An efficient approximate computing circuit is developed for polynomial functions through the hybrid of analog and stochastic domains. Different from the ordinary time-based stochastic computing (TBSC), the proposed circuit exploits not only the duty cycle of pulses but also the pulse strength of the analog current to carry information for multiplications. The accumulation of many multiplications is performed by merely collecting the stochastic-current. As the calculation depth increases, the growth of latency (while summations), signal power weakening, and disparity of output signals (while multiplications) are substantially avoidable in contrast to that in the conventional TBSC. Furthermore, the calculation range spreads to bipolar infinite without scaling, theoretically. The proposed multi-domain stochastic computing (MDSC) is designed and simulated in a 0.18 µm CMOS technology by employing a set of current mirrors and an improved scheme of the TBSC circuit based on the Neuron-MOS mechanism. For proof-of-concept, the multiply and accumulate calculations (MACs) are implemented, achieving an average accuracy of 95.3%. More importantly, the transistor counting, power consumption, and latency decrease to 6.1%, 55.4%, and 4.2% of the state-of-art TBSC circuit, respectively. The robustness against temperature and process variations is also investigated and presented in detail.

Named Entity Recognition (NER) systems are often realized by supervised methods such as CRF and neural network methods, which require large annotated data. In some domains that small annotated training data is available, multi-domain or multi-task learning methods are often used. In this paper, we explore the methods that use news domain and Chinese Word Segmentation (CWS) task to improve the performance of Chinese named entity recognition in weibo domain. We first propose two baseline models combining multi-domain and multi-task information. The two baseline models share information between different domains and tasks through sharing parameters simply. Then, we propose a Double ADVersarial model (DoubADV model). The model uses two adversarial networks considering the shared and private features in different domains and tasks. Experimental results show that our DoubADV model outperforms other baseline models and achieves state-of-the-art performance compared with previous works in multi-domain and multi-task situation.

One of the key objectives of 5G is to evolve the current mobile network architecture from “one-fit-all” design model to a more customized and dynamically scaling one that enables the deployment of parallel systems, tailored to the service requirements on top of a shared infrastructure. Indeed, the envisioned 5G services may require different needs in terms of capacity, latency, bandwidth, reliability and security, which cannot be efficiently sustained by the same network infrastructure. Coming to address these customization challenges, network softwarization expressed through Software Defined Networking (SDN) programmable network infrastructures, Network Function Virtualization (NFV) running network functions as software and cloud computing flexibility paradigms, is seen as a possible panacea to addressing the variations in the network requirements posed by the 5G use cases. This will enable network flexibility and programmability, allow the creation and lifecycle management of virtual network slices tailored to the needs of 5G verticals expressed in the form of Mobile Virtual Network Operators (MVNOs) for automotive, eHealth, massive IoT, massive multimedia broadband. In this vein, this paper introduces a potential 5G architecture that enables the orchestration, instantiation and management of end-to-end network slices over multiple administrative and technological domains. The architecture is described from both the management and the service perspective, underlining the common functionality as well as how the response to the diversified service requirements can be achieved through proper software network components development.

Considering that existing clutter cancellation methods process information either in the time domain or in the spatial domain, this paper proposes a new clutter cancellation method that utilizes joint multi-domain information for passive radar. Assuming that there is a receiving array at the surveillance channel, firstly we propose a multi-domain information clutter cancellation model by constructing a time domain weighted matrix and a spatial weighted vector. Secondly the weighted matrix and vector can be updated adaptively utilizing the constant modulus constraint. Finally the weighted matrix is derived from the principle of optimal filtering and the recursion formula of weighted vector is obtained utilizing the Gauss-Newton method. Making use of the information in both time and spatial domain, the proposed method attenuates the noise and residual clutter whose directions are different from that of the target echo. Simulation results prove that the proposed method has higher clutter attenuation (CA) compared with the traditional methods in the low signal to noise ratio condition, and it also improves the detection performance of weak targets.

Software defined networking (SDN) and OpenFlow, which enables the abstraction of vendor/technology-specific attributes, improve the control and management flexibility of optical transport networks. In this paper, we present an interoperability demonstration of SDN/OpenFlow-based optical path control for multi-domain/multi-technology optical transport networks. We also summarize the abstraction approaches proposed for multi-technology network integration at SDN controllers.

Network virtualization is one of the promising technologies that can increase flexibility, diversity, and manageability of networks. Building optimal virtual networks across multiple domains is getting much attention, but existing studies were based on an unrealistic assumption, that is, providers' private information can be disclosed; as is well known, providers never actually do that. In this paper, we propose a new method that solves this multi-domain problem without revealing providers' private information. Our method uses an advanced secure computation technique called multi-party computation (MPC). Although MPC enables existing unsecured methods to optimize virtual networks securely, it requires very large time to finish the optimization due to the MPC's complex distributed protocols. Our method, in contrast, is designed to involve only a small number of MPC operations to find the optimal solution, and it allows providers to execute a large part of the optimization process independently without heavy distributed protocols. Evaluation results show that our method is faster than an existing method enhanced with MPC by several orders of magnitude. We also unveil that our method has the same level of embedding cost.

