Patterns for Providing Real-Time Guarantees in DOC Middleware - Doctoral Dissertation, May 2002

The advent of open and widely adopted standards such as Common Object Request Broker Architecture (CORBA) [47] has simplified and standardized the development of distributed applications. For applications with real-time constraints, including avionics, manufacturing, and defense systems, these standards are evolving to include Quality-of-Service (QoS) specifications. Operating systems such as Real-time Linux [60] have responded with interfaces and algorithms to guarantee real-time response; similarly, languages such as Real-time Java [59] include mechanisms for specifying real-time properties for threads. However, the middleware upon which large distributed applications are based has not yet addressed end-to-end guarantees of QoS specifications. Unless this challenge can be met, developers must resort to ad hoc solutions that may not scale or migrate well among different platforms. This thesis provides two contributions to the study of real-time Distributed Object Computing (DOC) middleware. First, it identifies potential bottlenecks and problems with respect to guaranteeing real-time performance in contemporary middleware. Experimental results illustrate how these problems lead to incorrect real-time behavior in contemporary middleware platforms. Second, this thesis presents designs and techniques for providing real-time QoS guarantees in DOC middleware in the context of TAO [6], an open-source and widely adopted implementation of real-time CORBA. Architectural solutions presented here are coupled with empirical evaluations of end-to-end real-time behavior. Analysis of the problems, forces, solutions, and consequences are presented in terms of patterns and frame-works, so that solutions obtained for TAO can be appropriately applied to other real-time systems

A Generative Programming Framework for Adaptive Middleware

Historically, many distributed real-time and embedded (DRE) systems were developed manually from scratch, leading to stove-piped solutions that while correct in both functional and QoS properties were very expensive to develop and difficult to maintain and extend. First-generation middleware technologies such as CORBA 2.x [1], XML [2], and SOAP [3], served to shield application developers from low-level platform details, thus raising the level of abstraction at which distributed systems are developed and supporting reuse of infrastructure to amortize development costs over the lifetime of a system. However, interdependencies between services and object interfaces resulting from these programming models significantly limited the degree of reuse that could be achieved in practice. Component middleware technologies such as the CORBA Component Model (CCM) [4], J2EE [5], and .NET [6], were developed to address many of these limitations. In CCM, for example, standardization of component containers, ports, and homes offered a framework within which reuse of server as well as client infrastructure was facilitated. Component-oriented middleware has addressed a wide range of application domains, but unfortunately for DRE systems, the focus of these technologies has been primarily on functional and not QoS properties. For example, although CCM supports configuration of functional component attributes like their interconnections, key QoS attributes for DRE systems, such as execution times and invocation rates are inadequately configurable through conventional CCM [7]. Research on QoS-aware component models such as the CIAO project [8, 7] is showing significant promise in making QoS configuration a first-class part of the component pro-gramming model, thus further reducing accidental complex-ities of building DRE systems. However, it is important to note a fundamental difference between configuration of functional and QoS properties even within such a unified compo-nent model: the dominant decomposition of functional properties is essentially object-oriented, while the dominant decomposition of QoS properties is essentially aspect-oriented. That is, functional properties tend to be stable with respect to component boundaries and configuration lifecycle stages, while QoS properties tend to cross-cut component boundaries, and may be revised as more information is known in later configuration stages [7]. In this paper, we describe how a focus on aspect frameworks for configuring QoS properties both com-plements and extends QoS-aware component models. This paper makes three main contributions to the state of the art in DRE systems middleware. First, it describes a simple but representative problem for configuring QoS aspects that cross-cut both architectural layers and system lifecycle boundaries, which motivates our focus on aspect frameworks. Second, it provides a formalization of that problem using first order logic, which both guides the design of aspect configuration infrastructure, and offers a way to connect these techniques with model-integrated computing [9] approaches to further reduce the programming burden on DRE system developers. Third, it describes alternative mechanisms to ensure correct configuration of the aspects involved, and notes the phases of the DRE system lifecycle at which each such configuration mechanism is most appropriate

