Using social media technologies for enterprise resource markets engineering

The study evaluates possibility of using social media technologies for implementing a full-fledged artificial market model, called Enterprise Resources Market. The existent model allows real-time resource self-scheduling (information and physical) for Internet-based enterprises employing agent-based peer-to-peer publish and subsribe approach with semantic matching of offers and requests. The market-style self-scheduling systems are complex to design and adopt in real-world for well-established and conservative industries. The new practical model suggests using popular microblogging platforms as global societal communication frameworks, and semantic wikis for collaborative describing resources and services, with aim of building enterprise resource markets specifically for individuals and small enterprises/organizations

MOSDEN: An Internet of Things Middleware for Resource Constrained Mobile Devices

The Internet of Things (IoT) is part of Future Internet and will comprise many billions of Internet Connected Objects (ICO) or `things' where things can sense, communicate, compute and potentially actuate as well as have intelligence, multi-modal interfaces, physical/ virtual identities and attributes. Collecting data from these objects is an important task as it allows software systems to understand the environment better. Many different hardware devices may involve in the process of collecting and uploading sensor data to the cloud where complex processing can occur. Further, we cannot expect all these objects to be connected to the computers due to technical and economical reasons. Therefore, we should be able to utilize resource constrained devices to collect data from these ICOs. On the other hand, it is critical to process the collected sensor data before sending them to the cloud to make sure the sustainability of the infrastructure due to energy constraints. This requires to move the sensor data processing tasks towards the resource constrained computational devices (e.g. mobile phones). In this paper, we propose Mobile Sensor Data Processing Engine (MOSDEN), an plug-in-based IoT middleware for mobile devices, that allows to collect and process sensor data without programming efforts. Our architecture also supports sensing as a service model. We present the results of the evaluations that demonstrate its suitability towards real world deployments. Our proposed middleware is built on Android platform

Agent-based simulation as tool for teaching principles of microeconomics

The paper proposes an agent-based computer simulation as a supplementary tool for teaching the principles of microeconomics. Such simulation can graphically illustrate how the individual behavior produces the studied aggregate outcomes, can bridge the gap between the abstract theories and the real world, and can mitigate the emotional aversion students have against some theories. The approach is demonstrated on a case of allocation of a scare resource: the model is described, the simulator is created, and its features are analyzed. The simulator has been made available on the Internet for free.Článek navrhuje používat multiagentovou počítačovou simulaci jako doplňkový nástroj pro výuky základů mikroekonomie. Multiagentová simulace může přehledně ilustrovat, jak individuální chování vytváří zkoumané agregátní výsledky, překlenout propast mezi abstraktní teorií a reálným světem a zmírnit emocionální problémy, které někteří studenti mají s určitými teoriemi. Tento přístup je ukázán na případu alokace vzácných zdrojů: teoretický model je popsán, simulátor vytvořen a jeho vlastnosti analyzovány. Vlastní simulátor je zdarma k dispozici na internetu.The paper proposes an agent-based computer simulation as a supplementary tool for teaching the principles of microeconomics. Such simulation can graphically illustrate how the individual behavior produces the studied aggregate outcomes, can bridge the gap between the abstract theories and the real world, and can mitigate the emotional aversion students have against some theories. The approach is demonstrated on a case of allocation of a scare resource: the model is described, the simulator is created, and its features are analyzed. The simulator has been made available on the Internet for free

Binary Independent Component Analysis with OR Mixtures

Independent component analysis (ICA) is a computational method for separating a multivariate signal into subcomponents assuming the mutual statistical independence of the non-Gaussian source signals. The classical Independent Components Analysis (ICA) framework usually assumes linear combinations of independent sources over the field of realvalued numbers R. In this paper, we investigate binary ICA for OR mixtures (bICA), which can find applications in many domains including medical diagnosis, multi-cluster assignment, Internet tomography and network resource management. We prove that bICA is uniquely identifiable under the disjunctive generation model, and propose a deterministic iterative algorithm to determine the distribution of the latent random variables and the mixing matrix. The inverse problem concerning inferring the values of latent variables are also considered along with noisy measurements. We conduct an extensive simulation study to verify the effectiveness of the propose algorithm and present examples of real-world applications where bICA can be applied.Comment: Manuscript submitted to IEEE Transactions on Signal Processin

