Mobilemicroservices Architecture for Remote Monitoring of Patients : A Feasibility Study

Recent developments in smart mobile devices (SMDs), wearable sensors, the Internet, mobile networks, and computing power provide new healthcare opportunities that are not restricted geographically. This paper aims to introduce Mobilemicroservices Architecture (MMA) based on a study on architectures. In MMA, an HTTP-based Mobilemicroservivce (MM) is allocated to each SMD's sensor. The key benefits are extendibility, scalability, ease of use for the patient, security, and the possibility to collect raw data without the necessity to involve cloud services. Feasibility was investigated in a two-year project, where MMA-based solutions were used to collect motor function data from patients with Parkinson's disease. First, we collected motor function data from 98 patients and healthy controls during their visit to a clinic. Second, we monitored the same subjects in real-time for three days in their everyday living environment. These MMA applications represent HTTP-based business-logic computing in which the SMDs' resources are accessible globally.publishedVersionPeer reviewe

Matching 5G Connected Vehicles to Sensed Vehicles for Safe Cooperative Autonomous Driving

5G connected autonomous vehicles (CAVs) help enhance perception of driving environment and cooperation among vehicles by sharing sensing and driving information, which is a promising technology to avoid accidents and improve road-use efficiency. A key issue for cooperation among CAVs is matching communicating vehicles to those captured in sensors such as cameras, LiDAR, etc.. Incorrect vehicle matching may cause serious accidents. While centimeter level positioning is now available for autonomous vehicles, matching connected vehicles to sensed vehicles (MCSV) is still challenging and has rarely been studied. In this paper, we are motivated to investigate the MCSV problem for 5G CAVs, propose and assess solutions for the problem to bridge the research gap. We formulate the MCSV problem and propose two MCSV approaches to support cooperative driving. The first approach is based on vehicle registration number (VRN), which is unique to identify a vehicle and can be shared among CAVs for MCSV. VRN is hashed before sharing to protect privacy, and will be compared to the shared one for vehicle matching. The second MCSV approach is based on visual features of vehicle’s external views, which are shared with other CAVs and compared to those obtained from visual sensors to match the vehicles of interest. A new MCSV dataset is developed to assess the effectiveness of the proposed approaches. Experiment results show that both approaches are feasible and useful, and they achieve a very low false positive rate, which is critical for cooperative driving safety

Performance analysis of mobile networks under signalling storms

There are numerous security challenges in cellular mobile networks, many of which originate from the Internet world. One of these challenges is to answer the problem with increasing rate of signalling messages produced by smart devices. In particular, many services in the Internet are provided through mobile applications in an unobstructed manner, such that users get an always connected feeling. These services, which usually come from instant messaging, advertising and social networking areas, impose significant signalling loads on mobile networks by frequent exchange of control data in the background. Such services and applications could be built intentionally or unintentionally, and result in denial of service attacks known as signalling attacks or storms. Negative consequences, among others, include degradations of mobile network’s services, partial or complete net- work failures, increased battery consumption for infected mobile terminals. This thesis examines the influence of signalling storms on different mobile technologies, and proposes defensive mechanisms. More specifically, using stochastic modelling techniques, this thesis first presents a model of the vulnerability in a single 3G UMTS mobile terminal, and studies the influence of the system’s internal parameters on stability under a signalling storm. Further on, it presents a queueing network model of the radio access part of 3G UMTS and examines the effect of the radio resource control (RRC) inactivity timers. In presence of an attack, the proposed dynamic setting of the timers manage to lower the signalling load in the network and to increase the threshold above which a network failure could happen. Further on, the network model is upgraded into a more generic and detailed model, represent different generations of mobile technologies. It is than used to compare technologies with dedicated and shared organisation of resource allocation, referred to as traditional and contemporary networks, using performance metrics such as: signalling and communication delay, blocking probability, signalling load on the network’s nodes, bandwidth holding time, etc. Finally, based on the carried analysis, two mechanisms are proposed for detection of storms in real time, based on counting of same-type bandwidth allocations, and usage of allocated bandwidth. The mechanisms are evaluated using discrete event simulation in 3G UMTS, and experiments are done combining the detectors with a simple attack mitigation approach.Open Acces

