Agent based infrastructure for real-time applications

In this paper we propose a new infrastructure for real-time applications. As a preliminary, we describe basic characteristics of the most popular real-time services like VoIP, videoconferencing, live media streaming, and network multiplayer games. We focus on the end-to-end latency, bandwidth and efficient transmission methods. Next, we present our project concepts, infrastructure model, details of implementation and our testing environment which was designed for testing many aspects of real-time services. The system combines mechanisms for ensuring best possible connection quality (QoS), load balance of servers in infrastructure and gives control over the packet routing decisions. Additionally, provided security mechanisms make it a good choice even in the environment where a high security level is required. The system is based on the Peer-to-Peer (P2P) model and data between users is routed over an overlay network, consisting of all participating peers as network nodes. This overlay can by used for application level multicast or live media stream. In the logging process each user is assigned to a specific node (based on his geographic location and nodes load). Because nodes are participating in data transmission, we have control over the data flow route. It is possible to specify the desired route, so, regardless of the external routing protocol, we can avoid paths that are susceptible to eavesdropping. Another feature of the presented system is usage of agents. Each agent acts within the single node. Its main task is to constantly control the quality of transmission. It analyzes such parameters like link bandwidth use, number of lost packets, time interval between each packet etc. The information collected by the agents from all nodes allows to build a dynamic routing table. Every node uses the Dijkstra's algorithm to find the best at the moment route to all other nodes. The routes are constantly modified as a consequence of changes found by agents or updates sent by other nodes. In VoD services agents also analyze popularity of streamed media, which helps build intelligent video cache. To ensure greater security and high reliability of the system, we have provided a reputation mechanism. It is used during bringing up to date the information about possible routes and their quality, given by other nodes. Owing to this solution nodes and routes which are more reliable get higher priority

A Security Model for Mobile Agents using X.509 Proxy Certificates

Mobile agent technology presents an attractive alternative to the client-server paradigm for several network and real-time applications. However, for most applications, the lack of a viable agent security model has limited the adoption of the agent paradigm. This thesis presents a security model for mobile agents based on a security infrastructure for Computational Grids, and specifically, on X.509 Proxy Certificates. Proxy Certificates serve as credentials for Grid applications, and their primary purpose is temporary delegation of authority. Exploiting the similarity between Grid applications and mobile agent applications, this thesis motivates the use of Proxy Certificates as credentials for mobile agents. A new extension for Proxy Certificates is proposed in order to make them suited to mobile agent applications, and mechanisms are presented for agent-to-host authentication, restriction of agent privileges, and secure delegation of authority during spawning of new agents. Finally, the implementation of the proposed security mechanisms as modules within a multi-lingual and modular agent infrastructure, the Distributed Agent Delivery System, is discussed

Wide-Area Time-Synchronized Closed-Loop Control of Power Systems And Decentralized Active Distribution Networks

The rapidly expanding power system grid infrastructure and the need to reduce the occurrence of major blackouts and prevention or hardening of systems against cyber-attacks, have led to increased interest in the improved resilience of the electrical grid. Distributed and decentralized control have been widely applied to computer science research. However, for power system applications, the real-time application of decentralized and distributed control algorithms introduce several challenges. In this dissertation, new algorithms and methods for decentralized control, protection and energy management of Wide Area Monitoring, Protection and Control (WAMPAC) and the Active Distribution Network (ADN) are developed to improve the resiliency of the power system. To evaluate the findings of this dissertation, a laboratory-scale integrated Wide WAMPAC and ADN control platform was designed and implemented. The developed platform consists of phasor measurement units (PMU), intelligent electronic devices (IED) and programmable logic controllers (PLC). On top of the designed hardware control platform, a multi-agent cyber-physical interoperability viii framework was developed for real-time verification of the developed decentralized and distributed algorithms using local wireless and Internet-based cloud communication. A novel real-time multiagent system interoperability testbed was developed to enable utility independent private microgrids standardized interoperability framework and define behavioral models for expandability and plug-and-play operation. The state-of-theart power system multiagent framework is improved by providing specific attributes and a deliberative behavior modeling capability. The proposed multi-agent framework is validated in a laboratory based testbed involving developed intelligent electronic device prototypes and actual microgrid setups. Experimental results are demonstrated for both decentralized and distributed control approaches. A new adaptive real-time protection and remedial action scheme (RAS) method using agent-based distributed communication was developed for autonomous hybrid AC/DC microgrids to increase resiliency and continuous operability after fault conditions. Unlike the conventional consecutive time delay-based overcurrent protection schemes, the developed technique defines a selectivity mechanism considering the RAS of the microgrid after fault instant based on feeder characteristics and the location of the IEDs. The experimental results showed a significant improvement in terms of resiliency of microgrids through protection using agent-based distributed communication

