence matrices with reduced ranks, which are generated based on an initial influence matrix obtained from a training set. The method adopts Nonnegative Matrix Factorization (NMF) to reduce the influence matrix dimension and thus to extract the latent features. To validate and demonstrate its ability, about 160 university students voluntarily participated in a mobile application usage monitoring experiment. An empirical study on real collected data reveals that the influencing structure consisted of six influencing groups with two types of mutual influence, i.e. intra-group influence and inter-group influence. The results also highlight the importance of sparseness control on NMF for discovering latent influencing groups. The obtained influencing structure provides better predictive performance than state-of-the-art collaborative filtering methods as well as conventional methods such as user-based collaborative filtering techniques and simple popularity.

Software product-line engineering is the successful reuse of technology when applied to component-based software development. The main concept and structure of this technology is developing reusable core assets by applying commonality and variability, and then developing new software reusing these core assets. Recently, the emergence of service-oriented environments, called SOA, has provided flexible reuse environments by reusing pre-developed component structure as service units; this is platform-independent and can integrate into heterogeneous environments. The core asset of an SOA is the service. Therefore, we can increase the reusability of an SOA by combining it with the concept of a product-line. These days, there exists research that combines SOA and product-lines, taking into account reusability. However, current research does not consider the interaction between the provider and consumer in SOA environments. Furthermore, this research tends to focus on more fragmentary aspects of product-line engineering, such as modeling and proposing variability in services. In this paper, we propose a mechanism named 2-Level SOA, including a supporting environment. This proposed mechanism deploys and manages the reusable service. In addition, by reusing and customizing this reusable service, we can develop and generate new services. Our proposed approach provides a structure to maximize the flexibility of SOA, develops services that consider systematic reuse, and constructs service-oriented applications by reusing this pre-developed reusable service. Therefore, our approach can increase both efficiency and productivity when developing service-oriented applications.

In this letter, we argue that user resources will be still useful in the information-centric network (ICN). From this point of view, we first examine how P2P utilizing user resources looks like in ICN. Then, we identify challenging research issues to utilize user resources in ICN.

This letter presents a flexible signal structure supporting localization service for time domain synchronous OFDM (TDS-OFDM) in multi-service transmission applications. Localization is treated as one specific service and the corresponding data is allocated within the physical layer pipe (PLP) of the first subframe. The concept of variable sub-carrier spacing to combat Doppler spread is also introduced for the localization service. Simulation results indicate that the proposed scheme outperforms the conventional scheme and at the same time achieves high positioning accuracy.

We propose an optimization method for power distribution network that explicitly deals with timing. We have found and focused on the facts that decoupling capacitance (decap) does not necessarily improve gate delay depending on the switching timing within a cycle and that power wire expansion may locally degrade the voltage. To resolve the above facts, we devised an efficient sensitivity calculation of timing to decap size and power wire width for guiding optimization. The proposed method, which is based on statistical noise modeling and timing analysis, accelerates sensitivity calculation with an approximation and adjoint sensitivity analysis. Experimental results show that decap allocation based on the sensitivity analysis efficiently minimizes the worst-case circuit delay within a given decap budget. Compared to the maximum decap placement, the delay improvement due to decap increases by 3.13% even while the total amount of decaps is reduced to 40%. The wire sizing with the proposed method also efficiently reduces required wire resource necessary to attain the same circuit delay by 11.5%.

In order to reduce cost and improve efficiency, many data centers adopt virtualization solutions. The advent of virtualization allows multiple virtual machines hosted on a single physical server. However, this poses new challenges for resource management. Web workloads which are dominant in data centers are known to vary dynamically with time. In order to meet application's service level agreement (SLA), how to allocate resources for virtual machines has become an important challenge in virtualized server environments, especially when dealing with fluctuating workloads and complex server applications. User experience is an important manifestation of SLA and attracts more attention. In this paper, the SLA is defined by server-side response time. Traditional resource allocation based on resource utilization has some drawbacks. We argue that dynamic resource allocation directly based on real-time user experience is more reasonable and also has practical significance. To address the problem, we propose a system architecture that combines response time measurements and analysis of user experience for resource allocation. An optimization model is introduced to dynamically allocate the resources among virtual machines. When resources are insufficient, we provide service differentiation and firstly guarantee resource requirements of applications that have higher priorities. We evaluate our proposal using TPC-W and Webbench. The experimental results show that our system can judiciously allocate system resources. The system helps stabilize applications' user experience. It can reduce the mean deviation of user experience from desired targets.

The accuracy of non-rigid 3D face recognition is highly influenced by the capability to model the expression deformations. Given a training set of non-neutral and neutral 3D face scan pairs from the same subject, a set of Fourier series coefficients for each face scan is reconstructed. The residues on each frequency of the Fourier series between the finely aligned pairs contain the expression deformation patterns and PCA is applied to learn these patterns. The proposed expression deformation model is then built by the eigenvectors with top eigenvalues from PCA. Recognition experiments are conducted on a 3D face database that features a rich set of facial expression deformations, and experimental results demonstrate the feasibility and merits of the proposed model.

