Context aware M-commerce services: C-IOB model approach

Context-aware computing is useful in providing individualized services focusing mainly on acquiring surrounding context of user. By comparison, only very little research has been completed in integrating context from different environments, despite of its usefulness in diverse applications such as healthcare, M-commerce and tourist guide applications. In particular, one of the most important criteria in providing personalized service in a highly dynamic environment and constantly changing user environment, is to develop a context model which aggregates context from different domains to infer context of an entity at the more abstract level. Hence, the purpose of this paper is to propose a context model based on cognitive aspects to relate contextual information that better captures the observation of certain worlds of interest for a more sophisticated context-aware service. We developed a C-IOB (Context-Information, Observation, Belief) conceptual model to analyze the context data from physical, system, application, and social domains to infer context at the more abstract level. The beliefs developed about an entity (person, place, things) are primitive in most theories of decision making so that applications can use these beliefs in addition to history of transaction for providing intelligent service. We enhance our proposed context model by further classifying context information into three categories: a well-defined, a qualitative and credible context information to make the system more realistic towards real world implementation. The proposed model is deployed to assist a M-commerce application. The simulation results show that the service selection and service delivery of the system are high compared to traditional system.

A context aware collaborative service provisioning system for mobile-commerce

In the process of service provisioning, providing required service to the user without user intervention, with reduction of the cognitive over loading is a real challenge. In this paper we propose a user centred context aware collaborative service provisioning system, which make use of context along with collaboration to provide the required service to the user dynamically. The system uses a novel approach of query expansion along with interactive and rating matrix based collaboration. Performance of the system is evaluated in Mobile-Commerce environment. The results show that the system is time efficient and perform with better precision and recall in comparison with context aware system.

A weight based context analysis system to provide a required UMM service

Ubiquitous Computing is an emerging paradigm which facilitates user to access preferred services, wherever they are, whenever they want, and the way they need, with zero administration. While moving from one place to another the user does not need to specify and configure their surrounding environment, the system initiates necessary adaptation by itself to cope up with the changing environment. In this paper we propose a system to provide context-aware ubiquitous multimedia services, without user’s intervention. We analyze the context of the user based on weights, identify the UMMS (Ubiquitous Multimedia Service) based on the collected context information and user profile, search for the optimal server to provide the required service, then adapts the service according to user’s local environment and preferences, etc. The experiment conducted several times with different context parameters, their weights and various preferences for a user. The results are quite encouraging.

Context based service discovery for ubiquitous applications

Service discovery is vital in ubiquitous applications, where a large number of devices and software components collaborate unobtrusively and provide numerous services without user intervention. Existing service discovery schemes use a service matching process in order to offer services of interest to the users. Potentially, the context information of the users and surrounding environment can be used to improve the quality of service matching. To make use of context information in service matching, a service discovery technique needs to address certain challenges. Firstly, it is required that the context information shall have unambiguous representation. Secondly, the devices in the environment shall be able to disseminate high level and low level context information seamlessly in the different networks. And thirdly, dynamic nature of the context information be taken into account. We propose a C-IOB(Context-Information, Observation and Belief) based service discovery model which deals with the above challenges by processing the context information and by formulating the beliefs based on the observations. With these formulated beliefs the required services will be provided to the users. The method has been tested with a typical ubiquitous museum guide application over different cases. The simulation results are time efficient and quite encouraging.

An approximation to the QoS aware throughput region of a tree network under IEEE 802.15.4 CSMA/CA with application to wireless sensor network design

In the context of wireless sensor networks, we are motivated by the design of a tree network spanning a set of source nodes that generate packets, a set of additional relay nodes that only forward packets from the sources, and a data sink. We assume that the paths from the sources to the sink have bounded hop count, that the nodes use the IEEE 802.15.4 CSMA/CA for medium access control, and that there are no hidden terminals. In this setting, starting with a set of simple fixed point equations, we derive explicit conditions on the packet generation rates at the sources, so that the tree network approximately provides certain quality of service (QoS) such as end-to-end delivery probability and mean delay. The structures of our conditions provide insight on the dependence of the network performance on the arrival rate vector, and the topological properties of the tree network. Our numerical experiments suggest that our approximations are able to capture a significant part of the QoS aware throughput region (of a tree network), that is adequate for many sensor network applications. Furthermore, for the special case of equal arrival rates, default backoff parameters, and for a range of values of target QoS, we show that among all path-length-bounded trees (spanning a given set of sources and the data sink) that meet the conditions derived in the paper, a shortest path tree achieves the maximum throughput. (C) 2015 Elsevier B.V. All rights reserved.

