Ubiquitous Cloud Research Articles

REVIEW ON TASK SCHEDULING IN UBIQUITOUS CLOUDS

The cloud being a prominent area for research, is ubiquitous as it serves the client needs irrespective of time and place. It has become the most preferred network due to its guaranteed service rendering and cost effectiveness. The increase in the capability of the cloud services has increased the number of users to adapt to cloud. The increase in the adaption towards cloud in turn results with insufficiency in the proper and the simultaneous allocation of the resources according to the requisitions. So the task scheduling and resource allocation for the cloud becomes essential. As the conventional methods of task scheduling arrive to a local optima solution that are less-effective, the paper surveys the meta-heuristic optimization based task scheduling and the resource allocation for the ubiquitous cloud environment, that arrives to an more optimal solution at a faster rate and at ease. The paper presents the survey of the optimization techniques of task scheduling available for the cloud and the discussion of the improvement of the performance metrics in terms of make-span, throughput, cost, latency and successful service provisioning compared to the other conventional methods.

Fog computing enabled cost-effective distributed summarization of surveillance videos for smart cities

Fog computing is emerging an attractive paradigm for both academics and industry alike. Fog computing holds potential for new breeds of services and user experience. However, Fog computing is still nascent and requires strong groundwork to adopt as practically feasible, cost-effective, efficient and easily deployable alternate to currently ubiquitous cloud. Fog computing promises to introduce cloud-like services on local network while reducing the cost. In this paper, we present a novel resource efficient framework for distributed video summarization over a multi-region fog computing paradigm. The nodes of the Fog network is based on resource constrained device Raspberry Pi. Surveillance videos are distributed on different nodes and a summary is generated over the Fog network, which is periodically pushed to the cloud to reduce bandwidth consumption. Different realistic workload in the form of a surveillance videos are used to evaluate the proposed system. Experimental results suggest that even by using an extremely limited resource, single board computer, the proposed framework has very little overhead with good scalability over off-the-shelf costly cloud solutions, validating its effectiveness for IoT-assisted smart cities.

Realizing the Global Edge Cloud

The recent trend toward application hosting in large data centers should and will be counterbalanced by a ubiquitous edge cloud with deeply programmable networking. The Internet to date has been dominated by sending data to programs and people; the next Internet will be dominated by managing data and the connections to people generating and needing the data. In this article, we describe why the Internet is on the cusp of this transition, two prototypes of this next Internet, PlanetLab [1] and the Global Environment for Network Innovations (GENI) [2], and the architectural concepts that emerge from them. We describe the next step: the viral stage, GENI-as-a- Service.

IPOJO flow: a declarative service workflow architecture for ubiquitous cloud applications

The growth of innovative services backed up by various sensors and devices provides an unprecedented potential for ubiquitous computing applications and systems. However, in order to benefit from the recent developments, the current service middleware technology needs a catch-up of being able to fully support interactions among the services. OSGi is considered as a viable service framework solution due to its ability to deal with the dynamism inherent with ubiquitous cloud environments. iPOJO has also emerged as a service component model that simplifies the development of OSGi applications. However, the technology runs short of providing adequate support to foster declarative service compositions of realistic interaction topologies. Noticing this deficiency, we propose an iPOJO component-based service workflow architecture, named iPOJO Flow, where component services can easily be composed together to form realistic, complicated applications. Along with the architectural design, the paper also introduces a new DSL to specify service workflow topologies in a declarative way. The effectiveness of our proposed approach is validated through a prototype demonstration, comparative design analysis, and performance experiments.

Characteristics and categorization of services in CLOUBI: A CLOud-based UBIquitous architecture

Challenges in pure ubiquitous computing, including the limitation of being multi-domain, absence of a uniform namespace, impossible intensive mobility of users, limited resources, lack of scalability, intensive applications, and so forth, have led researchers to provide hybrid ubiquitous architectu res that are generally cloud-based. However, various types of services have not been considered in the introduced hybrid architectures nor have any of these architectures provided a general categorization of services independent of application type. The current paper introduces a cloud-based ubiquitous architecture called as CLOUBI. The main purpose of this architecture is to remove restrictions on pure ubiquitous architectures. In addition, two general categories of services are presented in this architecture, of which one is based on the nature of services and the other on the distance between the requesting and responding entities, with both being independent of application type. In the nature-based categorization, services are divided into four types: data, context-aware, software, and hardware. In the distance-based categorization, services are of five types: near, local, remote, global, and far. In order to design CLOUBI architecture and formulate its proposed categorization, various criteria are examined, including the types of inputs, nature of requests, characteristics of an ideal ubiquitous architecture, and features expected from the services in hybrid architectures. In addition, the most important security concerns related to ubiquitous cloud computing architectures are discussed.

