Software as a service

About: Software as a service is a research topic. Over the lifetime, 8514 publications have been published within this topic receiving 136177 citations. The topic is also known as: Service as a Software Substitute & SaaSS.

A comber approach to protect cloud computing against XML DDoS and HTTP DDoS attack

Abstract: Cloud computing is an internet based pay as use service which provides three layered services (Software as a Service, Platform as a Service and Infrastructure as a Service) to its consumers on demand. These on demand service facilities provide to its consumers in multitenant environment but as facility increases complexity and security problems also increase. Here all the resources are at one place in data centers. Cloud uses public and private APIs (Application Programming Interface) to provide services to its consumers in multitenant environment. In this environment Distributed Denial of Service attack (DDoS), especially HTTP, XML or REST based DDoS attacks may be very dangerous and may provide very harmful effects for availability of services and all consumers will get affected at the same time. One other reason is that because the cloud computing users make their request in XML then send this request using HTTP protocol and build their system interface with REST protocol such as Amazon EC2 or Microsoft Azure. So the threaten coming from distributed REST attacks are more and easy to implement by the attacker, but to security expert very difficult to resolve. So to resolve these attacks this paper introduces a comber approach for security services called filtering tree. This filtering tree has five filters to detect and resolve XML and HTTP DDoS attack.

Understanding the influence of absorptive capacity and ambidexterity on the process of business model change - the case of on-premise and cloud-computing software

Abstract: The increasing popularity of Software as a Service has strongly affected the established business model of on-premise enterprise software. Software as a Service has distinctive characteristics of disruptive innovations that typically create several difficulties for incumbent firms, in particular with regard to adapting business models. To date, however, little empirical understanding exists regarding the dynamics of business model change - a topic of special importance to the highly dynamic software industry, which is characterised by rapid and regular emergence of disruptive innovations. As disruptive innovations require gathering distant knowledge and experimenting with new ideas, this study addresses theoretical gaps regarding the role of absorptive capacity and organisational ambidexterity in the process of business model change owing to the emergence of a disruptive innovation. Drawing on evidence from multiple case studies of six incumbent vendors of enterprise resource-planning software and informed by a thorough review of related secondary data, we investigate the pace and path of incumbents' business model adaptations. We propose a theoretical model that refines prior literature on absorptive capacity and organisational ambidexterity, particularly with regard to the process of business model change. This study identifies further technological factors that determine how and why incumbents change business models. In addition, our study provides in-depth insights on the technological trajectory of enterprise resource-planning software switching from on-premise to on-demand software services. © 2016 Blackwell Publishing Ltd

System and method for provisioning software

Abstract: A method of remotely provisioning a managed hardware device connected to a network and having a hard drive, includes on a remote server connected to the network, creating a service order defining provisioning requirements of the device, discovering said device from said server, sending a service robot to the device from said server, sending a software container to the device from said server, starting up software in said container, and monitoring the device from said server.

Integrated Data Management for a Fleet of Search-and-rescue Robots

Abstract: Search-and-rescue operations have recently been confronted with the introduction of robotic tools that assist the human search-and-rescue workers in their dangerous but life-saving job of searching for human survivors after major catastrophes. However, the world of search and rescue is highly reliant on strict procedures for the transfer of messages, alarms, data, and command and control over the deployed assets. The introduction of robotic tools into this world causes an important structural change in this procedural toolchain. Moreover, the introduction of search-and-rescue robots acting as data gatherers could potentially lead to an information overload toward the human search-and-rescue workers, if the data acquired by these robotic tools are not managed in an intelligent way. With that in mind, we present in this paper an integrated data combination and data management architecture that is able to accommodate real-time data gathered by a fleet of robotic vehicles on a crisis site, and we present and publish these data in a way that is easy to understand by end-users. In the scope of this paper, a fleet of unmanned ground and aerial search-and-rescue vehicles is considered, developed within the scope of the European ICARUS project. As a first step toward the integrated data-management methodology, the different robotic systems require an interoperable framework in order to pass data from one to another and toward the unified command and control station. As a second step, a data fusion methodology will be presented, combining the data acquired by the different heterogenic robotic systems. The computation needed for this process is done in a novel mobile data center and then (as a third step) published in a software as a service (SaaS) model. The SaaS model helps in providing access to robotic data over ubiquitous Ethernet connections. As a final step, we show how the presented data-management architecture allows for reusing recorded exercises with real robots and rescue teams for training purposes and teaching search-and-rescue personnel how to handle the different robotic tools. The system was validated in two experiments. First, in the controlled environment of a military testing base, a fleet of unmanned ground and aerial vehicles was deployed in an earthquake-response scenario. The data gathered by the different interoperable robotic systems were combined by a novel mobile data center and presented to the end-user public. Second, an unmanned aerial system was deployed on an actual mission with an international relief team to help with the relief operations after major flooding in Bosnia in the spring of 2014. Due to the nature of the event (floods), no ground vehicles were deployed here, but all data acquired by the aerial system (mainly three-dimensional maps) were stored in the ICARUS data center, where they were securely published for authorized personnel all over the world. This mission (which is, to our knowledge, the first recorded deployment of an unmanned aerial system by an official governmental international search-and-rescue team in another country) proved also the concept of the procedural integration of the ICARUS data management system into the existing procedural toolchain of the search and rescue workers, and this in an international context (deployment from Belgium to Bosnia). The feedback received from the search-and-rescue personnel on both validation exercises was highly positive, proving that the ICARUS data management system can efficiently increase the situational awareness of the search-and-rescue personnel.