Computer Science

We present a new least-privilege-based model of addressing on which to base memory management functionality in an OS for modern computers like phones or server-based accelerators. Existing software assumptions do not account for heterogeneous cores with different views of the address space, leading to the related problems of numerous security bugs in memory management code (for example programming IOMMUs), and an inability of mainstream OSes to securely manage the complete set of hardware resources on, say, a phone System-on-Chip. Our new work is based on a recent formal model of address translation hardware which views the machine as a configurable network of address spaces. We refine this to capture existing address translation hardware from modern SoCs and accelerators at a sufficiently fine granularity to model minimal rights both to access memory and configure translation hardware. We then build an executable specification in Haskell, which expresses the model and metadata structures in terms of partitioned capabilities. Finally, we show a fully functional implementation of the model in C created by extending the capability system of the Barrelfish research OS. Our evaluation shows that our unoptimized implementation has comparable (and in some cases) better performance than the Linux virtual memory system, despite both capturing all the functionality of modern hardware addressing and enabling least-privilege, decentralized authority to access physical memory and devices.

The Linux kernel is mostly designed for multi-programed environments, but high-performance applications have other requirements. Such applications are run standalone, and usually rely on runtime systems to distribute the application's workload on worker threads, one per core. However, due to current OSes limitations, it is not feasible to track whether workers are actually running or blocked due to, for instance, a requested resource. For I/O intensive applications, this leads to a significant performance degradation given that the core of a blocked thread becomes idle until it is able to run again. In this paper, we present the proof-of-concept of a Linux kernel extension denoted User-Monitored Threads (UMT) which tackles this problem. Our extension allows a user-space process to be notified of when the selected threads become blocked or unblocked, making it possible for a runtime to schedule additional work on the idle core. We implemented the extension on the Linux Kernel 5.1 and adapted the Nanos6 runtime of the OmpSs-2 programming model to take advantage of it. The whole prototype was tested on two applications which, on the tested hardware and the appropriate conditions, reported speedups of almost 2x.

This paper shows that it is possible to dramatically reduce the memory consumption of classes loaded in an embedded Java virtual machine without reducing its functionalities. We describe how to pack the constant pool by deleting entries which are only used during the class loading process. We present some benchmarks which demonstrate the efficiency of this mechanism. We finally suggest some additional optimizations which can be applied if some restrictions to the functionalities of the virtual machine can be tolerated.

The main objective of the paper is to improve the Round Robin (RR) algorithm using dynamic ITS by coalescing it with Shortest Remaining Time Next (SRTN) algorithm thus reducing the average waiting time, average turnaround time and the number of context switches. The original time slice has been calculated for each process based on its burst time.This is mostly suited for soft real time systems where meeting of deadlines is desirable to increase its performance. The advantage is that processes that are closer to their remaining completion time will get more chances to execute and leave the ready queue. This will reduce the number of processes in the ready queue by knocking out short jobs relatively faster in a hope to reduce the average waiting time, turn around time and number of context switches. This paper improves the algorithm [8] and the experimental analysis shows that the proposed algorithm performs better than algorithm [6] and [8] when the processes are having an increasing order, decreasing order and random order of burst time.

Scheduling is the central concept used frequently in Operating System. It helps in choosing the processes for execution. Round Robin (RR) is one of the most widely used CPU scheduling algorithm. But, its performance degrades with respect to context switching, which is an overhead and it occurs during each scheduling. Overall performance of the system depends on choice of an optimal time quantum, so that context switching can be reduced. In this paper, we have proposed a new variant of RR scheduling algorithm, known as Dynamic Quantum with Readjusted Round Robin (DQRRR) algorithm. We have experimentally shown that performance of DQRRR is better than RR by reducing number of context switching, average waiting time and average turn around time.

Round Robin, considered as the most widely adopted CPU scheduling algorithm, undergoes severe problems directly related to quantum size. If time quantum chosen is too large, the response time of the processes is considered too high. On the other hand, if this quantum is too small, it increases the overhead of the CPU. In this paper, we propose a new algorithm, called AN, based on a new approach called dynamic-time-quantum; the idea of this approach is to make the operating systems adjusts the time quantum according to the burst time of the set of waiting processes in the ready queue. Based on the simulations and experiments, we show that the new proposed algorithm solves the fixed time quantum problem and increases the performance of Round Robin.

The main objective of this paper is to develop the two different ways in which round robin architecture is modified and made suitable to be implemented in real time and embedded systems. The scheduling algorithm plays a significant role in the design of real time embedded systems. Simple round robin architecture is not efficient to be implemented in embedded systems because of higher context switch rate, larger waiting time and larger response time. Missing of deadlines will degrade the system performance in soft real time systems. The main objective of this paper is to develop the scheduling algorithm which removes the drawbacks in simple round robin architecture. A comparison with round robin architecture to the proposed architectures has been made. It is observed that the proposed architectures solves the problems encountered in round robin architecture in soft real time by decreasing the number of context switches waiting time and response time thereby increasing the system throughput.

Virtualization is generally adopted in server and desktop environments to provide for fault tolerance, resource management, and energy efficiency. Virtualization enables parallel execution of multiple operating systems (OSs) while sharing the hardware resources. Virtualization was previously not deemed as feasible technology for mobile and embedded devices due to their limited processing and memory resource. However, the enterprises are advocating Bring Your Own Device (BYOD) applications that enable co-existence of heterogeneous OSs on a single mobile device. Moreover, embedded device require virtualization for logical isolation of secure and general purpose OSs on a single device. In this paper, we investigate the processor architectures in the mobile and embedded space while examining their formal visualizability. We also compare the virtualization solutions enabling coexistence of multiple OSs in Multicore Processor System-on-Chip (MPSoC) mobile and embedded systems. We advocate that virtualization is necessary to manage resource in MPSoC designs and to enable BYOD, security, and logical isolation use cases.

Grid computing is a computation methodology using group of clusters connected over high-speed networks that involves coordinating and sharing computational power, data storage and network resources. Integrating a set of clusters of workstations into one large computing environment can improve the availability of computing power. The goal of scheduling is to achieve highest possible system throughput and to match the application need with the available computing resources. A secure scheduling model is presented, that performs job grouping activity at runtime. In a Grid environment, security is necessary because grid is a dynamic environment and participates are independent bodies with different policies, objectives and requirements. Authentication should be verified for Grid resource owners as well as resource requesters before they are allowed to join in scheduling activities. In order to achieve secure resource and job scheduling including minimum processing time and maximum resource utilization, A Secure Resource by using RSA algorithm on Networking and Job Scheduling model with Job Grouping strategy(JGS) in Grid Computing has been proposed. The result shows significant improvement in the processing time of jobs and resource utilization as compared to dynamic job grouping (DJG) based scheduling on smart grids (SG).

A method to boot a cluster of diskless network clients from a single write-protected NFS root file system is shown. The problems encountered when first implementing the setup and their solution are discussed. Finally, the setup is briefly compared to using a kernel-embedded root file system.