Multi-domain clock skew scheduling in general-synchronous framework is an effective technique to improve the performance of sequential circuits by using practical clock distribution network. Although the upper bound of performance of a circuit increases as the number of clock domains increases in multi-domain clock skew scheduling, the improvement of the performance becomes smaller while the cost of clock distribution network increases much. In this paper, a linear time algorithm that finds an optimum two-domain clock skew schedule in general-synchronous framework is proposed. Experimental results on ISCAS89 benchmark circuits and artificial data show that optimum circuits are efficiently obtained by our method in short time.

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.

The evolution of Internet, the growth of Internet users and the new enabled technological capabilities place new requirements to form the Future Internet. Many features improvements and challenges were imposed to build a better Internet, including securing roaming of data and services over multiple administrative domains. In this research, we propose a multi-domain access control infrastructure to authenticate and authorize roaming users through the use of the Diameter protocol and EAP. The Diameter Protocol is a AAA protocol that solves the problems of previous AAA protocols such as RADIUS. The Diameter EAP Application is one of Diameter applications that extends the Diameter Base Protocol to support authentication using EAP. The contributions in this paper are: 1) first implementation of Diameter EAP Application, called DiamEAP, capable of practical authentication and authorization services in a multi-domain environment, 2) extensibility design capable of adding any new EAP methods, as loadable plugins, without modifying the main part, and 3) provision of EAP-TLS plugin as one of the most secure EAP methods. DiamEAP Server basic performances were evaluated and tested in a real multi-domain environment where 200 users attempted to access network using the EAP-TLS method during an event of 4 days. As evaluation results, the processing time of DiamEAP using the EAP-TLS plugin for authentication of 10 requests is about 20 ms while that for 400 requests/second is about 1.9 second. Evaluation and operation results show that DiamEAP is scalable and stable with the ability to handle more than 6 hundreds of authentication requests per second without any crashes. DiamEAP is supported by the AAA working group of the WIDE Project.

In this paper, we address the on-demand end-to-end optical network construction problem for grid applications in new generation large-scale multi-domain wavelength switched optical networks (WSON). According to users' requests for high-performance distributed computing, groups of dedicated end-to-end lightpaths among geographically distributed grid resources can be established dynamically forming multiple-lightpath optical networks for grid applications, namely, optical grid network (OGN). To facilitate the automated OGN construction, we introduce an optical grid network infrastructure providing an integrated and self-contained OGN service to grid users with totally distributed control. In this infrastructure, for easy construction, especially in a large-scale multi-domain WSON environment, we propose an overlay approach to construct OGNs in a peer-to-peer fashion, which conceals the communication architecture of the underlying heterogeneous optical networks. In particular, we propose an adaptive construction mechanism that can develop the OGN flexibly by adapting to the dynamically changed optical network circumstance. To enable users to take the advantage of the end-to-end lightpaths of WSON directly, a wavelength-oriented end-host configuration scheme is proposed. Experimental results on a developed prototype and an optical-fibre test-bed network successfully validate the proposal.

MPLS-based path technology shows promise as a means of realizing reliable IP networks. Real-time services such as VoIP and video-conference supplied through a multi-domain MPLS network must be able 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 domain traversed by the inter-domain paths. Because each domain has its own policy for QoS class allocation, it is necessary to adaptively allocate the optimum QoS class based on estimation of the QoS class allocation policies in other domains. This paper proposes two kinds of adaptive QoS class allocation schemes, assuming that the arriving inter-domain path requests include the number of downstream domains traversed by the inter-domain paths and the remaining QoS value toward the destination nodes. First, a measurement-based scheme, based on measurement of the loss rates of inter-domain paths in the downstream domains, is proposed. This scheme estimates the QoS class allocation policies in the downstream domains, using the measured loss rates of path requests. Second, a state-dependent type scheme, based on measurement of the arrival rates of path requests in addition to the loss rates of paths in the downstream domains, is also proposed. This scheme allows an appropriate QoS class to be allocated according to the domain state. This paper proposes an application of the Markov decision theory to the modeling of state-dependent type scheme. The performances of the proposed schemes are evaluated and compared with those of the other less complicated non-adaptive schemes using a computer simulation. The results of the comparison reveal that the proposed schemes can adaptively increase the number of inter-domain paths accommodated in the considered domain, even when the QoS class allocation policies change in the other domains and the arrival pattern of path requests varies in the considered domain.

In this paper, we propose an end-to-end lightpath establishment method in multi-domain WDM networks. In this method, each domain contracts the provision of wavelength-state information and the number of wavelengths provided to neighbor domains. According to the contract, each source node selects the probed wavelengths, which are the candidates for backward wavelength reservation. In order to select wavelengths that are likely to be idle through the multi-domain network, the source node collects wavelength-state information from each destination node and ranks wavelengths for each destination node for giving priority. The source node selects the wavelengths with higher ranks. We propose two rank accounting methods for this purpose. Through simulation experiments, we show that the proposed rank accounting methods with the above contract provide better performance in terms of blocking probability with conventional methods, especially when intra-domain traffic is low. We present the effective number of contract wavelengths. Further, we also extend these rank accounting methods to methods that aggressively collect wavelength-state information from other destination nodes. We show further improvement of performance by the extended rank accounting methods.

