Adaptive Mid-term and Short-term Scheduling of Mixed-criticality Systems

A mixed-criticality real-time system is a real-time system having multiple tasks classified according to their criticality. Research on mixed-criticality systems started to provide an effective and cost efficient a priori verification process for safety critical systems. The higher the criticality of a task within a system and the more the system should guarantee the required level of service for it. However, such model poses new challenges with respect to scheduling and fault tolerance within real-time systems. Currently, mixed-criticality scheduling protocols severely degrade lower criticality tasks in case of resource shortage to provide the required level of service for the most critical ones. The actual research challenge in this field is to devise robust scheduling protocols to minimise the impact on less critical tasks. This dissertation introduces two approaches, one short-term and the other medium-term, to appropriately allocate computing resources to tasks within mixed-criticality systems both on uniprocessor and multiprocessor systems. The short-term strategy consists of a protocol named Lazy Bailout Protocol (LBP) to schedule mixed-criticality task sets on single core architectures. Scheduling decisions are made about tasks that are active in the ready queue and that have to be dispatched to the CPU. LBP minimises the service degradation for lower criticality tasks by providing to them a background execution during the system idle time. After, I refined LBP with variants that aim to further increase the service level provided for lower criticality tasks. However, this is achieved at an increased cost of either system offline analysis or complexity at runtime. The second approach, named Adaptive Tolerance-based Mixed-criticality Protocol (ATMP), decides at runtime which task has to be allocated to the active cores according to the available resources. ATMP permits to optimise the overall system utility by tuning the system workload in case of shortage of computing capacity at runtime. Unlike the majority of current mixed-criticality approaches, ATMP allows to smoothly degrade also higher criticality tasks to keep allocated lower criticality ones

Convex optimization framework for intermediate deadline assignment in soft and hard real-time distributed systems

It is generally challenging to determine end-to-end delays of applications for maximizing the aggregate system utility subject to timing constraints. Many practical approaches suggest the use of intermediate deadline of tasks in order to control and upper-bound their end-to-end delays. This paper proposes a unified framework for different time-sensitive, global optimization problems, and solves them in a distributed manner using Lagrangian duality. The framework uses global viewpoints to assign intermediate deadlines, taking resource contention among tasks into consideration. For soft real-time tasks, the proposed framework effectively addresses the deadline assignment problem while maximizing the aggregate quality of service. For hard real-time tasks, we show that existing heuristic solutions to the deadline assignment problem can be incorporated into the proposed framework, enriching their mathematical interpretation

Analysis and simulation of scheduling techniques for real-time embedded multi-core architectures

In this modern era of technological progress, multi-core processors have brought significant and consequential improvements in the available processing potential to the world of real-time embedded systems. These improvements impose a rapid increment of software complexity as well as processing demand placed on the underlying hardware. As a consequence, the need for efficient yet predictable multi-core scheduling techniques is on the rise. As part of this thesis, in-depth research of currently available multi-core scheduling techniques, belonging to both partitioned and global approaches, is done in the context of real-time embedded systems. The emphasis is on the degree of their usability on hard real-time systems, focusing on the scheduling techniques offering better processor affinity and the lower number of context switching. Also, an extensive research of currently available real-time test-beds as well as real-time operating systems is performed. Finally, a subset of the analyzed multi-core scheduling techniques comprising PSN-EDF, GSN-EDF, PD$^{2}$ and PD$^{2*}$ is simulated on the real-time test-bed LITMUS$^{RT}$

Tardiness Bounds and Overload in Soft Real-Time Systems

In some systems, such as future generations of unmanned aerial vehicles (UAVs), different software running on the same machine will require different timing guarantees. For example, flight control software has hard real-time (HRT) requirements---if a job (i.e., invocation of a program) completes late, then safety may be compromised, so jobs must be guaranteed to complete within short deadlines. However, mission control software is likely to have soft real-time (SRT) requirements---if a job completes slightly late, the result is not likely to be catastrophic, but lateness should never be unbounded. The global earliest-deadline-first (G-EDF) scheduler has been demonstrated to be useful for the multiprocessor scheduling of software with SRT requirements, and the multicore mixed-criticality (MC2) framework using G-EDF for SRT scheduling has been proposed to safely mix HRT and SRT work on multicore UAV platforms. This dissertation addresses limitations of this prior work. G-EDF is attractive for SRT systems because it allows the system to be fully utilized with reasonable overheads. Furthermore, previous analysis of G-EDF can provide "lateness bounds" on the amount of time between a job's deadline and its completion. However, smaller lateness bounds are preferable, and some programs may be more sensitive to lateness than others. In this dissertation, we explore the broader category of G-EDF-like (GEL) schedulers that have identical overhead characteristics to G-EDF. We show that by choosing GEL schedulers other than G-EDF, better lateness can be achieved, and that certain modifications can further improve lateness bounds while maintaining reasonable overheads. Specifically, successive jobs from the same program can be permitted to run in parallel with each other, or jobs can be split into smaller pieces by the operating system. Previous analysis of MC2 has always used less pessimistic execution time assumptions when analyzing SRT work than when analyzing HRT work. These assumptions can be violated, creating an overload that causes SRT guarantees to be violated. Furthermore, even in the expected case that such violations are transient, the system is not guaranteed to return to its normal operation. In this dissertation, we also provide a mechanism that can be used to provide such recovery.Doctor of Philosoph