MAGA: A Mobility-Aware Computation Offloading Decision for Distributed Mobile Cloud Computing

Distributed mobile cloud computing (MCC) is the new paradigm for providing ubiquitous cloud resources to mobile users with low latency. Mobility is an important factor in distributed MCC which may incur intermittent connectivity and consequently fail computation offloading requests. Latest researches on human mobility show that mobility of users present inherent patterns, periodicity, and predictability. This motivates us to propose a mobile access prediction algorithm based on tail matching subsequence, whose effectiveness and accuracy is validated by experiments using reality mobility dataset. Then MAGA, a mobility-aware offloading decision method for distributed MCC is proposed in this paper for single-job, multicomponent, and multisite offloading scenario. The proposed mobile access prediction is used in MAGA for cloudlet reliability estimation. An integer encoding-based adaptive genetic algorithm is used for offloading decision. Experiment results show the performance advantages of MAGA.

Towards a Better Understanding of Ubiquitous Cloud Computing

Ubiquitous Cloud Computing has been recently proposed as a new hybrid computing model. This paradigm has two aspects: (a) Making use of cloud services to realize context-awareness (especially for mobile phones) and (b) Introducing a new and hybrid computing model. Likewise, this paper mainly involves two subjects: To deeply investigate previous cloud services that have been utilized to design context-aware systems, and to propose an open architecture for the “Ubiquitous Cloud Computing” paradigm. The aim of this article is to technically discuss mutual trends of ubiquitous and cloud computing, to foster the dissemination of state-of-the-art research in this area, and to present future research directions.

UbeHealth: A Personalized Ubiquitous Cloud and Edge-Enabled Networked Healthcare System for Smart Cities

Smart city advancements are driving massive transformations of healthcare, the largest global industry. The drivers include increasing demands for ubiquitous, preventive, and personalized healthcare, to be provided to the public at reduced risks and costs. Mobile cloud computing could potentially meet the future healthcare demands by enabling anytime, anywhere capture and analyses of patients’ data. However, network latency, bandwidth, and reliability are among the many challenges hindering the realization of next-generation healthcare. This paper proposes a ubiquitous healthcare framework, UbeHealth, that leverages edge computing, deep learning, big data, high-performance computing (HPC), and the Internet of Things (IoT) to address the aforementioned challenges. The framework enables an enhanced network quality of service using its three main components and four layers. Deep learning, big data, and HPC are used to predict network traffic, which in turn are used by the Cloudlet and network layers to optimize data rates, data caching, and routing decisions. Application protocols of the traffic flows are classified, enabling the network layer to meet applications’ communication requirements better and to detect malicious traffic and anomalous data. Clustering is used to identify the different kinds of data originating from the same application protocols. A proof of concept UbeHealth system has been developed based on the framework. A detailed literature review is used to capture the design requirements for the proposed system. The system is described in detail including the algorithmic implementation of the three components and four layers. Three widely used data sets are used to evaluate the UbeHealth system.

A Novel Framework of Distributed Datacenter Networks to Support Intelligent Services: Architecture, Operation, and Solutions

Existing datacenter networks (DCNs) support the legacy cloud services well; nonetheless, it is inherently short of provisioning the emerging IoT services, such as the vehicle services, where real-time intelligence, cognition, and security are required, mainly due to its long distance with the IoT devices that generate the intelligent services. Regarding this, this paper proposes a new interconnection architecture for distributed DCNs by way of passive optical network (PON) technology to construct a ubiquitous cloud computing (UCC) environment with high scalability, resiliency, and data locality. A novel de-centralized architecture of virtualized mega DCNs on customized next-generation PONs (NGPONs) to provision UCC is proposed under the name of NGPON-DCN. In addition, a cost-effective deployment design framework and an associated revenue-driven elastic infrastructure-as-a-service delivery model are specified for creation and operation of such NGPON-DCN, followed by a discussion of anticipated key research challenges and optimization opportunities in this new NGPON-DCN convergence paradigm.

