A dual-core spot size converter (DC-SSC) is integrated with a lateral grating assisted lateral co-directional coupler (LGLC) tunable laser by using no additional complicated fabrication processes. The excess loss due to the DC-SSC is only 0.5 dB, and narrow full width half maximums (FWHMs) of vertical and horizontal far-field patterns (FFPs) produced by the laser are about 25° and 20°. This integration causes no degradations of the performance of the LGLC laser; in other words, it maintains good lasing characteristics, namely, wide tuning range of over 68 nm and SMSR of over 35 dB in the C-band under a 50 semi-cooled condition.

We present the theory and experiment of metal-cavity nanolasers and nanoLEDs flip-chip bonded to silicon under electrical injection at room temperature. We first review the recent progress on micro- and nanolasers. We then present the design rule and our theoretical model. We show the experimental results of our metal-cavity surface-emitting microlasers and compare with our theoretical results showing an excellent agreement. We found the important contributions of the nonradiative recombination currents including Auger recombination, surface recombination, and leakage currents. Finally, experimental demonstration of electrical injection nanoLEDs toward subwavelength nanoscale lasers is reported.

As anonymity increasingly becomes a necessary and legitimate aim in many applications, a number of anonymous authentication schemes have been suggested over the years. Among the many schemes is Lee and Kwon's password-based authentication scheme for wireless environments. Compared with previous schemes, Lee and Kwon's scheme not only improves anonymity by employing random temporary IDs but also provides user-friendliness by allowing human-memorable passwords. In this letter, we point out that Lee and Kwon's scheme, despite its many merits, is vulnerable to off-line password guessing attacks and a forgery attack. In addition, we show how to eliminate these vulnerabilities.

In this paper, we introduce an approach of service adaptation for behavior mismatching services using pushdown model checking. This approach uses pushdown systems as model of adaptors so that capturing non-regular behavior in service interactions is possible. Also, the use of pushdown model checking integrates adaptation and verification. This guarantees that an adaptor generated by our approach not only solves behavior mismatches but also satisfies usual verification properties if specified. Unlike conventional approaches, we do not count on specifications of adaptor contracts but take only information from behavior interfaces of services and perform fully automated adaptor generation. Three requirements relating to behavior mismatches, unbounded messages, and branchings are retrieved from behavior interfaces and used to build LTL properties for pushdown model checking. Properties for unbounded messages, i.e., messages sent and received arbitrary multiple times, are especially addressed since it characterizes non-regular behavior in service composition. This paper also shows some experimental results from a prototype tool and provides directions for building BPEL adaptors from behavior interface of generated adaptor. The results show that our approach does solve behavior mismatches and successfully capture non-regular behavior in service composition under the scale of real service applications.

In this letter, we provide an asymptotic error rate performance evaluation of space-time block codes from coordinate interleaved orthogonal designs (STBCs-CIODs), especially in shadowed Rayleigh fading channels. By evaluating a simplified probability density function (PDF) of Rayleigh and Rayleigh-lognormal channels affecting the STBC-CIOD system, we derive an accurate closed-form approximation for the tight upper and lower bounds on the symbol error rate (SER). We show that shadowing asymptotically affects coding gain only, and conclude that an increase in diversity order under shadowing causes slower convergence to asymptotic bound due to the relatively larger loss of coding gain. By comparing the derived formulas and Monte-Carlo simulations, we validate the accuracy of the theoretical results.

The conventional semi-orthogonal user pairing algorithm in uplink virtual MIMO systems can be used to improve the total system throughput but it usually fails to maintain good throughput performance for users experiencing relatively poor channel conditions. A novel user paring algorithm is presented in this paper to solve this fairness issue. Based on our analysis of the MMSE receiver, a new criterion called “inverse selection” is proposed for use in conjunction with the semi-orthogonal user selection. Simulation results show that the proposed algorithm can significantly improve the throughput of users with poor channel condition at only a small reduction of the overall throughput.