Investigating TCP performance in mobile ad hoc networks

Mobile ad hoc networks (MANETs) have become increasingly important in view of their promise of ubiquitous connectivity beyond traditional fixed infrastructure networks. Such networks, consisting of potentially highly mobile nodes, have provided new challenges by introducing special consideration stemming from the unique characteristics of the wireless medium and the dynamic nature of the network topology. The TCP protocol, which has been widely deployed on a multitude of internetworks including the Internet, is naturally viewed as the de facto reliable transport protocol for use in MANETs. However, assumptions made at TCP’s inception reflected characteristics of the prevalent wired infrastructure of networks at the time and could subsequently lead to sub-optimal performance when used in wireless ad hoc environments. The basic presupposition underlying TCP congestion control is that packet losses are predominantly an indication of congestion in the network. The detrimental effect of such an assumption on TCP’s performance in MANET environments has been a long-standing research problem. Hence, previous work has focused on addressing the ambiguity behind the cause of packet loss as perceived by TCP by proposing changes at various levels across the network protocol stack, such as at the MAC mechanism of the transceiver or via coupling with the routing protocol at the network layer. The main challenge addressed by the current work is to propose new methods to ameliorate the illness-effects of TCP’s misinterpretation of the causes of packet loss in MANETs. An assumed restriction on any proposed modifications is that resulting performance increases should be achievable by introducing limited changes confined to the transport layer. Such a restriction aids incremental adoption and ease of deployment by requiring minimal implementation effort. Further, the issue of packet loss ambiguity, from a transport layer perspective, has, by definition, to be dealt with in an end-to-end fashion. As such, a proposed solution may involve implementation at the sender, the receiver or both to address TCP shortcomings. Some attempts at describing TCP behaviour in MANETs have been previously reported in the literature. However, a thorough enquiry into the performance of those TCP agents popular in terms of research and adoption has been lacking. Specifically, very little work has been performed on an exhaustive analysis of TCP variants across different MANET routing protocols and under various mobility conditions. The first part of the dissertation addresses this shortcoming through extensive simulation evaluation in order to ascertain the relative performance merits of each TCP variant in terms of achieved goodput over dynamic topologies. Careful examination reveals sub-par performance of TCP Reno, the largely equivalent performance of NewReno and SACK, whilst the effectiveness of a proactive TCP variant (Vegas) is explicitly stated and justified for the first time in a dynamic MANET environment. Examination of the literature reveals that in addition to losses caused by route breakages, the hidden terminal effect contributes significantly to non-congestion induced packet losses in MANETs, which in turn has noticeably negative impact on TCP goodput. By adapting the conservative slow start mechanism of TCP Vegas into a form suitable for reactive TCP agents, like Reno, NewReno and SACK, the second part of the dissertation proposes a new Reno-based congestion avoidance mechanism which increases TCP goodput considerably across long paths by mitigating the negative effects of hidden terminals and alleviating some of the ambiguity of non-congestion related packet loss in MANETs. The proposed changes maintain intact the end-to-end semantics of TCP and are solely applicable to the sender. The new mechanism is further contrasted with an existing transport layer-focused solution and is shown to perform significantly better in a range of dynamic scenarios. As solution from an end-to-end perspective may be applicable to either or both communicating ends, the idea of implementing receiver-side alterations is also explored. Previous work has been primarily concerned with reducing receiver-generated cumulative ACK responses by “bundling” them into as few packets as possible thereby reducing misinterpretations of packet loss due to hidden terminals. However, a thorough evaluation of such receiver-side solutions reveals limitations in common evaluation practices and the solutions themselves. In an effort to address this shortcoming, the third part of this research work first specifies a tighter problem domain, identifying the circumstances under which the problem may be tackled by an end-to-end solution. Subsequent original analysis reveals that by taking into account optimisations possible in wireless communications, namely the partial or complete omission of the RTS/CTS handshake, noticeable improvements in TCP goodput are achievable especially over long paths. This novel modification is activated in a variety of topologies and is assessed using new metrics to more accurately gauge its effectiveness in a wireless multihop environment

