749990
Optimal Checkpointing of Real-Time Tasks
Analytical models for the design and evaluation of checkpointing of real-time tasks are developed. First, the execution of a real-time task is modeled under a common assumption of perfect coverage of on-line detection mechanisms (which is termed a basic model). Then, the model is generalized (to an extended model) to include more realistic cases, i.e., imperfect coverages of on-line detection mechanisms and acceptance tests. Finally, we determine an optimal placement of checkpoints to minimize the mean task execution time while the probability of an unreliable result (or lack of confidence) is kept below a specified level. In the basic model, it is shown that equidistant intercheckpoint intervals are optimal, whereas this is not necessarily true in the extended model. An algorithm for calculating the optimal number of checkpoints and intercheckpoint intervals is presented with some numerical examples for the extended model.
40618061
Transaction Recovery in Distributed DB/DC Systems: A Progressive Approach
920212
Resource scheduling in dependable integrated modular avionics
In the recent development of avionics systems, integrated modular avionics (IMA) is advocated for next generation architecture that needs integration of mixed criticality real-time applications. These integrated applications meet their own timing constraints while sharing avionics computer resources. To guarantee timing constraints and dependability of each application, an IMA-based system is equipped with the schemes for spatial and temporal partitioning. We refer the model as SP-RTS (strongly partitioned real-time system), which deals with processor partitions and communication channels as its basic scheduling entities. This paper presents a partition and channel-scheduling algorithm for the SP-RTS. The basic idea of the algorithm is to use a two-level hierarchical schedule that activates partitions (or channels) following a distance-constraints guaranteed cyclic schedule and then dispatches tasks (or messages) according to a fixed priority schedule. To enhance schedulability, we devised heuristic algorithms for deadline decomposition and channel combining. The simulation results show the schedulability analysis of the two-level scheduling algorithm and the beneficial characteristics of the proposed deadline decomposition and channel combining algorithms.
31591898
Scanning the issue - special issue on real-time systems
10753893
Evaluation of Error Recovery Blocks Used for Cooperating Processes
Three alternatives for implementing recovery blocks (RB's) are conceivable for backward error recovery in concurrent processing. These are the asynchronous, synchronous, and the pseudorecovery point implementations. Asynchronous RB's are based on the concept of maximum autonomy in each of concurrent processes. Consequently, establishment of RB's in a process is made independently of others and unbounded rollback propagations become a serious problem. In order to completely avoid unbounded rollback propagations, it is necessary to synchronize the establishment of recovery blocks in all cooperating processes. Process autonomy is sacrificed and processes are forced to wait for commitments from others to establish a recovery line, leading to inefficiency in time utilization. As a compromise between asynchronous and synchronous RB's we propose to insert pseudorecovery points (PRP's) so that unbounded rollback propagations may be avoided while maintaining process autonomy. We developed probabilistic models for analyzing these three methods under standard assumptions in computer performance analysis, i.e., exponential distributions for related random variables. With these models we have estimated 1) the interval between two successive recovery lines for asynchronous RB's, 2) mean loss in computation power for the synchronized method, and 3) additional overhead and rollback distance in case PRP's are used.
30590203
Efficient State-Saving Architectures for Power-Mode Switching
Time and energy is expended in switching between power modes (e.g., active, hibernate, sleep, etc.). Powering off cache is one major reason for this. When there is a switch in the power-mode involving cache power-off, the system spends time and energy in filling the cache with new data (inherent cache misses). In our technique, before powering off the cache, we save its state in Embedded DRAM and bring it back when the previous power mode is restored. Our experiments have showed that in a majority of cases the cache contents are too valuable to be erased. By saving the contents we can reduce switching speed and energy. We present a heuristic to save the most relevant cache contents so that power and delay overheads are minimized. To measure the area overhead a synthesizable VHDL model was designed.
16907116
Enhancing the Fuzzy Set Model with Positively Compensatory Operators
The conventional fuzzy set model uses the MIN and MAX operators for the evaluation of boolean operators AND and OR, respectively. It has been criticized to generate incorrect ranked output in many cases. This is because the MIN and MAX operators do not well correspond with human behavior for document ranking. There are a variety of fuzzy operators to replace the MIN and MAX operators. In this paper we first investigate the behavioral aspects of the fuzzy operators and address important issues to affect retrieval effectiveness. We then present the enhanced fuzzy set model based on positively compensatory operators, which are suitable for achieving high retrieval effectiveness. It is also shown through experiments that the enhanced fuzzy set model provides similar retrieval effectiveness and higher retrieval efficiency in comparison with the extended boolean model.
14604625
Single run optimization using the reverse-simulation method
An efticient “Simulation Optimization” technique is developed to solve system design problems which can not be expressed in explicit analytical or mathematical models. In particular, we explore a new paradigm called the “Reverse-Simulation optimization method” which is quite Merent from current simulation optimization methods in the literature. This paper focuses on the method of on-line determination of steady-state, which is a very important issue in ReverseSimulation optimization, and the construction of a Reverse-Simulation algorithm with expert systems. The proposed algorithm finds the steady-state of a system and an optimal state. The algorithm employs the Lyapunov exponent of Chaos theory to determine both the steady-state and optimal state of a system.
14229192
Ranking Documents in Thesaurus-Based Boolean Retrieval Systems
Abstract In this paper we investigate document ranking methods in thesaurus-based boolean retrieval systems, and propose a new thesaurus-based ranking algorithm called the Extended Relevance (E-Relevance) algorithm. The E-Relevance algorithm integrates the extended boolean model and the thesaurus-based relevance algorithm. Since the E-Relevance algorithm has all the desirable properties of the extended boolean model, it avoids the various problems of previous thesaurus-based ranking algorithms. The E-Relevance algorithm also ranks documents effectively by using term dependence information from the thesaurus. We have shown through performance comparison that the proposed algorithm achieves higher retrieval effectiveness than the others proposed earlier.
9799056
Fitting via alternative random-effect models
When there are two alternative random-effect models leading to the same marginal model, inferences from one model can be used for the other model. We illustrate how a likelihood method for fitting models with independent random effects can be applied to seemingly very different models with correlated random effects. We also discuss some merits of using these alternative models.
404374
The Learning and Emergence of Mildly Context Sensitive Languages
This paper describes a framework for studies of the adaptive acquisition and evolution of language, with the following components: language learning begins by associating words with cognitively salient representations (“grounding”); the sentences of each language are determined by properties of lexical items, and so only these need to be transmitted by learning; the learnable languages allow multiple agreements, multiple crossing agreements, and reduplication, as mildly context sensitive and human languages do; infinitely many different languages are learnable; many of the learnable languages include infinitely many sentences; in each language, inferential processes can be defined over succinct representations of the derivations themselves; the languages can be extended by innovative responses to communicative demands. Preliminary analytic results and a robotic implementation are described.