The minimized assumption generation has been recognized as an important improvement of the assume-guarantee verification method in order to generate minimal assumptions. The generated minimal assumptions can be used to recheck the whole component-based software at a lower computational cost. The method is not only fitted to component-based software but also has a potential to solve the state space explosion problem in model checking. However, the computational cost for generating the minimal assumption is very high so the method is difficult to be applied in practice. This paper presents an optimization as a continuous work of the minimized assumption generation method in order to reduce the complexity of the method. The key idea of this method is to find a smaller assumption in a sub-tree of the search tree containing the candidate assumptions using the depth-limited search strategy. With this approach, the improved method can generate assumptions with a lower computational cost and consumption memory than the minimized method. The generated assumptions are also effective for rechecking the systems at much lower computational cost in the context of software evolution. An implemented tool supporting the improved method and experimental results are also presented and discussed.

Code clones are duplicated or similar code fragments, and they have been known as major entities affecting the software maintainability. Sometimes there are “co-changes” in pair of code clones: when a code fragment is changed, the clone of the fragment is also changed. Such a co-change is one of key event to discuss the successful management of code clone. This paper analyzes the trends of co-changed code clones by using the length and the content of code clones. The empirical results show that: (1) there would be a specific length of clone to be mostly co-changed (around 60-100 tokens), and (2) code clones without any “control flow keywords” have a higher possibility to be co-changed than the others.

Discrete-Time fractional Brownian motion (DFBM) and its increment process, called discrete-time fractional Gaussian noise (DFGN), are usually used to describe natural and biomedical phenomena. These two processes are dominated by one parameter, called the Hurst exponent, which needs to be estimated in order to capture the characteristics of physical signals. In the previous work, a variance estimator for estimating the Hurst exponent directly via DFBM was provided, and it didn't consider point selection for linear regression. Since physical signals often appear to be DFGN-type, not DFBM-type, it is imperative to first transform DFGN into DFBM in real applications. In this paper, we show that the variance estimator possesses another form, which can be estimated directly via the autocorrelation functions of DFGN. The above extra procedure of transforming DFGN into DFBM can thus be avoided. On the other hand, the point selection for linear regression is also considered. Experimental results show that 4-point linear regression is almost optimal in most cases. Therefore, our proposed variance estimator is more efficient and accurate than the original one mentioned above. Besides, it is also superior to AR and MA methods in speed and accuracy.

Random beamforming(RBF) is a simple and practical method that can realize multi-user multi-input multi-output (MU-MIMO) systems. In this letter, we analyze the average sum rate of RBF with minimum mean squared error (MMSE) receive beamforming. To this end, we exploit the empirical eigenvalue distribution [5] and extreme value theory. The numerical verification shows that the proposed analysis provides a good approximation of the average sum rate of RBF even for the small number of antennas.

Radio frequency identification (RFID) system has gained attention as a new identification source that achieves a ubiquitous environment. Each RFID tag has a unique ID and is attached to an object. A user reads the unique ID of an RFID tag by using RFID readers and obtains the information on the object. One of the important technologies that use the RFID systems is the position estimation of RFID tags. Position estimation means estimating the location of the object with the RFID tag. Acquiring the location information of the RFID tag can be very useful. If a user can know the position of the RFID tag, the position estimation can be applied to a navigation system for walkers. In this paper, we propose a new position estimation method named Swift Communication Range Recognition (S-CRR) as an extended improvement on previous CRR that shortens the estimation delay. In this method, the position of an RFID tag is estimated by selecting the communication area model that corresponds to its boundary angles. We evaluated its performance by experiments and simulations of the RFID system. As the results, we found that S-CRR can estimate the position of an RFID tag comparatively accurately and quickly.

A low complexity log-likelihood ratio (LLR) calculation for high-order amplitude phase shift keying (APSK) signals is proposed. Using proper constellation partitioning together with a look-up table, the number of terms for the comparison of Euclidean distances can be significantly reduced. Compared with the log-sum LLR approximation, the proposed method reduces the computational complexity by more than 65% and 75% for 16-APSK and 32-APSK signals, respectively, with very small bit error rate performance degradation.

In this letter, we propose a Cooperation-aware topology control scheme with Opportunistic Interference Cancellation (COIC) to improve network capacity in wireless ad hoc networks by jointly considering both upper layer network capacity and physical layer cooperative communications with interference cancellation. We show that the benefits brought by cooperative communications are opportunistic and rely on network structures and channel conditions. Such opportunistic advantages have significant impacts on network capacity, and our proposed COIC can effectively capture these opportunities to substantially improve network capacity.

