Asymptotically idempotent aggregation operators for trust management in multi-agent systems

The study of trust management in multi-agent system, especially distributed, has grown over the last years. Trust is a complex subject that has no general consensus in literature, but has emerged the importance of reasoning about it computationally. Reputation systems takes into consideration the history of an entity’s actions/behavior in order to compute trust, collecting and aggregating ratings from members in a community. In this scenario the aggregation problem becomes fundamental, in particular depending on the environment. In this paper we describe a technique based on a class of asymptotically idempotent aggregation operators, suitable particulary for distributed anonymous environments

FRTRUST: a fuzzy reputation based model for trust management in semantic P2P grids

Grid and peer-to-peer (P2P) networks are two ideal technologies for file sharing. A P2P grid is a special case of grid networks in which P2P communications are used for communication between nodes and trust management. Use of this technology allows creation of a network with greater distribution and scalability. Semantic grids have appeared as an expansion of grid networks in which rich resource metadata are revealed and clearly handled. In a semantic P2P grid, nodes are clustered into different groups based on the semantic similarities between their services. This paper proposes a reputation model for trust management in a semantic P2P Grid. We use fuzzy theory, in a trust overlay network named FR TRUST that models the network structure and the storage of reputation information. In fact we present a reputation collection and computation system for semantic P2P Grids. The system uses fuzzy theory to compute a peer trust level, which can be either: Low, Medium, or High. Our experimental results demonstrate that FR TRUST combines low (and therefore desirable) a good computational complexity with high ranking accuracy.Comment: 12 Pages, 10 Figures, 3 Tables, InderScience, International Journal of Grid and Utility Computin

A fuzzy-based reliaility for JXTA-overlay P2P platform considering data download speed, peer congestion situation, number of interaction and packet loss parameters

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.In this paper, we propose and evaluate a new fuzzy-based reliability system for Peer-to-Peer (P2P) communications in JXTA-Overlay platform considering as a new parameter the peer congestion situation. In our system, we considered four input parameters: Data Download Speed (DDS), Peer Congestion Situation (PCS), Number of Interactions (NI) and Packet Loss (PL) to decide the Peer Reliability (PR). We evaluate the proposed system by computer simulations. The simulation results have shown that the proposed system has a good performance and can choose reliable peers to connect in JXTA-Overlay platform.Peer ReviewedPostprint (author's final draft

A fuzzy-based reliability system for JXTA-overlay P2P platform considering as new parameter sustained communication time

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.In this paper, we propose and evaluate a new fuzzy-based reliability system for Peer-to-Peer (P2P) Communications in JXTA-Overlay platform considering as a new parameter the sustained communication time. In our system, we considered four input parameters: Data Download Speed (DDS), Local Score (LS), Number of Interactions (NI) and Sustained Communication Time (SCT) to decide the Peer Reliability (PR). We evaluate the proposed system by computer simulations. The simulation results have shown that the proposed system has a good performance and can choose reliable peers to connect in JXTA-Overlay platform.Peer ReviewedPostprint (author's final draft

BPRS: Belief Propagation Based Iterative Recommender System

In this paper we introduce the first application of the Belief Propagation (BP) algorithm in the design of recommender systems. We formulate the recommendation problem as an inference problem and aim to compute the marginal probability distributions of the variables which represent the ratings to be predicted. However, computing these marginal probability functions is computationally prohibitive for large-scale systems. Therefore, we utilize the BP algorithm to efficiently compute these functions. Recommendations for each active user are then iteratively computed by probabilistic message passing. As opposed to the previous recommender algorithms, BPRS does not require solving the recommendation problem for all the users if it wishes to update the recommendations for only a single active. Further, BPRS computes the recommendations for each user with linear complexity and without requiring a training period. Via computer simulations (using the 100K MovieLens dataset), we verify that BPRS iteratively reduces the error in the predicted ratings of the users until it converges. Finally, we confirm that BPRS is comparable to the state of art methods such as Correlation-based neighborhood model (CorNgbr) and Singular Value Decomposition (SVD) in terms of rating and precision accuracy. Therefore, we believe that the BP-based recommendation algorithm is a new promising approach which offers a significant advantage on scalability while providing competitive accuracy for the recommender systems