18419915
Emergence of agent-based referral networks
We consider the problem of finding desirable services and sources of information in distributed multiagent systems. Traditional solutions, such as centralized directories, may be inaccurate and may often be unavailable in such settings. Therefore, the only way agents can find the right agents is through referrals. In order to make the referrals effective, the agents must adaptively select the agents with whom they interact. This adaptivity leads to the emergence of referral networks among agents. We study this network experimentally to see the emergence of social structures and the evolution of such structures under different scenarios.
1248870
An incentive mechanism for message relaying in unstructured peer-to-peer systems
Distributed message relaying is an important function of a peer-to-peer system to discover service providers. Existing search protocols in unstructured peer-to-peer systems either create huge burden on communications or cause long response time. Moreover, these systems are also vulnerable to the free riding problem. In this paper we present an incentive mechanism that not only mitigates the free riding problem, but also achieves good system efficiency in message relaying for peer discovery. In this mechanism promised rewards are passed along the message propagation process. A peer is rewarded if a service provider is found via a relaying path that includes this peer. We provide some analytic insights to the symmetric Nash equilibrium strategies of this game, and an approximate approach to calculate this equilibrium. Experiments show that this incentive mechanism brings a system utility generally higher than breadth-first search and random walks, based on both the estimated utility from our approximate equilibrium and the utility generated from learning in the incentive mechanism.
5803741
Incentive Mechanisms for Peer-to-Peer Systems
Most of the existing research in peer-to-peer systems focuses on protocol design and doesn’t consider the rationality of each peer. One phenomenon that should not be ignored is free riding. Some peers simply consume system resources but contribute nothing to the system. In this paper we present an agent-based peer-to-peer system, in which each peer is a software agent and the agents cooperate to search the whole system through referrals. We present a static and a dynamic pricing mechanism to motivate each agent to behave rationally while still achieving good overall system performance. We study the behavior of the agents under two pricing mechanisms and evaluate the impact of free riding using simulations.
11424736
Extending the ONESAF Testbed into a C4ISR Testbed
This article describes how the modeling and simulation environment of the OneSAF Testbed Baseline (OTB) v1.0 has been extended to enable the testing of heterogeneous algorithms that are being designed for real-world C4ISR applications. This has been accomplished by building an architecture that extends functional and logical components of the OTB system in the following ways: the use of the OTB Compact Terrain Database for terrain analysis and preliminary threat assessment, the addition of the RETSINA-OTB Bridge for the real-time query and control of OTB entities, and the addition of new DIS-based sensor entities for interoperation with Command and Control algorithms, to name a few. This article illustrates how to make a few small but general extensions to a modeling and simulation system to create a larger testbed system with minimum impact on the native system and with great potential for the range of applications that can exploit it.
205431881
An integrated approach to high-level information fusion
In today's fast paced military operational environment, vast amounts of information must be sorted out and fused not only to allow commanders to make situation assessments, but also to support the generation of hypotheses about enemy force disposition and enemy intent. Current information fusion technology has the following two limitations. First, current approaches do not consider the battlefield context as a first class entity. In contrast, we consider situational context in terms of terrain analysis and inference. Second, there are no integrated and implemented models of the high-level fusion process. This paper describes the HiLIFE (High-Level Information Fusion Environment) computational framework for seamless integration of high levels of fusion (levels 2, 3 and 4). The crucial components of HiLIFE that we present in this paper are: (1) multi-sensor fusion algorithms and their performance results that operate in heterogeneous sensor networks to determine not only single targets but also force aggregates, (2) computational approaches for terrain-based analysis and inference that automatically combine low-level terrain features (such as forested areas, rivers, etc.) and additional information, such as weather, and transforms them into high-level militarily relevant abstractions, such as NO-GO, SLOW-GO areas, avenues of approach, and engagement areas, (3) a model for inferring adversary intent by mapping sensor readings of opponent forces to possible opponent goals and actions, and (4) sensor management for positioning intelligence collection assets for further data acquisition. The HiLIFE framework closes the loop on information fusion by specifying how the different components can computationally work together in a coherent system. Furthermore, the framework is inspired by a military process, the Intelligence Preparation of the Battlefield, that grounds the framework in practice. HiLIFE is integrated with a distributed military simulation system, OTBSAF, and the RETSINA multi-agent infrastructure to provide agile and sophisticated reasoning. In addition, the paper presents validation results of the automated terrain analysis that were obtained through experiments using military intelligence Subject Matter Experts (SMEs).