In the MIMO-OFDM multiple access channel (MIMO-OFDM-MAC) uplink scenario, the base station decides the uplink parameters for multiple users based on channel state information (CSI) from each user in the system. The performance of MIMO-OFDM-MAC systems can be significantly improved by using an adaptive transmission and resource allocation schemes which consider the correlation effect of line of sight (LOS) and non line of sight (NLOS) channel conditions for different users in the system. A lot of papers have been published on resource allocation schemes for MIMO-OFDM systems. However, most of these resource allocation schemes have been considered for MIMO-OFDMA systems, where users are separated in the frequency domain and each user uses the same uplink and downlink channels in the same channel conditions. On the other hand, in the mulituser MIMO-OFDM systems, more than one user can be assigned the same frequency and channel conditions for the MIMO-OFDM broadcast channel (downlink) and MIMO-OFDM-MAC channel (uplink) are not the same. Therefore, the same resource allocation schemes for the conventional MIMO-OFDM systems can not be applied to multiuser MIMO-OFDM systems with different uplink and downlink channel conditions. Until now, most of the resource allocation schemes have been considered only for downlink MIMO-OFDM broadcast (MIMO-OFDM-BC) channel and very few papers tackle the fairness among users. Moreover, no paper considers a scheme to realize proportional data rate fairness among users in the MIMO-OFDM-MAC condition. In this paper, we propose a proportional data rate fairness resource allocation scheme with adaptive bit loading for MIMO-ODFM-MAC systems by considering the correlation effects of LOS and NLOS channel conditions in both spatial and frequency domains. Computer simulation results show that the proposed scheme can give larger system capacity while maintaining the proportional data rate fairness requirements among users in the system under the constraint of total transmit power and predetermined target BER.

We propose an optimal access-point (AP) selection algorithm for maximizing the aggregated throughput of each AP (system throughput) while preserving newly arrived-user throughput in multi rate WLAN system. In our algorithm, newly arrived users cooperate with a wireless local area network (WLAN) system they are trying to use, i.e., they are willing to move toward an appropriate AP before the newly arrived user connects to AP. To select the AP by using our AP selection algorithm, the newly arriving users request two novel parameter values, “the minimum acceptable throughput” with which newly arrived users can be satisfied and “the minimum movable distance” in which a user can move to an appropriate AP. While preserving these conditions, we maximize system throughput. When users cannot obtain a throughput greater than “the minimum acceptable throughput” with our proposed AP selection algorithm, they are rejected. Because, if users use streaming applications, which have strict bandwidth demands, with a very low bit-rate connection, they will not be satisfied. Thus, the newly arrived users having low bit-rate connection may be allowed to be rejected before the newly arrived user connects. In this paper, we show the optimal AP by using theoretical proof. We discuss the effectiveness of our proposed AP selection algorithm by using numerical analysis. We also clarify and analyze the characteristics of system throughput. Moreover, we show that a newly arrived user can select the movable distance and acceptable throughput by using examples from graphs depicting every position of newly arrived users. By using the graphs, we also show the relationship between the two parameters (the movable distance and the acceptable throughput) and the optimal AP, and the relationship between the two parameters and optimal system throughput when the movable distance and acceptable throughput are variable.

We propose and implement a cloud architecture of virtual Trusted Platform Modules (TPMs) to improve the usability of TPMs. In this architecture, virtual TPMs can be obtained from the TPM cloud on demand. Hence, the TPM functionality is available for applications that do not have physical TPMs in their local platforms. Moreover, the TPM cloud allows users to access their keys and data in the same virtual TPM even if they move to untrusted platforms. The TPM cloud is easy to access for applications in different languages since cloud computing delivers services in standard protocols. The functionality of the TPM cloud is demonstrated by applying it to implement the Needham-Schroeder public-key protocol for web authentications, such that the strong security provided by TPMs is integrated into high level applications. The chain of trust based on the TPM cloud is discussed and the security properties of the virtual TPMs in the cloud is analyzed.

