Scheduling for electricity cost in a smart grid

We study an offline scheduling problem arising in demand response management in a smart grid. Consumers send in power requests with a flexible set of timeslots during which their requests can be served. For example, a consumer may request the dishwasher to operate for 1 h during the periods 8am to 11am or 2pm to 4pm. The grid controller, upon receiving power requests, schedules each request within the specified duration. The electricity cost is measured by a convex function of the load in each timeslot. The objective of the problem is to schedule all requests with the minimum total electricity cost. As a first attempt, we consider a special case in which the power requirement and the duration a for which a request needs service are both unit-size. For this problem, we present a polynomial time offline algorithm that gives an optimal solution and shows that the time complexity can be further improved if the given set of timeslots forms a contiguous interval.     

Adaptive Resource Allocation for Service-Based Systems

Due to its major advantages, service-oriented architecture (SOA) has been adopted in various distributed systems, such as web services, grid computing systems, utility computing systems and cloud computing systems. These systems are referred as service-based systems (SBS). In order to effectively use these systems in various applications, one major challenge which must be addressed is to manage the quality of services (QoS) to satisfy users’ requirements. In SBS, multiple services are often hosted by the same server and compete for the limited system resources of the server, such as CPU-time, memory and network bandwidth. In addition, service compositions, resource status of servers, workflow priorities and QoS requirements are usually dynamically changing in runtime. Hence, it is necessary to have effective techniques to allocate the system resources to each service provided by a server in order to satisfy the QoS requirements of multiple workflows in SBS. In this paper, a resource allocation approach is presented to adaptively allocating the system resources of servers to their services in runtime in order to satisfy one of the most important QoS requirements, the throughput, of multiple workflows in SBS.     

A model-based approach to form tolerance evaluation using non-uniform rational B-splines

Tolerance evaluation is critical to quality assurance in modern manufacturing. In contrast to traditional measurement which relies on specific hard gauges, coordinate measuring machines provide more flexibility for dimensional measurement and tolerance evaluations. To fully automate CMM inspection and tolerance evaluation, CAD/CMM integration is an important key. Although the subject of CAD-directed inspection has been widely researched, CAD model-based tolerance evaluation has received less attention. This paper presents a CAD model-based approach for evaluating general form tolerances using non-uniform rational B-splines. Unlike classical methods which construct substitute geometric features from the measurement data, this method evaluates form tolerances by comparing the measurement data with a nominal CAD model. Non-uniform rational B-spline (NURBS) is used to represent general form features since NURBS offers a common format for modeling different form features. With this unified database, a general best-fit algorithm is developed that can be applied to the evaluation of various form tolerances. Computer simulations have been performed on different form features to study the robustness and efficiency of the algorithm. Application to the profile analysis of turbo charger housing and turbine blade die segments are also presented.     

Real-time moustache detection by combining image decolorization and texture detection with applications to facial gender recognition

There are still many challenging problems in facial gender recognition which is mainly due to the complex variances of face appearance. Although there has been tremendous research effort to develop robust gender recognition over the past decade, none has explicitly exploited the domain knowledge of the difference in appearance between male and female. Moustache contributes substantially to the facial appearance difference between male and female and could be a good feature to be incorporated into facial gender recognition. Little work on moustache segmentation has been reported in the literature. In this paper, a novel real-time moustache detection method is proposed which combines face feature extraction, image decolorization and texture detection. Image decolorization, which converts a color image to grayscale, aims to enhance the color contrast while preserving the grayscale. On the other hand, moustache appearance is normally grayscale surrounded by the skin color face tissue. Hence, it is a fast and efficient way to segment the moustache by using the decolorization technology. In order to make the algorithm robust to the variances of illumination and head pose, an adaptive decolorization segmentation has been proposed in which both the segmentation threshold selection and the moustache region following are guided by some special regions defined by their geometric relationship with the salient facial features. Furthermore, a texture-based moustache classifier is developed to compensate the decolorization-based segmentation which could detect the darker skin or shadow around the mouth caused by the small lines or skin thicker from where he/she smiles as moustache. The face is verified as the face containing a moustache only when it satisfies: (1) a larger moustache region can be found by applying the decolorization segmentation; (2) the segmented moustache region is detected as moustache by the texture moustache detector. The experimental results on color FERET database showed that the proposed approach can achieve 89 % moustache face detection rate with 0.1 % false acceptance rate. By incorporating the moustache detector into a facial gender recognition system, the gender recognition accuracy on a large database has been improved from 91 to 93.5 %.     