5934185
Trust and reputation management in a small-world network
Successful commerce relies heavily upon the reputations that the different parties acquire through their dealings with each other. We view an e-commerce community as a social network, which supports reputations both for expertise (providing good service) and helpfulness (providing good referrals). We study the small-world phenomena such as the emergence of subcommunities, and pivot vertices (which link different subcommunities) in the social network, and discovered that the quality of the network improves with the presence of a pivot.
18656180
Application of PGA on Optimization of Distribution of Shopping Centers
In this study, the distribution of shopping centers is optimized in terms of realizing the shortest car-based shopping trips in an urban area. Modal split is performed between road and public traffic networks is calculated, and then the interaction between land-use and transportation in the context of choice of shopping destinations is modeled to build the optimal function. Parallel genetic algorithm (PGA) is applied to solve the optimal problem on distribution of the area of shopping centers. Several problems in application of PGA are discussed. A case study is undertaken in order to examine the effectiveness of this method.
14066256
Grid Service Discovery with Rough Sets
The computational grid is rapidly evolving into a service-oriented computing infrastructure that facilitates resource sharing and large-scale problem solving over the Internet. Service discovery becomes an issue of vital importance in utilizing grid facilities. This paper presents ROSSE, a Rough sets-based search engine for grid service discovery. Building on the Rough sets theory, ROSSE is novel in its capability to deal with the uncertainty of properties when matching services. In this way, ROSSE can discover the services that are most relevant to a service query from a functional point of view. Since functionally matched services may have distinct nonfunctional properties related to the quality of service (QoS), ROSSE introduces a QoS model to further filter matched services with their QoS values to maximize user satisfaction in service discovery. ROSSE is evaluated from the aspects of accuracy and efficiency in discovery of computing services.
16993095
Genetic Polymorphisms of Nine X-STR Loci in Four Population Groups from Inner Mongolia, China
Nine short tandem repeat (STR) markers on the X chromosome (DXS101, DXS6789, DXS6799, DXS6804, DXS7132, DXS7133, DXS7423, DXS8378, and HPRTB) were analyzed in four population groups (Mongol, Ewenki, Oroqen, and Daur) from Inner Mongolia, China, in order to learn about the genetic diversity, forensic suitability, and possible genetic affinities of the populations. Frequency estimates, Hardy-Weinberg equilibrium, and other parameters of forensic interest were computed. The results revealed that the nine markers have a moderate degree of variability in the population groups. Most heterozygosity values for the nine loci range from 0.480 to 0.891, and there are evident differences of genetic variability among the populations. A UPGMA tree constructed on the basis of the generated data shows very low genetic distance between Mongol and Han (Xi'an) populations. Our results based on genetic distance analysis are consistent with the results of earlier studies based on linguistics and the immigration history and origin of these populations. The minisatellite loci on the X chromosome studied here are not only useful in showing significant genetic variation between the populations, but also are suitable for human identity testing among Inner Mongolian populations.
8762235
A Three-Layer Virtual Director Model for Supporting Automated Multi-Site Distributed Education
In multi-site distributed education (MSDE), video streams from multiple sites are available. To best utilize the limited screen space at each site, we develop a customizable, automated display management system in this paper, i.e., only user-preferred streams will be shown as triggered by events and timers. The configuration of such user preference, however, is challenging because it has to be both human-friendly and machine-friendly. To address this challenge, we propose a three-layer virtual director model. In the user layer, we identify three categories of parameters that can represent a wide range of user preferences yet are easy to use. These preferences are then automatically translated into a machine-friendly timed automaton in the execution layer. The automaton is simulated dynamically, which selects a subset of streams to show on the screen through a display layer. Evaluation results demonstrate the correctness and efficiency of the proposed framework
22909785
A dynamic holding strategy in public transit systems with real-time information
Abstract
Holding strategies are among the most commonly used operation control strategies in transit systems. In this paper, a dynamic holding strategy is developed, which consists of two major steps: (1) judging whether an early bus should be held, and (2) optimizing the holding times of the held bus. A model based on support vector machine (SVM), which contains four input variables (time-of-day, segment, the latest speed on the next segment, and the bus speed on the current segment) for forecasting the early bus departure times from the next stop is also developed. Then, in order to determine the optimal holding times, a model aiming to minimize the user costs is constructed and a genetic algorithm is used to optimize the holding times. Finally, the dynamic holding strategy proposed in this study is illustrated with the microscopic simulation model Paramics and some conclusions are drawn.