An efficient, scalable speech recognition architecture combining topic detection and topic-dependent language modeling is proposed for multi-domain spoken language systems. In the proposed approach, the inferred topic is automatically detected from the user's utterance, and speech recognition is then performed by applying an appropriate topic-dependent language model. This approach enables users to freely switch between domains while maintaining high recognition accuracy. As topic detection is performed on a single utterance, detection errors may occur and propagate through the system. To improve robustness, a hierarchical back-off mechanism is introduced where detailed topic models are applied when topic detection is confident and wider models that cover multiple topics are applied in cases of uncertainty. The performance of the proposed architecture is evaluated when combined with two topic detection methods: unigram likelihood and SVMs (Support Vector Machines). On the ATR Basic Travel Expression Corpus, both methods provide a significant reduction in WER (9.7% and 10.3%, respectively) compared to a single language model system. Furthermore, recognition accuracy is comparable to performing decoding with all topic-dependent models in parallel, while the required computational cost is much reduced.

The research communitiy has shown considerable interest in studying access control in single Trusted Operating Systems (TOS). However, interactions among multiple TOSs have attracted relatively little attention. In this paper, we propose a Collaborative Role-Based Access Control (C-RBAC) model for distributed systems in which accesses across system domain boundaries are allowed. Access entities in a TOS vary in time. The changes in the organizational structure of the access entities in one system may influence other cooperating systems. In addition, policy-freeness, domain and rule conflicts are possible. These problems restrict the flexibility and scalability of coordination. We propose drafting a meta-component to play the role of a coordinator in multi-domain role-based access control. It is then possible to impart flexibility and scalability in a secure fashion. Experimental studies of the proposed model with the Network File System and SELinux system support our conclusion.

In this paper, Message Passing Interface (MPI) techniques are used to implement high-order full 3-D Navier-Stokes equations in multi-domain applications. A two-domain interface with five-point overlapping used previously is expanded to a multi-domain computation. There are normally two approaches for this expansion. One is to break up the domain into two parts through domain decomposition (say, one overlapping), then using MPI directives to further break up each domain into n parts. Another is to break the domain up into 2n parts with (2n-1) overlappings. In our present effort, the latter approach is used and finite-size overlappings are employed to exchange data between adjacent multi-dimensional sub-domains. It is an alternative way to parallelize the high-order full 3-D Navier-Stokes equations into multi-domain applications without adding much complexity. Results with high-order boundary treatments show consistency among multi-domain calculations and single-domain results.

Differentiated Service (DiffServ) is a technology designed to provide Quality of Service (QoS) in the Internet, and is superior to Integrated Service (IntServ) technology with respect to the simplicity of its architecture and the scalability of networks. Although various simulation studies and estimations over testbeds have investigated the QoS that is offered via the DiffServ framework, almost all of them focused on the characteristics in a single DiffServ domain. However, the Internet is actually composed of a large number of AS domains, and thus packets are very likely to arrive at their destinations after going through many different domains. Therefore, we have analyzed the QoS performance in a model consisting of multiple DiffServ domains, and focused especially on the quality provided by Assured Forwarding Service (AF) to achieve statistical bandwidth allocation with AF-PHB. Our simulation results show some throughput characteristics of flows over multiple Diffserv domains, which clarify how network configurations impact the QoS over multiple DiffServ domains.

Multi-domain spoken dialogue systems with high degree of intelligence and domain extensibility have long been desired but difficult to achieve. When the user freely surfs among different topics during the dialogue, it will be very difficult for the system to control the switching of the topics and domains while keeping the dialogue consistent, and decide when and how to take the initiative. This paper presents a distributed agent architecture for multi-domain spoken dialogue systems with high domain extensibility and intelligence. Under this architecture, different spoken dialogue agents (SDA's) handling different domains can be developed independently, and then smoothly cooperate with one another to achieve the user's multiple goals, while a user interface agent (UIA) can access the correct spoken dialogue agent through a domain switching protocol, and carry over the dialogue state and history so as to keep the knowledge processed coherently across different domains.

Rapid advancing technology and customer demand for sophisticated services are driving the global telecommunications environment into fully competitive and multi service providers environment. To cope with this new environment successfully, open network and open telecommunication management are essential. Telecommunication management is becoming more and more important to realize flexible and dynamic telecommunication services. This paper first gives a view of the new environment in the telecommunication industry and discusses the direction to be taken by service providers. Then, a concept of multi-domain management is proposed to meet a dynamically changing environment. Finally, the paper describes the subjects for the development of telecommunication management system and suggests that a competition based on harmony between the users, service providers and vendors is needed to make customers satisfied with telecommunication services.