Operational Cost of Running Real-Time Mobile Cloud Applications

This chapter describes the concepts and cost models used for determining the cost of providing cloud services to mobile applications using different pricing models. Two recently implemented mobile-cloud applications are studied in terms of both the cost of providing such services by the cloud operator, and the cost of operating them by the cloud user. Computing resource requirements of both applications are identified and worksheets are presented to demonstrate how businesses can estimate the operational cost of implementing such real-time mobile cloud applications at a large scale, as well as how much cloud operators can profit from providing resources for these applications. In addition, the nature of available service level agreements (SLA) and the importance of quality of service (QoS) specifications within these SLAs are emphasized and explained for mobile cloud application deployment.

A Tutorial on Network Latency and Its Measurements

Internet latency is crucial in providing reliable and efficient networked services when servers are placed in geographically diverse locations. The trend of mobile, cloud, and distributed computing accelerates the importance of accurate latency measurement due to its nature of rapidly changing locations and interactivity. Accurately measuring latency, however, is not easy due to lack of testing resources, the sheer volume of collected data points, the tedious and repetitive aspect of measurement practice, clock synchronization, and network dynamics. This chapter discusses the techniques that use PlanetLab to measure latency in the Internet, its underlying infrastructure, representative latency results obtained from experiments, and how to use these measure latencies. The chapter covers 1) details of using PlanetLab, 2) the Internet infrastructure that causes the discrepancy between local and global latencies, and 3) measured latency results from our own experiments and analysis on the distributions, averages, and their implications.

Hardware and Software Aspects of VM-Based Mobile-Cloud Offloading

To allow mobile devices to support resource intensive applications beyond their capabilities, mobile-cloud offloading is introduced to extend the resources of mobile devices by leveraging cloud resources. In this chapter, we will survey the state-of-the-art in VM-based mobile-cloud offloading techniques including their software and architectural aspects in detail. For the software aspects, we will provide the current improvements to different layers of various virtualization systems, particularly focusing on mobile-cloud offloading. Approaches at different offloading granularities will be reviewed and their advantages and disadvantages will be discussed. For the architectural support aspects of the virtualization, three platforms including Intel x86, ARM and NVidia GPUs will be reviewed in terms of their special architectural designs to accommodate virtualization and VM-based offloading.

Towards Privacy-Preserving Medical Cloud Computing Using Homomorphic Encryption

Personal health monitoring tools, such as commercially available wireless ECG patches, can significantly reduce healthcare costs by allowing patient monitoring outside the healthcare organizations. These tools transmit the acquired medical data into the cloud, which could provide an invaluable diagnosis tool for healthcare professionals. Despite the potential of such systems to revolutionize the medical field, the adoption of medical cloud computing in general has been slow due to the strict privacy regulations on patient health information. We present a novel medical cloud computing approach that eliminates privacy concerns associated with the cloud provider. Our approach capitalizes on Fully Homomorphic Encryption (FHE), which enables computations on private health information without actually observing the underlying data. For a feasibility study, we present a working implementation of a long-term cardiac health monitoring application using a well-established open source FHE library.

Reach to Mobile Platforms and Availability

This chapter is practical system planning tutorial for internetworks that include radio-WANs. Author is retired USCG officer with both operational and program planning experience. In second career, author taught ‘plowshares into swords internetworking' at the graduate level. The coaching herein reflects operational, planning, and academic experiences. Considering mobile communications requires adjusting some assumptions and working knowledge from a wholly wired internetwork. The advent of radio – the necessary means to mobile – entails changes in topology, capacity and nature of the media (shared). Further, the extension of the internetwork to mobile usually means rather overt embracing of mission critical applications.

Theoretical Foundation and GPU Implementation of Face Recognition

Enabling a machine to detect and recognize faces requires significant computational power. This particular system of face recognition makes use of OpenCV (Computer Vision) libraries while leveraging Graphics Processing Units (GPUs) to accelerate the process towards real-time. The processing and recognition algorithms are best sorted into three distinct steps: detection, projection, and search. Each of these steps has unique computational characteristics and requirements driving performance. In particular, the detection and projection processes can be accelerated significantly with GPU usage due to the data types and arithmetic types associated with the algorithms, such as matrix manipulation. This chapter provides a survey of the three main processes and how they contribute to the overarching recognition process.

Secure Health Monitoring in the Cloud Using Homomorphic Encryption

Extending cloud computing to medical software, where the hospitals rent the software from the provider sounds like a natural evolution for cloud computing. One problem with cloud computing, though, is ensuring the medical data privacy in applications such as long term health monitoring. Previously proposed solutions based on Fully Homomorphic Encryption (FHE) completely eliminate privacy concerns, but are extremely slow to be practical. Our key proposition in this paper is a new approach to applying FHE into the data that is stored in the cloud. Instead of using the existing circuit-based programming models, we propose a solution based on Branching Programs. While this restricts the type of data elements that FHE can be applied to, it achieves dramatic speed-up as compared to traditional circuit-based methods. Our claims are proven with simulations applied to real ECG data.

Volunteer Computing on Mobile Devices

Different forms of parallel computing have been proposed to address the high computational requirements of many applications. Building on advances in parallel computing, volunteer computing has been shown to be an efficient way to exploit the computational resources of under utilized devices that are available around the world. The idea of including mobile devices, such as smartphones and tablets, in existing volunteer computing systems has recently been investigated. In this chapter, we present the current state of the art in the mobile volunteer computing research field, where personal mobile devices are the elements that perform the computation. Starting from the motivations and challenges behind the adoption of personal mobile devices as computational resources, we then provide a literature review of the different architectures that have been proposed to support parallel computing on mobile devices. Finally, we present some open issues that need to be investigated in order to extend user participation and improve the overall system performance for mobile volunteer computing.

Energy Efficient Real-Time Distributed Communication Architectures for Military Tactical Communication Systems

For military communication systems, it is important to achieve robust and energy efficient real-time communication among a group of mobile users without the support of a pre-existing infrastructure. Furthermore, these communication systems must support multiple communication modes, such as unicast, multicast, and network-wide broadcast, to serve the varied needs in military communication systems. One use for these military communication systems is in support of real-time mobile cloud computing, where the response time is of utmost importance; therefore, satisfying real-time communication requirements is crucial. In this chapter, we present a brief overview of military tactical communications and networking (MTCAN). As an important example of MTCAN, we present the evolution of the TRACE family of protocols, describing the design of the TRACE protocols according to the tactical communications and networking requirements. We conclude the chapter by identifying how the TRACE protocols can enable mobile cloud computing within military communication systems.

Sensing as a Service in Cloud-Centric Internet of Things Architecture

Sensing-as-a-Service (S2aaS) is a cloud-inspired service model which enables access to the Internet of Things (IoT) architecture. The IoT denotes virtually interconnected objects that are uniquely identifiable, and are capable of sensing, computing and communicating. Built-in sensors in mobile devices can leverage the performance of IoT applications in terms of energy and communication overhead savings by sending their data to the cloud servers. Sensed data from mobile devices can be accessed by IoT applications on a pay-as-you-go fashion. Efficient sensing service provider search techniques are emerging components of this architecture, and they should be accompanied with effective sensing provider recruitment algorithms. Furthermore, reliability and trustworthiness of participatory sensed data appears as a big challenge. This chapter provides an overview of the state of the art in S2aaS systems, and reports recent proposals to address the most crucial challenges. Furthermore, the chapter points out the open issues and future directions for the researchers in this field.