An anonymous credential system enables individuals to selectively prove their attributes while all other knowledge remains hidden. We considered the applicability of such a system to large scale infrastructure systems and perceived that revocations are still a problem. Then we contrived a scenario to lessen the number of revocations by using more attributes. In this scenario, each individual needs to handle a huge number of attributes, which is not practical with conventional systems. In particular, each individual needs to prove small amounts of attributes among a huge number of attributes and the manager of the system needs to certify a huge number of attributes of individuals periodically. These processes consume extremely large resources. This paper proposes an anonymous credential system in which both a user's proving attributes set, which is included in a huge attribute set, and manager's certifying attributes are very efficient. Conclusion Our proposal enables an anonymous credential system to be deployed as a large scale infrastructure system.

This paper presents a new generalized single threshold model that can be used in communications and cellular networks. In the proposed model, called Single Hysteresis Model (SHM), it is assumed that the amount of resources accessible for a new call of a given class can depend on two load areas of the system. The switching between areas is modulated by the two-state Markov chain which determines the average time the system spends in a particular load area, i.e. the area in which calls of selected classes with a reduced amount of resources (high load area) and with the initial amount of resources (low load area) are serviced. The results obtained for the discussed analytical model are compared with the results of the simulation of an exemplary WCDMA radio interface carrying a mixture of different multi-rate traffic streams. The research study confirms high accuracy of the proposed model.

Telecommunications networks have become an important social infrastructure, and their robustness is considered to be a matter of social significance. Conventional network planning methods are generally based on the maximum volume of ordinary traffic and only assume explicitly specified failure scenarios. Therefore, present networks have marginal survivability against multiple failures induced by an extraordinarily high volume of traffic generated during times of natural disasters or popular social events. This paper proposes a telecommunications network planning method based on probabilistic risk assessment. In this method, risk criterion reflecting the degree of risk due to extraordinarily large traffic loads is predefined and estimated using probabilistic risk assessment. The probabilistic risk assessment can efficiently calculate the small but non-negligible probability that a series of multiple failures will occur in the considered network. Detailed procedures for the proposed planning method are explained using a district mobile network in terms of the extraordinarily large traffic volume resulting from earthquakes. As an application example of the proposed method, capacity dimensioning for the local session servers within the district mobile network is executed to reduce the risk criterion most effectively. Moreover, the optimum traffic-rerouting scheme that minimizes the estimated risk criterion is ascertained simultaneously. From the application example, the proposed planning method is verified to realize a telecommunications network with sufficient robustness against the extraordinarily high volume of traffic caused by the earthquakes.

This paper proposes a novel approach to traffic state estimation using mobile phones. In this work, a real-time traffic data collection policy based on the so-called “3R” philosophy, a unique vehicle classification method, and a reasonable traffic state quantification model are proposed. The “3R” philosophy, in which the Right data are collected by the Right mobile devices at the Right time, helps to improve not only the effectiveness but also the scalability of the traffic state estimation model. The vehicle classification method using the simple data collected by mobile phones makes the traffic state estimation more accurate. The traffic state quantification model integrates both the mean speed capacity and the density of a traffic flow to improve the comprehensibility of the traffic condition. The experimental results reveal the effectiveness as well as the robustness of the proposed solutions.

In the network operator-friendly P2P traffic control technique such as P4P, peers are supposed to select their communication partners by following a guidance issued by the network operator. Thus, the guidance has significant impact on the traffic control. However, detailed performance study of available guidances is missing. Most existing approaches do not show how they affect intra-domain traffic control in detail while mostly focusing on inter-domain traffic control. In this paper, we try to understand how the guidances affect the intra and inter-domain traffic control for better guidance improving the traffic control. Through simulations, we reveal the following. The performance-based guidance reflecting the networking status shows attractive results in distributing the traffic over intra-domain links and in reducing the cross-domain traffic and the charging volume of inter-domain link compared to the distance-based guidance enforcing simple localization. However, the performance-based guidance shows one limitation that can cause unstable traffic control. To overcome the identified limitation, we propose peer-assisted measurement and traffic estimation approach. Then, we verify our approach through simulations.

ATFM (Air Traffic Flow Management) keeps air traffic flows safe and orderly. When the estimated workload exceeds capacity limit, traffic demand is controlled. In Japan, The ATFM system estimates controller's workload by a lot of parameter that depend on sector characteristics represented by traffic flow. The calculation of the value needs a lot of analysis. Author proposes a simple method for estimating the workload created by the traffic situation.

