What should be the ultimate form of the cloud computing environment? The solution should have two important features; “Fine-Granularity” and “Participation.” To realize an attractive and feasible solution with these features, we propose a “participating fine-grained cloud computing platform” that a large number of personal or small-company resource suppliers participate in, configure and provide cloud computing on. This enables users to be supplied with smaller units of resources such as computing, memory, content, and applications, in comparison with the traditional Infrastructure as a Service (IaaS). Furthermore, to search for nearby resources efficiently among the many available on the platform, we also propose Resource Breadcrumbs (RBC) as a key technology of our proposed platform to provide in-network guidance capability autonomously for users' queries. RBC allows supplier-nodes to distribute guidance information directed to themselves with dedicated control messages; in addition, the information can be logged along the trail of message from supplier to user. With this distributed information, users can to autonomously locate nearby resources. Distributed management also reduces computational load on the central database and enables a participating fine-grained cloud platform at lower cost.

TV white space (TVWS) brings potential opportunities to relieve the growing spectrum scarcity. Therefore organizations like the FCC have suggested the co-channel deployment of cellular networks (CNs) on condition that a keep-out distance from the protected region of TV receivers is maintained. However the consequent CN interference has not been described. In addition, considering the wide range of TV coverage, it is also inefficient and wasteful not applying the vacant spectra for secondary user (SU) communication by opportunistic access inside the TV coverage zone. In this paper, we first investigate the aggregate interference from CNs outside the protected area to find out how the interference is generated, and then research the available spectrum resource distribution for SUs inside the TV coverage zone under aggregate interference constraints to utilize TVWS more efficiently. Specifically, we model CN in three aspects. A close-form interference probability distribution function (PDF) is proposed. Since the PDF is too complex to analyze, we approximate it as Gaussian and prove the accuracy of our approximation with Kolmogorov-Smirnov test. Then, available spectra maximization is formulated as an optimization problem under both TV and SU receiver outage probability constraints. We find that available spectra demonstrate a volcano-shaped geographical distribution and optimal network-status-aware SU transmit power exists to maximize the spectra. Our analysis reveals the characteristics of interference in TVWS and contributes to the utilization improvement of white space.

Small cell networks have been promoted as an enabling solution to enhance indoor coverage and improve spectral efficiency. Users usually deploy small cells on-demand and pay no attention to global profile in residential areas or offices. The reduction of cell radius leads to dense deployment which brings intractable computation complexity for resource allocation. In this paper, we develop a semi-distributed resource allocation algorithm by dividing small cell networks into clusters with limited inter-cluster interference and selecting a reference cluster for interference estimation to reduce the coordination degree. Numerical results show that the proposed algorithm can maintain similar system performance while having low complexity and reduced information exchange overheads.

We analyze the error performance of coding for ordered random variables with side information at the decoder, where encoder input as well as side information are deliberately extracted from the output of correlated sources. A tight upper bound on error probability is derived for linear encoding, and minimum distance decoding for a binary source and Gaussian distributed side information. Some features caused by the signal extraction are discussed.

Electrostatic discharge (ESD) generators cause electromagnetic (EM) noises not only at ESD tests but also even before and after the tests. This may provide inconsistent test results, but the mechanism has not been well examined. To explain the mechanism qualitatively, we investigated a generation source model of EM noises from an ESD generator in conjunction with the functional control sequences of built-in relay switches and the DC high voltage power supply. To validate this model, we used a magnetic field probe to measure the induced EM noises before, during, and after contact and air discharges in accordance with the corresponding timing of the functional control sequences. As a result, we confirmed that the EM noises are induced when the relay switches operate before and at ESD testing and after ESD tests for both contact and air discharges. In addition, we found that the noise peaks due to contact discharges increase with charge voltages, and the peaks just before and at the testing are relatively larger than the ones after the tests, while the peaks of the induced noises at the air discharge testing do not always increase with charge voltages, but reach a maximum at 3kV. In addition, the peaks of the induced noises at the air discharge testing become smaller than either the peaks just before the testing and those after the tests at charge voltages above 6kV. This suggests that the EM noises just before ESD testing and after the test may cause the EUT to malfunction when air discharge tests with charge voltages over 6kV are conducted. A new control sequence of the built-in relay switch was also proposed for reducing the EM noises after ESD tests, which was validated through noise measurements.