A Unified Model for the Two-stage Offline-then-Online Resource Allocation

With the popularity of the Internet, traditional offline resource allocation has evolved into a new form, called online resource allocation. It features the online arrivals of agents in the system and the real-time decision-making requirement upon the arrival of each online agent. Both offline and online resource allocation have wide applications in various real-world matching markets ranging from ridesharing to crowdsourcing. There are some emerging applications such as rebalancing in bike sharing and trip-vehicle dispatching in ridesharing, which involve a two-stage resource allocation process. The process consists of an offline phase and another sequential online phase, and both phases compete for the same set of resources. In this paper, we propose a unified model which incorporates both offline and online resource allocation into a single framework. Our model assumes non-uniform and known arrival distributions for online agents in the second online phase, which can be learned from historical data. We propose a parameterized linear programming (LP)-based algorithm, which is shown to be at most a constant factor of $1/4$ from the optimal. Experimental results on the real dataset show that our LP-based approaches outperform the LP-agnostic heuristics in terms of robustness and effectiveness.Comment: Accepted by IJCAI 2020 (http://static.ijcai.org/2020-accepted_papers.html) and SOLE copyright holder is IJCAI (International Joint Conferences on Artificial Intelligence), all rights reserve

Design and Implementation of an Architectural Framework for Web Portals in a Ubiquitous Pervasive Environment

Web Portals function as a single point of access to information on the World Wide Web (WWW). The web portal always contacts the portal’s gateway for the information flow that causes network traffic over the Internet. Moreover, it provides real time/dynamic access to the stored information, but not access to the real time information. This inherent functionality of web portals limits their role for resource constrained digital devices in the Ubiquitous era (U-era). This paper presents a framework for the web portal in the U-era. We have introduced the concept of Local Regions in the proposed framework, so that the local queries could be solved locally rather than having to route them over the Internet. Moreover, our framework enables one-to-one device communication for real time information flow. To provide an in-depth analysis, firstly, we provide an analytical model for query processing at the servers for our framework-oriented web portal. At the end, we have deployed a testbed, as one of the world’s largest IP based wireless sensor networks testbed, and real time measurements are observed that prove the efficacy and workability of the proposed framework

A payload-based mutual authentication scheme for Internet of Things

The Internet of Things (IoT) is a vision that broadens the scope of the Internet by incorporating physical objects to identify themselves to the participating entities. This innovative concept enables a physical object to represent itself in the digital world. There have been a lot of speculations and future forecasts about these physical objects connected with the Internet, however, most of them lack secure features and are vulnerable to a wide range of attacks. Miniature sensor nodes, embedded in these physical objects, limit the support for computationally complex and resource-consuming secured algorithms. In this paper, we propose a lightweight mutual authentication scheme for the real-world physical objects of an IoT environment. It is a payload-based encryption scheme which uses a simple four-way handshake mechanism to verify the identities of the participating objects. The real-world objects communicate with each other using the client–server interaction model. Our proposed scheme uses the lightweight features of Constrained Application Protocol (CoAP) to enable the clients to observe resources residing on the server, in an energy-efficient manner. We use Advanced Encryption Standard (AES), with a key length of bits, to establish a secured session for resource observation. We evaluate our scheme for a real-world scenario using NetDuino Plus 2 boards. Our scheme is computationally efficient, incurs less connection overhead and at the same time, provides a robust defence against various attacks such as, resource exhaustion, Denial-of-Service, replay and physical tampering

Modelling the Integrated QoS for Wireless Sensor Networks with Heterogeneous Data Traffic

The future of Internet of Things (IoT) is envisaged to consist of a high amount of wireless resource-constrained devices connected to the Internet. Moreover, a lot of novel real-world services offered by IoT devices are realized by wireless sensor networks (WSNs). Integrating WSN to the Internet has therefore brought forward the requirements of an end-to-end quality of service (QoS) guarantee. In this paper, the QoS requirements for the WSN-Internet integration are investigated by first distinguishing the Internet QoS from the WSN QoS. Next, this study emphasizes on WSN applications that involve traffic with different levels of importance, thus the way realtime traffic and delay-tolerant traffic are handled to guarantee QoS in the network is studied. Additionally, an overview of the integration strategies is given, and the delay-tolerant network (DTN) gateway, being one of the desirable approaches for integrating WSNs to the Internet, is discussed. Next, the implementation of the service model is presented, by considering both traffic prioritization and service differentiation. Based on the simulation results in OPNET Modeler, it is observed that real-time traffic achieve low bound delay while delay-tolerant traffic experience a lower packet dropped, hence indicating that the needs of real-time and delay-tolerant traffic can be better met by treating both packet types differently. Furthermore, a vehicular network is used as an example case to describe the applicability of the framework in a real IoT application environment, followed by a discussion on the future work of this research