10440176
Task assignment with imprecise information for real-time operation in a supply chain
Abstract Real-time operation is often required in a supply chain, where it is desirable to re-optimize the schedules each time a new order is submitted. An organization in a supply chain may not be able to perform all the tasks it has received completely due to lack of resources. It has to delegate those subtasks which it cannot perform to its suppliers in the supply chain. In a practical situation, the suppliers may be parts of more than one supply chain. Hence the organization does not have a complete control over the schedules of its suppliers. There should be coordination within and across organizations for producing the schedules. Usually, multiple objectives (or criteria) like quality, cost, and duration are associated with a task. Preference ratings, assigned by the end-user or the organization itself, may be associated with these criteria. The preference ratings may be specified in an imprecise manner by using ordinal values or linguistic terms. The assignment of the tasks to the suppliers, which is a multiobjective decision making problem, has to be done quickly for real-time operation. In this paper, a supply chain is first modeled using a multiagent framework and an architecture for the agents located at every organization in the chain is presented. We then propose a real-time scheduler that can schedule new orders with soft real-time deadlines. An algorithm for the task assignment using the fuzzy set approach for the real-time operation in a supply chain is then proposed. Comparison of the algorithm versus other commonly used heuristic methods for task assignment is done in a simulated environment. The experimental results show significant performance gains for a large range of task arrival rates. However, the performance deteriorates for very high arrival rates. In order to overcome this limitation, we present a hybrid algorithm that augments the fuzzy technique and does not suffer from performance degradation even for high arrival rates.
65058359
Group Based Routing in Disconnected Ad Hoc Networks
In this paper, we propose a routing protocol for disconnected ad hoc networks where most nodes tend to move about in groups. To the best of our knowledge, no routing protocol for disconnected ad hoc networks has been designed earlier keeping in mind possible group patterns formed by the movement of nodes. Our protocol works by identifying groups using an efficient distributed group membership protocol, and then routing at the group level, rather than at the node level. The protocol is designed so that existing concepts of routing in disconnected ad hoc networks can be extended to work at the group level. Initial simulations across a broad spectrum of parameters suggest that our protocol performs better in terms of delivery ratio and latency over traditional approaches like AODV [1], and also over disconnected routing approaches like the 2-Hop routing protocol [2].
22674996
Estimating Link Characteristics of Internet Paths With FPathchar
RESEARCH PROJECTS Understanding the design tradeoffs of cooperative streaming multicast: Cooperative end-system multicast (CEM) is emerging as a promi sing paradigm for video distribution since the bandwidth overhead of dissemi nating content is shared among the participants themselves. Prior research in CEMs h as focused either on the design of new protocols or on comparisons of complete sys tems. However, the inherent tradeoffs between different CEM designs, particu larly under a wide range of operating conditions, are not well understood. In this wo rk [1], we empirically and systematically evaluate CEM design choices. We synthes ize our results into a model that captures the inherent tradeoffs in CEMs, which i n particular, conjectures that no CEM design can simultaneously achieve low over head, low lag, and high streaming quality.
1713935
Designing Caching Strategies for Common NFS Workloads
9811083
Performance enhancement of a contract net protocol based system through instance-based learning
The contract net protocol (CNP) is a widely used coordination mechanism in multiagent systems. It has a lot of communication overhead due to the broadcast of the task announcements. The performance of the CNP degrades drastically when the number of communicating agents and the number of tasks announced increases. Hence, it has problems of scalability. In order to overcome this limitation, an instance-based learning (IBL) mechanism is designed that uses previously stored instances in order to select a target agent. This avoids the expensive bidding process. The scheme is implemented in a simulated distributed hospital system where the CNP is used for resource sharing across hospitals. Experimental results demonstrate that with the incorporation of the IBL, the system performance improves significantly. The system is better scalable with respect to the number of tasks.
3086074
An Exercise in Fault-Containment: Self-Stabilizing Leader Election
Self-stabilizing algorithms are designed to guarantee convergence to some desired stable state from arbitrary initial states arising out of an arbitrarily large number of faults. However, in a well-designed system, the simultaneous occurrence of a large number of faults is rare. It is therefore desirable to design algorithms that are not only self-stabilizing, but also have the ability to recover very fast from a bounded number of faults. As an illustration, we present a simple self-stabilizing leader election protocol that recovers in O(1) time from a state with a single transient fault on oriented rings. Only the faulty node and its two neighbors change their state during convergence to a stable state. Thus, the effect of a single fault is tightly contained around the fault. The technique for transforming a self-stabilizing algorithm into its fault-contained version is simple and general, and can be applied to other problems as well that satisfy certain properties.
14760800
Deciding Separation Logic Formulae by SAT and Incremental Negative Cycle Elimination
Separation logic is a subset of the quantifier-free first order logic. It has been successfully used in the automated verification of systems that have large (or unbounded) integer-valued state variables, such as pipelined processor designs and timed systems. In this paper, we present a fast decision procedure for separation logic, which combines Boolean satisfiability (SAT) with a graph based incremental negative cycle elimination algorithm. Our solver abstracts a separation logic formula into a Boolean formula by replacing each predicate with a Boolean variable. Transitivity constraints over predicates are detected from the constraint graph and added on a need-to basis. Our solver handles Boolean and theory conflicts uniformly at the Boolean level. The graph based algorithm supports not only incremental theory propagation, but also constant time theory backtracking without using a cumbersome history stack. Experimental results on a large set of benchmarks show that our new decision procedure is scalable, and outperforms existing techniques for this logic.
