14422830
Compiler-guided register reliability improvement against soft errors
With the scaling of technology, transient errors caused by external particle strikes have become a critical challenge for microprocessor design. As embedded processors are widely used in reliability-sensitive environments, it becomes increasingly important to develop cost-effective techniques to improve the processor reliability against soft errors. This paper focuses on studying the register file immunity against soft errors since modern processors typically employ a large number of registers, which are accessed very frequently. As a result, soft errors occurred in registers can easily propagate to functional units or the memory system, leading to silent data error (SDC) or system crash.To develop cost-effective techniques to fight soft errors for embedded processors, the first step is to understand the register file susceptibility to soft errors and its impact on the system reliability accurately. Toward this goal, this paper proposes the concept of register vulnerability factor (RVF) to characterize the probability that register transient errors can escape the register file and thus potentially impact the system reliability. Built upon the RVF concept, we then propose two cost-effective compiler-guided techniques to improve the register file reliability by lowering the RVF value. Our experiments indicate that on average, the RVF can be reduced to 9.1% and 9.5% by the hyperblock-based instruction re-scheduling and the reliability-oriented register assignment respectively, which can potentially lower the reliability cost significantly while protecting register files against transient errors.
9354212
High-Performance Job-Shop Scheduling With A Time-Delay TD-lambda Network
Job-shop scheduling is an important task for manufacturing industries. We are interested in the particular task of scheduling payload processing for NASA's space shuttle program. This paper summarizes our previous work on formulating this task for solution by the reinforcement learning algorithm T D(). A shortcoming of this previous work was its reliance on hand-engineered input features. This paper shows how to extend the time-delay neural network (TDNN) architecture to apply it to irregular-length schedules. Experimental tests show that this TDNN-TD() network can match the performance of our previous hand-engineered system. The tests also show that both neural network approaches signiicantly out-perform the best previous (non-learning) solution to this problem in terms of the quality of the resulting schedules and the number of search steps required to construct them.
17633305
The Impact of Cache Organization in Optimizing Microprocessor Power Consumption
In the recent years, power consumption has become increasingly an important design concern as silicon area and performance in modern computer systems design. Several factors have contributed to this trend. Perhaps the most visible have been the remarkable success and growth of Personal Digital Assistants (PDA’s), Cellular phones and pagers, etc .This work is an attempt to explore the impact of feature size shrinkage and cache configuration on optimizing power consumption in modern processors. The work studies two commercially known RISC microprocessors. The StrongARM and the Alpha-21064 microprocessors. The latter is the ancestor of the former and is therefore used here as the baseline in our analysis. Our analysis has illustrated quantitatively great power saving when technology is downsized and cache is well organized
43025995
Processing Probabilistic Range Query over Imprecise Data Based on Quality of Result
Sensors are employed in many applications to monitor entities such as environment temperature or illumination. Because of limited resources (e.g., battery power and wireless bandwidth), it is impractical for the database to track continuous changing readings from sensors at all times. Consequently, database may produce incorrect query results based on recorded data. However, if the error between the recorded value and the actual value is bounded, probabilistic approach can be applied to process queries over the imprecise data in database. The paper proposes a quality of result based probabilistic range query processing method. Two measures are defined to evaluate the quality of result. A probability model is proposed to estimate the quality of returned results. Based on the model, an algorithm is developed to choose the probability threshold according to user’s requirement on the quality of result.
12895493
Improvement of HITS-based algorithms on web documents
In this paper, we present two ways to improve the precision of HITS-based algorithms on Web documents. First, by analyzing the limitations of current HITS-based algorithms, we propose a new weighted HITS-based method that assigns appropriate weights to in-links of root documents. Then, we combine content analysis with HITS-based algorithms and study the effects of four representative relevance scoring methods, VSM, Okapi, TLS, and CDR, using a set of broad topic queries. Our experimental results show that our weighted HITS-based method performs significantly better than Bharat's improved HITS algorithm. When we combine our weighted HITS-based method or Bharat's HITS algorithm with any of the four relevance scoring methods, the combined methods are only marginally better than our weighted HITS-based method. Between the four relevance-scoring methods, there is no significant quality difference when they are combined with a HITS-based algorithm.
