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A Break in the Clouds: Towards a Cloud Definition

The unabated flurry of research activities to augment various mobile devices in terms of compute-intensive task execution by leveraging heterogeneous resources of available devices in the local vicinity has created a new research domain called mobile ad hoc cloud MAC or mobile cloud. It is a new type of mobile cloud computing MCC. MAC is deemed to be a candidate blueprint for future compute-intensive applications with the aim of delivering high functionalities and rich impressive experience to mobile users. However, MAC is yet in its infancy, and a comprehensive survey of the domain is still lacking. In this paper, we survey the state-of-the-art research efforts carried out in the MAC domain. We analyze several problems inhibiting the adoption of MAC and review corresponding solutions by devising a taxonomy. Moreover, MAC roots are analyzed and taxonomized as architectural components, applications, objectives, characteristics, execution model, scheduling type, formation technologies, and node types. The similarities and differences among existing proposed solutions by highlighting the advantages and disadvantages are also investigated. We also compare the literature based on objectives. Furthermore, our study advocates that the problems stem from the intrinsic characteristics of MAC by identifying several new principles. Lastly, several open research challenges such as incentives, heterogeneity-ware task allocation, mobility, minimal data exchange, and security and privacy are presented as future research directions. Copyright © 2016 John Wiley & Sons, Ltd.

Mobile ad hoc cloud: A survey

A survey of adaptation techniques in computation offloading

The past decade has seen the emergence of Vehicular Clouds as a topic of research in its own right. Vehicular clouds were inspired by the reality of present-day vehicles featuring an impressive array of on-board compute, storage and sensing capabilities and by the insight that these on-board capabilities are a vast untapped resource that, at the moment, is wasted. Harvesting these vehicular resources and putting them to work in a meaningful and productive way promises to have a significant and lasting societal impact. One of the defining ways in which vehicular clouds differ from conventional clouds is resource volatility. As vehicles enter and leave the cloud, new compute resources become available while others depart, creating a volatile environment where reasoning about fundamental performance metrics becomes very challenging. Given that vehicular clouds and their numerous variants have becomes a very active field of research, this seems to be a good moment to survey the state of the art of vehicular cloud research. In this survey, we adopt an inclusive rather than an exclusive definition of various flavors of vehicular clouds. Vehicular clouds, in their many incarnations, have a huge array of potential applications. In order to bring this potential to fruition, significant research challenges have to be overcome. With this in mind, this survey identifies promising applications and draws attention to a number of research challenges facing the vehicular clouds community at large.

A Survey of Vehicular Cloud Research: Trends, Applications and Challenges

At present, many cloud services are managed by using open source software, such as OpenStack and Eucalyptus, because of the unification management of data, cost reduction, quick delivery and work savings. The operation phase of cloud computing has a unique feature, such as the provisioning processes, the network-based operation and the diversity of data, because the operation phase of cloud computing changes depending on many external factors. We propose a jump diffusion model with two-dimensional Wiener processes in order to consider the interesting aspects of the network traffic and big data on cloud computing. In particular, we assess the stability of cloud software by using the sample paths obtained from the jump diffusion model with two-dimensional Wiener processes. Moreover, we discuss the optimal maintenance problem based on the proposed jump diffusion model. Furthermore, we analyze actual data to show numerical examples of dependability optimization based on the software maintenance cost considering big data on cloud computing.

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Reliability Analysis Based on a Jump Diffusion Model with Two Wiener Processes for Cloud Computing with Big Data

Mobile cloud computing promises more effective and efficient utilization of the ever-increasing pool of computing resources available on modern mobile devices. To support mobile cloud computing, we propose a Collaborative Autonomic Resource Management System (CARMS), which automatically manages task scheduling and resource allocation to realize efficient cloud formation and computing in a dynamic mobile environment. CARMS utilizes our previously proposed Global Resource Positioning System (GRPS) to track current and future availability of mobile resources. In this paper, we present CARMS architecture and its associated Adaptive List-based Scheduling and Allocation AlgorithM (ALSALAM) for adaptive task scheduling and resource allocation. ALSALAM uses the continually updated data from the loosely federated GRPS to automatically select appropriate mobile nodes to participate informing clouds, and to adjust both task scheduling and resource allocation according to the changing conditions due to the dynamicity of resources and tasks in an existing cloud. Our simulation results show that CARMS offers effective and efficient support for mobile cloud computing that has not yet been adequately provided by prior research. KeywordsMobile cloud computing; Resource management; Dynamic resource maps;Autonomic computing; Collaborative computing.

