Network aware P2P multimedia streaming: capacity or locality?

P2P content providers are motivated to localize traffic within Autonomous Systems and therefore alleviate the tension with ISPs stemming from costly inter-AS traffic generated by geographically distributed P2P users. In this paper, we first present a new three-tier framework to conduct a thorough study on the impact of various capacity aware or locality aware neighbor selection and chunk scheduling strategies. Specifically, we propose a novel hybrid neighbor selection strategy with the flexibility to elect neighbors based on either type of network awareness with different probabilities. We find that network awareness in terms of both capacity and locality potentially degrades system QoS as a whole and that capacity awareness faces effort-based unfairness, but enables contribution-based fairness. Extensive simulations show that hybrid neighbor selection can not only promote traffic locality but lift streaming quality and that the crux of traffic locality promotion is active overlay construction. Based on this observation, we then propose a totally decentralized network awareness protocol, equipped with hybrid neighbor selection. In realistic simulation environments, this protocol can reduce inter-AS traffic from 95% to 38% a locality performance comparable with tracker-side strategies (35%) under the premise of high streaming quality. Our performance evaluation results provide valuable insights for both theoretical study on selfish topologies and real-deployed system design. © 2011 IEEE.published_or_final_versionThe 2011 IEEE International Conference on Peer-to-Peer Computing (P2P 2011), Kyoto, Japan, 31 August-2 September 2011. In Proceedings of P2P, 2011, p. 54-6

A control methodology for automated manufacturing

The application of computers in the manufacturing industry has substantially altered the control procedures used to program a whole manufacturing process. Currently, one the problems which automated manufacturing systems are experiencing is the lack of a good overall control system. The subject of this research has been centred on the identification of the problems involved in current methods of control and their advantages and disadvantages in an automated manufacturing system. As a result, a different type of control system has been proposed which distributes both the control and the decision making. This control model is an hybrid of hierarchical and hierarchical control systems which takes advantage of the best points offered by both types of control structures. The Durham FMS rig has been used as a testbed for an automated manufacturing system to which the hybrid control system has been applied. The implementation of this control system would not have been possible without the design and development of a System Integration Tool (SIT). The system is capable of real-time scheduling of the system activities. Activities within the system are monitored in real-time and a recording of the system events is available, which allows the user to analyse the activities of the system off-line. A network independent communication technique was developed for the Durham FMS which allowed the manufacturing cells to exercise peer-to-peer communication. The SIT also allowed the integration of equipment from different vendors in the FMS

A Multi-Vehicle Cooperative Localization Approach for an Autonomy Framework

Offensive techniques produced by technological advancement present opportunities for adversaries to threaten the operational advantages of our joint and allied forces. Combating these new methodologies requires continuous and rapid development towards our own set of \game-changing technologies. Through focused development of unmanned systems and autonomy, the Air Force can strive to maintain its technological superiority. Furthermore, creating a robust framework capable of testing and evaluating the principles that define autonomy allows for the exploration of future capabilities. This research presents development towards a hybrid reactive/deliberative architecture that will allow for the testing of the principles of task, cognitive, and peer flexibility. Specifically, this work explores peer flexibility in multi-robot systems to solve a localization problem using the Hybrid Architecture for Multiple Robots (HAMR) as a basis for the framework. To achieve this task a combination of vehicle perception and navigation tools formulate inferences on an operating environment. These inferences are then used for the construction of Factor Graphs upon which the core algorithm for localization implements iSAM2, a high performing incremental matrix factorization method. A key component for individual vehicle control within the framework is the Unified Behavior Framework (UBF), a behavior-based control architecture which uses modular arbitration techniques to generate actions that enable actuator control. Additionally, compartmentalization of a World Model is explored through the use of containers to minimize communication overhead and streamline state information. The design for this platform takes on a polymorphic approach for modularity and robustness enabling future development

Design Optimisation of Hybrid Photovoltaic and Energy Storage Systems through Smart Grid Technologies to Maximise Economic Benefit