Structured quasi-cyclic low-density parity-check (QC-LDPC) codes have been adopted in many wireless communication standards, such as WiMAX, Wi-Fi and WPAN. To completely support the variable code rate (multi-rate) and variable code length (multi-length) implementation for universal applications, the partial-parallel layered LDPC decoder architecture is straightforward and widely used in the decoder design. In this paper, we propose a high parallel LDPC decoder architecture for WiMAX system with dedicated ASIC design. Different from the block by block decoding schedule in most partial-parallel layered architectures, all the messages within each layer are updated simultaneously in the proposed fully-parallel layered decoder architecture. Meanwhile, the message updating is separated into bit-serial style to reduce hardware complexity. A 6-bit implementation is adopted in the decoder chip, since simulations demonstrate that 6-bit quantization is the best trade-off between performance and complexity. Moreover, the two-layer concurrent processing technique is proposed to further increase the parallelism for low code rates. Implementation results show that the decoder chip saves 22.2% storage bits and only takes 2448 clock cycles per iteration for all the code rates defined in WiMAX standard. It occupies 3.36 mm2 in SMIC 65 nm CMOS process, and realizes 1056 Mbps throughput at 1.2 V, 110 MHz and 10 iterations with 115 mW power occupation, which infers a power efficiency of 10.9 pJ/bit/iteration. The power efficiency is improved 63.6% in normalized comparison with the state-of-art WiMAX LDPC decoder.

We present a privacy preserving method based on inserting dummy data into original data on the data structure called Zero-suppressed BDDs (ZDDs). Our task is distributed itemset mining, which is frequent itemset mining from horizontally partitioned databases stored in distributed places called sites. We focus on the fundamental case in which there are two sites and each site has a database managed by its owner. By dividing the process of distributed itemset mining into the set union and the set intersection, we show how to make the operations secure in the sense of undistinguishability of data, which is our criterion for privacy preserving based on the already proposed criterion, p-indistinguishability. Our method conceals the original data in each operation by inserting dummy data, where ZDDs, BDD-based directed acyclic graphs, are adopted to represent sets of itemsets compactly and to implement the set operations in constructing the distributed itemset mining process. As far as we know, this is the first technique which gives a concrete representation of sets of itemsets and an implementation of set operations for privacy preserving in distributed itemset mining. Our experiments show that the proposed method provides undistinguishability of dummy data. Furthermore, we compare our method with Secure Multiparty Computation (SMC), which is one of the well-known techniques of secure computation.

The globalization of commerce has increased the importance of retrieving and updating complex and distributed information efficiently. Web services currently show that the most promise for building distributed application systems and model-driven architecture is a new approach to developing such applications. The expanding scale and complexity of enterprise information systems (EISs) under distributed computing environments has made sharing and exchanging data particularly challenging. Data services are applications tailored specifically for information oriented tasks to deal with business service requirements, and are heavily dependent on the distributed architecture of consumer data processing. The implementation of a data service can eliminate inconsistency among various application systems in the exchange of data. This paper proposes a data-oriented model-driven developmental framework to deal with these issues, in which a platform independent model (PIM) is divided into a service model, a logic data model, and a service composition model. We also divide a platform specific model (PSM) into a physical data model and a data service model. In this development method, we define five meta-models and outline a set of rules governing the transformation from PIMs into PSMs. A code generator is also included to transform each PSM into the application code. We include a case study to demonstrate the feasibility and merits of the proposed development framework with a case study.

Ranking the encrypted documents stored on secure cloud computing servers is becoming prominent with the expansion of the encrypted data collection. In our work, order preserving encryption is employed to pre-rank the encrypted documents. Paillier's additive homomorphic encryption is used to re-rank the top pre-ranked documents of some considerate scale.

A multiuser precoding algorithm based on matching weighted signal-to-leakage-and-noise ratio (SLNR) is proposed for multiuser MIMO downlink systems. In the proposed algorithm, the matching weight factor is selected based on the effective channel gain, and the leakage power caused by each user is weighted by the factor. The precoding vector is obtained by maximizing the matching weighted SLNR. Simulation results show the superiority of the proposed scheme in terms of bit error rate over the conventional SLNR schemes.

In this paper, we propose a decentralized strategy to find out the linear precoding matrices for a two-hop multiuser relay communication system. From a game-theoretic perspective, we model the source allocation process as a strategic noncooperative game for fixing relay precoding matrix and the multiuser interference treating as additive colored noise. Alternately, from the global optimization perspective, we prove that the optimum relay precoding matrix follows the transceiver Winner filter structure for giving a set of source transmit matrices. Closed-form solutions are finally obtained by using our proposed joint iterative SMSE algorithm and numerical results are provided to give insights on the proposed algorithms.

In this paper, we focus on the cancellation of interference among Destination Users (DU's) and the improvement of achievable sum rate of the nonregenerative multiuser Multiple-Input Multiple-Output (MIMO) relay downlink system. A novel design method of transmit weight is proposed to successively eliminate the interference among DU's, each of which is equipped with multiple receive antennas. We firstly investigate the transmit weight design for the Amplify-and-Forward (AF) relay scheme where the Relay Station (RS) just retransmits the received signals from Base Station (BS), then extend it to the joint design scheme of transmit weights at the both BS and RS. In the proposed joint design scheme, through the comparison of lower bound of achievable rate, an effective DU selection algorithm is proposed to generate the transmit weight at the RS and obtain the multiuser diversity. Dirty Paper Coding (DPC) technique is employed to remove the interference among DU's and ensures the achievable rate of downlink. Theoretical derivation and simulation results demonstrate the effectiveness of the proposed scheme in obtaining the achievable rate performance and BER characteristics.

In this paper, low-complexity generalized singular value decomposition (GSVD) based beamforming schemes are proposed for a cognitive radio (CR) network in which multiple secondary users (SUs) with multiple antennas coexist with multiple primary users (PUs). In general, optimal beamforming, which suppresses the interference caused at PUs to below a certain threshold and maximizes the signal-to-interference-plus-noise ratios (SINRs) of multiple SUs simultaneously, requires a complicated iterative optimization process. To overcome the computational complexity, we introduce a signal-to-leakage-plus-noise ratio (SLNR) maximizing beamforming scheme in which the weight can be obtained by using the GSVD algorithm, and does not require any iterations or matrix squaring operations. Here, to satisfy the leakage constraints at PUs, two linear methods, zero forcing (ZF) preprocessing and power allocation, are proposed.