Priority inheritance in soft real-time databases

Due to resource sharing among tasks, priority inversion can occur during priority-driven preemptive scheduling. In this work, we investigate solutions to the priority inversion problem in a soft real-time database environment where two-phhse locking is employed for concurrency control. We examine two basic schemes for addressing the priority inversion problem, one based on priority inheritance and the other based on priority abort. We also study a new scheme, called conditional priority inheritance, which attempts to capitalize on the advantages of each of the two basic schemes. In contrast with previous results obtained in real-time operating systems, our performance studies, conducted on an actual real-time database testbed, indicate that the basic priority inheritance protocol is inappropriate for solving the priority inversion problem in real-time database systems. We identify the reasons for this performance. We also show that the conditional priority inheritance scheme and the priority abort scheme perform well for a wide range of system workloads.This work was supported by the National Science Foundation under Grant IRI-8908693 and by the U.S. Office of Naval Research under Grant N00014-85-K0398.A previous version of this paper appeared in Real-Time Systems Symposium, Dec. 1991.     

Implications of proxy caching for provisioning networks and servers

In this paper, we examine the potential benefits of Web proxy caches in improving the effective capacity of servers and networks. Since networks and servers are typically provisioned based on a high percentile of the load, we focus on the effects of proxy caching on the tail of the load distribution. We find that, unlike their substantial impact on the average load, proxies have a diminished impact on the tail of the load distribution. The exact reduction in the tail and the corresponding capacity savings depend on the nature of the workload and the percentile of the load distribution chosen for provisioning networks and servers-the higher the percentile, the smaller the savings. For workloads considered in this study, compared with over a 50% reduction in the average load, the savings in network and server capacity was only 20%-35% for the 99th percentile of the load distribution. We also find that while proxies can be somewhat useful in smoothing out some of the burstiness in Web workloads; the resulting workload continues, however, to exhibit substantial burstiness and a heavy-tailed nature. We identify one-time requests for large objects to be the limiting factor that diminishes the impact of proxies on the tail of load distribution. We conclude that, while proxies are immensely useful to users due to the reduction in the average response time, they are less effective in improving the capacities of networks and servers.     

The Spring kernel: a new paradigm for real-time systems

A real-time operating system kernel, called the Spring kernel, that provides some of the basic support required for large, complex, next-generation real-time systems, especially in meeting timing constraints, is presented. The approach meets the need to build predictable yet flexible real-time systems. Most current real-time operating systems contain the same basic paradigms found in time-sharing operating systems and often use a basic priority-scheduling mechanism that provides no direct support for meeting timing constraints. Spring uses two criteria to classify tasks' interaction with and effects on the environment: importance and timing requirements. Implementation experience with Spring is described     

A formal characterization of epsilon serializability

Epsilon serializability (ESR) is a generalization of classic serializability (SR). In this paper, we provide a precise characterization of ESR when queries that may view inconsistent data run concurrently with consistent update transactions. Our first goal is to understand the behavior of queries in the presence of conflicts and to show how ESR in fact is a generalization of SR. So, using the ACTA framework, we formally express the intertransaction conflicts that are recognized by ESR and through that define ESR, analogous to the manner in which conflict-based serializability is defined. Secondly, expressions are derived for the amount of inconsistency (in a data item) viewed by a query and its effects on the results of a query. These inconsistencies arise from concurrent updates allowed by ESR. Thirdly, in order to maintain the inconsistencies within bounds associated with each query, the expressions are used to determine the preconditions that operations have to satisfy. The results of a query, and the errors in it, depend on what a query does with the (possibly inconsistent) data viewed by it. One of the important byproducts of this work is the identification of different types of queries which lend themselves to an analysis of the effects of data inconsistency on the results of the query     

Enabling local actions by global consensus

Presented is an algorithm for determining whether total global consensus exists for a process to execute a local action that has interaction constraints. The algorithm assumes a virtual ring of processes each of which possesses a token. Multiple processes can simultaneously attempt and succeed in performing actions that do not constrain each other, thus exploiting the available parallelism. The algorithm can be tailored to handle any situation in which the action of one process is constrained by actions of other processes and where total global consensus is required. The use of execution time estimates and information concerning the attempts and activities of other processes reduces the number of failed attempts and hence unnecessary communication.     