13088866
Specification-based anomaly detection: a new approach for detecting network intrusions
Unlike signature or misuse based intrusion detection techniques, anomaly detection is capable of detecting novel attacks. However, the use of anomaly detection in practice is hampered by a high rate of false alarms. Specification-based techniques have been shown to produce a low rate of false alarms, but are not as effective as anomaly detection in detecting novel attacks, especially when it comes to network probing and denial-of-service attacks. This paper presents a new approach that combines specification-based and anomaly-based intrusion detection, mitigating the weaknesses of the two approaches while magnifying their strengths. Our approach begins with state-machine specifications of network protocols, and augments these state machines with information about statistics that need to be maintained to detect anomalies. We present a specification language in which all of this information can be captured in a succinct manner. We demonstrate the effectiveness of the approach on the 1999 Lincoln Labs intrusion detection evaluation data, where we are able to detect all of the probing and denial-of-service attacks with a low rate of false alarms (less than 10 per day). Whereas feature selection was a crucial step that required a great deal of expertise and insight in the case of previous anomaly detection approaches, we show that the use of protocol specifications in our approach simplifies this problem. Moreover, the machine learning component of our approach is robust enough to operate without human supervision, and fast enough that no sampling techniques need to be employed. As further evidence of effectiveness, we present results of applying our approach to detect stealthy email viruses in an intranet environment.
11038357
Reasoning About Threads Communicating via Locks
We propose a new technique for the static analysis of concurrent programs comprised of multiple threads. In general, the problem is known to be undecidable even for programs with only two threads but where the threads communicate using CCS-style pairwise rendezvous [11]. However, in practice, a large fraction of concurrent programs can either be directly modeled as threads communicating solely using locks or can be reduced to such systems either by applying standard abstract interpretation techniques or by exploiting separation of control from data. For such a framework, we show that for the commonly occurring case of threads with nested access to locks, the problem is efficiently decidable. Our technique involves reducing the analysis of a concurrent program with multiple threads to individually analyzing augmented versions of the given threads. This not only yields decidability but also avoids construction of the state space of the concurrent program at hand and thus bypasses the state explosion problem making our technique scalable. We go on to show that for programs with threads that have non-nested access to locks, the static analysis problem for programs with even two threads becomes undecidable even for reachability, thus sharpening the result of [11]. As a case study, we consider the Daisy file system [1] which is a benchmark for analyzing the efficacy of different methodologies for debugging concurrent programs and provide results for the detection of several bugs.
41630036
Virage image search engine: an open framework for image management
Until recently, the management of large image databases has relied exclusively on manually entered alphanumeric annotations. Systems are beginning to emerge in both the research and commercial sectors based on 'content-based' image retrieval, a technique which explicitly manages image assets by directly representing their visual attributes. The Virage image search engine provides an open framework for building such systems. The Virage engine expresses visual features as image 'primitives.' Primitives can be very general (such as color, shape, or texture) or quite domain specific (face recognition, cancer cell detection, etc.). The basic philosophy underlying this architecture is a transformation from the data-rich representation of explicit image pixels to a compact, semantic-rich representation of visually salient characteristics. In practice, the design of such primitives is non-trivial, and is driven by a number of conflicting real-world constraints (e.g. computation time vs. accuracy). The virage engine provides an open framework for developers to 'plug-in' primitives to solve specific image management problems. The architecture has been designed to support both static images and video in a unified paradigm. The infrastructure provided by the Virage engine can be utilized to address high-level problems as well, such as automatic, unsupervised keyword assignment, or image classification.
2635468
A System for Managing Alternate Models in Model-Based Mediation
In [1,3], we have described the problem of model-based mediation (MBM) as an extension of the global-as-view paradigm of information integration. The need for this extension arises in many application domains where the information sources to be integrated not only differ in their export formats, data models, and query capabilities, but have widely different schema with very little overlap in attributes. In scientific applications, the information sources come from different subdisciplines, and despite their poorly overlapping schema, can be integrated because they capture different aspects of the same scientific objects or phenomena, and can be conceptually integrated due to scientific reasons. In the MBM paradigm, a “mediation engineer” consults with domain experts to explicitly model the “glue knowledge” using a set of facts and rules at the mediator. Integrated views are defined in MBM on top of the exported schemas from the information sources together with the glue knowledge source that ties them together. We have successfully applied the MBM technique to develop the KIND mediator or Neuroscience information sources [1]-[4]. To accomplish this, sources in the MBM framework export their conceptual models (CMs), consisting of the logical schema, domain constraints, and object contexts, i.e., formulas that relate their conceptual schema with the global domain knowledge maintained at the mediator. Thus model-based mediation has a hybrid approach to information integration - on the one hand at the mediator integrated views are defined over source CMs and the Knowledge Map using a global-as-view approach; on the other hand, object-contexts of the source are defined as local-as-view.