The multiple-input multiple-output (MIMO)-Orthogonal frequency division multiplexing (OFDM) system has a serious drawback in that it has high peak-to-average power ratio (PAPR). Therefore, in this letter, we propose an effective PAPR reduction scheme for MIMO-OFDM systems with nonlinear high power amplifier (HPA). The proposed scheme very effectively reduces the PAPR through the adaptive nonlinear estimator (ANE) which estimates the MSE between the OFDM signals before and after the nonlinear HPA and the low probability of false side information (SI) by receive diversity.

The location-based routing protocol has proven to be scalable and efficient in large wireless sensor networks with mobile sinks. A great challenge in location-based routing protocols is the design of scalable distributed location service that tracks the current locations of mobile sinks. Although various location services have been proposed in the literature, hierarchical-based location services have the significant advantage of high scalability. However, most of them depend on a global hierarchy of grids. A major disadvantage of this design is that high control overhead occurs when mobile sinks cross the boundaries of the top level grids. In this paper, we introduce Hierarchical Ring Location Service (HRLS) protocol, a practical distributed location service that provides sink location information in a scalable and distributed manner. In contrast to existing hierarchical-based location services, each sink in HRLS constructs its own hierarchy of grid rings distributively. To reduce the communication overhead of location update, sinks utilize the lazy update mechanism with their indirect location. Once a sensor node detects a target, it queries the location of a sink by sending request packets in eight directions. HRLS is evaluated through mathematical analysis and simulations. Compared with a well-known hierarchical-based location service, our results show that HRLS provides a more scalable and efficient distributed location service in scenarios with various network size, sink mobility and increasing number of source nodes.

The wireless sensor network (WSN) is a technology that senses environmental information and provides appropriate services to users. There are diverse application areas for WSNs such as disaster prevention, military, and facility management. Despite the many prospective applications, WSN s are vulnerable to various malicious attacks. In false report attacks, a malicious attacker steals a few sensor nodes and obtains security materials such as authentication keys from the nodes. The attacker then injects false event reports to the network through the captured nodes. The injected false reports confuse users or deplete the limited energy of the nodes in the network. Many filtering schemes have been proposed to detect and remove false reports. In the statistical en route filtering (SEF) scheme, each node shares authentication keys selected from a global key pool. Due to the limited memory, each node is able to store only a small portion of the global key pool. Therefore, the routing paths of the event reports significantly affect the filtering (i.e., detecting) probability of false reports. In this paper, we propose a method to determine the routing paths of event reports both hop by hop and on demand at each node. In this method, each node chooses the next node on the path from the event source to the sink node based on the key indexes of its neighbor nodes. Experiments show that the proposed method is far more energy efficient than the SEF when the false traffic ratio (FTR) is ≥ 50% in the network.

Application of transverse magnetic field (TMF) is one of the most important ways to improve electric life and breaking capacity of DC relays. For better understanding of dependence of arc durations on transverse magnetic field, a series of experiments were conducted under an external transverse magnetic field with 12 pairs of AgSnO2 contacts in a DC 28 V 60 A/30 A/5 A circuit, respectively. By using permanent magnets, the transverse magnetic field was obtained and the magnetic flux density at the gap center was varied from 13 to 94 mT. The results show that breaking arc duration is decreased monotonically with increases in the magnetic flux density, but making arc duration isn't decreased monotonically with increases in the magnetic flux density. In addition, both the magnetic flux density and the breaking arc duration have threshold values Bl and Tbmin, respectively, which means the breaking arc duration is almost stable with the value Tbmin even if the magnetic flux density is higher than Bl.

An ad hoc network is a decentralized network that consists of mobile nodes with wireless communication devices without the aid of access points. A Vehicular Ad-hoc NETwork (VANET) is one of the representative applications of the ad hoc network. Epidemic routing has been proposed as a routing protocol based on Store-Carry-Forward mechanism for VANET environment. However, in Epidemic Routing, network resources such as packet buffer of a node are significantly consumed because data packets are spread across the network. Therefore, this paper proposes a new autonomous clustering-based data transfer scheme using positions and moving direction of vehicles for VANETs. The autonomous clustering configures multiple clusters in the network and then only the cluster head that manages the cluster stores data packets. Whenever the cluster meets a new cluster, the cluster head of the cluster decides whether it should forward data packets to the new cluster based on its own position, the destination node's position, and moving direction of the cluster. Finally, this paper presents the simulation results to show the effectiveness of the proposed scheme.

