114,904 research outputs found

    Game Theoretical Approach for Joint Relay Selection and Resource Allocation in Mobile Device Networks

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    With the improvement of hardware, more and more multimedia applications are allowed to run in the mobile device. However, due to the limited radio bandwidth, wireless network performance becomes a critical issue. Common mobile solutions are based on the centralized structure, which require an access point to handle all the communication requirement in the work area. The transmission performance of centralized framework relies on the density of access points. But increasing the number of access points will cost lot of money and the interference between access point will reduce the transmission quality. Thanks to the wireless sensor network implementations, the distributed wireless network solution has been well studied. Now, many mobile network studies introduce the device to device idea which is a distributed structure of mobile network. Unlike wireless sensor networks, mobile networks have more movability and higher transmission speed requirement. In order to be used in mobile networks, a distributed network management algorithm needs to perform faster and more accurate. In this thesis, a new pairing algorithm is proposed to provide a better transmission quality for multimedia data. In the proposed approach, the multimedia data is quantized by distortion reduction. Then, the source-relay pairing solution is optimized by a history tracing system using game theory to improve the expected overall distortion reduction of the entire network. Several parameters are introduced in the proposed solution, so the optimization would fit for different situations. Simulation results show that the proposed algorithm achieves higher overall distortion reduction by avoiding the competition between nodes. Simulation results also show the parameters would affect the system performance, such as optimization speed, system stability and system overall transmit speed

    Distributed and Centralized Task Allocation: When and Where to Use Them

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    Self-organisation is frequently advocated as the solution for managing large, dynamic systems. Distributed algorithms are implicitly designed for infinitely large problems, while small systems are regarded as being controllable using traditional, centralised approaches. Many real-world systems, however, do not fit conveniently into these "small" or "large" categories, resulting in a range of cases where the optimal solution is ambiguous. This difficulty is exacerbated by enthusiasts of either approach constructing problems that suit their preferred control architecture. We address this ambiguity by building an abstract model of task allocation in a community of specialised agents. We are inspired by the problem of work distribution in distributed satellite systems, but the model is also relevant to the resource allocation problems in distributed robotics, autonomic computing and wireless sensor networks. We compare the behaviour of a self-organising, market-based task allocation strategy to a classical approach that uses a central controller with global knowledge. The objective is not to prove one mechanism inherently superior to the other; instead we are interested in the regions of problem space where each of them dominates. Simulation is used to explore the trade-off between energy consumption and robustness in a system of intermediate size, with fixed communication costs and varying rates of component failure. We identify boundaries between regions in the parameter space where one or the other architecture will be favoured. This allows us to derive guidelines for system designers, thus contributing to the development of a disciplined approach to controlling distributed systems using self-organising mechanisms

    Location Estimation in Wireless Sensor Networks Using Spring-Relaxation Technique

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    Accurate and low-cost autonomous self-localization is a critical requirement of various applications of a large-scale distributed wireless sensor network (WSN). Due to its massive deployment of sensors, explicit measurements based on specialized localization hardware such as the Global Positioning System (GPS) is not practical. In this paper, we propose a low-cost WSN localization solution. Our design uses received signal strength indicators for ranging, light weight distributed algorithms based on the spring-relaxation technique for location computation, and the cooperative approach to achieve certain location estimation accuracy with a low number of nodes with known locations. We provide analysis to show the suitability of the spring-relaxation technique for WSN localization with cooperative approach, and perform simulation experiments to illustrate its accuracy in localization
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