Optimal advertising campaign generation for multiple brands using MOGA

The paper proposes a new modified multiobjective genetic algorithm (MOGA) for the problem of optimal television (TV) advertising campaign generation for multiple brands. This NP-hard combinatorial optimization problem with numerous constraints is one of the key issues for an advertising agency when producing the optimal TV mediaplan. The classical approach to the solution of this problem is the greedy heuristic, which relies on the strength of the preceding commercial breaks when selecting the next break to add to the campaign. While the greedy heuristic is capable of generating only a group of solutions that are closely related in the objective space, the proposed modified MOGA produces a Pareto-optimal set of chromosomes that: 1) outperform the greedy heuristic and 2) let the mediaplanner choose from a variety of uniformly distributed tradeoff solutions. To achieve these results, the special problem-specific solution encoding, genetic operators, and original local optimization routine were developed for the algorithm. These techniques allow the algorithm to manipulate with only feasible individuals, thus, significantly improving its performance that is complicated by the problem constraints. The efficiency of the developed optimization method is verified using the real data sets from the Canadian advertising industry

Improved Linear Precoding over Block Diagonalization in Multi-cell Cooperative Networks

In downlink multiuser multiple-input multiple-output (MIMO) systems, block diagonalization (BD) is a practical linear precoding scheme which achieves the same degrees of freedom (DoF) as the optimal linear/nonlinear precoding schemes. However, its sum-rate performance is rather poor in the practical SNR regime due to the transmit power boost problem. In this paper, we propose an improved linear precoding scheme over BD with a so-called "effective-SNR-enhancement" technique. The transmit covariance matrices are obtained by firstly solving a power minimization problem subject to the minimum rate constraint achieved by BD, and then properly scaling the solution to satisfy the power constraints. It is proved that such approach equivalently enhances the system SNR, and hence compensates the transmit power boost problem associated with BD. The power minimization problem is in general non-convex. We therefore propose an efficient algorithm that solves the problem heuristically. Simulation results show significant sum rate gains over the optimal BD and the existing minimum mean square error (MMSE) based precoding schemes.Comment: 21 pages, 4 figure

Energy management in communication networks: a journey through modelling and optimization glasses

The widespread proliferation of Internet and wireless applications has produced a significant increase of ICT energy footprint. As a response, in the last five years, significant efforts have been undertaken to include energy-awareness into network management. Several green networking frameworks have been proposed by carefully managing the network routing and the power state of network devices. Even though approaches proposed differ based on network technologies and sleep modes of nodes and interfaces, they all aim at tailoring the active network resources to the varying traffic needs in order to minimize energy consumption. From a modeling point of view, this has several commonalities with classical network design and routing problems, even if with different objectives and in a dynamic context. With most researchers focused on addressing the complex and crucial technological aspects of green networking schemes, there has been so far little attention on understanding the modeling similarities and differences of proposed solutions. This paper fills the gap surveying the literature with optimization modeling glasses, following a tutorial approach that guides through the different components of the models with a unified symbolism. A detailed classification of the previous work based on the modeling issues included is also proposed

On the use of reference points for the biobjective Inventory Routing Problem

The article presents a study on the biobjective inventory routing problem. Contrary to most previous research, the problem is treated as a true multi-objective optimization problem, with the goal of identifying Pareto-optimal solutions. Due to the hardness of the problem at hand, a reference point based optimization approach is presented and implemented into an optimization and decision support system, which allows for the computation of a true subset of the optimal outcomes. Experimental investigation involving local search metaheuristics are conducted on benchmark data, and numerical results are reported and analyzed

Route Planning in Transportation Networks

We survey recent advances in algorithms for route planning in transportation networks. For road networks, we show that one can compute driving directions in milliseconds or less even at continental scale. A variety of techniques provide different trade-offs between preprocessing effort, space requirements, and query time. Some algorithms can answer queries in a fraction of a microsecond, while others can deal efficiently with real-time traffic. Journey planning on public transportation systems, although conceptually similar, is a significantly harder problem due to its inherent time-dependent and multicriteria nature. Although exact algorithms are fast enough for interactive queries on metropolitan transit systems, dealing with continent-sized instances requires simplifications or heavy preprocessing. The multimodal route planning problem, which seeks journeys combining schedule-based transportation (buses, trains) with unrestricted modes (walking, driving), is even harder, relying on approximate solutions even for metropolitan inputs.Comment: This is an updated version of the technical report MSR-TR-2014-4, previously published by Microsoft Research. This work was mostly done while the authors Daniel Delling, Andrew Goldberg, and Renato F. Werneck were at Microsoft Research Silicon Valle