Applications of wireless sensor technologies in construction

The construction industry is characterised by a number of problems in crucial fields such as health, safety and logistics. Since these problems affect the progress of construction projects, the construction industry has attempted to introduce the use of innovative information and communication technologies on the construction site. Specific technologies which find applicability on the construction site are wireless sensors, and especially radio-frequency identification (RFID) technology. RFID tagging is a technology capable of tracking items. The technology has been applied on the construction site for various applications, such as asset tracking. There are many problems related to health, safety and logistics on the construction site which could be resolved using RFID technology. In the health and safety field, the problems which exist are the monitoring of dangerous areas on the construction site, such as large excavation areas, the collisions between workers and vehicles, between vehicles and equipment and between vehicles, the detection of hazardous substances on the construction site when the construction work has been completed and the collection of hazard notifications from specific areas of the construction site as feedback for the prevention of future accidents. In the logistics field, the tracking of a material during its delivery on the construction site, its transportation to specific subcontractors and its future utilisation as well as the monitoring of the rate of use of materials on the construction site, the checking of the sequence of steel members and the monitoring of the temperature of porous materials are issues which can be realised using RFID technology. In order to facilitate the use of RFID technology for the specific health, safety and logistics problems, a system has been developed. The operation of this system is based on the combined use of hardware and software elements. The hardware elements of the developed system are a wireless local area network, RFID readers and tags. Its software elements are a software development kit based on which, a number of graphical user interfaces have been created for the interaction of the users with the REID tags, and Notepad files which store data collected from REID tags through the graphical user interfaces. Each of the graphical user interfaces is designed in such a way so that it corresponds to the requirements of the health, safety or logistics situation in which it is used. The proposed system has been tested on a simulated construction site by a group of experts and a number of findings have been produced. Specifically, the testing of the proposed system showed that RFID technology can connect the different stages which characterise the construction supply chain. In addition, it showed the capability of the technology to be integrated with construction processes. The testing of the system also revealed the barriers and the enablers to the use of RFID technology in the construction industry. An example of such a barrier is the unwillingness of the people of the construction industry to quit traditional techniques in favour of a new technology. Enablers which enhance the use of RFID technology in the construction industry are the lack of complexity which characterises the operation of RFID tagging and the relatively low cost of RFID tags. In general, RFID technology is an innovative sensor technology which can help the construction industry through its asset tracking ability. However, further research should be done on the improvement of RFID technology on specific characteristics, such as its inability to provide location coordinates and the resilience of the electromagnetic signal emitted by the RFID reader when there are metallic objects around the reader

Row generation techniques for approximate solution of linear programming problems

Ankara : The Department of Industrial Engineering and the Institute of Engineering and Science of Bilkent University, 2010.Thesis (Master's) -- Bilkent University, 2010.Includes bibliographical references leaves 69-77.In this study, row generation techniques are applied on general linear programming problems with a very large number of constraints with respect to the problem dimension. A lower bound is obtained for the change in the objective value caused by the generation of a specific row. To achieve row selection that results in a large shift in the feasible region and the objective value at each row generation iteration, the lower bound is used in the comparison of row generation candidates. For a warm-start to the solution procedure, an effective selection of the subset of constraints that constitutes the initial LP is considered. Several strategies are discussed to form such a small subset of constraints so as to obtain an initial solution close to the feasible region of the original LP. Approximation schemes are designed and compared to make possible the termination of row generation at a solution in the proximity of an optimal solution of the input LP. The row generation algorithm presented in this study, which is enhanced with a warm-start strategy and an approximation scheme is implemented and tested for computation time and the number of rows generated. Two efficient primal simplex method variants are used for benchmarking computation times, and the row generation algorithm appears to perform better than at least one of them especially when number of constraints is large.Paç, A BurakM.S

Federated learning for edge computing: A survey

New technologies bring opportunities to deploy AI and machine learning to the edge of the network, allowing edge devices to train simple models that can then be deployed in practice. Federated learning (FL) is a distributed machine learning technique to create a global model by learning from multiple decentralized edge clients. Although FL methods offer several advantages, including scalability and data privacy, they also introduce some risks and drawbacks in terms of computational complexity in the case of heterogeneous devices. Internet of Things (IoT) devices may have limited computing resources, poorer connection quality, or may use different operating systems. This paper provides an overview of the methods used in FL with a focus on edge devices with limited computational resources. This paper also presents FL frameworks that are currently popular and that provide communication between clients and servers. In this context, various topics are described, which include contributions and trends in the literature. This includes basic models and designs of system architecture, possibilities of application in practice, privacy and security, and resource management. Challenges related to the computational requirements of edge devices such as hardware heterogeneity, communication overload or limited resources of devices are discussed.Web of Science1218art. no. 912

Three Horizons of AI: Towards a Theory of Change Model for Machine Learning

Artificial intelligence, and specifically, predictive models based on machine learning, will be the basis of future economic and social systems. While a great deal of focus has been placed on job loss in the face of automation, the more profound effect of machine learning will be fundamental changes throughout our technologically based social systems, as we witness the increasing use of machine learning systems in governance roles. Machine learning has so far shown itself to be a double edged sword in its ability to accelerate social justice: therapy chatbots, for example, have shown how we might scale mental healthcare to include persons who may not be able to afford a therapist. But precrime predictive algorithms in use by some of North America’s largest police forces are biased by flawed data sets and tend to perpetuate racial and economic stereotypes. My project will research, analyse, deconstruct, and then map trends in machine learning onto a Three Horizons foresight framework with a 12 year time horizon. I will describe a third horizon vision for machine learning as a social and not economic innovation that delivers social impact, second horizon strategies that might steer applications of machine learning towards greater designedness for social justice, and a Theory of Change alternative to the concept of business model to describe how we might implement machine learning strategies for human rather than economic growth