Scheduling and locking in multiprocessor real-time operating systems

With the widespread adoption of multicore architectures, multiprocessors are now a standard deployment platform for (soft) real-time applications. This dissertation addresses two questions fundamental to the design of multicore-ready real-time operating systems: (1) Which scheduling policies offer the greatest flexibility in satisfying temporal constraints; and (2) which locking algorithms should be used to avoid unpredictable delays? With regard to Question 1, LITMUSRT, a real-time extension of the Linux kernel, is presented and its design is discussed in detail. Notably, LITMUSRT implements link-based scheduling, a novel approach to controlling blocking due to non-preemptive sections. Each implemented scheduler (22 configurations in total) is evaluated under consideration of overheads on a 24-core Intel Xeon platform. The experiments show that partitioned earliest-deadline first (EDF) scheduling is generally preferable in a hard real-time setting, whereas global and clustered EDF scheduling are effective in a soft real-time setting. With regard to Question 2, real-time locking protocols are required to ensure that the maximum delay due to priority inversion can be bounded a priori. Several spinlock- and semaphore-based multiprocessor real-time locking protocols for mutual exclusion (mutex), reader-writer (RW) exclusion, and k-exclusion are proposed and analyzed. A new category of RW locks suited to worst-case analysis, termed phase-fair locks, is proposed and three efficient phase-fair spinlock implementations are provided (one with few atomic operations, one with low space requirements, and one with constant RMR complexity). Maximum priority-inversion blocking is proposed as a natural complexity measure for semaphore protocols. It is shown that there are two classes of schedulability analysis, namely suspension-oblivious and suspension-aware analysis, that yield two different lower bounds on blocking. Five asymptotically optimal locking protocols are designed and analyzed: a family of mutex, RW, and k-exclusion protocols for global, partitioned, and clustered scheduling that are asymptotically optimal in the suspension-oblivious case, and a mutex protocol for partitioned scheduling that is asymptotically optimal in the suspension-aware case. A LITMUSRT-based empirical evaluation is presented that shows these protocols to be practical

Ensuring Service Level Agreements for Composite Services by Means of Request Scheduling

Building distributed systems according to the Service-Oriented Architecture (SOA) allows simplifying the integration process, reducing development costs and increasing scalability, interoperability and openness. SOA endorses the reusability of existing services and aggregating them into new service layers for future recycling. At the same time, the complexity of large service-oriented systems negatively reflects on their behavior in terms of the exhibited Quality of Service. To address this problem this thesis focuses on using request scheduling for meeting Service Level Agreements (SLAs). The special focus is given to composite services specified by means of workflow languages. The proposed solution suggests using two level scheduling: global and local. The global policies assign the response time requirements for component service invocations. The local scheduling policies are responsible for performing request scheduling in order to meet these requirements. The proposed scheduling approach can be deployed without altering the code of the scheduled services, does not require a central point of control and is platform independent. The experiments, conducted using a simulation, were used to study the effectiveness and the feasibility of the proposed scheduling schemes in respect to various deployment requirements. The validity of the simulation was confirmed by comparing its results to the results obtained in experiments with a real-world service. The proposed approach was shown to work well under different traffic conditions and with different types of SLAs