In this paper, we propose a secondary user (SU) resource assignment algorithm for a multi-hop (MH) cognitive radio network to improve the end-to-end throughput. In the MH networks used for spectrum sharing, each SU needs to improve the throughput by taking the primary user (PU) protection into account. For overcoming this problem, we estimate the PU acceptable received power, which is determined by the acknowledgment packet (ACK) power from the PU receiver at each SU. With this estimation, we propose an SU optimal transmit power control algorithm to not only maximize the end-to-end throughput of the SU MH flow but also maintain the considered PU acceptable interference power. In this study, a distributed joint allocation algorithm has been used to solve the optimization problem and to effectively allocate the power of each SU.

In this work, the differential received signal strength based localization problem is addressed. Based on the measurement model, we present the constrained weighted least squares (CWLS) approach, which is difficult to be solved directly due to its nonconvex nature. However, by performing the semidefinite relaxation (SDR) technique, the CWLS problem can be relaxed into a semidefinite programming problem (SDP), which can be efficiently solved using modern convex optimization algorithms. Moreover, the SDR is proved to be tight, and hence ensures the corresponding SDP find the optimal solution of the original CWLS problem. Numerical simulations are included to corroborate the theoretical results and promising performance.

A cloud system is defined as a large scale computer system that contains running high performance computers and responds to a large number of incoming tasks over the Internet. In this paper, we consider the problem to schedule computational jobs efficiently regarding system resource constraint and introduce a cuckoo search (CS) algorithm. Experimental results show that CS outperforms the genetic algorithm in terms of fitness value.

So far, many approaches for detecting code clones have been proposed based on the different degrees of normalizations (e.g. removal of white spaces, tokenization, and regularization of identifiers). Different degrees of normalizations lead to different granularities of source code to be detect as code clones. To investigate how the normalizations impact the code clone detection, this study proposes six approaches for detecting code clones with preprocessing input source files using different degrees of normalizations. More precisely, each normalization is applied to the input source files and then equivalence class partitioning is performed to the files in the preprocessing. After that, code clones are detected from a set of files that are representatives of each equivalence class using a token-based code clone detection tool named CCFinder. The proposed approaches can be categorized into two types, approaches with non-normalization and normalization. The former is the detection of only identical files without any normalization. Meanwhile, the latter category is the detection of identical files with different degrees of normalizations such as removal of all lines containing macros. From the case study, we observed that our proposed approaches detect code clones faster than the approach that uses only CCFinder. We also found the approach with non-normalization is the fastest among the proposed approaches in many cases.

Recently, array speaker products have received attention in the field of consumer electronics, and control technologies for arrayed speaker units, including beamforming and wave field synthesis (WFS), have been developed for various purposes. An important application of these algorithms is focused source reproduction. The focused source reproduction capability is strongly coupled with the array length. The array length is a very important design factor in consumer products, but it is very short in home entertainment systems, compared with ideal WFS systems or theater speaker systems. Therefore, a well-defined measure for the maximum focusing range is necessary for designing an array speaker product. In this paper, a maximum focusable range measure is proposed and is analyzed by simulation of a small array speaker. The analysis results show that the proposed maximum focusable range has properties strongly related to the capability for focused source reproduction.

In this paper, resource-efficient multiple description coding (MDC) multicast is investigated in cognitive radio networks with the consideration of imperfect spectrum sensing and imperfect channel feedback. Our objective is to maximize the system goodput, which is defined as the total successfully received data rate of all multicast users, while guaranteeing the maximum transmit power budget and the maximum average received interference constraint. Owing to the uncertainty of the spectrum state and the non-closed-form expression of the objective function, it is difficult to solve the problem directly. To circumvent this problem, a pretreatment is performed, in which we first estimate the real spectrum state of primary users and then propose a Gaussian approximation for the probability density functions of transmission channel gains to simplify the computation of the objective function. Thereafter, a two-stage resource allocation algorithm is presented to accomplish the subcarrier assignment, the optimal transmit channel gain to interference plus noise ratio (T-CINR) setting, and the transmit power allocation separately. Simulation results show that the proposed scheme is able to offset more than 80% of the performance loss caused by imperfect channel feedback when the feedback error is not high, while keeping the average interference on primary users below the prescribed threshold.