This paper investigates the performance of a combination of the affine encoder and the maximum mutual information decoder for symmetric channels, and proves that the random coding error exponent can be attained by this combination even if the conditional probability of the symmetric channel is not known to the encoder and decoder. This result clarifies that the restriction of the encoder to the class of affine encoders does not affect the asymptotic performance of the universal code for symmetric channels.

This paper proposes new scheduling algorithms for best effort (BE) traffic classification in business femtocell networks. The purpose of traffic classification is to provide differentiated services to BE users depending on their traffic classes, and the concept of traffic classification is called Inter User Best Effort (IUBE) in CDMA2000 1x Evolution Data Optimized (EVDO) standard. Traffic differentiation is achieved by introducing Grade of Service (GoS) as a quality of service (QoS) parameter into the scheduler's decision metric (DM). New scheduling algorithms are called QoS Round Robin (QoS-RR), QoS Proportionally Fair (QoS-PF), QoS maximum data rate control (DRC) (QoS-maxDRC), QoS average DRC (QoS-aveDRC), QoS exponent DRC (QoS-expDRC), QoS maxDRC-PF (QoS-maxDRC-PF). Two different femtocell throughput experiments are performed using real femtocell devices in order to collect real DRC values. The first experiment examines 4, 8, 12 and 16 IUBE users, while second experiment examines 4 IUBE + 2 Voice over IP (VoIP), 8 IUBE + 2 VoIP, 12 IUBE + 2 VoIP, 16 IUBE + 2 (VoIP) users. Average sector throughput, IUBE traffic differentiation, VoIP delay bound error values are investigated to compare the performance of the proposed scheduling algorithms. In conclusion, QoS-maxDRC-PF scheduler is proposed for business femtocell environment.

Temporal and spatial (geographical) fluctuations, which are present in the traffic of wireless sensor networks (WSNs), have a significant affect on the transmission performance and power consumption of WSNs. Several medium access control (MAC) mechanisms have been proposed for IEEE802.15.4 cluster-based WSNs to counter the temporal and spatial traffic fluctuations. However, these mechanisms cannot always achieve simultaneous improvement in both transmission performance and power consumption. In this paper, we propose two enhanced 2-level active period control mechanisms, BI&CAP control and BI&SD&CAP control, to achieve higher system performance than conventional control mechanisms. Various computer simulation results demonstrate the effectiveness of the proposed mechanisms for WSNs with various traffic fluctuations.

In a two-way half-duplex system where source nodes are equipped with multiple antennas and a relay with a single antenna, we study the diversity multiplexing tradeoff (DMT) achieved by orthogonal decode-and-forward (ODF), orthogonal amplify-and-forward (OAF), non-orthogonal decode-and-forward (NDF) and non-orthogonal amplify-and-forward (NAF), respectively. Their closed-form DMT are derived with given transmission time of each terminal, and optimized by allocating the transmission time. From these analyses, NDF achieves the best performance in terms of DMT in low spectral efficiency scenarios, while NAF outperforms other protocols in high spectral efficiency scenarios.

An anomalous change in traffic distributions caused by an external inter-domain routing change leads to congestion of some network links, which then affects the network quality or disrupts traffic. Thus, network operators need to promptly deal with these problems by changing the routing policy or by soliciting the help of an involved or neighboring network operator through operator channels. In addition, they need to diagnose situations in which customers are affected by the incident or in which destinations become unreachable. Although this task is indispensable, understanding the situation is difficult since the cause lies outside the operators' network domains. To alleviate the load on operators, we developed a system for monitoring traffic shifts and the disruptions caused by BGP routing changes. It is challenging to extract information that is more valid from a large amount of BGP update messages and traffic flow records. By correlating these data, the system provides meaningful reports and visualized traffic statistics, and it enables operators to easily detect the cause of traffic changes and to investigate the extent of damage. We demonstrate the effectiveness of the system and evaluate its feasibility by applying it to an ISP backbone network. In addition, we present a case study of traffic changes that the system detected.

This paper presents a history of the IPFIX working group, from initial chartering through development and testing, re-chartering and further development, and looking ahead to future developments. As a standardised way of exporting information about traffic flows, IPFIX has attracted a growing number of implementors, who have continued to develop it in useful ways without changing its underlying architecture. This makes it a good example of how to develop a new technology. Further, it demonstrates widespread recognition of the importance of network measurement in the development, deployment and production stages of networks and the applications that depend on them.

