Cloud Computing on Smartphone

Cloud computing is the most recent technology for data storage & access. Cloud computing includes specific space on the server, the data can be accessed from or stored on the cloud. Cloud computing results into the high speed data accessed capability. Now a days, Every organization have their own cloud where the data is stored related to their work and whenever required it is accessed. Cloud computing is the platform as a service, key players in this sector is Google, Amazon and Microsoft. Smartphone’s and tablets have another growing market so these two technologies combined to form the new concept that is the Smartphone application will access the cloud. The platform evaluated which are suitable for the Smartphone devices is Amazon Web Services. These services allow features like Compute, Database & Storage. Keywords—cloud computing, Smartphones,Android,Amazon

Context Aware Adaptable Applications - A global approach

Actual applications (mostly component based) requirements cannot be expressed without a ubiquitous and mobile part for end-users as well as for M2M applications (Machine to Machine). Such an evolution implies context management in order to evaluate the consequences of the mobility and corresponding mechanisms to adapt or to be adapted to the new environment. Applications are then qualified as context aware applications. This first part of this paper presents an overview of context and its management by application adaptation. This part starts by a definition and proposes a model for the context. It also presents various techniques to adapt applications to the context: from self-adaptation to supervised approached. The second part is an overview of architectures for adaptable applications. It focuses on platforms based solutions and shows information flows between application, platform and context. Finally it makes a synthesis proposition with a platform for adaptable context-aware applications called Kalimucho. Then we present implementations tools for software components and a dataflow models in order to implement the Kalimucho platform

Internet of things: why we are not there yet

Twenty-one years past since Weiser’s vision of ubiquitous computing (UbiComp) has been written, and it is yet to be fully fulfilled despite of almost all the needed technologies already available. Still, the widespread interest in UbiComp and the results in some of its fields pose a question: why we are not there yet? It seems we miss the ‘octopus’ head. In this paper, we will try to depict the reasons why we are not there yet, from three different points of view: interaction media, device integration and applications

Towards Securing Peer-to-peer SIP in the MANET Context: Existing Work and Perspectives

The Session Initiation Protocol (SIP) is a key building block of many social applications, including VoIP communication and instant messaging. In its original architecture, SIP heavily relies on servers such as proxies and registrars. Mobile Ad hoc NETworks (MANETs) are networks comprised of mobile devices that communicate over wireless links, such as tactical radio networks or vehicular networks. In such networks, no fixed infrastructure exists and server-based solutions need to be redesigned to work in a peer-to-peer fashion. We survey existing proposals for the implementation of SIP over such MANETs and analyze their security issues. We then discuss potential solutions and their suitability in the MANET context

Service Isolation vs. Consolidation: Implications for Iaas Cloud Application Deployment

Service isolation, achieved by deploying components of multi -tier applications using separate virtual machines (VMs), is a common \u27best\u27 practice. Various advantages cited include simpler deployment architectures, easier resource scalability for supporting dynamic application throughput requirements, and support for component-level fault tolerance . This paper presents results from an empirical study which investigates the performance implications of component placement for deployments of multi -tier applications to Infrastructure-as-a- Service (IaaS) clouds. Relationship s between performance and resource utilization (CPU, disk, network) are investigated to better understand the implications which result from how applications are deployed. All possible deployments for two variants of a multi -tier application were tested, one computationally bound by the model, the other bound by a geospatial database. The best performing deployments required as few as 2 VMs, half the number required for service isolation, demonstrating potential cost savings with service consolidation. Resource use (CPU time, disk I/O, and network I/O) varied based on component placement and VM memory allocation. Using separate VMs to host each application component resulted in performance overhead of ~1 -2%. Relationships between resource utilization an d performance were harnessed to build a multiple linear regression model to predict performance of component deployments. CPU time, disk sector reads, and disk sector writes are identified as the most powerful performance predictors for component deployments