8426940
A dynamic pricing mechanism for P2P referral systems
Most existing research on peer-to-peer systems focuses on protocol design. In this paper, we consider the issue of free riding in peer-to-peer referral systems. Free riders are agents that refuse either to answer a query or to give referrals. Free riding is detrimental to the system, since it may prevent requesters from finding high quality providers efficiently. To mitigate the issue of free riding, we propose a dynamic pricing mechanism to motivate the agents to behave rationally. Service providers learn appropriate prices of referrals and answers in order to maximize their payoffs through stochastic iterative learning algorithms.
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).
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.
10926456
An agent-based approach to knowledge management
Traditional approaches to knowledge management are essentially limited to document management. However, much knowledge in organizations or communities resides in an informal social network and may be accessed only by asking the right people. This paper describes MARS, a multiagent referral system for knowledge management. MARS assigns a software agent to each user. The agents facilitate their users' interactions and help manage their personal social networks. Moreover, the agents cooperate with one another by giving and taking referrals to help their users find the right parties to contact for a specific knowledge need.
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.
677559
TEEVE: the next generation architecture for tele-immersive environments
Tele-immersive 3D multi-camera room environments are starting to emerge and with them new challenging research questions. One important question is how to organize the large amount of visual data, being captured, processed, transmitted and displayed, and their corresponding resources, over current COTS computing and networking infrastructures so that "everybody" would be able to install and use tele-immersive environments for conferencing and other activities. In this paper, we propose a novel cross-layer control and streaming framework over general purpose delivery infrastructure, called TEEVE (tele-immersive environments for everybody). TEEVE aims for effective and adaptive coordination, synchronization, and soft QoS-enabled delivery of tele-immersive visual streams to remote room(s). The TEEVE experiments between two tele-immersive rooms residing in different institutions more than 2000 miles apart show that we can sustain communication of up to 12 3D video streams with 4/spl sim/5 3D frames per second for each stream, yielding 4/spl sim/5 tele-immersive video rate.
35646601
Iterated logarithmic expansions of the pathwise code lengths for exponential families
Rissanen's (1978, 1986, 1989, 1996) minimum description length (MDL) principle is a statistical modeling principle motivated by coding theory. For exponential families we obtain pathwise expansions, to the constant order, of the predictive and mixture codelengths used in MDL. The results are useful for understanding different MDL forms.
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.
28131114
Utilizing Fuzzy Petri Net for Choreography Based Semantic Web Services Discovery
Semantic Web Services have received great popularity these days for their capability of providing more automatic web services discoveries and compositions. However, the issue of behavior compatibility is still not properly solved. In this paper, we propose a choreography-based formal approach to discover semantic web services that are compatible with their behaviors. The fuzzy petri net is used to perform the modeling, verification, analysis and evaluation for the matchmaking of semantic web services. The requested and provided services are modeled by two fuzzy petri nets combined through a set of combination rules. By analyzing the composite fuzzy petri net, the behavior compatibility can be verified, and the matching degree between requested and provided services can be obtained. With our approach, the success rate and accuracy of the semantic web services discoveries can be improved, and the final services set can be optimized.
41743230
Automatically wrapping legacy software into services: A grid case study
The computational grid is rapidly evolving into a service-oriented computing infrastructure that facilitates resource sharing for solving large-scale data and computationally intensive problems. Peer-to-peer (P2P) systems have emerged as an infrastructure enabling technologies for enhanced scalability and reliability in file sharing and content distribution. It is envisioned that P2P enabled service-oriented grid systems would virtualize various resources as services with high scalability and reliability. Many legacy software resources exist nowadays, but making them grid aware services for effective resource sharing has become an issue of vital importance. This paper presents GSLab, a toolkit for automatically wrapping legacy software into services that can be published, discovered and reused in grid environments. GSLab employs Sun Grid Engine (SGE) to enhance its performance in execution of wrapped services. Using GSLab, we have automatically wrapped a legacy computer animation rendering code written in C as a service that can be discovered and accessed in a SGE environment. The evaluation results show that the performance of GSLab improves with an increase in the number of computing nodes involved.