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Collaborative Autonomic Resource Management System for Mobile Cloud Computing

The emergence of Mobile Ad-hoc Clouds (MACs) promises more effective and collaborative elastic resource-infinite computing However, the highly dynamic, mobile, heterogeneous, fractionized, and scattered nature of computing resources coupled with the isolated non-cooperative nature of current resource management systems make it impossible for current virtualization and resource management techniques to guarantee resilient cloud service delivery In this paper, we present PlanetCloud, our MAC management platform with an intrinsic support for resilient, highly mobile, cooperative, and dynamically-configurable MACs We use PlanetCloud for the construction and management of resilient hybrid MACs (HMACs) over mobile and stationary computing resources PlanetCloud comprises a trustworthy fine-grained virtualization layer and a task management layer PlanetCloud employs the concepts of application virtualization and fractionation using intrinsically-resilient and aware micro virtual machines, or Cells in our terminology, to encapsulate executable applicationfractions Such employment isolates the running application from the underlying physical resource enabling seamless execution over heterogeneous resources, lightweight load migration, and low cost of failure Integral to PlanetCloud is resource forecasting and selection mechanism, which provide a MAC with future appropriate resource availability in space and time Further, these features enable a large set of mobile, heterogeneous, and scattered resources to collaborate through PlanetCloud smart management platforms that seamlessly consolidates such resources into a resilient HMAC Using analysis and simulation, we evaluate a PlanetCloud-managed resilient HMAC Results show that PlanetCloud can provision high level of resource availability transparently maintaining the applications' QoS while preventing service disruption even in highly dynamic environments Additionally, results showed that our approach to minimizing the cost of failure and facilitating easy load migration elevates the resilience of the HMAC to a great extent

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Resilient hybrid Mobile Ad-hoc Cloud over collaborating heterogeneous nodes

We are witnessing the emergence of the ubiquitous resource-infinite computing paradigm. Significant benefits accrue, ranging from added convenience and services for users, to enhanced efficiency and reduced cost for organizations, to improved on-demand resource availability for under-connected areas, extreme environments and distress situations. To this end, we proposed PlanetCloud, a distributed platform that aims to facilitate ubiquitous cloud computing. Integral to PlanetCloud is a Global Resource Positioning System (GRPS), which is an opt-in dynamic spatiotemporal resource calendaring and scheduling system ubiquitously accessed via a portable application (termed iCloud). In this paper, we motivate and present the GRPS concept and its architecture. GRPS would enable the provisioning of, otherwise idle, fixed and mobile resources to effect ubiquitous computing clouds. It aims to aid the formation of mobile computing clouds by providing a dynamic real-time resource scheduling and tracking system that can be accessed through the iCloud. GPRS is designed to access and maintain dynamic data from spatiotemporal calendars, social networking and other sources to enhance resource discovery, forecasting and status tracking to provide access to the right-sized cloud resources anytime and anywhere. We provide an analytical model to compute the resource request-response time. Our results show that we can adapt the performance of a response according to node density and contention window size.

A global resource positioning system for ubiquitous clouds

The exponential growth of computational power and the advent of a multitude of energy-rich fixed and mobile nodes coupled with the emergence of modern resource management and virtualization technologies, Mobile Ad-hoc Clouds (MACs) are emerging as a viable computational asset A major challenge is to construct MACs comprising highly dynamic, mobile, heterogeneous, fractionated, and scattered resources Conventional resource virtualization technologies do not seamlessly consolidate such resources while adequately isolating the resource layer concerns from the executing code logic, which is key for MACs to operate and provision basic services To this end, we propose Planet Cloud, a smart MAC management platform with an intrinsic support for highly mobile, heterogeneously-composed and dynamically-configured MACs Planet Cloud enables MACs to autonomously adapt to real-time dynamic variation in its underlying infrastructure isolating the hardware and code management concerns Such isolation enabled seamless task deployment, execution, migration, dynamic/adaptive resource allocation, and automated failure recovery Analysis and simulation show that the proposed platform can safely and reliably provision and maintain the needed computational power for the MAC to operate in a highly dynamic mobile work environment

Towards a Mobile Ad-Hoc Cloud Management Platform

Mobile cloud computing (MCC) is evolving to efficiently and collaboratively utilize the ever-increasing pool of computing resources available on mobile devices. In such high dynamic networks, nodes are susceptible to failure for many reasons, for example, being out of battery or hijacked. Managing reliability of dynamic mobile resources provides a strong motivation for proactive autonomic management capabilities in the MCC. To this end, we propose a reliable collaborative mobilecloud management system (MobiCloud), which automatically manages task scheduling and reliable resource allocation. MobiCloud utilizes our new opt-in, prediction and trust management services to realize reliable cloud formation and maintenance in a dynamic mobile environment. In this paper, we present MobiCloud architecture and its associated Proactive Adaptive List-based Scheduling and Allocation AlgorithM (P-ALSALAM) for MCC. This algorithm dynamically maps applications' requirements to the currently or potentially reliable mobile resources. Simulation results demonstrate that our proposed system not only significantly improves performance, but also substantially enhances the stability of mobileclouds.

Ahmed Khalifa

Papers

Collaborative Autonomic Resource Management System for Mobile Cloud Computing

Resilient hybrid Mobile Ad-hoc Cloud over collaborating heterogeneous nodes

A global resource positioning system for ubiquitous clouds

Towards a Mobile Ad-Hoc Cloud Management Platform

MobiCloud: A reliable collaborative mobilecloud management system