Description:
To support a wide variety of applications ranging from military surveillance to health care clinic monitoring, a wireless sensor network must obtain accurate location for each sensor. A number of localization schemes have been developed to allow each sensor node to acquire its location.However, most of these techniques assume benign environments,and thus cannot survive malicious attacks in hostile environments where external and/or compromised nodes may launch attacks. This paper proposes a new computationally efficient and resilient localization scheme based on the clustering of benign location reference anchors. Moreover, this paper reports both simulation and field experiments using a test bed of MICAz motes performed to compare the proposed approach with several recent secure localization schemes. The experimental results demonstrate that the proposed scheme has the fastest execution time among all resilient localization schemes that can be used for the current generation of sensor platforms (e.g., MICA series of motes)

Description:
Many sensor network applications require sensors’ locations to function correctly. Despite the recent advances, location discovery for sensor networks in hostile environments has been mostly overlooked. Most of the existing localization protocols for sensor networks are vulnerable in hostile environments. The security of location discovery can certainly be enhanced by authentication. However, the possible node compromises and the fact that location determination uses certain physical features (e.g., received signal strength) of radio signals make authentication not as effective as in traditional security applications. This paper presents two methods to tolerate malicious attacks against range based location discovery in sensor networks. The first method filters out malicious beacon signals on the basis of the “consistency” among multiple beacon signals, while the second method tolerates malicious beacon signals by adopting an iteratively refined voting scheme. Both methods can survive malicious attacks even if the attacks bypass authentication,provided that the benign beacon signals constitute the majority of the beacon signals. This paper also presents the implementation and experimental evaluation (through both field experiments and simulation) of all the secure and resilient location estimation schemes that can be used on the current generation of sensor platforms (e.g., MICA series of motes), including the techniques proposed in this paper, in a network of MICAz motes. The experimental results demonstrate the effectiveness of the proposed methods, and also give the secure and resilient location estimation scheme most suitalbe for the current generation of sensor networks.

Description:
We describe an approach for developing knowledge based medical decision support systems based on the rather new technology of case-based reasoning. This work is based on the results of the Inreca European project and preliminary results from the Inreca project which particularly deals with medical applications. One goal was to start from case-based reasoning technology for technical diagnosis, as it was available among the partners, and ‘scale-up’ to more general non-technical decision support tasks as typically given in medical domains. Inreca technology is used to build an initial decision support system at the Russian Toxicology Information and Advisory Center in Moscow for diagnosing poison cases that are caused by psychotropes

Description:
Knowledge intensive organizations have vast array of information contained in large document repositories. With the advent of E-commerce and corporate intranets/extranets, these repositories are expected to grow at a fast pace. This explosive growth has led to huge, fragmented, and unstructured document collections. Although it has become easier to collect and store information in document collections, it has become increasingly difficult to retrieve relevant information from these large document collections. This paper addresses the issue of improving retrieval performance (in terms of precision and recall) for retrieval from document collections.There are three important paradigms of research in the area of information retrieval (IR): Probabilistic IR, Knowledge-based IR, and, Artificial Intelligence based techniques like neural networks and symbolic learning. Very few researchers have tried to use evolutionary algorithms like genetic algorithms (GA’s). Previous attempts at using GA’s have concentrated on modifying document representations or modifying query representations. This work looks at the possibility of applying GA’s to dapt various matching functions. It is hoped that such an adaptation of the matching functions will lead to a better retrieval performance than that obtained by using a single matching function. An overall matching function is treated as a weighted combination of scores produced by individual matching functions. This overall score is used to rank and retrieve documents. Weights associated with individual functions are searched using Genetic Algorithm.

Description:
This paper presents techniques to integrate and reason about complementary intrusion evidence such as alerts generated by intrusion detection systems (IDSs) and reports by system monitoring or vulnerability scanning tools. To facilitate the modeling of intrusion evidence, this paper classifies intrusion evidence into either event-based evidence or state-based evidence. Event-based evidence refers to observations (or detections) of intrusive actions (e.g., IDS alerts),while state-based evidence refers to observations of the effects of intrusions on system states. Based on the interdependency between event-based and state-based evidence, this paper develops techniques to automatically integrate complementary evidence into Bayesian networks, and reasonabout uncertain or unknown intrusion evidence based on verified evidence. The experimental results in this paper demonstrate the potential of the proposed techniques. In particular, additional observations by system monitoring or vulnerability scanning tools can potentially reduce the false alert rate and increase the confidence in alerts corresponding to successful attacks.

