Cost- and Energy-Aware Multi-Flow Mobile Data Offloading Using Markov Decision Process

With the rapid increase in demand for mobile data, mobile network operators are trying to expand wireless network capacity by deploying wireless local area network (LAN) hotspots on which they can offload their mobile traffic. However, these network-centric methods usually do not fulfill the interests of mobile users (MUs). Taking into consideration many issues, MUs should be able to decide whether to offload their traffic to a complementary wireless LAN. Our previous work studied single-flow wireless LAN offloading from a MU's perspective by considering delay-tolerance of traffic, monetary cost and energy consumption. In this paper, we study the multi-flow mobile data offloading problem from a MU's perspective in which a MU has multiple applications to download data simultaneously from remote servers, and different applications' data have different deadlines. We formulate the wireless LAN offloading problem as a finite-horizon discrete-time Markov decision process (MDP) and establish an optimal policy by a dynamic programming based algorithm. Since the time complexity of the dynamic programming based offloading algorithm is still high, we propose a low time complexity heuristic offloading algorithm with performance sacrifice. Extensive simulations are conducted to validate our proposed offloading algorithms

A new model for the development of information systems

The most commonly used systems specification and design techniques in commercial computing are described and compared; Information Engineering as proposed by James Martin, A Framework for Information Definition-Muitiview proposed by Wood-Harper et al, Real-world Modeling as described by Jackson, Structured Analysis and Design as In Demarco, Yourdon and Constantine and Output-Oriented Structured Requirement Definition proposed by Orr. In addition, system prototyping is discussed, including the role of prototyping in large software development projects and as a tool for the design of human-computer interfaces. Other areas described and discussed include decision support systems (DSS) and knowledge based management support systems. The context is in the design and development approaches for DSS, prototyping for DSS, expert system for DSS and the integration of DSS and information system. The design and development of human-computer interface is also discussed in relation to user Interface complexity and adaptive interfaces. Further, the important issue of user involvement and support within the development process Is discussed. Thus, weaknesses of current approaches to the system development process are identified and a new model for the development of information system is proposed. In proposing the model, data and functional analysis structured method and methodology for decision support systems (DSS) development is presented including guidelines for the development of knowledge based DSS. The new proposed model is put to test in the design, development and implementation of large integrated commercial systems including DSS. Results and discussion on the use of the model is reported with special consideration to the users' and developers' view of the model. Finally the objectives of this research program are examined in relation to what has been achieved during this program of research. The prospect of using the model for the development of information systems are concluded with references to current and future goals

Automated camera ranking and selection using video content and scene context

PhDWhen observing a scene with multiple cameras, an important problem to solve is to automatically identify “what camera feed should be shown and when?” The answer to this question is of interest for a number of applications and scenarios ranging from sports to surveillance. In this thesis we present a framework for the ranking of each video frame and camera across time and the camera network, respectively. This ranking is then used for automated video production. In the first stage information from each camera view and from the objects in it is extracted and represented in a way that allows for object- and frame-ranking. First objects are detected and ranked within and across camera views. This ranking takes into account both visible and contextual information related to the object. Then content ranking is performed based on the objects in the view and camera-network level information. We propose two novel techniques for content ranking namely: Routing Based Ranking (RBR) and Multivariate Gaussian based Ranking (MVG). In RBR we use a rule based framework where weighted fusion of object and frame level information takes place while in MVG the rank is estimated as a multivariate Gaussian distribution. Through experimental and subjective validation we demonstrate that the proposed content ranking strategies allows the identification of the best-camera at each time. The second part of the thesis focuses on the automatic generation of N-to-1 videos based on the ranked content. We demonstrate that in such production settings it is undesirable to have frequent inter-camera switching. Thus motivating the need for a compromise, between selecting the best camera most of the time and minimising the frequent inter-camera switching, we demonstrate that state-of-the-art techniques for this task are inadequate and fail in dynamic scenes. We propose three novel methods for automated camera selection. The first method (¡go f ) performs a joint optimization of a cost function that depends on both the view quality and inter-camera switching so that a i Abstract ii pleasing best-view video sequence can be composed. The other two methods (¡dbn and ¡util) include the selection decision into the ranking-strategy. In ¡dbn we model the best-camera selection as a state sequence via Directed Acyclic Graphs (DAG) designed as a Dynamic Bayesian Network (DBN), which encodes the contextual knowledge about the camera network and employs the past information to minimize the inter camera switches. In comparison ¡util utilizes the past as well as the future information in a Partially Observable Markov Decision Process (POMDP) where the camera-selection at a certain time is influenced by the past information and its repercussions in the future. The performance of the proposed approach is demonstrated on multiple real and synthetic multi-camera setups. We compare the proposed architectures with various baseline methods with encouraging results. The performance of the proposed approaches is also validated through extensive subjective testing

Information management for viable organisations

The recent global „credit crunch? has brought sharply into focus the need for better understanding of what it takes for organisations to survive. This research seeks to help organisations maintain their „viability? – the ability to maintain a separate existence and survive on their own. Whilst there are a multitude of factors that contribute to organisational viability, information can be viewed as the lifeblood of organisations. This research increases our understanding of how organisations can manage information effectively to help maintain their viability. The viable systems model (VSM) is an established modelling technique that enables the detailed analysis of organisational activity to examine how the structure and functions performed in an organisation contribute to its „viability?. The VSM has been widely applied, in small/large companies, industries and governments. However, whilst the VSM concentrates on the structure and functions necessary for an organisation to be viable, it pays much less attention to information deployment in organisations. Indeed, the VSM is criticised in the literature for being unable to provide much help with detailed information and communication structures and new theories are called for to explore the way people interact and what information they need in the VSM. This research analyses qualitative data collected from four case studies to contribute to our understanding of the role that information plays in organisational viability, making three key contributions to the academic literature. In the information management literature, this research provides new insight into the roles that specific information plays in organisations. In the systems thinking literature, this research extends our understanding of the VSM and builds on its powerful diagnostic capability to provide further criteria to aid in the diagnosis of viable organisations. In the information systems literature, this research develops a framework that can be used to help organisations design more effective information systems

Aligning Global and Local Aspects of A National Information Programme for Health: Developing a Critical and Socio-Technical Appreciation

Written by a full-time clinician, this thesis explores an example of ‘Big IT’ in healthcare, the National Programme for IT in the United Kingdom National Health Service. It is unique in exploring the interaction between people and information technology in the healthcare workplace, from an engaged standpoint within one of the National Programme’s implementation sites, in order to provide a critical and a socio-technical appreciation

Plethora : a framework for the intelligent control of robotic assembly systems

Plethora : a framework for the intelligent control of robotic assembly system