This paper investigates the system-level throughput of non-orthogonal multiple access (NOMA) with a successive interference canceller (SIC) in the cellular downlink assuming proportional fair (PF)-based radio resource (bandwidth and transmission power) allocation. The purpose of this study is to examine the possibility of applying NOMA with a SIC to the systems beyond the 4G cellular system. Both the mean and cell-edge user throughput are important in a real system. PF-based scheduling is known to achieve a good tradeoff between them by maximizing the product of the user throughput among users within a cell. In NOMA with a SIC, the scheduler allocates the same frequency to multiple users simultaneously, which necessitates multiuser scheduling. To achieve a better tradeoff between the mean and cell-edge user throughput, we propose and compare three power allocation strategies among users, which are jointly implemented with multiuser scheduling. Extensive simulation results show that NOMA with a SIC with a moderate number of non-orthogonally multiplexed users significantly enhances the system-level throughput performance compared to orthogonal multiple access (OMA), which is widely used in 3.9 and 4G mobile communication systems.

Device-to-device (D2D) multicast communication is a useful way to improve the communication efficiency of local services. This study considers a scenario of D2D multicast communication in a single frequency network (SFN) system and investigates the frequency resource allocation problem. Firstly, we propose that D2D user equipments (DUEs) do not share frequency with cellular user equipments (CUEs) in the same SFN, but reuse frequency with CUEs in other SFNs, by which the interference between D2D and cellular communications can be avoided. Then, under the principle that two nearest D2D multicast groups cannot reuse the same frequency, the study develops a distance-based fair frequency resource allocation (DFRA) algorithm. The DFRA algorithm ensures control of the interference within a reasonable range and fairly allocate the available frequency resources to the D2D multicast groups. Numerical simulation results show that the proposed resource allocation algorithm is effective in improving the data rate and reducing the outage probability for D2D communications.

In this paper, we consider distributed estimation where the measurement at each of the distributed sensor nodes is quantized before being transmitted to a fusion node which produces an estimate of the parameter of interest. Since each quantized measurement can be linked to a region where the parameter is found, aggregating the information obtained from multiple nodes corresponds to generating intersections between the regions. Thus, we develop estimation algorithms that seek to find the intersection region with the maximum likelihood rather than the parameter itself. Specifically, we propose two practical techniques that facilitate fast search with significantly reduced complexity and apply the proposed techniques to a system where an acoustic amplitude sensor model is employed at each node for source localization. Our simulation results show that our proposed algorithms achieve good performance with reasonable complexity as compared with the minimum mean squared error (MMSE) and the maximum likelihood (ML) estimators.

In this paper, we consider the lossy source coding problem with delayed side information at the decoder. We assume that delay is unknown but the maximum of delay is known to the encoder and the decoder, where we allow the maximum of delay to change with the block length. In this coding problem, we show an upper bound and a lower bound of the rate-distortion (RD) function, where the RD function is the infimum of rates of codes in which the distortion between the source sequence and the reproduction sequence satisfies a certain distortion level. We also clarify that the upper bound coincides with the lower bound when maximums of delay per block length converge to a constant. Then, we give a necessary and sufficient condition in which the RD function is equal to that for the case without delay. Furthermore, we give an example of a source which does not satisfy this necessary and sufficient condition.

The mobile cloud computing (MCC) paradigm is aimed at integrating mobile devices with cloud computing. In the client-server architecture of MCC, mobile devices offload tasks to the cloud to utilize the computation and storage resources of data centers. However, due to the rapid increase in the traffic demand and complexity of mobile applications, service providers have to continuously upgrade their infrastructures at great expense. At the same time, modern mobile devices have greater resources (communication, computation, and sensing), and these resources are not always fully utilized by device users. Therefore, mobile devices, from time to time, encounter other devices that could provide resources to them. Because the amount of such resources has increased with the number of mobile devices, researchers have begun to consider making use of these resources, located at the “edge” of mobile networks, to increase the scalability of future information networks. This has led to a cooperation based architecture of MCC. This paper reports the concept and design of an resource sharing mechanism that utilize resources in mobile devices through opportunistic contacts between them. Theoretical models and formal definitions of problems are presented. The efficiency of the proposed mechanism is validated through formal proofs and extensive simulation.