Optimal mass transport for geometric modeling based on variational principles in convex geometry

In geometric modeling, surface parameterization plays an important role for converting triangle meshes to spline surfaces. Parameterization will introduce distortions. Conventional parameterization methods emphasize on angle-preservation, which may induce huge area distortions and cause large spline fitting errors and trigger numerical instabilities.To overcome this difficulty, this work proposes a novel area-preserving parameterization method, which is based on an optimal mass transport theory and convex geometry. Optimal mass transport mapping is measure-preserving and minimizes the transportation cost. According to Brenier’s theorem, for quadratic distance transportation costs, the optimal mass transport map is the gradient of a convex function. The graph of the convex function is a convex polyhedron with prescribed normal and areas. The existence and the uniqueness of such a polyhedron have been proved by the Minkowski-Alexandrov theorem in convex geometry. This work gives an explicit method to construct such a polyhedron based on the variational principle, and formulates the solution to the optimal transport map as the unique optimum of a convex energy. In practice, the energy optimization can be carried out using Newton’s method, and each iteration constructs a power Voronoi diagram dynamically. We tested the proposal algorithms on 3D surfaces scanned from real life. Experimental results demonstrate the efficiency and efficacy of the proposed variational approach for the optimal transport map.     

Heterogeneous CPU Services Using Differentiated Admission Control

We present an adaptive rate-controlled scheduler for heterogeneous applications running on general purpose computers. Our scheduler can effectively support diverse application requirements. It employs uniform rate-based sharing. Application heterogeneity is satisfied by partitioning CPU capacity into service classes, each with a different criterion for admission control. As a result, we are able to provide at once guaranteed performance, flexible allocation of rates with excellent scalability and intermediate service classes offering tradeoffs between reserved rate utilization and the strength of guarantees. Our scheduler has been implemented in Solaris 2.5.1. It runs existing applications without modifications. We present experimental results showing the scalability, efficiency, guaranteed performance, and overload performance aspects of our scheduler. We demonstrate the importance of priority inheritance implemented in our scheduler for stable system performance.     

Cryptanalysis of simple three-party key exchange protocol (S-3PAKE)

Password-authenticated key exchange (PAKE) protocols allow parties to share secret keys in an authentic manner based on an easily memorizable password. Recently, Lu and Cao proposed a three-party password-authenticated key exchange protocol, so called S-3PAKE, based on ideas of the Abdalla and Pointcheval two-party SPAKE extended to three parties. S-3PAKE can be seen to have a structure alternative to that of another three-party PAKE protocol (3PAKE) by Abdalla and Pointcheval. Furthermore, a simple improvement to S-3PAKE was proposed very recently by Chung and Ku to resist the kind of attacks that applied to earlier versions of 3PAKE. In this paper, we show that S-3PAKE falls to unknown key-share attacks by any other client, and undetectable online dictionary attacks by any adversary. The latter attack equally applies to the recently improved S-3PAKE. Indeed, the provable security approach should be taken when designing PAKEs; and furthermore our results highlight that extra cautions still be exercised when defining models and constructing proofs in this direction.     

A variational formulation for fingerprint orientation modeling

Orientation pattern is an important feature for characterizing fingerprint and plays critical roles in fingerprint recognition and fingerprint classification. This paper proposes a framework for modeling the fingerprint orientation field based on the variational principle, where the orientation pattern can be estimated through solving the associated Euler–Lagrange equation. Compared with existing methods, our proposed method has the following features. Firstly, it does not require any prior information about the structure of the acquired fingerprint, such as location of singular point(s). Secondly, it explicitly provides freedom for modeling the singularity in the orientation field. Thirdly, it has less number of parameters. Comparison has been made with respect to state-of-the-arts in fingerprint orientation modeling in terms of modeling accuracy, fingerprint enhancement and singular point detection. Advantages of the proposed method are demonstrated.     

An SNS-based model for finding collaborative partners

This paper proposes a model, Recommendation of Appropriate Partners (RAP), used on a Social Networking Service (SNS) for locating appropriate “helpers” for users based on individual users’ Chain of Friends (CoF) relationships. Using the RAP model, individual users can participate in a collaborative online community in remote locations, whereby helpers are willing to help other users solve their tasks/problems, and it is intended that both the users and helpers gain knowledge from these interactive online sessions. An example of the RAP-based system was implemented to invite Program Committee members to an international conference. The system was evaluated and the experimental results show that our model is very effective for discovering collaboration partners and finding users with similar interests in order to create communities for providing future and longer-term helping exchange.