11,829 research outputs found
Data centric trust evaluation and prediction framework for IOT
© 2017 ITU. Application of trust principals in internet of things (IoT) has allowed to provide more trustworthy services among the corresponding stakeholders. The most common method of assessing trust in IoT applications is to estimate trust level of the end entities (entity-centric) relative to the trustor. In these systems, trust level of the data is assumed to be the same as the trust level of the data source. However, most of the IoT based systems are data centric and operate in dynamic environments, which need immediate actions without waiting for a trust report from end entities. We address this challenge by extending our previous proposals on trust establishment for entities based on their reputation, experience and knowledge, to trust estimation of data items [1-3]. First, we present a hybrid trust framework for evaluating both data trust and entity trust, which will be enhanced as a standardization for future data driven society. The modules including data trust metric extraction, data trust aggregation, evaluation and prediction are elaborated inside the proposed framework. Finally, a possible design model is described to implement the proposed ideas
The Road Ahead for Networking: A Survey on ICN-IP Coexistence Solutions
In recent years, the current Internet has experienced an unexpected paradigm
shift in the usage model, which has pushed researchers towards the design of
the Information-Centric Networking (ICN) paradigm as a possible replacement of
the existing architecture. Even though both Academia and Industry have
investigated the feasibility and effectiveness of ICN, achieving the complete
replacement of the Internet Protocol (IP) is a challenging task.
Some research groups have already addressed the coexistence by designing
their own architectures, but none of those is the final solution to move
towards the future Internet considering the unaltered state of the networking.
To design such architecture, the research community needs now a comprehensive
overview of the existing solutions that have so far addressed the coexistence.
The purpose of this paper is to reach this goal by providing the first
comprehensive survey and classification of the coexistence architectures
according to their features (i.e., deployment approach, deployment scenarios,
addressed coexistence requirements and architecture or technology used) and
evaluation parameters (i.e., challenges emerging during the deployment and the
runtime behaviour of an architecture). We believe that this paper will finally
fill the gap required for moving towards the design of the final coexistence
architecture.Comment: 23 pages, 16 figures, 3 table
Addressing the Challenges in Federating Edge Resources
This book chapter considers how Edge deployments can be brought to bear in a
global context by federating them across multiple geographic regions to create
a global Edge-based fabric that decentralizes data center computation. This is
currently impractical, not only because of technical challenges, but is also
shrouded by social, legal and geopolitical issues. In this chapter, we discuss
two key challenges - networking and management in federating Edge deployments.
Additionally, we consider resource and modeling challenges that will need to be
addressed for a federated Edge.Comment: Book Chapter accepted to the Fog and Edge Computing: Principles and
Paradigms; Editors Buyya, Sriram
On Constructing Persistent Identifiers with Persistent Resolution Targets
Persistent Identifiers (PID) are the foundation referencing digital assets in
scientific publications, books, and digital repositories. In its realization,
PIDs contain metadata and resolving targets in form of URLs that point to data
sets located on the network. In contrast to PIDs, the target URLs are typically
changing over time; thus, PIDs need continuous maintenance -- an effort that is
increasing tremendously with the advancement of e-Science and the advent of the
Internet-of-Things (IoT). Nowadays, billions of sensors and data sets are
subject of PID assignment. This paper presents a new approach of embedding
location independent targets into PIDs that allows the creation of
maintenance-free PIDs using content-centric network technology and overlay
networks. For proving the validity of the presented approach, the Handle PID
System is used in conjunction with Magnet Link access information encoding,
state-of-the-art decentralized data distribution with BitTorrent, and Named
Data Networking (NDN) as location-independent data access technology for
networks. Contrasting existing approaches, no green-field implementation of PID
or major modifications of the Handle System is required to enable
location-independent data dissemination with maintenance-free PIDs.Comment: Published IEEE paper of the FedCSIS 2016 (SoFAST-WS'16) conference,
11.-14. September 2016, Gdansk, Poland. Also available online:
http://ieeexplore.ieee.org/document/7733372
EC-CENTRIC: An Energy- and Context-Centric Perspective on IoT Systems and Protocol Design
The radio transceiver of an IoT device is often where most of the energy is consumed. For this reason, most research so far has focused on low power circuit and energy efficient physical layer designs, with the goal of reducing the average energy per information bit required for communication. While these efforts are valuable per se, their actual effectiveness can be partially neutralized by ill-designed network, processing and resource management solutions, which can become a primary factor of performance degradation, in terms of throughput, responsiveness and energy efficiency. The objective of this paper is to describe an energy-centric and context-aware optimization framework that accounts for the energy impact of the fundamental functionalities of an IoT system and that proceeds along three main technical thrusts: 1) balancing signal-dependent processing techniques (compression and feature extraction) and communication tasks; 2) jointly designing channel access and routing protocols to maximize the network lifetime; 3) providing self-adaptability to different operating conditions through the adoption of suitable learning architectures and of flexible/reconfigurable algorithms and protocols. After discussing this framework, we present some preliminary results that validate the effectiveness of our proposed line of action, and show how the use of adaptive signal processing and channel access techniques allows an IoT network to dynamically tune lifetime for signal distortion, according to the requirements dictated by the application
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