Computer Science

This paper describes the realization of a new Linux distribution based on Ubuntu Linux and Xenomai Real-Time framework. This realization is motivated by the eminent need of real-time systems in modern computer science courses. The majority of the technical choices are made after qualitative comparison. The main goal of this distribution is to offer standard Operating Systems (OS) that include Xenomai infrastructure and the essential tools to begin hard real-time application development inside a convivial desktop environment. The released live/installable DVD can be adopted to emulate several classic RTOS Application Program Interfaces (APIs), directly use and understand real-time Linux in convivial desktop environment and prototyping real-time embedded applications.

Multicore processors have proved to be the right choice for both desktop and server systems because it can support high performance with an acceptable budget expenditure. In this work, we have compared several works in cache contention and found that such works have identified several techniques for cache contention other than cache size including FSB, Memory Controller and prefetching hardware. We found that Distributed Intensity Online (DIO) is a very promising cache contention algorithm since it can achieve up to 2% from the optimal technique. Moreover, we propose a new framework for cache contention based on resource ontologies. In which ontologies instances will be used for communication between diverse processes instead of grasping schedules based on hardware.

The growing need for continuous processing capabilities has led to the development of multicore systems with a complex cache hierarchy. Such multicore systems are generally designed for improving the performance in average case, while hard real-time systems must consider worst-case scenarios. An open challenge is therefore to efficiently schedule hard real-time tasks on a multicore architecture. In this work, we propose a mathematical formulation for computing a static scheduling that minimize L1 data cache misses between hard real-time tasks on a multicore architecture using communication affinities.

Timing channels are a significant and growing security threat in computer systems, with no established solution. We have recently argued that the OS must provide time protection, in analogy to the established memory protection, to protect applications from information leakage through timing channels. Based on a recently-proposed implementation of time protection in the seL4 microkernel, we investigate how such an implementation could be formally proved to prevent timing channels. We postulate that this should be possible by reasoning about a highly abstracted representation of the shared hardware resources that cause timing channels.

We introduce a user mode file system, CannyFS, that hides latency by assuming all I/O operations will succeed. The user mode process will in turn report errors, allowing proper cleanup and a repeated attempt to take place. We demonstrate benefits for the model tasks of extracting archives and removing directory trees in a real-life HPC environment, giving typical reductions in time use of over 80%. This approach can be considered a view of HPC jobs and their I/O activity as transactions. In general, file systems lack clearly defined transaction semantics. Over time, the competing trends to add cache and maintain data integrity have resulted in different practical tradeoffs. High-performance computing is a special case where overall throughput demands are high. Latency can also be high, with non-local storage. In addition, a theoretically possible I/O error (like permission denied, loss of connection, exceeding disk quota) will frequently warrant the resubmission of a full job or task, rather than traditional error reporting or handling. Therefore, opportunistically treating each I/O operation as successful, and part of a larger transaction, can speed up some applications that do not leverage asynchronous I/O.

The smartphone market has grown so wide that it assumed a strategic relevance. Today the most common smartphone OSs are Google's Android and Apple's iOS. The former is particularly interesting due to its open source nature, that allows everyone to deeply inspect every aspect of the OS. Android source code is also bundled with an hardware emulator, based on the open source software Qemu, that allows the user to run the Android OS without the need of a physical device. We first present a procedure to extract information flows from a generic system. We then focus on Android and Qemu architectures and their logging infrastructures. Finally, we detail what happens inside an Android device in a particular scenario: the system boot.

CPU scheduling is one of the most crucial operations performed by operating systems. Different conventional algorithms like FCFS, SJF, Priority, and RR (Round Robin) are available for CPU Scheduling. The effectiveness of Priority and Round Robin scheduling algorithm completely depends on selection of priority features of processes and on the choice of time quantum. In this paper a new CPU scheduling algorithm has been proposed, named as CSPDABRR (Characteristic specific Prioritized Dynamic Average Burst Round Robin), that uses seven priority features for calculating priority of processes and uses dynamic time quantum instead of static time quantum used in RR. The performance of the proposed algorithm is experimentally compared with traditional RR and Priority scheduling algorithm in both uni-processor and multi-processor environment. The results of our approach presented in this paper demonstrate improved performance in terms of average waiting time, average turnaround time, and optimal priority feature.

Distributed algorithms that operate in the fail-recovery model rely on the state stored in stable memory to guarantee the irreversibility of operations even in the presence of failures. The performance of these algorithms lean heavily on the performance of stable memory. Current storage technologies have a defined performance profile: data is accessed in blocks of hundreds or thousands of bytes, random access to these blocks is expensive and sequential access is somewhat better. File system implementations hide some of the performance limitations of the underlying storage devices using buffers and caches. However, fail-recovery distributed algorithms bypass some of these techniques and perform synchronous writes to be able to tolerate a failure during the write itself. Assuming the distributed system designer is able to buffer the algorithm's writes, we ask how buffer size and latency complement each other. In this paper we start to answer this question by characterizing the performance (throughput and latency) of typical stable memory devices using a representative set of current file systems.

In this paper, we present a system called Checkbochs, a machine simulator that checks rules about its guest operating system and applications at the hardware level. The properties to be checked can be implemented as `plugins' in the Checkbochs simulator. Some of the properties that were checked using Checkbochs include null-pointer checks, format-string vulnerabilities, user/kernel pointer checks, and race-conditions. On implementing these checks, we were able to uncover previously-unknown bugs in widely used Linux distributions. We also tested our tools on undergraduate coursework, and found numerous bugs.

In this paper, we rethink how an OS supports virtual memory. Classical VM is an opaque abstraction of RAM, backed by demand paging. However, most systems today (from phones to data-centers) do not page, and indeed may require the performance benefits of non-paged physical memory, precise NUMA allocation, etc. Moreover, MMU hardware is now useful for other purposes, such as detecting page access or providing large page translation. Accordingly, the venerable VM abstraction in OSes like Windows and Linux has acquired a plethora of extra APIs to poke at the policy behind the illusion of a virtual address space. Instead, we present Cichlid, a memory system which inverts this model. Applications explicitly manage their physical RAM of different types, and directly (though safely) program the translation hardware. Cichlid is implemented in Barrelfish, requires no virtualization support, and outperforms VMM-based approaches for all but the smallest working sets. We show that Cichlid enables use-cases for virtual memory not possible in Linux today, and other use-cases are simple to program and significantly faster.