Mirrored serpentine microstrip lines are proposed for a parallel high speed digital signaling to reduce the peak far-end crosstalk (FEXT) voltage. Mirrored serpentine microstrip lines consist of two serpentine microstrip lines, each one equal to a conventional normal serpentine microstrip line. However, one serpentine microstrip line of the mirrored serpentine microstrip lines is flipped in the length direction, and thus, two serpentine microstrip lines face each other. Time domain reflectometry measurements show that the peak FEXT voltage of the mirrored serpentine microstrip lines is reduced by 56.4% of that of conventional microstrip lines and 30.0% of that of conventional normal serpentine microstrip lines.

Virtualization technologies are widely deployed in data centers to improve system utilization. However, they increase the workload for operators, who have to manage the structure of virtual networks in data centers. A virtual-network management system which automates the integration of the configurations of the virtual networks is provided. The proposed system collects the configurations from server virtualization platforms and VLAN-supported switches, and integrates these configurations according to a newly developed XML-based management information model for virtual-network configurations. Preliminary evaluations show that the proposed system helps operators by reducing the time to acquire the configurations from devices and correct the inconsistency of operators' configuration management database by about 40 percent. Further, they also show that the proposed system has excellent scalability; the system takes less than 20 minutes to acquire the virtual-network configurations from a large scale network that includes 300 virtual machines. These results imply that the proposed system is effective for improving the configuration management process for virtual networks in data centers.

Cooperative relaying, while effective in mitigating fading effects, might reduce the overall network throughput since its overhead such as additional time slot and frequency band can be significant. In order to overcome this problem, this paper proposes a superposition coding based cooperative relay scheme to provide reliable transmission with little or no overhead. This scheme exploits the superimposed messages for users in the network to achieve the simultaneous transmission of two or more independent data streams. This scheme reduces the number of transmission phases to the same as that of conventional cooperative relay schemes. The symbol error performance of the proposed scheme is analyzed and simulated.

Information diffusion analysis in social networks is of significance since it enables us to deeply understand dynamic social interactions among users. In this paper, we introduce approaches to discovering information diffusion process in social networks based on process mining. Process mining techniques are applied from three perspectives: social network analysis, process discovery and community recognition. We then present experimental results by using a real-life social network data. The proposed techniques are expected to employ as new analytical tools in online social networks such as blog and wikis for company marketers, politicians, news reporters and online writers.

This letter presents a method for obtaining an exact average symbol error rate (ASER) of M-phase shift keying (M-PSK) transmission for the Nth best opportunistic amplify-and-forward (OAF) relay systems over Rayleigh fading channels. This approach begins with deriving the relay selection probability when a relay is selected as the Nth best one with respect to the received signal-to-noise ratio. We then derive the modified moment generating function (MGF) for the Nth best OAF relay systems by taking the given Nth best-relay selection probability into consideration. Based on the modified MGF, we derive the exact ASER which accurately explicates the Nth best OAF relay system characteristics. Simulation results confirm the exactness of the analysis results for M-PSK transmission with respect to the number of relays, the Nth best relay selection, and the relay position.

Clickstreams in users' navigation logs have various data which are related to users' web surfing. Those are visit counts, stay times, product types, etc. When we observe these data, we can divide clickstreams into sub-clickstreams so that the pages in a sub-clickstream share more contexts with each other than with the pages in other sub-clickstreams. In this paper, we propose a method which extracts more informative rules from clickstreams for web page recommendation based on genetic programming and association rules. First, we split clickstreams into sub-clickstreams by contexts for generating more informative rules. In order to split clickstreams in consideration of context, we extract six features from users' navigation logs. A set of split rules is generated by combining those features through genetic programming, and then informative rules for recommendation are extracted with the association rule mining algorithm. Through experiments, we verify that the proposed method is more effective than the other methods in various conditions.

