Z
Zahra Pooranian
Researcher at University of Padua
Publications - 40
Citations - 1441
Zahra Pooranian is an academic researcher from University of Padua. The author has contributed to research in topics: Grid computing & Scheduling (computing). The author has an hindex of 18, co-authored 38 publications receiving 1068 citations. Previous affiliations of Zahra Pooranian include Islamic Azad University & University of Surrey.
Papers
More filters
Journal ArticleDOI
P-SEP: a prolong stable election routing algorithm for energy-limited heterogeneous fog-supported wireless sensor networks
TL;DR: A modified Stable Election Protocol (SEP), named Prolong-SEP (P- SEP) is presented to prolong the stable period of Fog-supported sensor networks by maintaining balanced energy consumption.
Journal ArticleDOI
FOCAN: A Fog-supported smart city network architecture for management of applications in the Internet of Everything environments
Paola G. Vinueza Naranjo,Zahra Pooranian,Mohammad Shojafar,Mohammad Shojafar,Mauro Conti,Rajkumar Buyya +5 more
TL;DR: A Fog-supported smart city network architecture called Fog Computing Architecture Network (FOCAN), a multi-tier structure in which the applications running on things jointly compute, route, and communicate with one another through the smart city environment to decrease latency and improve energy provisioning and the efficiency of services among things with different capabilities.
Posted Content
FOCAN: A Fog-supported Smart City Network Architecture for Management of Applications in the Internet of Everything Environments
Paola G. Vinueza Naranjo,Zahra Pooranian,Mohammad Shojafar,Mohammad Shojafar,Mauro Conti,Rajkumar Buyya +5 more
TL;DR: In this paper, a multi-tier architecture called Fog Computing Architecture Network (FOCAN) is proposed to reduce the latency and energy consumption of Internet of Everything (IoE) devices running various applications.
Journal ArticleDOI
Similarity-based Android Malware Detection Using Hamming Distance of Static Binary Features
Rahim Taheri,Meysam Ghahramani,Reza Javidan,Mohammad Shojafar,Mohammad Shojafar,Zahra Pooranian,Mauro Conti +6 more
TL;DR: Four malware detection methods using Hamming distance to find similarity between samples which are first nearest neighbor (FNN), all nearest neighbors (ANN), weighted all nearestNeighbors (WANN), and k-medoid based nearestNeighborhood (KMNN) are developed.
Journal ArticleDOI
An efficient meta-heuristic algorithm for grid computing
TL;DR: This paper has combined PSO with the gravitational emulation local search (GELS) algorithm to form a new method, PSO–GELS, and experimental results demonstrate the effectiveness of PSO-GELS compared to other algorithms.