Frequency Monitoring Network (FNET) Data Center Development and Data Analysis

Frequency Monitoring Network (FNET) is an Internet-based, wide-area phasor measurement system that collects power system data using Frequency Disturbance Recorders (FDRs) that are installed at the distribution level. The FNET data center enables the monitoring of bulk power systems, and provides wide-area situational awareness and disturbance analysis for understanding power system disturbances and system operations. Therefore, the data center plays a very critical role in the entire FNET system framework. In recent years, many potential challenges brought by the rapid expansion of the FNET system have underlined the importance of designing the next-generation FNET data center. More discussions about the motivation and guidelines to design the next-generation FNET data center will be presented in Chapter 2, along with a brief introduction of the new infrastructure composing of multiple data storage and application layers. A distributed alarming agent that communicates between real-time applications and near-real-time applications is discussed in detail. Chapter 3 proposes the data storage solutions for FNET time-series measurement data, configuration data and analysis records. Chapter 4 addresses the challenges of the real-time application development. The algorithm, configuration parameters and data processing procedures of the real-time event detection, oscillation detection, and islanding detection are presented in detail. Chapter 5 introduces the implementation of the FNET map-based web display using the measurement data feed provided by the openHistorian data publisher service. Besides contributing to the situation awareness applications, the researches presented here explore novel data analysis perspectives to investigate power grids’ behavior. Chapter 6 introduces a frequency distribution probability calculation method, applies this method to frequency measurement data from 2005-2013 collected by the FNET system, investigates the distribution probability of frequency data over North American and also worldwide power grids, and compares the distribution patterns during different years, seasons, days of a week and periods of a day. Chapter 7 presents a solution method to produce replay videos based on FDRs’ normalized voltage magnitude data and investigates the voltage magnitude pattern changes over the Eastern Interconnection (EI) during events and days by using historical FNET measurement data. Conclusions and possible future research topics are given in Chapter 8

ENERO: Efficient Real-Time WAN Routing Optimization with Deep Reinforcement Learning

Wide Area Networks (WAN) are a key infrastructure in today's society. During the last years, WANs have seen a considerable increase in network's traffic and network applications, imposing new requirements on existing network technologies (e.g., low latency and high throughput). Consequently, Internet Service Providers (ISP) are under pressure to ensure the customer's Quality of Service and fulfill Service Level Agreements. Network operators leverage Traffic Engineering (TE) techniques to efficiently manage network's resources. However, WAN's traffic can drastically change during time and the connectivity can be affected due to external factors (e.g., link failures). Therefore, TE solutions must be able to adapt to dynamic scenarios in real-time. In this paper we propose Enero, an efficient real-time TE solution based on a two-stage optimization process. In the first one, Enero leverages Deep Reinforcement Learning (DRL) to optimize the routing configuration by generating a long-term TE strategy. To enable efficient operation over dynamic network scenarios (e.g., when link failures occur), we integrated a Graph Neural Network into the DRL agent. In the second stage, Enero uses a Local Search algorithm to improve DRL's solution without adding computational overhead to the optimization process. The experimental results indicate that Enero is able to operate in real-world dynamic network topologies in 4.5 seconds on average for topologies up to 100 edges.Comment: 12 pages, 9 figure

Ontology driven multi-agent systems : an architecture for sensor web applications.

Thesis (Ph.D.)-University of KwaZulu-Natal, 2009.Advances in sensor technology and space science have resulted in the availability of vast quantities of high quality earth observation data. This data can be used for monitoring the earth and to enhance our understanding of natural processes. Sensor Web researchers are working on constructing a worldwide computing infrastructure that enables dynamic sharing and analysis of complex heterogeneous earth observation data sets. Key challenges that are currently being investigated include data integration; service discovery, reuse and composition; semantic interoperability; and system dynamism. Two emerging technologies that have shown promise in dealing with these challenges are ontologies and software agents. This research investigates how these technologies can be integrated into an Ontology Driven Multi-Agent System (ODMAS) for the Sensor Web. The research proposes an ODMAS framework and an implemented middleware platform, i.e. the Sensor Web Agent Platform (SWAP). SWAP deals with ontology construction, ontology use, and agent based design, implementation and deployment. It provides a semantic infrastructure, an abstract architecture, an internal agent architecture and a Multi-Agent System (MAS) middleware platform. Distinguishing features include: the incorporation of Bayesian Networks to represent and reason about uncertain knowledge; ontologies to describe system entities such as agent services, interaction protocols and agent workflows; and a flexible adapter based MAS platform that facilitates agent development, execution and deployment. SWAP aims to guide and ease the design, development and deployment of dynamic alerting and monitoring applications. The efficacy of SWAP is demonstrated by two satellite image processing applications, viz. wildfire detection and monitoring informal settlement. This approach can provide significant benefits to a wide range of Sensor Web users. These include: developers for deploying agents and agent based applications; end users for accessing, managing and visualising information provided by real time monitoring applications, and scientists who can use the Sensor Web as a scientific computing platform to facilitate knowledge sharing and discovery. An Ontology Driven Multi-Agent Sensor Web has the potential to forever change the way in which geospatial data and knowledge is accessed and used. This research describes this far reaching vision, identifies key challenges and provides a first step towards the vision

Design of a middleware for QoS-aware distribution transparent content delivery

Developers of distributed multimedia applications face a diversity of multimedia formats, streaming platforms and streaming protocols. Furthermore, support for end-to-end quality-of-service (QoS) is a crucial factor for the development of future distributed multimedia systems. This paper discusses the architecture, design and implementation of a QoS-aware middleware platform for content delivery. The platform supports the development of distributed multimedia applications and can deliver content with QoS guarantees. QoS support is offered by means of an agent infrastructure for QoS negotiation and enforcement. Properties of content are represented using a generic content representation model described using the OMG Meta Object Facility (MOF) model. A content delivery framework manages stream paths for content delivery despite differences in streaming protocols and content encoding. The integration of the QoS support, content representation and content delivery framework results in a QoS-aware middleware that enables representation transparent and location transparent delivery of content