Real-time QoS Monitoring for Big Data Analytics in Mobile Environment: an Overview <s> THE QUALITY OF SERVICE PROVISIONING OF THE MOBILE LARGE SCALE AD HOC <s> The general field of mobile ad hoc networking is still in its infancy. Particularly, the challenge of providing Quality-of-Service (QoS) support for ad hoc networks is an open problem and remains relatively uncharted territory. Providing a complete QoS solution for the ad hoc networking environment requires the interaction and cooperation of several components. These components include: (1) a QoS routing protocol, (2) a resource reservation scheme and (3) a QoS capable medium access control (MAC) layer. In this paper, we present a survey of the current research that has addressed each of these components in the context of ad hoc networks. This work is intended to provide a broad and comprehensive view of the various components and protocols required to provide QoS support in computer networks, focusing primarily on ad hoc networks. First, we introduce the unique characteristics of mobile ad hoc networks, which distinguishing this new network architecture from traditional infrastructured wired and wireless networks (i.e. cellular-based networks). We also discuss the impact of these characteristics on QoS provisioning. Next, we describe the first QoS model proposed for mobile ad hoc networks and its relationship to QoS models proposed for the Internet. We then present a review of the proposed algorithms for each QoS component (e.g. QoS routing, resource reservation and the MAC layer). Copyright © 2002 John Wiley & Sons, Ltd. <s> BIB001 </s> Real-time QoS Monitoring for Big Data Analytics in Mobile Environment: an Overview <s> THE QUALITY OF SERVICE PROVISIONING OF THE MOBILE LARGE SCALE AD HOC <s> Mobile Cloud Computing (MCC) is broadening the ubiquitous market for mobile devices. Because of the hardware limitation of mobile devices, the heavy computing tasks should be processed by service images (SIs) on the cloud. Due to the scalability and mobility of users and services, dynamic resource demands and time-varying network condition, SIs must be re-located to adapt the new circumstances. In this paper, we formulate the SI placement as an optimization problem which minimizes the communication cost subject to resource demand constraints. We then propose a real-time SI placement scheme which includes two sequent stages of clustering/filtering and condensed placement to solve the formulated problem. The former omits the infeasible slots prior to placement in order to improve computational complexity. The latter focuses on the SI placement through a novel condensed solution. The numerical results show that our solution converges to the global optimum with a negligible gap while performing much faster execution time compared with the exhaustive search method. This improvement leverages the real-time services especially in MCC environment. <s> BIB002
The QoS provisioning for the mobile network (in these cases relating to the wireless ad hoc networks) has been very vital in settling on the mobile network-centric competition. The new concept of the quality of service Provisioning has been devolved and research on the same has been done. However, the quality of service for the mobile ad hocs is an imperative aspect in relation to the reliance of and transmission of data from remote locations BIB001 . The most appropriate architecture of the quality of service for the monitoring of the mobile big data and the interrelate networks requires the application of several source nodes and the actions of the flows. In order for the quality of service to be fully integrative and adjustable to the real time flows there are four main components that play in hand. The scalable quality of service, congestion control, the adaptive bandwidth management and the data call admission control The overview of the mobile computing was initially coined in after the cloud computing concept. In the current information technology scenery the mobile cloud computing has attracted a lot of attention from many industry players thus making an area of interest (Pandey, Voorsluys, Niu, Khandoker & Buyya, 2012). In order to fully understand the workability of the MMC and its relationship with the big data analytics is very essential to have clear overview of the architecture up on which the Mobile cloud computing relies on. The full structure operates up on several layers and components. At the users end the interaction the leads to the determination of the requirements of the quality of service is provided by the Software as the service this includes the Microsoft live mesh, the android play store and the apple cloud. Subsequently, this develops to the platform as a service this mainly involves the actual engines that operates the wares and the software's, in this case includes the Google app engines and the Microsoft azures. The other layer that help in the determination and the analysis of the quality of service for the real time Mobile computing environment is the Infrastructures for the cases of the mobile environment this includes the EC2 and B3. The final layer is the data centers that help in the storage and the management of the mobile big data BIB002 ).