Understanding user experience of mobile video: Framework, measurement, and optimization

Since users have become the focus of product/service design in last decade, the term User eXperience (UX) has been frequently used in the field of Human-Computer-Interaction (HCI). Research on UX facilitates a better understanding of the various aspects of the user’s interaction with the product or service. Mobile video, as a new and promising service and research field, has attracted great attention. Due to the significance of UX in the success of mobile video (Jordan, 2002), many researchers have centered on this area, examining users’ expectations, motivations, requirements, and usage context. As a result, many influencing factors have been explored (Buchinger, Kriglstein, Brandt & Hlavacs, 2011; Buchinger, Kriglstein & Hlavacs, 2009). However, a general framework for specific mobile video service is lacking for structuring such a great number of factors. To measure user experience of multimedia services such as mobile video, quality of experience (QoE) has recently become a prominent concept. In contrast to the traditionally used concept quality of service (QoS), QoE not only involves objectively measuring the delivered service but also takes into account user’s needs and desires when using the service, emphasizing the user’s overall acceptability on the service. Many QoE metrics are able to estimate the user perceived quality or acceptability of mobile video, but may be not enough accurate for the overall UX prediction due to the complexity of UX. Only a few frameworks of QoE have addressed more aspects of UX for mobile multimedia applications but need be transformed into practical measures. The challenge of optimizing UX remains adaptations to the resource constrains (e.g., network conditions, mobile device capabilities, and heterogeneous usage contexts) as well as meeting complicated user requirements (e.g., usage purposes and personal preferences). In this chapter, we investigate the existing important UX frameworks, compare their similarities and discuss some important features that fit in the mobile video service. Based on the previous research, we propose a simple UX framework for mobile video application by mapping a variety of influencing factors of UX upon a typical mobile video delivery system. Each component and its factors are explored with comprehensive literature reviews. The proposed framework may benefit in user-centred design of mobile video through taking a complete consideration of UX influences and in improvement of mobile videoservice quality by adjusting the values of certain factors to produce a positive user experience. It may also facilitate relative research in the way of locating important issues to study, clarifying research scopes, and setting up proper study procedures. We then review a great deal of research on UX measurement, including QoE metrics and QoE frameworks of mobile multimedia. Finally, we discuss how to achieve an optimal quality of user experience by focusing on the issues of various aspects of UX of mobile video. In the conclusion, we suggest some open issues for future study

Dynamic deployment of context-aware access control policies for constrained security devices

Securing the access to a server, guaranteeing a certain level of protection over an encrypted communication channel, executing particular counter measures when attacks are detected are examples of security requirements. Such requirements are identi ed based on organizational purposes and expectations in terms of resource access and availability and also on system vulnerabilities and threats. All these requirements belong to the so-called security policy. Deploying the policy means enforcing, i.e., con guring, those security components and mechanisms so that the system behavior be nally the one speci ed by the policy. The deployment issue becomes more di cult as the growing organizational requirements and expectations generally leave behind the integration of new security functionalities in the information system: the information system will not always embed the necessary security functionalities for the proper deployment of contextual security requirements. To overcome this issue, our solution is based on a central entity approach which takes in charge unmanaged contextual requirements and dynamically redeploys the policy when context changes are detected by this central entity. We also present an improvement over the OrBAC (Organization-Based Access Control) model. Up to now, a controller based on a contextual OrBAC policy is passive, in the sense that it assumes policy evaluation triggered by access requests. Therefore, it does not allow reasoning about policy state evolution when actions occur. The modi cations introduced by our work overcome this limitation and provide a proactive version of the model by integrating concepts from action speci cation languages