Description:
This paper presents an application of simulation optimization in construction utilizing genetic algorithms. The paperfocuses on the use of genetic algorithms (GAs) as a tool for optimizing the total cost of earthmoving operations accounting for available equipment models to contractors and their corresponding quantities. The developed genetic algorithm has a powerful computational utility that increases its efficiency. The fitness of generated chromosomes is calculated utilizing a simulation engine dedicated for earthmoving operations which is dynamically linked to the developed genetic algorithm. The impact of the algorithm’s control parameters on its conversion is also examined. A numerical example is presented to illustrate the capabilities of the developed algorithm in selecting near-optimum fleet configurations.

Description:
This paper presents solution of optimal power flow problem of large distribution systems via a simple genetic algorithm. The objective is to minimize the fuel cost and keep the power outputs of generators, bus voltages, shunt capacitors/reactors and transformers tap-setting in their secure limits. CPU times can be reduced by decomposing the optimization constraints to active constraints manipulated directly by the genetic algorithm, and passive constraints maintained in their soft limits using a conventional constraint load flow. The IEEE 30-bus system has been studied to show the effectiveness of the algorithm.

Description:
This paper is concerned with an abstract exploration of code mobility constructs designed for use in settings where the level of granularity associated with the mobile units exhibits significant variability. Units of mobility that are both finer and coarser grained than the unit of execution are examined. To accomplish this, we take the extreme view that every line of code and every variable declaration are potentially mobile, i.e., it may be duplicated or moved from one program context to another on the same host or across the network. We also assume that complex code assemblies may move with equal ease. The result is CODEWEAVE, a model that shows how to develop new forms of code mobility, assign them precise meaning, and facilitate formal verification of programs employing them. The design of CODEWEAVE relies greatly on Mobile UNITY, a notation and proof logic for mobile computing. Mobile UNITY offers a computational milieu for examining a wide range of constructs and semantic alternatives in a clean abstract setting, i.e., unconstrained by compilation and performance considerations traditionally associated with programming language design. Ultimately, the notation offered by CODEWEAVE is given exact semantic definition by means of a direct mapping to the underlying Mobile UNITY model. The abstract and formal treatment of code mobility offered by CODEWEAVE establishes a technical foundation for examining competing proposals and for subsequent integration of some of the mobility constructs both at the language level and within middleware for mobility.

Description:
Lime is a middleware supporting the development of applications that exhibit physical mobility of hosts, logical mobility of agents, or both. Lime adopts a coordination perspective inspired by work on the Linda model. The context for computation, represented in Linda by a globally accessible, persistent tuple space, is represented in Lime by transient sharing of the tuple spaces carried by each individual mobile unit. Linda tuple spaces are also extended with a notion of location and with the ability to react to a given state. The hypothesis underlying our work is that the resulting model provides a minimalist set of abstractions that enable rapid and dependable development of mobile applications. In this paper, we illustrate the model underlying Lime, present its current design and implementation, report about its initial evaluation in applications that involve physical mobility, and discuss lessons learned and future enhancements that will drive its evolution.

Description:
The design of ad hoc mobile applications often requires the availability of a consistent view of the application state among the participating hosts. Such views are important because they simplify both the programming and verification tasks. Essential to constructing a consistent view is the ability to know what hosts are within proximity of each other, i.e., form a group in support of the particular application. In this paper we propose an algorithm that allows hosts within communication range to maintain a consistent view of the group membership despite movement and frequent disconnections. The novel features of this algorithm are its reliance on location information and a conservative notion of logical connectivity that creates the illusion of announced disconnection. Movement patterns and delays are factored in the policy that determines which physical connections are susceptible to disconnection.