CloudBot: Advanced mobile botnets using ubiquitous cloud technologies

The mobile botnet is a collection of compromised mobile devices that can remotely receive commands from the botmaster. Exploiting unique features of mobile networks and smartphones, mobile botnets pose a severe threat to mobile users, because smartphones have become an indispensable part of our daily lives and carried a lot of private information. With the development of cloud computing technologies, botmaster can utilize ubiquitous cloud technologies to construct robust and scalable C&C (command and control) channel for mobile botnet. In this paper, we propose Cloudbot, a novel mobile botnet, which outperforms existing mobile botnets in terms of robustness, controllability, scalability, and stealthiness. Although the basic idea of using cloud technologies seems straightforward, we explore the design space of exploiting such services and tackle several challenging issues to overcome the limitations of existing mobile botnets. We have implemented CloudBot by exploiting popular push services and cloud storage services, and evaluated it through extensive experiments. The results demonstrate not only the feasibility of CloudBot but also its advantages, such as stealthiness, robustness, and performance.

Analysis of performance measures in cloud-based ubiquitous SaaS CRM project systems

Customer relationship management (CRM) traditionally uses software as a service (SaaS) technology in ubiquitous cloud computing SaaS CRM solutions. In this study, the opinions of experts and of three case companies in Internet application fields were studied. In cloud CRM projects, DEMATEL-based analytical network processes and the VIKOR technique are multi-criteria decision-making analysis tools that do not require prior assumptions to explore the weights and performances among project risk, project management, and organizational performance, based on the research framework of the Stimulus–Organism–Response model. The empirical results showed that the greatest criterion of relative weight is primarily associated with the risk dimension, representing experts’ evaluations of project risk. Furthermore, cloud CRM experts and companies revealed that financial performance should be improved during the course of a project. The findings of this study provide a valuable reference for cloud CRM Internet service solutions.

An Ubiquitous Cloud Integrated Smart University Tracking System for Ensuring Safety of Students

An Ubiquitous Cloud Integrated Smart University Tracking System for Ensuring Safety of Students

CloudCampus: building an ubiquitous cloud with classroom PCs at a university campus

CloudCampus: building an ubiquitous cloud with classroom PCs at a university campus

CloudCampus: building an ubiquitous cloud with classroom PCs at an university campus

While cloud computing is still a developing paradigm, many of the existing challenges point to new research trends, as resource and power saving. Current datacentres are being used more efficiently, new hardware tries to comply with energy saving and software helps to fulfil these goals. On the other hand, the resource optimisation can also be undertaken by maximising the existing resources, even if not intended for cloud purposes or have state-of-the-art hardware. This paper investigated how to integrate common desktop PCs, with a wide cardinality inside a university campus, on a cloud infrastructure to lower cost efforts, and how to deliver appropriate services to researchers. We propose a model to categorise applications, show how to build the infrastructure and present performance and consumption results.

Cloud-Enhanced Robotic System for Smart City Crowd Control

Cloud robotics in smart cities is an emerging paradigm that enables autonomous robotic agents to communicate and collaborate with a cloud computing infrastructure. It complements the Internet of Things (IoT) by creating an expanded network where robots offload data-intensive computation to the ubiquitous cloud to ensure quality of service (QoS). However, offloading for robots is significantly complex due to their unique characteristics of mobility, skill-learning, data collection, and decision-making capabilities. In this paper, a generic cloud robotics framework is proposed to realize smart city vision while taking into consideration its various complexities. Specifically, we present an integrated framework for a crowd control system where cloud-enhanced robots are deployed to perform necessary tasks. The task offloading is formulated as a constrained optimization problem capable of handling any task flow that can be characterized by a Direct Acyclic Graph (DAG). We consider two scenarios of minimizing energy and time, respectively, and develop a genetic algorithm (GA)-based approach to identify the optimal task offloading decisions. The performance comparison with two benchmarks shows that our GA scheme achieves desired energy and time performance. We also show the adaptability of our algorithm by varying the values for bandwidth and movement. The results suggest their impact on offloading. Finally, we present a multi-task flow optimal path sequence problem that highlights how the robot can plan its task completion via movements that expend the minimum energy. This integrates path planning with offloading for robotics. To the best of our knowledge, this is the first attempt to evaluate cloud-based task offloading for a smart city crowd control system.