Programming frameworks for mobile sensing

The proliferation of smart mobile devices in people’s daily lives is making context-aware computing a reality. A plethora of sensors available in these devices can be utilized to understand users’ context better. Apps can provide more relevant data or services to the user based on improved understanding of user’s context. With the advent of cloud-assisted mobile platforms, apps can also perform collaborative computation over the sensing data collected from a group of users. However, there are still two main issues: (1) A lack of simple and effective personal sensing frameworks: existing frameworks do not provide support for real-time fusing of data from motion and visual sensors in a simple manner, and no existing framework collectively utilizes sensors from multiple personal devices and personal IoT sensors, and (2) a lack of collaborative/distributed computing frameworks for mobile users. This dissertation presents solutions for these two issues. The first issue is addressed by TagPix and Sentio, two frameworks for mobile sensing. The second issue is addressed by Moitree, a middleware for mobile distributed computing, and CASINO, a collaborative sensor-driven offloading system. TagPix is a real-time, privacy preserving photo tagging framework, which works locally on the phones and consumes little resources (e.g., battery). It generates relevant tags for landscape photos by utilizing sensors of a mobile device and it does not require any previous training or indexing. When a user aims the mobile camera to a particular landmark, the framework uses accelerometer and geomagnetic field sensor to identify in which direction the user is aiming the camera at. It then uses a landmark database and employs a smart distance estimation algorithm to identify which landmark(s) is targeted by the user. The framework then generates relevant tags for the captured photo using these information. A more versatile sensing framework can be developed using sensors from multiple devices possessed by a user. Sentio is such a framework which enables apps to seamlessly utilize the collective sensing capabilities of the user’s personal devices and of the IoT sensors located in the proximity of the user. With Sentio, an app running on any personal mobile/wearable device can access any sensor of the user in real-time using the same API, can selectively switch to the most suitable sensor of a particular type when multiple sensors of this type are available at different devices, and can build composite sensors. Sentio offers seamless connectivity to sensors even if the sensor-accessing code is offloaded to the cloud. Sentio provides these functionalities with a high-level API and a distributed middleware that handles all low-level communication and sensor management tasks. This dissertation also proposes Moitree, a middleware for the mobile cloud platforms where each mobile device is augmented by an avatar, a per-user always-on software entity that resides in the cloud. Mobile-avatar pairs participate in distributed computing as a unified computing entity. Moitree provides a common programming and execution framework for mobile distributed apps. Moitree allows the components of a distributed app to execute seamlessly over a set of mobile/avatar pairs, with the provision of offloading computation and communication to the cloud. The programming framework has two key features: user collaborations are modeled using group semantics - groups are created dynamically based on context and are hierarchical; data communication among group members is offloaded to the cloud through high-level communication channels. Finally, this dissertation presents and discusses CASINO, a collaborative sensor-driven computation offloading framework which can be used alongside Moitree. This framework includes a new scheduling algorithm which minimizes the total completion time of a collaborative computation that executes over a set of mobile/avatar pairs. Using the CASINO API, the programmers can mark their classes and functions as ”offloadable”. The framework collects profiling information (network, CPU, battery, etc.) from participating users’ mobile devices and avatars, and then schedules ”offloadable” tasks in mobiles and avatars in a way that reduces the total completion time. The scheduling problem is proven to be NP-Hard and there is no polynomial time optimization algorithm for it. The proposed algorithm can generate a schedule in polynomial time using a topological sorting and greedy technique

Flexible Scheduling in Middleware for Distributed rate-based real-time applications - Doctoral Dissertation, May 2002

Distributed rate-based real-time systems, such as process control and avionics mission computing systems, have traditionally been scheduled statically. Static scheduling provides assurance of schedulability prior to run-time overhead. However, static scheduling is brittle in the face of unanticipated overload, and treats invocation-to-invocation variations in resource requirements inflexibly. As a consequence, processing resources are often under-utilized in the average case, and the resulting systems are hard to adapt to meet new real-time processing requirements. Dynamic scheduling offers relief from the limitations of static scheduling. However, dynamic scheduling offers relief from the limitations of static scheduling. However, dynamic scheduling often has a high run-time cost because certain decisions are enforced on-line. Furthermore, under conditions of overload tasks can be scheduled dynamically that may never be dispatched, or that upon dispatch would miss their deadlines. We review the implications of these factors on rate-based distributed systems, and posits the necessity to combine static and dynamic approaches to exploit the strengths and compensate for the weakness of either approach in isolation. We present a general hybrid approach to real-time scheduling and dispatching in middleware, that can employ both static and dynamic components. This approach provides (1) feasibility assurance for the most critical tasks, (2) the ability to extend this assurance incrementally to operations in successively lower criticality equivalence classes, (3) the ability to trade off bounds on feasible utilization and dispatching over-head in cases where, for example, execution jitter is a factor or rates are not harmonically related, and (4) overall flexibility to make more optimal use of scarce computing resources and to enforce a wider range of application-specified execution requirements. This approach also meets additional constraints of an increasingly important class of rate-based systems, those with requirements for robust management of real-time performance in the face of rapidly and widely changing operating conditions. To support these requirements, we present a middleware framework that implements the hybrid scheduling and dispatching approach described above, and also provides support for (1) adaptive re-scheduling of operations at run-time and (2) reflective alternation among several scheduling strategies to improve real-time performance in the face of changing operating conditions. Adaptive re-scheduling must be performed whenever operating conditions exceed the ability of the scheduling and dispatching infrastructure to meet the critical real-time requirements of the system under the currently specified rates and execution times of operations. Adaptive re-scheduling relies on the ability to change the rates of execution of at least some operations, and may occur under the control of a higher-level middleware resource manager. Different rates of execution may be specified under different operating conditions, and the number of such possible combinations may be arbitrarily large. Furthermore, adaptive rescheduling may in turn require notification of rate-sensitive application components. It is therefore desirable to handle variations in operating conditions entirely within the scheduling and dispatching infrastructure when possible. A rate-based distributed real-time application, or a higher-level resource manager, could thus fall back on adaptive re-scheduling only when it cannot achieve acceptable real-time performance through self-adaptation. Reflective alternation among scheduling heuristics offers a way to tune real-time performance internally, and we offer foundational support for this approach. In particular, run-time observable information such as that provided by our metrics-feedback framework makes it possible to detect that a given current scheduling heuristic is underperforming the level of service another could provide. Furthermore we present empirical results for our framework in a realistic avionics mission computing environment. This forms the basis for guided adaption. This dissertation makes five contributions in support of flexible and adaptive scheduling and dispatching in middleware. First, we provide a middle scheduling framework that supports arbitrary and fine-grained composition of static/dynamic scheduling, to assure critical timeliness constraints while improving noncritical performance under a range of conditions. Second, we provide a flexible dispatching infrastructure framework composed of fine-grained primitives, and describe how appropriate configurations can be generated automatically based on the output of the scheduling framework. Third, we describe algorithms to reduce the overhead and duration of adaptive rescheduling, based on sorting for rate selection and priority assignment. Fourth, we provide timely and efficient performance information through an optimized metrics-feedback framework, to support higher-level reflection and adaptation decisions. Fifth, we present the results of empirical studies to quantify and evaluate the performance of alternative canonical scheduling heuristics, across a range of load and load jitter conditions. These studies were conducted within an avionics mission computing applications framework running on realistic middleware and embedded hardware. The results obtained from these studies (1) demonstrate the potential benefits of reflective alternation among distinct scheduling heuristics at run-time, and (2) suggest performance factors of interest for future work on adaptive control policies and mechanisms using this framework

