Cognitive caching for the future sensors in fog networking

Date

2017-12-01

Author

Al-Turjman, Fadi

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

153
views

0
downloads

In this paper, we propose a Cognitive Caching approach for the Future Fog (CCFF) that takes into consideration the value of the exchanged data in Information Centric Sensor Networks (ICSNs). Our approach depends on four functional parameters in ICSNs. These four main parameters are: age of the data, popularity of on-demand requests, delay to receive the requested information and data fidelity. These parameters are considered together to assign a value to the cached data while retaining the most valuable one in the cache for prolonged time periods. This CCFF approach provides significant availability for most valuable and difficult to retrieve data in the ICSNs. Extensive simulations and case studies have been examined in this research in order to compare to other dominant cache management frameworks in the literature under varying circumstances such as data popularity, cache size, data publisher load, and node connectivity degree. Formal fidelity and trust analysis has been applied as well to emphasize the effectiveness of CCFF in Fog paradigms, where edge devices can retrieve unsecured data from the authorized nodes in the cloud.

Subject Keywords

Computer Science (miscellaneous), Applied Mathematics

URI

https://hdl.handle.net/11511/63389

Journal

PERVASIVE AND MOBILE COMPUTING

DOI

https://doi.org/10.1016/j.pmcj.2017.06.004

Collections

Engineering, Article

Suggestions

OpenMETU
Core

A new likelihood approach to autonomous multiple model estimation Söken, Halil Ersin (Elsevier BV, 2020-04-01) This paper presents an autonomous multiple model (AMM) estimation algorithm for hybrid systems with sudden changes in their parameters. Estimates of Kalman filters (KFs) that are tuned and employed for different system modes are merged based on a newly defined likelihood function without any necessity for filter interaction. The proposed likelihood function is composed of two measures, the filter agility measure and the steady-state error measure. These measures are derived based on filter adaptation rules....
PERFORMANCE COMPARISON OF VARIOUS HEXAHEDRAL ELEMENT QUALITY METRICS VIA PARAMETRIC DISTORTION OF AN IDEAL ELEMENT Yalcin, Engin; YILMAZ, ASIM EGEMEN; Kuzuoğlu, Mustafa (World Scientific Pub Co Pte Lt, 2013-08-01) In this study, by means of parametric distortion of an ideal hexahedral element, we investigate the accuracy and sensitivity of some hexahedral element quality metrics existing in the literature. We also investigate and compare the relative computational costs of each metrics. We try to identify the weaknesses and strengths of all metrics under interrogation, and come up with some proposals for practical use.
A Two-Tier Distributed Fuzzy Logic Based Protocol for Efficient Data Aggregation in Multihop Wireless Sensor Networks SERT, SEYYİT ALPER; Alchihabi, Abdullah; Yazıcı, Adnan (Institute of Electrical and Electronics Engineers (IEEE), 2018-12-01) This study proposes a two-tier distributed fuzzy logic based protocol (TTDFP) to improve the efficiency of data aggregation operations in multihop wireless sensor networks (WSNs). Clustering is utilized for efficient aggregation requirements in terms of consumed energy. In a clustered network, member (leaf) nodes transmit obtained data to cluster-heads (CHs) and CHs relay received packets to the base station. In multihop wireless networks, this CH-generated transmission occurs over other CHs. Due to the ado...
Domain-Structured Chaos in a Hopfield Neural Network Akhmet, Marat (World Scientific Pub Co Pte Lt, 2019-12-30) In this paper, we provide a new method for constructing chaotic Hopfield neural networks. Our approach is based on structuring the domain to form a special set through the discrete evolution of the network state variables. In the chaotic regime, the formed set is invariant under the system governing the dynamics of the neural network. The approach can be viewed as an extension of the unimodality technique for one-dimensional map, thereby generating chaos from higher-dimensional systems. We show that the dis...
LOCAL OPERATOR ALGEBRAS FRACTIONAL POSITIVITY AND THE QUANTUM MOMENT PROBLEM Dosi, Anar (American Mathematical Society (AMS), 2011-02-01) In the present paper we introduce quantum measures as a concept of quantum functional analysis and develop the fractional space technique in the quantum (or local operator) space framework. We prove that each local operator algebra (or quantum *-algebra) has a fractional space realization. This approach allows us to formulate and prove a noncommutative Albrecht-Vasilescu extension theorem, which in turn solves the quantum moment problem.

Citation Formats

F. Al-Turjman, “Cognitive caching for the future sensors in fog networking,” PERVASIVE AND MOBILE COMPUTING, pp. 317–334, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/63389.