The processor-sharing (PS) rule arises as a natural paradigm in a variety of practical situations, including time-shared computer systems. Although there has been much work on Poisson-input queueing analysis for the PS rule, there have been few results for renewal-input GI/G/1 (PS) systems. We consider the GI/G/1 (PS) system to provide develop a two-moment approximation for the mean performance measures. We derive the relationship between the mean unfinished work and the conditional mean sojourn time for the GI/G/1 (PS) system. Using this relationship, we derive approximate formulas for the mean conditional sojourn time, mean sojourn time, and the mean number of customers in the GI/G/1 (PS) system. Numerical examples are presented to compare the approximation with exact and simulated results. We show that the proposed approximate formulas have good accuracy.

Per-flow traffic measurement is essential for network management; billing, traffic engineering, mitigating denial of service attacks, to mention just a few. In this field, the fundamental problem is that the size of expensive SRAM is too small to hold traffic data from high-speed networks. In this paper, we propose a new method for per-flow traffic measurement, which is based on the virtual vector that was originally designed for the problem of spread estimation. We modify the original virtual vector and show that this simple change yields a highly effective per-flow traffic estimator. Experiments show that our proposed scheme outperforms the state-of-the-art method in terms of both processing time and space requirement.

In this letter, we investigate the Nth-best user selection scheme for amplify-and-forward cooperative systems over Rayleigh fading channels. We deduce the probability density function, the cumulative density function, and the moment generating function of the end-to-end signal-to-noise ratio of the system. Then, the respective closed-form expressions of the average symbol error probability and the outage probability at the destination are derived. The diversity order obtained in the scheme increases with user number but becomes less as the selection sequence number N increases. Simulation results verify the analytical results.

Traffic adaptive 2-level active period control has been proposed to enhance system performance in cluster-based wireless sensor networks (WSNs) employing IEEE 802.15.4 medium access control (MAC) under temporal and spatial (geographical) non-uniform traffic environments. This paper proposes an adaptive method of controlling the backoff window for traffic adaptive 2-level active period control. The proposed method adjusts the size of the backoff window according to the length of the current active period, which is determined by 2-level active period control, and the time position for channel access in the active period. The results evaluated through computer simulations reveal that the proposed method can improve throughput as well as achieve high energy efficiency in cluster-based WSNs with non-uniform traffic distributions.

We present a new structure for parallel affine projection (AP) filters with different step-sizes. By observing their error signals, the proposed alternating AP (A-AP) filter selects one of the two AP filters and updates the weights of the selected filter for each iteration. As a result, the total computations required for the proposed structure is almost the same as that for a single AP filter. Experimental results show that the proposed alternating selection scheme extracts the best properties of each component filter, namely fast convergence and small steady-state error.

A safe prime p is a prime such that (p-1)/2 is also a prime. A primality test or a safe primality test is normally a combination of trial division and a probabilistic primality test. Since the number of small odd primes used in the trial division affects the performance of the combination, researchers have studied how to obtain the optimal number of small odd primes to be used in the trial division and the expected running time of the combination for primality tests. However, in the case of safe primality tests, the analysis of the combination is more difficult, and thus no such results have been given. In this paper, we present the first probabilistic analysis on the expected running time and the optimal number of small odd primes to be used in the trial division for optimizing the tests. Experimental results show that our probabilistic analysis estimates the behavior of the safe primality tests very well.

In this paper, we propose a framework of connectivity analysis for aviation ad hoc networks on flight paths. First, a general analytical connectivity model for the common one-dimensional ad hoc network is newly developed. Then it is applied for modeling the connectivity of ad hoc networks among aircraft along flight paths where aircraft arrival process follows a Poisson distribution. Connectivity is expressed in terms of connectedness probability of two nodes in the network, connected distance, and network coverage extension factor. An exact closed form derivation of connectedness probability is proposed. The radical effect of mobility on the network connectedness of aircraft over a single flight path is analyzed. The network connectedness probability depends on node density and node distribution, which are derived from node arrival rate and node velocity. Based on these results, the proposed model is extended to the practical case of paths with multi-velocity air traffic classes. Using this model, the critical values of system parameters for the network of aircraft with certain connectivity requirements can be derived. It helps to evaluate network extension capability under the constraints of various system parameters.

We propose a new resource prediction method for the Demand Assigned Multiple Access (DAMA) scheme in satellite networks. Inaccurate prediction of future traffic causes degradation of QoS and utilization due to the long delay in satellite networks. The Dynamic Leveling Scheme (DLS) use a leveling method to modify its prediction to a discrete one to change the precision of the prediction result. This new scheme has two features: 1) It enhances the probability of successful prediction and 2) it can be applied to any type of existing prediction method. Simulations show enhanced utilization and performance of the satellite link.