81 research outputs found
Localized Algorithm for Segregation of Critical/Non-critical Nodes in Mobile Ad Hoc and Sensor Networks
AbstractTimely segregation of connectivity-centric critical/non-critical nodes is extremely crucial in mobile ad hoc and sensor networks to assess network vulnerabilities against critical node failures and provide precautionary means for survivability. This paper presents a localized algorithm for segregation of critical/non-critical nodes (LASCNN) that opts to distinguish critical/non-critical nodes to the network connectivity based on limited topology information. Each node establishes and maintains a k-hop connection list and employ LASCNN to determine whether it is critical/non- critical. Based on the list, LASCNN marks a node as critical if its k-hop neighbor's become disconnected without the node, non-critical otherwise. Simulation experiments demonstrate the scalability of LASCNN and shows the performance is quite competitive compared to a scheme with global network information. The accuracy of LASCNN in determining critical nodes is 87% (1-hop) and 93% (2-hop) and non-critical nodes 91% (1-hop) and 93% (2-hop)
Edge-centric multimodal authentication system using encrypted biometric templates
Data security, complete system control, and missed storage and computing opportunities in personal portable devices are some of the major limitations of the centralized cloud environment. Among these limitations, security is a prime concern due to potential unauthorized access to private data. Biometrics, in particular, is considered sensitive data, and its usage is subject to the privacy protection law. To address this issue, a multimodal authentication system using encrypted biometrics for the edge-centric cloud environment is proposed in this study. Personal portable devices are utilized for encrypting biometrics in the proposed system, which optimizes the use of resources and tackles another limitation of the cloud environment. Biometrics is encrypted using a new method. In the proposed system, the edges transmit the encrypted speech and face for processing in the cloud. The cloud then decrypts the biometrics and performs authentication to confirm the identity of an individual. The model for speech authentication is based on two types of features, namely, Mel-frequency cepstral coefficients and perceptual linear prediction coefficients. The model for face authentication is implemented by determining the eigenfaces. The final decision about the identity of a user is based on majority voting. Experimental results show that the new encryption method can reliably hide the identity of an individual and accurately decrypt the biometrics, which is vital for errorless authentication
Fog based Secure Framework for Personal Health Records Systems
The rapid development of personal health records (PHR) systems enables an
individual to collect, create, store and share his PHR to authorized entities.
Health care systems within the smart city environment require a patient to
share his PRH data with a multitude of institutions' repositories located in
the cloud. The cloud computing paradigm cannot meet such a massive
transformative healthcare systems due to drawbacks including network latency,
scalability and bandwidth. Fog computing relieves the burden of conventional
cloud computing by availing intermediate fog nodes between the end users and
the remote servers. Aiming at a massive demand of PHR data within a ubiquitous
smart city, we propose a secure and fog assisted framework for PHR systems to
address security, access control and privacy concerns. Built under a fog-based
architecture, the proposed framework makes use of efficient key exchange
protocol coupled with ciphertext attribute based encryption (CP-ABE) to
guarantee confidentiality and fine-grained access control within the system
respectively. We also make use of digital signature combined with CP-ABE to
ensure the system authentication and users privacy. We provide the analysis of
the proposed framework in terms of security and performance.Comment: 12 pages (CMC Journal, Tech Science Press
Comprehensive survey of various energy storage technology used in hybrid energy
Various power generation technologies, such as wind turbines and solar power plants, have been increasingly installed in renewable energy projects as a result of rising demand and ongoing efforts by global researchers to mitigate environmental effects. The sole source of energy for such generation is nature. The incorporation of the green unit into the power grid also results in volatility. The stabilization of frequencies is critical and depends on the balance of supply and demand. An efficient monitoring scheme called Load Frequency Monitoring (LFM) is introduced to reduce the frequency deviation from its natural state. Specific energy storage systems may be considered to improve the efficiency of the control system. The storage system contributes to the load rate, peak rushing, black start support, etc., in addition to high energy and rapid responsive features. A detailed study of different power storage systems, their current business scenario, and the application of LFM facilities, as well as their analysis and disturbance, is presented in this paper. According to the literature analysis, the current approaches can be divided into two categories: grid and load scale structures. This article also distinguishes between the organized aggregate system and the uncoordinated system control scheme, both of which have advantages and disadvantages in terms of technology.Funding: The authors would like to acknowledge the financial support from Taif University Researchers Supporting Project Number (TURSP-2020/278), Taif University, Taif, Saudi Arabia.Scopu
Gafor : Genetic algorithm based fuzzy optimized re-clustering in wireless sensor networks
Acknowledgments: The authors are grateful to the Deanship of Scientific Research at King Saud University for funding this work through Vice Deanship of Scientific Research Chairs: Chair of Pervasive and Mobile Computing. Funding: This research was funded by King Saud University in 2020.Peer reviewedPublisher PD
Towards prevention of sportsmen burnout : Formal analysis of sub-optimal tournament scheduling
Funding Statement: The authors are grateful to the Deanship of Scientific Research at King Saud University, Saudi Arabia for funding this work through the Vice Deanship of Scientific Research Chairs: Chair of Pervasive and Mobile Computing.Peer reviewedPublisher PD
Software Defined Network-Based Multi-Access Edge Framework for Vehicular Networks
The authors are grateful to the Deanship of Scientific Research at King Saud University for funding this work through Vice Deanship of Scientific Research Chairs: Chair of Pervasive and Mobile Computing.Peer reviewe
A framework for cloud-based healthcare services to monitor noncommunicable diseases patient
Monitoring patients who have noncommunicable diseases is a big challenge. These illnesses require a continuous monitoring that leads to high cost for patients\u27 healthcare. Several solutions proposed reducing the impact of these diseases in terms of economic with respect to quality of services. One of the best solutions is mobile healthcare, where patients do not need to be hospitalized under supervision of caregivers. This paper presents a new hybrid framework based on mobile multimedia cloud that is scalable and efficient and provides cost-effective monitoring solution for noncommunicable disease patient. In order to validate the effectiveness of the framework, we also propose a novel evaluation model based on Analytical Hierarchy Process (AHP), which incorporates some criteria from multiple decision makers in the context of healthcare monitoring applications. Using the proposed evaluation model, we analyzed three possible frameworks (proposed hybrid framework, mobile, and multimedia frameworks) in terms of their applicability in the real healthcare environment
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