Q u e nti n S c h u ell er K as hi n at h B as u M u h a m m a d Y o u n as S c h o ol of E n gi n e eri n g, C o m p uti n g a n d M at h e m ati cs O xf or d Br o o k es U ni v ersit y O xf or d, U nit e d Ki n g d o m { k b as u, m. y o u n as } @ br o o k es. a c. u k
Cloud service selection process is significantly challenging and complicated as there are various QoS factors to consider when selecting cloud services. This paper proposes a new QoS-aware selection model systematically and succinctly representing QoS attributes which cloud consumers can easily use and understand when selecting cloud services. In order to ensure the credibility of the cloud service selection, the proposed model collects QoS data from different sources including cloud providers, users' reviews and cloud monitoring tools. It implements Multi-Criteria Decision Making models in order to rank services based on various QoS attributes. The proposed model is implemented as a simulation tool which is deployed on Amazon cloud platform. Using the simulation tool, the proposed model is rigorously evaluated through a number of experiments by taking into account data from widely used commercial cloud service providers. The experimental results show that the proposed model ranks and selects cloud services according to the QoS requirements of cloud service consumers. Unlike existing approaches the proposed model takes into account multi-level QoS attributes and data from real cloud providers when ranking cloud services.
Cloud service selection is complicated by the prospect that there exist a large number of services and each service is characterized by multiple QoS attributes. Various commercial tools have been developed in order to help cloud consumers with selecting best cloud services. This paper provides an in-depth analysis of the three commercial cloud service selection tools as well as the way they represent QoS attributes. Accordingly, it proposes a new model that succinctly represents QoS attributes which cloud consumers can easily use (and understand) when selecting cloud services. The proposed model also classifies the QoS attributes into four main categories of technical, strategic & organizational, economic and political & legislative. These QoS attributes can also be seamlessly fed into the multi-criteria decision (e.g., MCDM)-which compares and ranks different QoS attributes of multiple alternatives in order to decide which services are most suitable for cloud consumers.
With the growing popularity of cloud computing the number of cloud service providers and services have significantly increased. Thus selecting the best cloud services becomes a challenging task for prospective cloud users. The process of selecting cloud services involves various factors such as characteristics and models of cloud services, user requirements and knowledge, and service level agreement (SLA), to name a few. This paper investigates into the cloud service selection tools, techniques and models by taking into account the distinguishing characteristics of cloud services. It also reviews and analyses academic research as well as commercial tools in order to identify their strengths and weaknesses in the cloud services selection process. It proposes a framework in order to improve the cloud service selection by taking into account services capabilities, quality attributes, level of user's knowledge and service level agreements. The paper also envisions various directions for future research.
Satellite networks are seen as having the potential to play an important role in machine-to-machine (M2M) communications and the Internet of Things, which in turn is seen as being important to a number of service sectors. However, certain M2M application have bounded latency requirements that in some cases may be quite stringent. Satellite networks general much higher latency that wired networks and therefore may not be able to meet the requirements of all M2M applications. This paper compares the latency requirements of certain time-critical applications with reported satellite network latency and address the problem of latency evaluation of networks support these types of application including those involving satellite links.
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