Android platform based linux kernel rootkit

2011 ◽  
Author(s):  
Dong-Hoon You ◽  
Bong-Nam Noh
Keyword(s):  
Linux Kernel ◽  
Android Platform

scholarly journals Mobile Operating Systems – Android: Version Alpha to 5.X: Lollipop

2015 ◽  
Vol 1 (1) ◽  
Author(s):  
Varsha Dubey
Keyword(s):  
Operating System ◽  
Market Share ◽  
Operating Systems ◽  
Smart Phones ◽  
Linux Kernel ◽  
Android Platform ◽  
Android Operating System ◽  
Mobile Handset

The android operating system is basically an operating system for mobiles and is rapidly gaining market share, with dozens of smart phones and tablets either released or set to be released. It is mobile operating system that uses a modified version of the Linux kernel 2.6. Google developed Android as part of the Open Handset Alliance, a group of more than 30 mobile and technology companies working to open up the mobile handset environment. Android’s development kit supports many of the standard packages used by Jetty, due to that fact and Jetty’s modularity and lightweight foot print, it was possible to port Jetty to it so that it will be able to run on the Android platform.

Machine learning for load balancing in the Linux kernel

2020 ◽  
Author(s):  
Jingde Chen ◽  
Subho S. Banerjee ◽  
Zbigniew T. Kalbarczyk ◽  
Ravishankar K. Iyer
Keyword(s):  
Machine Learning ◽  
Load Balancing ◽  
Linux Kernel

RCU Usage In the Linux Kernel

2020 ◽  
Vol 54 (1) ◽  
pp. 47-63
Author(s):  
Paul E. McKenney ◽  
Joel Fernandes ◽  
Silas Boyd-Wickizer ◽  
Jonathan Walpole
Keyword(s):  
Linux Kernel

scholarly journals Thread-Aware Mechanism to Enhance Inter-Node Load Balancing for Multithreaded Applications on NUMA Systems

2021 ◽  
Vol 11 (14) ◽  
pp. 6486
Author(s):  
Mei-Ling Chiang ◽  
Wei-Lun Su
Keyword(s):  
Load Balancing ◽  
Critical Path ◽  
Selection Procedure ◽  
Remote Memory ◽  
Data Mapping ◽  
Linux Kernel ◽  
Access Memory ◽  
Selection Policy ◽  
Benchmark Suite ◽  
Thread Mapping

NUMA multi-core systems divide system resources into several nodes. When an imbalance in the load between cores occurs, the kernel scheduler’s load balancing mechanism then migrates threads between cores or across NUMA nodes. Remote memory access is required for a thread to access memory on the previous node, which degrades performance. Threads to be migrated must be selected effectively and efficiently since the related operations run in the critical path of the kernel scheduler. This study focuses on improving inter-node load balancing for multithreaded applications. We propose a thread-aware selection policy that considers the distribution of threads on nodes for each thread group while migrating one thread for inter-node load balancing. The thread is selected for which its thread group has the least exclusive thread distribution, and thread members are distributed more evenly on nodes. This has less influence on data mapping and thread mapping for the thread group. We further devise several enhancements to eliminate superfluous evaluations for multithreaded processes, so the selection procedure is more efficient. The experimental results for the commonly used PARSEC 3.0 benchmark suite show that the modified Linux kernel with the proposed selection policy increases performance by 10.7% compared with the unmodified Linux kernel.

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