No abstract

Cloud computing has emerged as one of the latest technologies for delivering on-demand advanced services over the internet. Various cloud providers have developed datacentres which are spread at several geographically locations, and are available for utilization from internet users. However, as the number of resource consumers is increasing significantly, it becomes apparent that the capacity-oriented clouds require coming together and agreeing on common acting behaviours for improving the quality of service, hence providing an overall optimal load allocation. In this direction, current solutions do not support a coordinated distribution of different cloud workloads. Even geographically distributed data-centres from the same vendor (e.g. Amazon) don't support a seamless mechanic for balancing hosted services as the users require indicating their selected hosts' location. To answer this limitation, a recently emerged inter-clouds notion comes to expand cloud capabilities and to offer an improved sharing paradigm of workloads. Herein we present a state-ofthe-art review with a particular focus on the adoptability of current meta-schedulers for managing workloads, towards the inter-cloud era. Specifically, by exploiting inter-cloud requirements (e.g. flexibility, geographically distribution etc.) we evaluate various meta-schedulers for future inter-clouds.

There is an increasing interest in Internet of Things (IoT) and healthcare is considered to be one of the most common applications of it. Using the IoT paradigm, various devices including smart-phones and sensor-embedded healthcare applications can be used for monitoring health. In this study, we model an IoT use case scenario with regard to monitoring the activities associated with health. In particular, we present our use case using the SimIoT extended simulation toolkit to demonstrate the various functions and the interactions occurring within the IoT-enabled healthcare context. Specifically, we extend the functionalities of the SimIC simulation toolkit by adding the IoT layer that incorporates IoT devices which generated data for the private clouds. We focus our experimental analysis from the perspective of cloud performance to illustrate the turnaround and makespan of the system.

Simulating the Inter-Cloud' (SimIC) is a discrete event simulation toolkit based on the process oriented simulation package of SimJava. The SimIC aims of replicating an inter-cloud facility wherein multiple clouds collaborate with each other for distributing service requests with regards to the desired simulation setup. The package encompasses the fundamental entities of the inter-cloud metascheduling algorithm such as users, meta-brokers, localbrokers, datacenters, hosts, hypervisors and virtual machines (VMs). Additionally, resource discovery and scheduling policies together with VMs allocation, re-scheduling and VM migration strategies are included as well. Using the SimIC a modeler can design a fully dynamic inter-cloud setting wherein collaboration is founded on meta-scheduling inspired characteristics of distributed resource managers that exchange user requirements as driven events in real-time simulations. The SimIC aims of achieving interoperability, flexibility and service elasticity while at the same time introducing the notion of heterogeneity of multiple clouds' configurations. In addition it accepts an optimization of a variety of selected performance criteria for a diversity of entities. The crucial factor of dynamics consideration has implemented by allowing reactive orchestration based on current workload of already executed heterogeneous user specifications. These are in the form of text files that the modeler can load in the toolkit and occurs in real-time at different simulation intervals. Finally, a unique request is scheduled for execution to an internal cloud datacenter host VM that is capable of performing the service contract. This is formally designed in Service Level Agreements (SLAs) based upon user profiling.