Information reliability in complex multitask networks

Abstract

The emergence of distributed and complex networks has altered the field of information and data processing in the past few years. In distributed networks, the connected neighboring nodes can cooperate and share information with each other in order to solve particular tasks. However, in many applications the agents might be reluctant to share their true data with all their neighbors due to privacy and security constraints. In this paper, we study the performance of multitask distributed networks where sharing genuine information is subject to a cost. We formulate an information credibility model which results in the probability of sharing genuine information at each time instant according to the cost. Each agent then shares its true information with only a subset of its neighbors while sending fabricated data to the rest according to this probability. This behavior can affect the performance of the whole network in an adverse manner especially in cases where the cost is high. To overcome this problem, we propose an adaptive reputation protocol which enables the agents to evaluate the behavior of their neighbors over time and select the most reputable subset of neighbors to share genuine information with. We provide an extensive simulation-based analysis to compare the performance of the proposed method with several other distributed learning strategies. The results show that the proposed method outperforms the other learning strategies and enables the network to have a superior performance especially when the cost of sharing genuine information is high.

Adaptive Network Model for Assisting People with Disabilities through Crowd Monitoring and Control

“…The same adaptive systems can be used to check the reliability of the received information in a multi-agent computer network. This is useful in maintaining the security of such networks [23]. A wider application of the technique can be seen in medicine where the medical images are classified through a cooperative dictionary learning approach [24]; or, considering the electrodes of an electroencephalography system as the nodes of a cooperative network, such a system can find applications in brain-computer interfacing [25,26].…”

Eeg Connectivity - Informed Cooperative Adaptive Line Enhancer for Recognition of Brain State

“…Generally, there are no clues about the values of a l k and often for an N node neighbourhood each link weight is considered equal to 1/N [7]. Single-and multi-task cooperative networks have diverse range of applications such as in [8] [9] [10]. In application to EEG, accurate estimation of the combination parameters becomes very crucial as they play the major role in both recognition of brain state and classification of the states eliciting similar EEG waveforms.…”

Cooperative Monitoring and Dissemination of Urban Events Supported by Dynamic Clustering of Vehicles

“…These events can be of several types, such as fires, accidents, assaults, cars on the run, wanted persons or vehicles, blockades, public protests, among many others. The prompt and efficient handling of these events, through the collaboration among agents distributed in the environment is essential to guarantee the safety and assistance of the individuals that are directly or indirectly involved [3]. In addition, a quick response ensures a smooth operation of the city activities.…”