University of Technology Sydney. Faculty of Engineering and Information Technology.Advances in photovoltaic and battery energy storage system (BESS) technologies have made hybrid PV-BESS systems an attractive prospect for residential energy consumers. However, the process to select an appropriate system is non-trivial due to the relatively high cost of batteries, a multitude of available retail electricity plans, the removal of incentive schemes and the impending introduction of disruptive technologies such as peer-to-peer energy trading. The introduction of Smart Grid technologies, particularly smart meters, enables consumers to leverage high temporal resolution energy consumption data to optimise system design based on an individual customer's circumstance. In this research, real-world energy consumption data for a large sample of homes are applied to an optimisation strategy developed to the select system size, tilt, azimuth and retail electricity plan for a residential PV-BESS based on a customer's temporal load profile. A case study examining a real world hybrid PV-BESS is presented to demonstrate the potential benefit of applying the optimisation process established in this research. Particle swarm optimisation (PSO) is utilised as the underlying optimisation algorithm given its suitability to mixed integer non-linear programming problems, characteristic of the energy models developed in this research. To improve global search performance with minimal parameter adjustments, various forms of PSO are applied including quantum-behaved PSO and a modified version with a comprehensive learning component. To facilitate energy yield modelling, accurate hourly solar irradiation and photovoltaic array generation models are critical to the optimisation process. Numerous models have been developed to estimate diffuse and direct irradiance components based on global irradiation measurements. The Boland–Ridley–Lauret (BRL) model consists of a single set of parameters for all global locations. There is scope to improve the BRL model to better match local climatic conditions. In this research, the Köppen-Geiger climate classification system is considered to develop a set of adjusted BRL models for Australian conditions, which are subsequently applied to the energy models developed in this research. With the future application of peer-to-peer energy trading markets, prospective investors would benefit from prior consideration of market conditions and the penetration rates of participant PV-BESS systems when designing such systems. In this research, a lifetime assessment of PV-BESS systems is undertaken for a hypothetical peer-to-peer market of over 2,000 participants. Trader margin, participant margin, network tariff structures and PV-BESS penetration rate scenarios are considered to examine the impacts on the optimal PV-BESS design maximising the economic return

Peer-to-peer and community-based markets: A comprehensive review

The advent of more proactive consumers, the so-called "prosumers", with production and storage capabilities, is empowering the consumers and bringing new opportunities and challenges to the operation of power systems in a market environment. Recently, a novel proposal for the design and operation of electricity markets has emerged: these so-called peer-to-peer (P2P) electricity markets conceptually allow the prosumers to directly share their electrical energy and investment. Such P2P markets rely on a consumer-centric and bottom-up perspective by giving the opportunity to consumers to freely choose the way they are to source their electric energy. A community can also be formed by prosumers who want to collaborate, or in terms of operational energy management. This paper contributes with an overview of these new P2P markets that starts with the motivation, challenges, market designs moving to the potential future developments in this field, providing recommendations while considering a test-case

A Novel Locality Algorithm and Peer-to-Peer Communication Infrastructure for Optimizing Network Performance in Smart Microgrids

[EN] Peer-to-Peer (P2P) overlay communications networks have emerged as a new paradigm for implementing distributed services in microgrids due to their potential benefits: they are robust, scalable, fault-tolerant, and they can route messages even with a large number of nodes which are frequently entering or leaving from the network. However, current P2P systems have been mainly developed for file sharing or cycle sharing applications where the processes of searching and managing resources are not optimized. Locality algorithms have gained a lot of attention due to their potential to provide an optimized path to groups with similar interests for routing messages in order to get better network performance. This paper develops a fully functional decentralized communication architecture with a new P2P locality algorithm and a specific protocol for monitoring and control of microgrids. Experimental results show that the proposed locality algorithm reduces the number of lookup messages and the lookup delay time. Moreover, the proposed communication architecture heavily depends of the lookup used algorithm as well as the placement of the communication layers within the architecture. Experimental results will show that the proposed techniques meet the network requirements of smart microgrids even with a large number of nodes on stream.This work is supported by the Spanish Ministry of Economy and Competitiveness (MINECO) and the European Regional Development Fund (ERDF) under Grant ENE2015-64087-C2-2R. This work is supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under BES-2013-064539.Marzal-Romeu, S.; González-Medina, R.; Salas-Puente, RA.; Figueres Amorós, E.; Garcerá, G. (2017). A Novel Locality Algorithm and Peer-to-Peer Communication Infrastructure for Optimizing Network Performance in Smart Microgrids. 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