Assessment of Today’s Mobile Banking Applications from the View of Customer Requirements

Mobile banking is a subset of electronic banking which underlies not only the determinants of the banking business but also the special conditions of mobile commerce. This paper analyzes customer needs and expectations from the mobile applications’ view and from the banking view in order to derive a defined set of requirements. Based on these results, existing mobile banking applications are assessed. Their major shortcomings are explained, opportunities for their improvement are shown and the impact of upcoming new technology is discussed. The outcome of the paper is a defined set of customer requirements to mobile banking applications, the identification and assessment of four standard types of current mobile banking applications and an explanation of major failure reasons along with opportunities for their improvement.

Towards NFC payments using a lightweight architecture for the Web of Things

The Web (and Internet) of Things has seen the rapid emergence of new protocols and standards, which provide for innovative models of interaction for applications. One such model fostered by the Web of Things (WoT) ecosystem is that of contactless interaction between devices. Near Field Communication (NFC) technology is one such enabler of contactless interactions. Contactless technology for the WoT requires all parties to agree one common definition and implementation and, in this paper, we propose a new lightweight architecture for the WoT, based on RESTful approaches. We show how the proposed architecture supports the concept of a mobile wallet, enabling users to make secure payments employing NFC technology with their mobile devices. In so doing, we argue that the vision of the WoT is brought a step closer to fruition

Acceleration-as-a-Service: Exploiting Virtualised GPUs for a Financial Application

'How can GPU acceleration be obtained as a service in a cluster?' This question has become increasingly significant due to the inefficiency of installing GPUs on all nodes of a cluster. The research reported in this paper is motivated to address the above question by employing rCUDA (remote CUDA), a framework that facilitates Acceleration-as-a-Service (AaaS), such that the nodes of a cluster can request the acceleration of a set of remote GPUs on demand. The rCUDA framework exploits virtualisation and ensures that multiple nodes can share the same GPU. In this paper we test the feasibility of the rCUDA framework on a real-world application employed in the financial risk industry that can benefit from AaaS in the production setting. The results confirm the feasibility of rCUDA and highlight that rCUDA achieves similar performance compared to CUDA, provides consistent results, and more importantly, allows for a single application to benefit from all the GPUs available in the cluster without loosing efficiency.Comment: 11th IEEE International Conference on eScience (IEEE eScience) - Munich, Germany, 201

GeantV: Results from the prototype of concurrent vector particle transport simulation in HEP

Full detector simulation was among the largest CPU consumer in all CERN experiment software stacks for the first two runs of the Large Hadron Collider (LHC). In the early 2010's, the projections were that simulation demands would scale linearly with luminosity increase, compensated only partially by an increase of computing resources. The extension of fast simulation approaches to more use cases, covering a larger fraction of the simulation budget, is only part of the solution due to intrinsic precision limitations. The remainder corresponds to speeding-up the simulation software by several factors, which is out of reach using simple optimizations on the current code base. In this context, the GeantV R&D project was launched, aiming to redesign the legacy particle transport codes in order to make them benefit from fine-grained parallelism features such as vectorization, but also from increased code and data locality. This paper presents extensively the results and achievements of this R&D, as well as the conclusions and lessons learnt from the beta prototype.Comment: 34 pages, 26 figures, 24 table

Distributed Hybrid Simulation of the Internet of Things and Smart Territories

This paper deals with the use of hybrid simulation to build and compose heterogeneous simulation scenarios that can be proficiently exploited to model and represent the Internet of Things (IoT). Hybrid simulation is a methodology that combines multiple modalities of modeling/simulation. Complex scenarios are decomposed into simpler ones, each one being simulated through a specific simulation strategy. All these simulation building blocks are then synchronized and coordinated. This simulation methodology is an ideal one to represent IoT setups, which are usually very demanding, due to the heterogeneity of possible scenarios arising from the massive deployment of an enormous amount of sensors and devices. We present a use case concerned with the distributed simulation of smart territories, a novel view of decentralized geographical spaces that, thanks to the use of IoT, builds ICT services to manage resources in a way that is sustainable and not harmful to the environment. Three different simulation models are combined together, namely, an adaptive agent-based parallel and distributed simulator, an OMNeT++ based discrete event simulator and a script-language simulator based on MATLAB. Results from a performance analysis confirm the viability of using hybrid simulation to model complex IoT scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487