8,958 research outputs found

    Using big data for customer centric marketing

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    This chapter deliberates on “big data” and provides a short overview of business intelligence and emerging analytics. It underlines the importance of data for customer-centricity in marketing. This contribution contends that businesses ought to engage in marketing automation tools and apply them to create relevant, targeted customer experiences. Today’s business increasingly rely on digital media and mobile technologies as on-demand, real-time marketing has become more personalised than ever. Therefore, companies and brands are striving to nurture fruitful and long lasting relationships with customers. In a nutshell, this chapter explains why companies should recognise the value of data analysis and mobile applications as tools that drive consumer insights and engagement. It suggests that a strategic approach to big data could drive consumer preferences and may also help to improve the organisational performance.peer-reviewe

    Smart antenna system management utilising multi-agent systems

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    Abstract : Cellular communication networks are large and distributed systems that provide billions of people around the world with means of communication. Antennas as used currently in cellular communication networks do not provide efficient resource management given the growth in the current communication network scenario. Most of the problems are related to the number of devices that can connect to an antenna, the coverage map of an antenna, and frequency management. A smart antenna grid can cover the same area as traditional cellular system towers with some enhancements. Smart antenna grids can include a device in an area that requires connectivity rather than covering of the entire area. Frequencies are handled per antenna base, with more focus on providing stable communication. The objective of the dissertation is to improve resource management of smart antenna grids by making use of a multi-agent system. The dissertation uses a simulation environment that illustrates a smart antenna grid that operates with a multi-agent system that is responsible for resource management. The simulation environment is used to execute ten scenarios that intends to place large amounts of strain on the resources of the smart antenna grid to determine the effectiveness of using a multi-agent system. The ten scenarios show that when resources deplete, the multi-agent system intervenes, and that when there are too many devices connected to one smart antenna, the devices are managed. At the same time, when there are antennas that have frequency problems, the frequencies are reassigned. One of the scenarios simulated the shutdown of antennas forcing devices to disconnect from the antenna and connect to a different antenna. The multi-agent system shows that the different agents can manage the resources in a smart grid that is related to frequencies, antennas and devices.M.Sc. (Computer Science

    DYVERSE: DYnamic VERtical Scaling in Multi-tenant Edge Environments

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    Multi-tenancy in resource-constrained environments is a key challenge in Edge computing. In this paper, we develop 'DYVERSE: DYnamic VERtical Scaling in Edge' environments, which is the first light-weight and dynamic vertical scaling mechanism for managing resources allocated to applications for facilitating multi-tenancy in Edge environments. To enable dynamic vertical scaling, one static and three dynamic priority management approaches that are workload-aware, community-aware and system-aware, respectively are proposed. This research advocates that dynamic vertical scaling and priority management approaches reduce Service Level Objective (SLO) violation rates. An online-game and a face detection workload in a Cloud-Edge test-bed are used to validate the research. The merits of DYVERSE is that there is only a sub-second overhead per Edge server when 32 Edge servers are deployed on a single Edge node. When compared to executing applications on the Edge servers without dynamic vertical scaling, static priorities and dynamic priorities reduce SLO violation rates of requests by up to 4% and 12% for the online game, respectively, and in both cases 6% for the face detection workload. Moreover, for both workloads, the system-aware dynamic vertical scaling method effectively reduces the latency of non-violated requests, when compared to other methods
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