7 resultados para Multi-user

em Aston University Research Archive


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Link quality-based rate adaptation has been widely used for IEEE 802.11 networks. However, network performance is affected by both link quality and random channel access. Selection of transmit modes for optimal link throughput can cause medium access control (MAC) throughput loss. In this paper, we investigate this issue and propose a generalised cross-layer rate adaptation algorithm. It considers jointly link quality and channel access to optimise network throughput. The objective is to examine the potential benefits by cross-layer design. An efficient analytic model is proposed to evaluate rate adaptation algorithms under dynamic channel and multi-user access environments. The proposed algorithm is compared to link throughput optimisation-based algorithm. It is found rate adaptation by optimising link layer throughput can result in large performance loss, which cannot be compensated by the means of optimising MAC access mechanism alone. Results show cross-layer design can achieve consistent and considerable performance gains of up to 20%. It deserves to be exploited in practical design for IEEE 802.11 networks.

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Research shows that consumers are readily embracing the Internet to buy products. This paper proposes that, in the case of grocery shopping, this may lead to sub-optimal decisions at the household level. Decisions online on what, where and from who to buy are normally taken by one individual. In the case of grocery shopping, decisions, however, need to be ‘vetted’ by ‘other’ individuals within the household. The ‘household wide related’ decisions influence how information technologies and systems for commerce should be designed and managed for optimum decision making. This paper argues, unlike previous research, that e-grocery retailing is failing to grow to its full potential not solely because of the ‘classical’ hazards and perceived risks associated with doing grocery shopping online but because e-grocery retailing strategy has failed to acknowledge the micro-household level specificities that affect decision making. Our exploratory research is based on empirical evidence which were collected through telephone interviews. We offer an insight into how e-grocery ‘fits’ and is ‘disrupted’ by the reality of day to day consumption decision making at the household level. Our main finding is to advocate a more role-neutral, multi-user and multi-technology approach to e-grocery shopping which re-defines the concept of the main shopper/decision maker thereby reconceptualising the ‘shopping logic’ for grocery products.

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It is desirable that energy performance improvement is not realized at the expense of other network performance parameters. This paper investigates the trade off between energy efficiency, spectral efficiency and user QoS performance for a multi-cell multi-user radio access network. Specifically, the energy consumption ratio (ECR) and the spectral efficiency of several common frequency domain packet schedulers in a cellular E-UTRAN downlink are compared for both the SISO transmission mode and the 2x2 Alamouti Space Frequency Block Code (SFBC) MIMO transmission mode. It is well known that the 2x2 SFBC MIMO transmission mode is more spectrally efficient compared to the SISO transmission mode, however, the relationship between energy efficiency and spectral efficiency is undecided. It is shown that, for the E-UTRAN downlink with fixed transmission power, spectral efficiency improvement results into energy efficiency improvement. The effect of SFBC MIMO versus SISO on the user QoS performance is also studied. © 2011 IEEE.

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT The research presented in this thesis is concerned with Discrete-Event Simulation (DES) modelling as a method to facilitate logistical policy development within the UK Less-than-Truckload (LTL) freight distribution sector which has been typified by “Pallet Networks” operating on a hub-and-spoke philosophy. Current literature relating to LTL hub-and-spoke and cross-dock freight distribution systems traditionally examines a variety of network and hub design configurations. Each is consistent with classical notions of creating process efficiency, improving productivity, reducing costs and generally creating economies of scale through notions of bulk optimisation. Whilst there is a growing abundance of papers discussing both the network design and hub operational components mentioned above, there is a shortcoming in the overall analysis when it comes to discussing the “spoke-terminal” of hub-and-spoke freight distribution systems and their capabilities for handling the diverse and discrete customer profiles of freight that multi-user LTL hub-and-spoke networks typically handle over the “last-mile” of the delivery, in particular, a mix of retail and non-retail customers. A simulation study is undertaken to investigate the impact on operational performance when the current combined spoke-terminal delivery tours are separated by ‘profile-type’ (i.e. retail or nonretail). The results indicate that a potential improvement in delivery performance can be made by separating retail and non-retail delivery runs at the spoke-terminal and that dedicated retail and non-retail delivery tours could be adopted in order to improve customer delivery requirements and adapt hub-deployed policies. The study also leverages key operator experiences to highlight the main practical implementation challenges when integrating the observed simulation results into the real-world. The study concludes that DES be harnessed as an enabling device to develop a ‘guide policy’. This policy needs to be flexible and should be applied in stages, taking into account the growing retail-exposure.

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In Information Filtering (IF) a user may be interested in several topics in parallel. But IF systems have been built on representational models derived from Information Retrieval and Text Categorization, which assume independence between terms. The linearity of these models results in user profiles that can only represent one topic of interest. We present a methodology that takes into account term dependencies to construct a single profile representation for multiple topics, in the form of a hierarchical term network. We also introduce a series of non-linear functions for evaluating documents against the profile. Initial experiments produced positive results.

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The number of interoperable research infrastructures has increased significantly with the growing awareness of the efforts made by the Global Earth Observation System of Systems (GEOSS). One of the Societal Benefit Areas (SBA) that is benefiting most from GEOSS is biodiversity, given the costs of monitoring the environment and managing complex information, from space observations to species records including their genetic characteristics. But GEOSS goes beyond simple data sharing to encourage the publishing and combination of models, an approach which can ease the handling of complex multi-disciplinary questions. It is the purpose of this paper to illustrate these concepts by presenting eHabitat, a basic Web Processing Service (WPS) for computing the likelihood of finding ecosystems with equal properties to those specified by a user. When chained with other services providing data on climate change, eHabitat can be used for ecological forecasting and becomes a useful tool for decision-makers assessing different strategies when selecting new areas to protect. eHabitat can use virtually any kind of thematic data that can be considered as useful when defining ecosystems and their future persistence under different climatic or development scenarios. The paper will present the architecture and illustrate the concepts through case studies which forecast the impact of climate change on protected areas or on the ecological niche of an African bird.

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The popularity of online social media platforms provides an unprecedented opportunity to study real-world complex networks of interactions. However, releasing this data to researchers and the public comes at the cost of potentially exposing private and sensitive user information. It has been shown that a naive anonymization of a network by removing the identity of the nodes is not sufficient to preserve users’ privacy. In order to deal with malicious attacks, k -anonymity solutions have been proposed to partially obfuscate topological information that can be used to infer nodes’ identity. In this paper, we study the problem of ensuring k anonymity in time-varying graphs, i.e., graphs with a structure that changes over time, and multi-layer graphs, i.e., graphs with multiple types of links. More specifically, we examine the case in which the attacker has access to the degree of the nodes. The goal is to generate a new graph where, given the degree of a node in each (temporal) layer of the graph, such a node remains indistinguishable from other k-1 nodes in the graph. In order to achieve this, we find the optimal partitioning of the graph nodes such that the cost of anonymizing the degree information within each group is minimum. We show that this reduces to a special case of a Generalized Assignment Problem, and we propose a simple yet effective algorithm to solve it. Finally, we introduce an iterated linear programming approach to enforce the realizability of the anonymized degree sequences. The efficacy of the method is assessed through an extensive set of experiments on synthetic and real-world graphs.