For real-time services, such as VoIP and videoconferencing supplied through a multi-domain MPLS network, it is vital to guarantee end-to-end QoS of the inter-domain paths. Thus, it is important to allocate an appropriate QoS class to the inter-domain paths in each transit domain. Because each domain has its own policy for QoS class allocation, each domain must then allocate an appropriate QoS class adaptively based on the estimation of the QoS class allocation policies adopted in other domains. This paper proposes an adaptive method for acquiring a QoS class allocation policy through the use of reinforcement learning. This method learns the appropriate policy through experience in the actual QoS class allocation process. Thus, the method can adapt to a complex environment where the arrival of inter-domain path requests does not follow a simple Poisson process and where the various QoS class allocation policies are adopted in other domains. The proposed method updates the allocation policy whenever a QoS class is actually allocated to an inter-domain path. Moreover, some of the allocation policies often utilized in the real operational environment can be updated and refined more frequently. For these reasons, the proposed method is designed to adapt rapidly to variances in the surrounding environment. Simulation results verify that the proposed method can quickly adapt to variations in the arrival process of inter-domain path requests and the QoS class allocation policies in other domains.

In a shared medium communication system, mobile users contend for channel access according to a given set of rules to avoid collisions and achieve efficient use of the medium. If one or more users do not comply with the agree rules either due to selfish or malicious behaviours, they will cause some impacts on the system performance, especially to the well-behaved users. In this paper, we consider the problem of user misbehaviours on the performance of a wireless infrastructure-based network using reservation-based MAC protocols. Key misbehaving strategies possible in such a network are identified and explained. To quantify the impact of these misbehaviours upon the network performance, three different misbehaving scenarios are developed to allow a systematic investigation of each misbehaving strategy. For each scenario, we have derived mathematical formulations for evaluating and analyzing the key performance metrics, i.e., probabilities of success of well-behaved and misbehaved users and the fairness index. Numerical results show that the presence of misbehaviours can cause different levels of damage depending on the misbehavior strategy used. The combined multi-token and increasing permission probability strategies where the misbehaved user selfishly accesses the channel more times and with higher probabilities than allowed is shown to cause the most severe impairment of performance and fairness.

This paper presents a method of measuring the traffic of IP multicast streaming, such as IPTV, by using IPFIX and PSAMP. The IP multicast streaming service has recently become one of the popular network services, but no IP multicast operation method has been established yet. In particular, traffic measurement of IP multicast streaming encounters two challenges: as monitoring a multicast path tree and QoS measurement. There is no method to monitor them continuously in large-scale networks. Hence, we explore measurement structure suitable for large-scale networks, and then using IPFIX and PSAMP, we propose an efficient a network-level quality measurement method for IPTV and a method to extract multicast path tree data. In addition, we demonstrate the feasibility of the measurement method by evaluating a prototype system.

This study compares the performances of waveband protection and wavelength path protection in survivable hierarchical optical path networks. Network costs and the number of switching operations necessary are evaluated for different ratios of protected demand. Numerical results demonstrate that waveband protection can drastically decrease the number of switching operations in the case of failure, while both waveband and wavelength path protection effectively reduce the network resources needed compared to single layer optical path networks.

In this letter, we propose a dissimilarity metric (DM) to measure the deviation of a cognitive radio from the network in terms of local sensing reports. Utilizing the probability mass function of the DM, we present a dissimilarity-based attacker detection algorithm to distinguish Byzantine attackers from honest users. The proposed algorithm is able to identify the attackers without a priori information of the attacking styles and is robust against both independent and dependent attacks.

This letter proposes a monopole multi-sector antenna with dielectric cylinder, and shows some results of simulations that examined the antenna characteristics. The dependency of radiation characteristics on relative permittivity εr shows the lens effect with increase of εr. Furthermore, the characteristics of the proposed antenna are improved by optimizing the termination conditions at the quiescent antennas. The backlobe level is lower than -10 dB. Also, the vertical HPBW and the conical HPBW are around 70.5° and 63.4°, respectively. The optimization improved the actual gain by 2 dB. It is found that the diameter of the proposed antenna is 1/3rd that of the conventional one.

Orthogonal frequency and code division multiplexing (OFCDM) is available as orthogonal frequency and code division multiple access (OFCDMA) by allocating subcarrier to users. OFCDMA is an efficient transmission method assigning the subcarrier and the channel code according to channel state or many different environments. However, OFCDMA is hard to apply many frequency spreading codes when it is compared with OFCDM because of the restrictive subcarriers. This problem leads to decrease the frequency diversity. Therefore we propose system that combines cyclic delay diversity (CDD) with cooperative relaying system based on OFCDMA. This system complements this restrict by spatial diversity. In addition to that, the proposed system obtains diversity gain without loss of the throughput when direct-path condition is not good.

The periodogram scheme is a versatile method for large frequency offset estimation which requires preambles, in general, and only a few reference signals. However, the drawback of the conventional scheme is its inaccuracy in detecting the integer part of frequency offset which dominates the accuracy of frequency offset estimation. In order to increase the accuracy of the estimation, we directly interpolate a coefficient of the periodogram. The conventional periodogram and proposed schemes are compared in terms of the mean square error performance in the long term evolution system. The performance of the proposed method is compared with the conventional one and the simulation results indicate the better performance of the proposed one.