Middleware Support for Aperiodic Tasks in Distributed Real-Time Systems

Many mission-critical distributed real-time applications must handle aperiodic tasks with end-to-end deadlines. However, existing middleware (e.g., RT-CORBA) lacks schedulability analysis and run-time enforcement mecha-nisms needed to give online real-time guarantees for ape-riodic tasks. The primary contribution of this work is the design, implementation, and performance evaluation of the first realization of deferrable server and admission control mechanisms for aperiodic tasks in middleware. Empirical results on a KURT-Linux testbed demonstrate the efficiency and effectiveness of our deferrable server and admission control mechanisms in TAO’s federated event service.

Performance evaluation of the reactor pattern using the OMNeT++ simulator

The design of large-scale, distributed, performance-sensitive systems presents numerous challenges due to their network-centric nature and stringent quality of service (QoS) require-ments. Standardized middleware implementations provide the key building blocks necessary to address these require-ments of the distributed systems. However, middleware are designed to be applicable for a wide range of domains and applications, which results in system developers requiring to choose the right set of building blocks to design their system. To reduce the impact on development costs and time-to-market, decisions on the right set of building blocks to use in systems design must be made as early as possible in system design. This paper addresses this concern by describ-ing a model-driven systems simulation approach to analyze, catch and rectify incorrect system design decisions at design-time. In this paper we focus on model-driven OMNeT++ simulation of the Reactor pattern, which provides event de-multiplexing and handling capability. Our experience with modeling the Reactor shows that this approach can be ex-tended to the performance analysis of other pattern-based blocks and indeed in the long term to the entire composed middleware framework

Timed Automata Models for Principled Composition of Middleware

Middleware for Distributed Real-time and Embedded (DRE) systems has grown more and more complex in recent years due to the varying functional and temporal requirements of complex real-time applications. To enable DRE middleware to be configured and customized to meet the demands of different applications, a body of ongoing research has focused on applying model-driven development techniques to developing QoS-enabled middleware. While current approaches for modeling middleware focus on easing the task of as-assembling, deploying and configuring middleware and middleware-based applications, a more formal basis for correct middleware composition and configuration in the context of individual applications is needed. While the modeling community has used application-level formal models that are more abstract to uncover certain flaws in system design, a more fundamental and lower-level set of models is needed to be able to uncover more subtle safety and timing errors introduced by interference between application computations, particularly in the face of alternative concurrency strategies in the middleware layer. In this research, we have examined how detailed formal models of lower-level middle-ware building blocks provide an appropriate level of abstraction both for modeling and synthesis of a variety of kinds of middleware from these building blocks. When combined with model checking techniques, these formal models can help developers in composing correct combinations of middleware mechanisms, and configuring those mechanisms for each particular application

Composable Models for Timing and Liveness Analysis in Distributed Real-Time Embedded Systems Middleware

Middleware for distributed real-time embedded (DRE) systems has grown increasingly complex, to address functional and temporal requirements of diverse applications. While current approaches to modeling middleware have eased the task of assembling, deploying and configuring middleware and the applications that use it, a lower-level set of formal models is needed to uncover subtle timing and liveness hazards introduced by interference between and within distributed computations, particularly in the face of alternative middleware concurrency strategies. In this paper, we propose timed automata as a formal model of low-level middleware building blocks from which a variety different middleware configurations can be constructed. When combined with analysis techniques such as model checking, this formal model can help developers in verifying the correctness of various middleware configurations with respect to the timing and liveness constraints of each particular application