Maximising microprocessor reliability through game theory and heuristics

PhD ThesisEmbedded Systems are becoming ever more pervasive in our society, with most routine daily tasks now involving their use in some form and the market predicted to be worth USD 220 billion, a rise of 300%, by 2018. Consumers expect more functionality with each design iteration, but for no detriment in perceived performance. These devices can range from simple low-cost chips to expensive and complex systems and are a major cost driver in the equipment design phase. For more than 35 years, designers have kept pace with Moore's Law, but as device size approaches the atomic limit, layouts are becoming so complicated that current scheduling techniques are also reaching their limit, meaning that more resource must be reserved to manage and deliver reliable operation. With the advent of many-core systems and further sources of unpredictability such as changeable power supplies and energy harvesting, this reservation of capability may become so large that systems will not be operating at their peak efficiency. These complex systems can be controlled through many techniques, with jobs scheduled either online prior to execution beginning or online at each time or event change. Increased processing power and job types means that current online scheduling methods that employ exhaustive search techniques will not be suitable to define schedules for such enigmatic task lists and that new techniques using statistic-based methods must be investigated to preserve Quality of Service. A new paradigm of scheduling through complex heuristics is one way to administer these next levels of processor effectively and allow the use of more simple devices in complex systems; thus reducing unit cost while retaining reliability a key goal identified by the International Technology Roadmap for Semi-conductors for Embedded Systems in Critical Environments. These changes would be beneficial in terms of cost reduction and system exibility within the next generation of device. This thesis investigates the use of heuristics and statistical methods in the operation of real-time systems, with the feasibility of Game Theory and Statistical Process Control for the successful supervision of high-load and critical jobs investigated. Heuristics are identified as an effective method of controlling complex real-time issues, with two-person non-cooperative games delivering Nash-optimal solutions where these exist. The simplified algorithms for creating and solving Game Theory events allow for its use within small embedded RISC devices and an increase in reliability for systems operating at the apex of their limits. Within this Thesis, Heuristic and Game Theoretic algorithms for a variety of real-time scenarios are postulated, investigated, refined and tested against existing schedule types; initially through MATLAB simulation before testing on an ARM Cortex M3 architecture functioning as a simplified automotive Electronic Control Unit.Doctoral Teaching Account from the EPSRC

A grid computing framework for commercial simulation packages

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.An increased need for collaborative research among different organizations, together with continuing advances in communication technology and computer hardware, has facilitated the development of distributed systems that can provide users non-trivial access to geographically dispersed computing resources (processors, storage, applications, data, instruments, etc.) that are administered in multiple computer domains. The term grid computing or grids is popularly used to refer to such distributed systems. A broader definition of grid computing includes the use of computing resources within an organization for running organization-specific applications. This research is in the context of using grid computing within an enterprise to maximize the use of available hardware and software resources for processing enterprise applications. Large scale scientific simulations have traditionally been the primary benefactor of grid computing. The application of this technology to simulation in industry has, however, been negligible. This research investigates how grid technology can be effectively exploited by simulation practitioners using Windows-based commercially available simulation packages to model simulations in industry. These packages are commonly referred to as Commercial Off-The-Shelf (COTS) Simulation Packages (CSPs). The study identifies several higher level grid services that could be potentially used to support the practise of simulation in industry. It proposes a grid computing framework to investigate these services in the context of CSP-based simulations. This framework is called the CSP-Grid Computing (CSP-GC) Framework. Each identified higher level grid service in this framework is referred to as a CSP-specific service. A total of six case studies are presented to experimentally evaluate how grid computing technologies can be used together with unmodified simulation packages to support some of the CSP-specific services. The contribution of this thesis is the CSP-GC framework that identifies how simulation practise in industry may benefit from the use of grid technology. A further contribution is the recognition of specific grid computing software (grid middleware) that can possibly be used together with existing CSPs to provide grid support. With its focus on end-users and end-user tools, it is intended that this research will encourage wider adoption of grid computing in the workplace and that simulation users will derive benefit from using this technology

A framework for flexible scheduling in real-time middleware

The traditional vehicle for the deployment of a real-time system has been a real-time operating system (RTOS). In recent years another programming approach has increasingly found its way into the real-time systems domain: the use of middleware. Examples are the so called pervasive systems (embedded, interactive but not mobile), and ubiquitous systems (embedded, interactive and mobile), e.g. hand-held devices. These tend to be dynamic systems that often exhibit a need for flexible scheduling because of their operating requirement; or their execution environment. Thus, today there is a true need in many realtime applications for more flexible scheduling than what is currently the stateof- prac'tice. By flexible scheduling we mean the ability of the program execution platform to provide a range of scheduling policies, all the way from hard real-time to soft real-time policies, from which an application can choose one most suited to its needs. Furthermore, some applications may need to be scheduled by one policy while others may need a different policy, e.g. fi'Ced priority or earliest deadline first (EDF) for hard real-time tasks, least slack time first (LST) or shortest remaining time for soft real-time tasks. It would be difficult for the middleware to expect this functionality from the RTOS. This would require a fine balance to be struck in the RTOS between flexibility and usability, and many years will probably pass until such approaches become mainstream and usable. 'This thesis maintains that this flexibility can be introduced into the middleware. It presents a viable solution to introducing flexible scheduling in real-time program execution middleware in the form of a flexible scheduling framework. Such a framework allows use of the same program execution middleware for a variety of applications - soft, firm and hard. In particular, the framework allows different scheduling policies to co-exist in the system and their tasks to share common resources. The thesis describes tlle framework's protocol, examines the different types of scheduling policies that can be supported, tests its correctness through the use of a model checker and evaluates the proposed framework by measuring its execution cost overhead. The framework is deemed appropriate for the types of real-time applications that need the services of flexible scheduling