Process variability-aware statistical hybrid modeling of dynamic power dissipation in 65 nm CMOS designs

A generalized technique is proposed for modeling the effects of process variations on dynamic power by directly relating the variations in process parameters to variations in dynamic power of a digital circuit. The dynamic power of a 2-input NAND gate is characterized by mixed-mode simulations, to be used as a library element for 65mn gate length technology. The proposed methodology is demonstrated with a multiplier circuit built using the NAND gate library, by characterizing its dynamic power through Monte Carlo analysis. The statistical technique of Response. Surface Methodology (RSM) using Design of Experiments (DOE) and Least Squares Method (LSM), are employed to generate a "hybrid model" for gate power to account for simultaneous variations in multiple process parameters. We demonstrate that our hybrid model based statistical design approach results in considerable savings in the power budget of low power CMOS designs with an error of less than 1%, with significant reductions in uncertainty by atleast 6X on a normalized basis, against worst case design.

Framework for enabling highly available distributed applications for utility computing

The move towards IT outsourcing is the first step towards an environment where compute infrastructure is treated as a service. In utility computing this IT service has to honor Service Level Agreements (SLA) in order to meet the desired Quality of Service (QoS) guarantees. Such an environment requires reliable services in order to maximize the utilization of the resources and to decrease the Total Cost of Ownership (TCO). Such reliability cannot come at the cost of resource duplication, since it increases the TCO of the data center and hence the cost per compute unit. We, in this paper, look into aspects of projecting impact of hardware failures on the SLAs and techniques required to take proactive recovery steps in case of a predicted failure. By maintaining health vectors of all hardware and system resources, we predict the failure probability of resources based on observed hardware errors/failure events, at runtime. This inturn influences an availability aware middleware to take proactive action (even before the application is affected in case the system and the application have low recoverability). The proposed framework has been prototyped on a system running HP-UX. Our offline analysis of the prediction system on hardware error logs indicate no more than 10% false positives. This work to the best of our knowledge is the first of its kind to perform an end-to-end analysis of the impact of a hardware fault on application SLAs, in a live system.

Parallel circuit partitioning on a reduced array architecture

The physical design of a VLSI circuit involves circuit partitioning as a subtask. Typically, it is necessary to partition a large electrical circuit into several smaller circuits such that the total cross-wiring is minimized. This problem is a variant of the more general graph partitioning problem, and it is known that there does not exist a polynomial time algorithm to obtain an optimal partition. The heuristic procedure proposed by Kernighan and Lin1,2 requires O(n2 log2n) time to obtain a near-optimal two-way partition of a circuit with n modules. In the VLSI context, due to the large problem size involved, this computational requirement is unacceptably high. This paper is concerned with the hardware acceleration of the Kernighan-Lin procedure on an SIMD architecture. The proposed parallel partitioning algorithm requires O(n) processors, and has a time complexity of O(n log2n). In the proposed scheme, the reduced array architecture is employed with due considerations towards cost effectiveness and VLSI realizability of the architecture.The authors are not aware of any earlier attempts to parallelize a circuit partitioning algorithm in general or the Kernighan-Lin algorithm in particular. The use of the reduced array architecture is novel and opens up the possibilities of using this computing structure for several other applications in electronic design automation.

Integrating strong and weak discontinuities without integration subcells and example applications in an XFEM/GFEM framework

Partition of unity methods, such as the extended finite element method, allows discontinuities to be simulated independently of the mesh (Int. J. Numer. Meth. Engng. 1999; 45:601-620). This eliminates the need for the mesh to be aligned with the discontinuity or cumbersome re-meshing, as the discontinuity evolves. However, to compute the stiffness matrix of the elements intersected by the discontinuity, a subdivision of the elements into quadrature subcells aligned with the discontinuity is commonly adopted. In this paper, we use a simple integration technique, proposed for polygonal domains (Int. J. Nuttier Meth. Engng 2009; 80(1):103-134. DOI: 10.1002/nme.2589) to suppress the need for element subdivision. Numerical results presented for a few benchmark problems in the context of linear elastic fracture mechanics and a multi-material problem show that the proposed method yields accurate results. Owing to its simplicity, the proposed integration technique can be easily integrated in any existing code. Copyright (C) 2010 John Wiley & Sons, Ltd.

