Named data networking for efficient IoT-based disaster management in a smart campus

Disasters are uncertain occasions that can impose a drastic impact on human life and building infrastructures. Information and Communication Technology (ICT) plays a vital role in coping with such situations by enabling and integrating multiple technological resources to develop Disaster Management Systems (DMSs). In this context, a majority of the existing DMSs use networking architectures based upon the Internet Protocol (IP) focusing on location-dependent communications. However, IP-based communications face the limitations of inefficient bandwidth utilization, high processing, data security, and excessive memory intake. To address these issues, Named Data Networking (NDN) has emerged as a promising communication paradigm, which is based on the Information-Centric Networking (ICN) architecture. An NDN is among the self-organizing communication networks that reduces the complexity of networking systems in addition to provide content security. Given this, many NDN-based DMSs have been proposed. The problem with the existing NDN-based DMS is that they use a PULL-based mechanism that ultimately results in higher delay and more energy consumption. In order to cater for time-critical scenarios, emergence-driven network engineering communication and computation models are required. In this paper, a novel DMS is proposed, i.e., Named Data Networking Disaster Management (NDN-DM), where a producer forwards a fire alert message to neighbouring consumers. This makes the nodes converge according to the disaster situation in a more efficient and secure way. Furthermore, we consider a fire scenario in a university campus and mobile nodes in the campus collaborate with each other to manage the fire situation. The proposed framework has been mathematically modeled and formally proved using timed automata-based transition systems and a real-time model checker, respectively. Additionally, the evaluation of the proposed NDM-DM has been performed using NS2. The results prove that the proposed scheme has reduced the end-to-end delay up from 2% to 10% and minimized up to 20% energy consumption, as energy improved from 3% to 20% compared with a state-of-the-art NDN-based DMS

Digital library research : current developments and trends

This column gives an overview of current trends in digital library research under the following headings: digital library architecture, systems, tools and technologies; digital content and collections; metadata; interoperability; standards; knowledge organisation systems; users and usability; legal, organisational, economic, and social issues in digital libraries

aDORe: a modular, standards-based Digital Object Repository

This paper describes the aDORe repository architecture, designed and implemented for ingesting, storing, and accessing a vast collection of Digital Objects at the Research Library of the Los Alamos National Laboratory. The aDORe architecture is highly modular and standards-based. In the architecture, the MPEG-21 Digital Item Declaration Language is used as the XML-based format to represent Digital Objects that can consist of multiple datastreams as Open Archival Information System Archival Information Packages (OAIS AIPs).Through an ingestion process, these OAIS AIPs are stored in a multitude of autonomous repositories. A Repository Index keeps track of the creation and location of all the autonomous repositories, whereas an Identifier Locator registers in which autonomous repository a given Digital Object or OAIS AIP resides. A front-end to the complete environment, the OAI-PMH Federator, is introduced for requesting OAIS Dissemination Information Packages (OAIS DIPs). These OAIS DIPs can be the stored OAIS AIPs themselves, or transformations thereof. This front-end allows OAI-PMH harvesters to recurrently and selectively collect batches of OAIS DIPs from aDORe, and hence to create multiple, parallel services using the collected objects. Another front-end, the OpenURL Resolver, is introduced for requesting OAIS Result Sets. An OAIS Result Set is a dissemination of an individual Digital Object or of its constituent datastreams. Both front-ends make use of an MPEG-21 Digital Item Processing Engine to apply services to OAIS AIPs, Digital Objects, or constituent datastreams that were specified in a dissemination request.Comment: Draft of submission to Computer Journa

EwayDataCollect: Web Service-Based Data Collection Tool for Education System

AbstractIn education system, there is a need to collect data from the education providers, to facilitate informative decision making by the policy makers. Data collection is handled using tools like questionnaires, online surveys, online forms submission, and Electronic Data Interchange. This paper presents, EwayDataCollect, a tool for online data collection in education system. EwayDataCollect leverages the web service technology for data collection. It uses web service interface which is interoperable and supports communication between heterogeneous environments. The tool enables computer to computer data collection of both, statistical and detailed data. It facilitates collection of data from any number of educational providers. EwayDataCollect consists of three components: (1) Eway-Invocation, (2) DCF-Dissemination, and (3) Eway-Processing. The first component is responsible for registering the data requestor, accepting Data Capture Format (DCF) and details like URLs and email-ids of data providers. The task of second component is to disseminate DCF to the data providers. The third component of tool collects filled DCF from the data provider's registered URL. The collected data is parsed and stored in a database. EwayDataCollect is faster and easier to use. EwayDataCollect architecture, implementation and application are presented in this paper