26485902
Identification of Crosscutting Requirements Based on Feature Dependency Analysis
Identification of crosscutting concerns at the requirements level is important for the modularization and evolution of requirements, and has attracted many research interests. This paper proposes a feature-oriented approach to the identification of crosscutting requirements based on feature dependency analysis. In this approach, features are used as basic elements to organize the requirements space, and two kinds of dynamic dependencies (i.e. interactions and weavings) between features are analyzed to find out the candidate crosscutting requirements and their influence on other requirements. A case study is also used to illustrate the application of this approach
60947848
Backbone Guided Local Search for Maximum Satisfiability
Maximum satisfiability (Max-SAT) is more general and more difficult to solve than satisfiability (SAT). In this paper, we first investigate the effectiveness of Walksat, one of the best local search algorithms designed for SAT, on Max-SAT. We show that Walksat is also effective on Max-SAT, while its effectiveness degrades as the problem is more constrained. We then develop a novel method that exploits the backbone information in the local minima from Walksat and applies the backbone information in different ways to improve the performance of the Walksat algorithm. We call our new algorithm backbone guided Walksat (BGWalksat). On large random SAT and Max-SAT problems as well as instances from the SATLIB, BGWalksat significantly improves Walksat's performance.
43120880
Principle component analysis and its variants for biometrics
Principle component analysis (PCA) has been widely used for analyzing the statistics of data. While applied to biometrics as a classification scheme, PCA faces certain challenges. We present a number of modifications to PCA in order to meet these challenges. Using face recognition as an example, we show how eigenflow, PCA applied to optimal flow, enables us to measure the difference between two images while allowing expression changes and registration error. We show how PCA can be updated to model time-varying statistics. We also show that PCA can be used to model the surface reflectance of human faces and reduce illumination variation that defeats most existing face recognition algorithms. Finally, we present distinguishing component analysis (DCA) and apply it to multimodal biometric authentication.
570616
Least privilege and privilege deprivation: towards tolerating mobile sink compromises in wireless sensor networks
Mobile sinks are needed in many sensor network applications for efficient data collection, data querying, localized sensor reprogramming, identifying and revoking compromised sensors, and other network maintenance. Employing mobile sinks however raises a new security challenge: if a mobile sink is given too many privileges, it will become very attractive for attack and compromise. Using a compromised mobile sink, an adversary may easily bring down or even take over the sensor network. Thus, security mechanisms that can tolerate mobile sink compromises are essential. In this paper, based on the principle of least privilege, we first propose several efficient schemes to restrict the privilege of a mobile sink without impeding its capability of carrying out any authorized operations for an assigned task. To further reduce the possible damages caused by a compromised mobile sink, we then propose efficient message forwarding schemes for depriving the privilege assigned to a compromised mobile sink immediately after its compromise has been detected. Through detailed analysis and simulations, we show that our schemes are secure and efficient, and are highly practical for sensor networks consisting of the current generation of sensors.
16468092
Group rekeying for filtering false data in sensor networks: a predistribution and local collaboration-based approach
When a sensor network is deployed in hostile environments, the adversary may compromise some sensor nodes, and use the compromised nodes to inject false sensing reports or modify the reports sent by other nodes. In order to defend against the attacks with low cost, researchers have proposed symmetric group key-based en-route filtering schemes, such as SEF [F. Ye et al., March 2004] and I-LHAP [S. Zhu et al., 2004]. However, if the adversary has compromised a large number of nodes, many group keys can be captured, and the filtering schemes may become ineffective or even useless. To deal with node compromise, the compromised nodes should be identified and the innocent nodes should update their group keys. Some existing intruder identification schemes can be used to identify the compromised nodes, but most existing group rekeying schemes are not suitable for sensor networks since they have large overhead and are not scalable. To address the problem, we propose a family of predistribution and local collaboration-based group rekeying (PCGR) schemes. These schemes are designed based on the ideas that future group keys can be preloaded to the sensor nodes before deployment, and neighbors can collaborate to protect and appropriately use the preloaded keys. Extensive analyses and simulations are conducted to evaluate the proposed schemes, and the results show that the proposed schemes can achieve a good level of security, outperform most previous group rekeying schemes, and significantly improve the effectiveness of filtering false data.
30318957
Replication cache: a small fully associative cache to improve data cache reliability
Soft error conscious cache design has become increasingly crucial for reliable computing. The widely used ECC or parity-based integrity checking techniques have only limited capability in error detection and correction, while incurring nontrivial penalty in area or performance. The N modular redundancy (NMR) scheme is too costly for processors with stringent cost constraints. This paper proposes a cost-effective solution to enhance data reliability significantly with minimum impact on performance. The idea is to add a small fully associative cache to store the replica of every write to the L1 data cache. Due to data locality and its full associativity, the replication cache can be kept small while providing replicas for a significant fraction of read hits in L1, which can be used to enhance data integrity against soft errors. Our experiments show that a replication cache with eight blocks can provide replicas for 97.3 percent of read hits in L1 on average. Moreover, compared with the recently proposed in-cache replication schemes, the replication cache is more energy efficient, while improving the data integrity against soft errors significantly.