The PROMPT real-time commit protocol

We investigate the performance implications of providing transaction atomicity for firm-deadline real-time applications, operating on distributed data. Using a detailed simulation model, the real-time performance of a representative set of classical transaction commit protocols is evaluated. The experimental results show that data distribution has a significant influence on real-time performance and that the choice of commit protocol clearly affects the magnitude of this influence. We also propose and evaluate a new commit protocol, PROMPT (Permits Reading Of Modified Prepared-data for Timeliness), that is specifically designed for the real-time domain. PROMPT allows transactions to “optimistically” borrow, in a controlled manner, the updated data of transactions currently in their commit phase. This controlled borrowing reduces the data inaccessibility and the priority inversion that is inherent in distributed real-time commit processing. A simulation-based evaluation shows PROMPT to be highly successful, as compared to the classical commit protocols, in minimizing the number of missed transaction deadlines. In fact, its performance is close to the best on-line performance that could be achieved using the optimistic lending approach. Further, it is easy to implement and incorporate in current database system software. Finally, PROMPT is compared against an alternative priority inheritance-based approach to addressing priority inversion during commit processing. The results indicate that priority inheritance does not provide tangible performance benefits     

To Schedule or to Execute: Decision Support and Performance Implications

This paper addresses a fundamental trade-off in dynamic scheduling between the cost of scheduling and the quality of the resulting schedules. The time allocated to scheduling must be controlled explicitly, in order to obtain good-quality schedules in reasonable times. As task constraints are relaxed, the algorithms proposed in this paper increase scheduling complexity to optimize longer and obtain high-quality schedules. When task constraints are tightened, the algorithms adjust scheduling complexity to reduce the adverse effect of long scheduling times on the schedule quality. We show that taking into account the scheduling time is crucial for honoring the deadlines of scheduled tasks. We investigate the performance of our algorithms in two scheduling models: one that allows idle-time intervals to exist in the schedule and another that does not. The model with idle-time intervals has important implications for dynamic scheduling which are discussed in the paper. Experimental evaluation of the proposed algorithms shows that our algorithms outperform other candidate algorithms in several parameter configurations.     

A survey of sensory data boundary estimation,covering and tracking techniques using collaborating sensors

Boundary estimation and tracking have important applications in the areas of environmental monitoring and disaster management. A boundary separates two regions of interest in a phenomenon. It can be visualized as an edge if there is a sharp change in the field value between the two regions or alternatively, as a contour with a field value $f=\tau$ separating two regions with field values $f>\tau$ and $f<\tau$. Examples include contours/boundaries of hazardous concentration in a pollutant spill, frontal boundary of a forest fire, isotherms, isohalines etc. Recent advances in the area of embedded sensor devices and robotics have led to deployments of networks of sensors capable of sensing, computing, communication and mobility. They are used to estimate the boundaries of interest in physical phenomena, monitor or track them over time and also in some cases, mitigate the spatial spread of the phenomena. Since these sensors work autonomously in the environment, minimizing the energy consumed while maximizing the accuracy of estimation or tracking is the main challenge for algorithms for boundary estimation and tracking. Several algorithms with these objectives have been proposed in the literature. In this work, we focus on the algorithms that estimate and cover boundaries found in the sensory data in a field and not the topological boundary of the sensor network per se, which is beyond the scope of this paper.Here, our objective is to provide a comprehensive survey of the algorithms for boundary estimation and tracking by providing a taxonomy based on two broad categories — (i) Boundary estimation and tracking, where the sensors estimate the boundary without physically covering the boundary and (ii) Boundary covering — where the sensors not only predict the location and estimate the entire boundary but also physically cover the boundary by surrounding and bounding it. We further classify the techniques based on (a) sensing capabilities —in situ, range or remote sensing (b) movement capabilities — static or mobile sensors and (c) boundary type — static or dynamic and (d) type of estimation — field estimation where the entire field is sampled to search for contours and localized estimation where sampling is done near the boundary and (e) different types of mobility models in the case of mobile sensors. We believe that such a survey has not been performed before. By capturing and classifying the current state-of-the-art and identifying open research problems, we hope to ignite interest and stimulate efforts towards promising solutions for real-world boundary estimation and tracking problems.     

Scheduling transactions with temporal constraints: exploiting data semantics

In this paper, issues involved in the design of a real-time database which maintains data temporal consistency are discussed. The concept of data-deadline is introduced and time cognizant transaction scheduling policies are proposed. Informally, data-deadline is a deadline assigned to a transaction due to the temporal constraints of the data accessed by the transaction. Further, two time cognizant forced wait policies which improve performance significantly by forcing a transaction to delay further execution until a new version of sensor data becomes available are proposed. A way to exploit temporal data similarity to improve performance is also proposed. Finally, these policies are evaluated through detailed simulation experiments. The simulation results show that taking advantage of temporal data semantics in transaction scheduling can significantly improve the performance of user transactions in realtime database systems. In particular, it is demonstrated that under the forced wait policy, the performance can be improved significantly. Further improvements result by exploiting data similarity.