Krithi Ramamritham

Real-time databases

Data in real-time databases has to be logically consistent as well as temporally consistent. The latter arises from the need to preserve the temporal validity of data items that reflect the state of the environment that is being controlled by the system. Some of the timing constraints on the transactions that process real-time data come from this need. These constraints, in turn, necessitate time-cognizant transaction processing so that transactions can be processed to meet their deadlines.This paper explores the issues in real-time database systems and presents an overview of the state of the art. After introducing the characteristics of data and transactions in real-time databases, we discuss issues that relate to the processing of time-constrained transactions. Specifically, we examine different approaches to resolving contention over data and processing resources. We also explore the problems of recovery, managing I/O, and handling overloads. Real-time databases have the potential to trade off the quality of the result of a query or a transaction for its timely processing. Quality can be measured in terms of the completeness, accuracy, currency, and consistency of the results. Several aspects of this trade-off are also considered.

Scheduling algorithms and operating systems support for real-time systems

This paper summarizes the state of the real-time field in the areas of scheduling and operating system kernels. Given the vast amount of work that has been done by both the operations research and computer science communities in the scheduling area, we discuss four paradigms underlying the scheduling approaches and present several exemplars of each. The four paradigms are: static table-driven scheduling, static priority preemptive scheduling, dynamic planning-based scheduling, and dynamic best effort scheduling. In the operating system context, we argue that most of the proprietary commercial kernels as well as real-time extensions to time-sharing operating system kernels do not fit the needs of predictable realtime systems. We discuss several research kernels that are currently being built to explicitly meet the needs of real-time applications. >

Efficient scheduling algorithms for real-time multiprocessor systems

Efficient scheduling algorithms based on heuristic functions are developed for scheduling a set of tasks on a multiprocessor system. The tasks are characterized by worst-case computation times, deadlines, and resources requirements. Starting with an empty partial schedule, each step of the search extends the current partial schedule by including one of the tasks yet to be scheduled. The heuristic functions used in the algorithm actively direct the search for a feasible schedule, i.e. they help choose the task that extends the current partial schedule. Two scheduling algorithms are evaluated by simulation. To extend the current partial schedule, one of the algorithms considers, at each step of the search, all the tasks that are yet to be scheduled as candidates. The second focuses its attention on a small subset of tasks with the shortest deadlines. The second algorithm is shown to be very effective when the maximum allowable scheduling overhead is fixed. This algorithm is hence appropriate for dynamic scheduling in real-time systems. >

Distributed scheduling of tasks with deadlines and resource requirements

A set of four heuristic algorithms is presented to schedule tasks that have headlines and resource requirements in a distributed system. When a task arrives at a node, the local scheduler at that node attempts to guarantee that the task will complete execution on that node before its deadline. If the attempt fails, the scheduling components on individual nodes cooperate to determine which other node in the system has sufficient resource surplus to guarantee the task. Simulation studies are performed to compare the performance of these algorithms with respect to each other as well to two baselines. The first baseline is the noncooperative algorithm where a task that cannot be guaranteed locally is not sent to any other node. The second is an (ideal) algorithm that behaves exactly like the bidding algorithm but incurs no communication overheads. The simulation studies examine how communication delay, task laxity, load differences on the nodes, and task computation times affect the performance of the algorithms. The results show that distributed scheduling is effective even in a hard real-time environment and that the relative performance of these algorithms is a function of the system state. >

Verifying completeness of relational query results in data publishing

In data publishing, the owner delegates the role of satisfying user queries to a third-party publisher. As the publisher may be untrusted or susceptible to attacks, it could produce incorrect query results. In this paper, we introduce a scheme for users to verify that their query results are complete (i.e., no qualifying tuples are omitted) and authentic (i.e., all the result values originated from the owner). The scheme supports range selection on key and non-key attributes, project as well as join queries on relational databases. Moreover, the proposed scheme complies with access control policies, is computationally secure, and can be implemented efficiently.

Synthesis of extended transaction models using ACTA

ACTA is a comprehensive transaction framework that facilitates the formal description of properties of extended transaction models. Specifically, using ACTA, one can specify and reason about (1) the effects of transactions on objects and (2) the interactions between transactions. This article presents ACTA as a tool for the synthesis of extended transaction models, one which supports the development and analysis of new extended transaction models in a systematic manner. Here, this is demonstrated by deriving new transaction definitions (1) by modifying the specifications of existing transaction models, (2) by combining the specifications of existing models, and (3) by starting from first principles. To exemplify the first, new models are synthesized from atomic transactions and join transactions. To illustrate the second, we synthesize a model that combines aspect of the nested- and split-transaction models. We demonstrate the latter by deriving the specification of an open-nested-transaction model from high-level requirements.

What is predictability for real-time systems?

ConclusionIn summary, predictability in real-time systems has been defined in many ways. For static real-time systems we can predict the overall system performance over large time frames (even over the life of the system) as well as predict the performance of individual tasks. If the prediction is that 100% of all tasks over the entire life of the system will meet their deadlines, then the system is predictable without resorting to any stochastic evaluation. In dynamic real-time systems we must resort to a stochastic evaluation for part of the performance evaluation. Predictability for these systems should mean that we are able to satisfy the timing requirements of critical tasks with 100% guarantee over the life of the system, be able to assess overall system performance over various time frames (a stochastic evaluation), and be able to assess individual task and task group performance at different times and as a function of the current system state. If all these assessments meet the timing requirements, then the system is predictable with respect to its timing requirements.

Dynamic Task Scheduling in Hard Real-Time Distributed systems

This algorithm for scheduling tasks with hard real-time constraints—that is, tasks that must meet their deadlines-works dynamically on loosely coupled distributed systems.

Allocation and scheduling of precedence-related periodic tasks

This paper discusses a static algorithm for allocating and scheduling components of periodic tasks across sites in distributed systems. Besides dealing with the periodicity constraints, (which have been the sole concern of many previous algorithms), this algorithm handles precedence, communication, as well as replication requirements of subtasks of the tasks. The algorithm determines the allocation of subtasks of periodic tasks to sites, the scheduled start times of subtasks allocated to a site, and the schedule for communication along the communication channel(s). Simulation results show that the heuristics and search techniques incorporated in the algorithm are very effective. >

Allocation and scheduling of complex periodic tasks

A static algorithm for allocating and scheduling components of complex periodic tasks across sites in distributed systems is discussed. Besides dealing with the periodicity constraints (which have been the sole concern of many previous algorithms), this algorithm handles precedence, communication, and fault-tolerance requirements of subtasks of the tasks. The algorithm determines the allocation of subtasks of periodic tasks to sites, the scheduled start times of subtasks allocated to a site, and the schedule for communication along the communication channel(s). Experimental evaluation of the algorithm shows that the heuristics and search techniques incorporated in the algorithm are extremely effective. Specifically, they show that, if a task set can be feasibly allocated and scheduled, the algorithm is highly likely to find it without any backtracking during the search.<<ETX>>