Buffer management in real-time active database systems
Real-time active database systems (RTADB) have attracted the attention of researchers in recent times. Such systems are envisioned as control systems for environments as diverse as process control, network management and automated financial trading. Sensors distributed throughout the system report the state of the system to the database. Unacceptable state reports typically results in corrective actions being triggered with deadlines. Thus RTADB's incorporate both real-time as well as active characteristics. We study buffer management in RTADB. Buffer management is recognized as not being a well studied area in real-time systems. As a result of our work, we postulate PAPER, a new buffer management scheme that relies on two strategies: prefetching and priority based buffer replacement. We report the result of studies of the performance of PAPER, as compared to that of existing buffer management algorithms. The insights derived from this paper impact both real-time database systems as well as real-time, active database systems.

title: MANDATE: MAnaging Networks Using DAtabase TEchnology
abstract: There has been a growing demand for the development of tools to manage enterprise communication networks. A management information database is the heart of a network management system-it provides the interface between all functions of the network management system and, therefore, has to provide sophisticated functionality allied with high performance. The authors introduce the design of MANDATE (MAnaging Networks using DAtabase TEchnology), a proposed database system for effectively supporting the management of large enterprise networks. The MANDATE design makes a conscious attempt to take advantage of the special characteristics of network data and transactions, and of advances in database technology, to efficiently derive some of the required management functionality.

title: Handling Sensor Data in Rapidly Changing Environments to Support Soft Real-Time Requirements
abstract: Databases have been mandated as the chosen platform to develop automated control systems for environments where the state of the system changes rapidly and actions need to be taken with timing constraints, for example, stock trading, air traffic control, network management, and process control to name a few. Input data in such systems come from sensors distributed throughout the physical environment being monitored. As the system state changes rapidly, the sensors report information fast and with high volumes. Control decisions in such systems are highly dependent on the accuracy and timeliness of such recorded sensor-reported data. In this paper we suggest ways to algorithmically maintain the accuracy and timeliness of sensor data by enforcing two properties termedrecency andtemporal consistency. Simultaneously, our algorithms also attempt to satisfyquality of service requirements on response times of queries submitted in such systems. The performance of these algorithms is validated through an extensive simulation.

title: Deterministic /spl delta/-connected overlay for peer-to-peer networks
abstract: The network connectivity is a basic requirement while implementing fundamental communication and storage abstractions in P2P networks, featuring scalability and fault-tolerance. The quality of services of abstractions like for example multicast, publish/subscribe, group membership or persistent storage is strongly related to the connectivity degree of the underlying overlay. Intuitively, a higher overlay connectivity ensures a reinforced reliability and consequently, the deployment of distributed applications with real-time constraints on top of these overlays becomes feasible even in environments characterized by a high dynamicity, i.e., nodes arriving and departing at a high rate. Our paper proposes a novel delta-connected DHT-free P2P overlay. Our overlay offers strong connectivity guarantees despite the system dynamicity. The construction and the maintenance of our overlay is completely decentralized and handled strictly locally, through deterministic algorithms whose correctness is rigorously proved

title: Stabilizing mobile philosophers
abstract: We present a self-stabilizing solution to a new version of the dining philosophers problem. We call this problem mobile philosophers problem because the philosophers can move around a logical ring formed out of a dynamic network.

title: A proxy-based approach for dynamic content acceleration on the WWW
abstract: Various dynamic content caching approaches have been proposed to address the performance and scalability problems faced by many Web sites that utilize dynamic content generation applications. Proxy-based caching approaches store content at various locations outside the site infrastructure and can improve Web site performance by reducing content generation delays, firewall processing delays, and bandwidth requirements. However, existing proxy-based caching approaches either: (a) cache at the page level, which does not guarantee that correct pages are served and provides very limited reusability, or (b) cache at the fragment level, which requires the use of pre-defined page layouts. To address these issues, several back end caching approaches have been proposed, including query result caching and fragment level caching. While back end approaches guarantee the correctness of results and offer the advantages of fine-grained caching, they neither address firewall delays nor reduce bandwidth requirements. The authors present an approach and an implementation of a dynamic proxy caching technique which combines the benefits of both proxy-based and back end caching approaches, yet does not suffer from their above-mentioned limitations.

title: Generating Boolean networks with a prescribed attractor structure
abstract: Dynamical modeling of gene regulation via network models constitutes a key problem for genomics. The long-run characteristics of a dynamical system are critical and their determination is a primary aspect of system analysis. In the other direction, system synthesis involves constructing a network possessing a given set of properties. This constitutes the inverse problem. Generally, the inverse problem is ill-posed, meaning there will be many networks, or perhaps none, possessing the desired properties. Relative to long-run behavior, we may wish to construct networks possessing a desirable steady-state distribution. This paper addresses the long-run inverse problem pertaining to Boolean networks (BNs).



The long-run behavior of a BN is characterized by its attractors. The rest of the state transition diagram is partitioned into level sets, the j-th level set being composed of all states that transition to one of the attractor states in exactly j transitions. We present two algorithms for the attractor inverse problem. The attractors are specified, and the sizes of the predictor sets and the number of levels are constrained. Algorithm complexity and performance are analyzed. The algorithmic solutions have immediate application. Under the assumption that sampling is from the steady state, a basic criterion for checking the validity of a designed network is that there should be concordance between the attractor states of the model and the data states. This criterion can be used to test a design algorithm: randomly select a set of states to be used as data states; generate a BN possessing the selected states as attractors, perhaps with some added requirements such as constraints on the number of predictors and the level structure; apply the design algorithm; and check the concordance between the attractor states of the designed network and the data states.


AVAILABILITY
The software and supplementary material is available at http://gsp.tamu.edu/Publications/BNs/bn.htm

title: Intervention in a family of Boolean networks
abstract: Intervention in a gene regulatory network is used to avoid undesirable states, such as those associated with a disease. Several types of intervention have been studied in the framework of a probabilistic Boolean network (PBN), which is a collection of Boolean networks in which the gene state vector transitions according to the rules of one of the constituent networks and where network choice is governed by a selection distribution. The theory of automatic control has been applied to find optimal strategies for manipulating external control variables that affect the transition probabilities to desirably affect dynamic evolution over a finite time horizon. In this paper we treat a case in which we lack the governing probability structure for Boolean network selection, so we simply have a family of Boolean networks, but where these networks possess a common attractor structure. This corresponds to the situation in which network construction is treated as an ill-posed inverse problem in which there are many Boolean networks created from the data under the constraint that they all possess attractor structures matching the data states, which are assumed to arise from sampling the steady state of the real biological network.



Given a family of Boolean networks possessing a common attractor structure composed of singleton attractors, a control algorithm is derived by minimizing a composite finite-horizon cost function that is a weighted average over all the individual networks, the idea being that we desire a control policy that on average suits the networks because these are viewed as equivalent relative to the data. The weighting for each network at any time point is taken to be proportional to the instantaneous estimated probability of that network being the underlying network governing the state transition. The results are applied to a family of Boolean networks derived from gene-expression data collected in a study of metastatic melanoma, the intent being to devise a control strategy that reduces the WNT5A gene's action in affecting biological regulation.


AVAILABILITY
The software is available on request.



The supplementary Information is available at http://ee.tamu.edu/~edward/tree