Abstract-Large-scale component-based enterprise applications that leverage Cloud resources expect Quality of Service (QoS) guarantees in accordance with service level agreements between the customer and service providers. In the context of Cloud computing, autoscaling mechanisms hold the promise of assuring QoS properties to the applications while simultaneously making efficient use of resources and keeping operational costs low for the service providers. Despite the perceived advantages of autoscaling, realizing the full potential of autoscaling is hard due to multiple challenges stemming from the need to precisely estimate resource usage in the face of significant variability in client workload patterns. This paper makes three contributions to overcome the general lack of effective techniques for workload forecasting and optimal resource allocation. First, it discusses the challenges involved in autoscaling in the cloud. Second, it develops a model-predictive algorithm for workload forecasting that is used for resource autoscaling. Finally, empirical results are provided that demonstrate that resources can be allocated and deallocated by our algorithm in a way that satisfies both the application QoS while keeping operational costs low.

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Abstract-The Internet of Things (IoT) is the result of many different enabling technologies such as embedded systems, wireless sensor networks, cloud computing, big-data, etc. used to gather, process, infer, and transmit data. Integrating all these technologies requires a comprehensive and holistic research effort to address all the challenges imposed by these technologies, especially for sensing and delivering information from physical world to cloud-hosted services. In this paper, we outline the most important issues related to standardization efforts, mobility of objects, networking and gateway access, and QoS support. In particular, we describe a novel IoT network architecture that integrates Software Defined Networking (SDN) and the Object Management Group's Data Distribution Service (DDS) middleware. The proposed architecture will improve service delivery of IoT system and will bring flexibility to the network.