Network selection is one of the hot issues in the fusion of heterogeneous wireless networks (HWNs). However, most of previous works only consider selecting single-access network, which wastes other available network resources, rarely take account of multi-access. To make full utilization of available coexisted networks, this paper proposes a novel multi-access selection algorithm based on joint utility optimization for users with multi-mode terminals. At first, the algorithm adopts exponential smoothing method (ESM) to get smoothed values of received signal strength (RSS). Then we obtain network joint utility function under the constraints of bandwidth and number of networks, with the consideration of trade-off between network benefit and cost. At last, Lagrange multiplier and dual optimization methods are used to maximize joint utility. Users select multiple networks according to the optimal association matrix of user and network. The simulation results show that the proposed algorithm can optimize network joint utility, improve throughput, effectively reduce vertical handoff number, and ensure Quality of Service (QoS).

Despite the increasing use of mobile computing, exploiting its full potential is difficult due to its inherent characteristics such as error-prone transmission channels, diverse node capabilities, frequent disconnections and mobility. Mobile Cloud Computing (MCC) is a paradigm that is aimed at overcoming previous problems through integrating mobile devices with cloud computing. Mobile devices, in the traditional client-server architecture of MCC, offload their tasks to the cloud to utilize the computation and storage resources of data centers. However, along with the development of hardware and software technologies in mobile devices, researchers have begun to take into consideration local resource sharing among mobile devices themselves. This is defined as the cooperation based architecture of MCC. Analogous to the conventional terminology, the resource platforms that are comprised of surrounding surrogate mobile devices are called local resource clouds. Some researchers have recently verified the feasibility and benefits of this strategy. However, existing work has neglected an important issue with this approach, i.e., how to construct local resource clouds in dynamic mobile wireless networks. This paper presents the concept and design of a local resource cloud that is both energy and time efficient. Along with theoretical models and formal definitions of problems, an efficient heuristic algorithm with low computational complexity is also presented. The results from simulations demonstrate the effectiveness of the proposed models and method.

Recently, radar resource management of multifunction radar is a challenging issue in electronically scanned array radar technology. This paper deals with radar beam scheduling, which is a core issue of radar resource management. This paper proposed stochastic scheduler algorithm using Simulated Annealing (SA) and Hybrid scheduler algorithm which automatically selects two different types of schedulers according to the radar load: Rule based scheduler using modified Butler algorithm for underload situations and SA based scheduler for overload situations. The proposed algorithms are evaluated in terms of scheduling latency, the number of scheduled tasks, and time complexity. The simulation results show that the performance of rule based scheduler is seriously degraded in overload situation. However, SA based scheduler and Hybrid scheduler have graceful performance degradation in overload situation. Compared with rule based scheduler, SA based scheduler and Hybrid scheduler can schedule many more tasks on time for the same operation duration in the overload situation. Even though their time complex is relatively high, it can be applied to real applications if the parameters are properly controlled. Especially, Hybrid scheduler has an advantage of low time complexity with good performance.

This paper proposes a sound source orientation estimation method that is suitable for a distributed microphone arrangement. The proposed method is based on orientation-extended beamforming (OEBF), which has four features: (a) robustness against reverberations, (b) robustness against noises, (c) free arrangements of microphones and (d) feasibility for real-time processing. In terms of (a) and (c), since OEBF is based on a general propagation model using transfer functions (TFs) that include all propagation phenomena such as reflections and diffractions, OEBF causes no model errors for the propagation phenomena, and is applicable to arbitrary microphone arrangements. Regarding (b), OEBF overcomes noise effects by incorporating three additional processes (Amplitude extraction, time-frequency mask and histogram integration) that are also proposed in this paper. As for (d), OEBF is executable in real-time basis as the execution process is the same as usual beamforming processes. A numerical experiment was performed to confirm the theoretical validity of OEBF. The results showed that OEBF was able to estimate sound source positions and orientations very precisely. Practical experiments were carried out using a 96-channel microphone array in real environments. The results indicated that OEBF worked properly even under reverberant and noisy environments and the averaged estimation error was given only 4°.