Voltage and Temperature Aware Statistical Leakage Analysis Framework Using Artificial Neural Networks

Artificial neural networks (ANNs) have shown great promise in modeling circuit parameters for computer aided design applications. Leakage currents, which depend on process parameters, supply voltage and temperature can be modeled accurately with ANNs. However, the complex nature of the ANN model, with the standard sigmoidal activation functions, does not allow analytical expressions for its mean and variance. We propose the use of a new activation function that allows us to derive an analytical expression for the mean and a semi-analytical expression for the variance of the ANN-based leakage model. To the best of our knowledge this is the first result in this direction. Our neural network model also includes the voltage and temperature as input parameters, thereby enabling voltage and temperature aware statistical leakage analysis (SLA). All existing SLA frameworks are closely tied to the exponential polynomial leakage model and hence fail to work with sophisticated ANN models. In this paper, we also set up an SLA framework that can efficiently work with these ANN models. Results show that the cumulative distribution function of leakage current of ISCAS'85 circuits can be predicted accurately with the error in mean and standard deviation, compared to Monte Carlo-based simulations, being less than 1% and 2% respectively across a range of voltage and temperature values.

Relation-Aware Isosurface Extraction in Multifield Data

We introduce a variation density function that profiles the relationship between multiple scalar fields over isosurfaces of a given scalar field. This profile serves as a valuable tool for multifield data exploration because it provides the user with cues to identify interesting isovalues of scalar fields. Existing isosurface-based techniques for scalar data exploration like Reeb graphs, contour spectra, isosurface statistics, etc., study a scalar field in isolation. We argue that the identification of interesting isovalues in a multifield data set should necessarily be based on the interaction between the different fields. We demonstrate the effectiveness of our approach by applying it to explore data from a wide variety of applications.

Quality-of-Transmission-Aware Manycasting Over Optical Burst-Switched Networks

Many next-generation distributed applications, such as grid computing, require a single source to communicate with a group of destinations. Traditionally, such applications are implemented using multicast communication. A typical multicast session requires creating the shortest-path tree to a fixed number of destinations. The fundamental issue in multicasting data to a fixed set of destinations is receiver blocking. If one of the destinations is not reachable, the entire multicast request (say, grid task request) may fail. Manycasting is a generalized variation of multicasting that provides the freedom to choose the best subset of destinations from a larger set of candidate destinations. We propose an impairment-aware algorithm to provide manycasting service in the optical layer, specifically OBS. We compare the performance of our proposed manycasting algorithm with traditional multicasting and multicast with over provisioning. Our results show a significant improvement in the blocking probability by implementing optical-layer manycasting.

The Reproducing Kernel DMS-FEM: 3D Shape Functions and Applications to Linear Solid Mechanics

We propose a family of 3D versions of a smooth finite element method (Sunilkumar and Roy 2010), wherein the globally smooth shape functions are derivable through the condition of polynomial reproduction with the tetrahedral B-splines (DMS-splines) or tensor-product forms of triangular B-splines and ID NURBS bases acting as the kernel functions. While the domain decomposition is accomplished through tetrahedral or triangular prism elements, an additional requirement here is an appropriate generation of knotclouds around the element vertices or corners. The possibility of sensitive dependence of numerical solutions to the placements of knotclouds is largely arrested by enforcing the condition of polynomial reproduction whilst deriving the shape functions. Nevertheless, given the higher complexity in forming the knotclouds for tetrahedral elements especially when higher demand is placed on the order of continuity of the shape functions across inter-element boundaries, we presently emphasize an exploration of the triangular prism based formulation in the context of several benchmark problems of interest in linear solid mechanics. In the absence of a more rigorous study on the convergence analyses, the numerical exercise, reported herein, helps establish the method as one of remarkable accuracy and robust performance against numerical ill-conditioning (such as locking of different kinds) vis-a-vis the conventional FEM.

An Effective Seamless Connectivity Scheme for Ubiquitous Applications

The idea of ubiquity and seamless connectivity in networks is gaining more importance in recent times because of the emergence of mobile devices with added capabilities like multiple interfaces and more processing abilities. The success of ubiquitous applications depends on how effectively the user is provided with seamless connectivity. In a ubiquitous application, seamless connectivity encompasses the smooth migration of a user between networks and providing him/her with context based information automatically at all times. In this work, we propose a seamless connectivity scheme in the true sense of ubiquitous networks by providing smooth migration to a user along with providing information based on his/her contexts automatically without re-registration with the foreign network. The scheme uses Ubi-SubSystems(USS) and Soft-Switches(SS) for maintaining the ubiquitous application resources and the users. The scheme has been tested by considering the ubiquitous touring system with several sets of tourist spots and users.