Integrated billing mechanisms in the Internet of Things to support information sharing and enable new business opportunities

The Internet of Things (IOT) concept and enabling technologies such as RFID offer the prospect of linking the real world of physical objects with the virtual world of information technology to improve visibility and traceability information within supply chains and across the entire lifecycles of products, as well as enabling more intuitive interactions and greater automation possibilities. There is a huge potential for savings through process optimization and profit generation within the IOT, but the sharing of financial benefits across companies remains an unsolved issue. Existing approaches towards sharing of costs and benefits have failed to scale so far. The integration of payment solutions into the IOT architecture could solve this problem. We have reviewed different possible levels of integration. Multiple payment solutions have been researched. Finally we have developed a model that meets the requirements of the IOT in relation to openness and scalability. It supports both hardware-centric and software-centric approaches to integration of payment solutions with the IOT. Different requirements concerning payment solutions within the IOT have been defined and considered in the proposed model. Possible solution providers include telcos, e-payment service providers and new players such as banks and standardization bodies. The proposed model of integrating the Internet of Things with payment solutions will lower the barrier to invoicing for the more granular visibility information generated using the IOT. Thus, it has the potential to enable recovery of the necessary investments in IOT infrastructure and accelerate adoption of the IOT, especially for projects that are only viable when multiple benefits throughout the supply chain need to be accumulated in order to achieve a Return on Investment (ROI). In a long-term perspective, it may enable IT-departments to become profit centres instead of cost centres. © 2010 - IOS Press and the authors. All rights reserved.

Dialogical strategies for orchestrating strategic innovation networks: the case of the Internet of Things

Strategic innovation has been shown to provide significant value for organisations whilst at the same time challenging traditional ways of thinking and working. There is less known, however, as to how organisations collaborate in innovation networks to achieve strategic innovation. In this paper we explore how innovation networks are orchestrated in developing a strategic innovation initiative around the Internet of Things. We show how a hub actor brings together a diverse group of actors to initially create and subsequently orchestrate the strategic innovation network through the employ of three dialogical strategies, namely persuasive projection, reflective development, and definitional control. Further, we illuminate how different types of legitimacy are established through these various dialogical strategies in orchestrating strategic innovation networks.

基于Internet工作流的复合Web服务框架

实现灵活方便的企业业务集成一直是信息领域的核心问题，也是B2B电子商务应用的关键。为此将Web服务和传统的工作流技术相结合，设计并实现了支持复合Web服务运行和管理的框架WSFlow。给出了WSFlow的总体结构，描述了其中的关键技术，包括Web服务与工作流活动的动态配置和绑定技术，复合Web服务流程的动态修改以及复合Web服务的运行监控等技术。

基于支持向量机的Internet流量分类研究

准确的网络流量分类是众多网络研究工作的基础,也一直是网络测量领域的研究热点.近年来,利用机器学习方法处理流量分类问题成为了该领域一个新兴的研究方向.在目前研究中应用较多的是朴素贝叶斯(nave Bayes,NB)及其改进算法.这些方法具有实现简单、分类高效的特点.但该方法过分依赖于样本空间的分布,具有内在的不稳定性.因此,提出一种基于支持向量机(support vector machine,SVM)的流量分类方法.该方法利用非线性变换和结构风险最小化(structural risk minimization,SRM)原则将流量分类问题转化为二次寻优问题,具有良好的分类准确率和稳定性.在理论分析的基础上,通过在实际网络流集合上与朴素贝叶斯算法的对比实验,可以看出使用支持向量机方法处理流量分类问题,具有以下3个优势:1)网络流属性不必满足条件独立假设,无须进行属性过滤;2)能够在先验知识相对不足的情况下,仍保持较高的分类准确率;3)不依赖于样本空间的分布,具有较好的分类稳定性.

结合操作者意图分析的Internet机器人控制方法研究

互联网传输过程中存在的随机时延,影响了操作者与遥操作机器人之间的实时交互,降低了系统稳定性和操作性能。论文提出一种新的方法,利用动态神经元群模型对操作者发送的控制指令序列进行分析,实现对操作者意图的推断。在随机时延条件下,遥操作机器人能够根据操作者意图和当前环境信息,通过局部自主控制完成期望任务动作。同时可以与主端操作者基于事件的控制指令进行切换,来保证系统的稳定性,提高整个控制系统的操作性能和效率。最后,通过互联网足球机器人平台进行实验,仿真结果验证了所提模型与方法的有效性和可行性。