This paper presents an efficient algorithm, NEAR, that allows sensor nodes to acquire their off-duty eligibility. Any node only needs to calculate the coverage degrees of the intersections on its sensing boundary, and cooperates with its neighbors to know if it is redundant or not. The computing complexity of NEAR is only O(nlogn).

This letter considers a dual-hop multiuser MIMO amplify-and-forward relay broadcast system with multi-antenna nodes. A unified scheme is addressed to jointly optimize the linear transceiver based on the sum mean-square error (MSE) and the sum rate criterion. The solutions are iteratively obtained by deriving the gradients of the objective functions for a gradient descent algorithm. Simulation results demonstrate the performance improvements in terms of the BER and the sum rate.

In this paper, we propose a joint diversity algorithm for error-rate minimization in multi-user spatial multiplexing (SM) systems with block diagonalization (BD)-precoding. The proposed algorithm adapts or selects the user set, transmit antenna subset, and the number of streams by an exhaustive search over the available resources. The proposed algorithm makes use of the multi-user diversity (MUD) and the spatial diversity gains as well as the array gain through selecting the best set. Exhaustive search, however, imposes a heavy burden in terms of computational complexity which exponentially increases with the size of the total number of users, streams, and transmit antennas. For complexity reduction, we propose two suboptimal algorithms which reduce the search space by first selecting the best user or by both selecting the best user and fixing the number of streams. Simulation results show that the proposed algorithms improve error probability over the conventional algorithm due to their diversity improvement and the signal-to-noise ratio (SNR) gains over the conventional algorithm. We also show that the suboptimal algorithms significantly reduce the computational complexity over exhaustive search with low-SNR loss.

of late, many researchers have been interested in sparse representation of signals and its applications such as Compressive Sensing in Cognitive Radio (CR) networks as a way of overcoming the issue of limited bandwidth. Compressive sensing based wideband spectrum sensing is a novel approach in cognitive radio systems. Also in these systems, using spatial-frequency opportunistic reuse is emerged interestingly by constructing and deploying spatial-frequency Power Spectral Density (PSD) maps. Since the CR sensors are distributed in the region of support, the sensed PSD by each sensor should be transmitted to a master node (base-station) in order to construct the PSD maps in space and frequency domains. When the number of sensors is large, this data transmission which is required for construction of PSD map can be challenging. In this paper, in order to transmit the CR sensors' data to the master node, the compressive sensing based scheme is used. Therefore, the measurements are sampled in a lower sampling rate than of the Nyquist rate. By using the proposed method, an acceptable PSD map for cognitive radio purposes can be achieved by only 30% of full data transmission. Also, simulation results show the robustness of the proposed method against the channel variations in comparison with classical methods. Different solution schemes such as Basis Pursuit, Lasso, Lars and Orthogonal Matching Pursuit are used and the quality performance of them is evaluated by several simulation results over a Rician channel with respect to several different compression and Signal to Noise Ratios. It is also illustrated that the performance of Basis Pursuit and Lasso methods outperform the other compression methods particularly in higher compression rates.

We propose a network coordinated opportunistic beamforming (NC-OBF) protocol for downlink K-cell networks with M-antenna base stations (BSs). In the NC-OBF scheme, based on pseudo-randomly generated BF vectors, a user scheduling strategy is introduced, where each BS opportunistically selects a set of mobile stations (MSs) whose desired signals generate the minimum interference to the other MSs. Its performance is then analyzed in terms of degrees-of-freedom (DoFs). As our achievability result, it is shown that KM DoFs are achievable if the number N of MSs in a cell scales at least as SNRKM-1, where SNR denotes the received signal-to-noise ratio. Furthermore, by deriving the corresponding upper bound on the DoFs, it is shown that the NC-OBF scheme is DoF-optimal. Note that the proposed scheme does not require the global channel state information and dimension expansion, thereby resulting in easier implementation.