Toward Low-Power Flash Memory: Prospect of Adopting Crystalline Oxide as Charge Trapping Layer

The rapid growth of data center, ubiquitous cloud computing, and mobile gadgets has made flash memory one of the major semiconductor markets. The booming request of flash memory has not only brought substantial economic and societal benefit but led to growing power consumption. The operation voltage of existent flash memory is in the range of 15–17 V which still has much room to be reduced to save power while ensuring environmental sustainability. To enable flash memory at lower voltage, developing innovative materials and structures is a prerequisite. Recently, crystalline oxide is extensively developed as a novel charge trapping layer (CTL) and holds the prospect of becoming a promising candidate for memory applications by demonstrating operation voltage lower than 10 V. In this paper, how crystalline oxide in the form of high-k dielectric and semiconductor material can be employed in flash memory as the CTL to reduce the operation voltage and the mechanism to achieve this goal are reviewed. From the good memory performance in terms of a large memory window of 1.5 V by programming/erasing at voltage lower than 10 V for 1 ms, endurance more than $10^{5}$ operation cycles, desirable retention at 85 °C, employing crystalline oxide as the CTL has ushered in a new field to implement green flash memory devices.

Cloud computing for ubiquitous computing on M2M and IoT environment mobile application

The ubiquitous cloud infrastructure different access methods are analyses to understand new message protocols that are used ubiquitous IoT mobile application environment that presented the cloud computing platform for mobile application. It supports a combined architecture of ubiquitous and cloud computing which provides a powerful framework for mobile application that requires high performance. The cloud infrastructure for ubiquitous computing environment mobile application (CI-UCEMA), which consist of three layers it cloud service layer (CSL), M2M service layer (MSL) and ubiquitous service layer (USL). The M2M consists of IoT services layer (MSL) will involve a decrease in complexity of both the improvement and controlling of IoT systems. This can be distinguished by improved interoperability and, carefully related, the improvement and use of normal. Security will also remain a grassroots regard as device management and provisioning are accomplished. The MSL is responsible for shielding the user from the underlying complexity and variability through self-tuning environment by mobility and adaptation which are points in CDPS and CIMS. The MSL components has human to object communication (HOC), human to human communication (HHC), object remote information device (OID) and micro M2M data access (M3DA). HOC has something concerned communications with PC, TV, PDA, Wearable PC, mobile phone and LTE black box. HHC supports services concerned with making same human to human communications environment in the everywhere. The UML (called uMain) is responsible for shielding the user from the underlying complexity and variability through self-tuning environment by mobility and adaptation which are points in cloud distributed parallel data processing service (CDPS) and cloud infrastructure management (CIMS). We have presented a system which gives a context-aware infrastructure that supports the gathering of context information from various simulations and the delivery of appropriate context information to mobile applications. Relevant simulations and experiments are given to evaluate the performance of the proposed system demand model. The CI-UCEMA is that have presented a ubiquitous computing environment on cloud computing platform for mobile application. This supports a combined architecture of ubiquitous and cloud computing this is a powerful framework for mobile applications along with high performance result.

CIMS: A Context-Based Intelligent Multimedia System for Ubiquitous Cloud Computing

Mobile users spend a tremendous amount of time surfing multimedia contents over the Internet to pursue their interests. A resource-constrained smart device demands more intensive computing tasks and lessens the battery life. To address the resource limitations (i.e., memory, lower maintenance cost, easier access, computing tasks) in mobile devices, mobile cloud computing is needed. Several approaches have been proposed to confront the challenges of mobile cloud computing, but difficulties still remain. However, in the coming years, context collecting, processing, and interchanging the results on a heavy network will cause vast computations and reduce the battery life in mobiles. In this paper, we propose a “context-based intelligent multimedia system” (CIMS) for ubiquitous cloud computing. The main goal of this research is to lessen the computing percentage, storage complexities, and battery life for mobile users by using pervasive cloud computing. Moreover, to reduce the computing and storage concerns in mobiles, the cloud server collects several groups of user profiles with similarities by executing K-means clustering on users’ data (context and multimedia contents). The distribution process conveys real-time notifications to smartphone users, according to what is stated in his/her profile. We considered a mobile cloud offloading system, which decides the offloading actions to/from cloud servers. Context-aware decision-making (CAD) customizes the mobile device performance with different specifications such as short response time and lesser energy consumption. The analysis says that our CIMS takes advantage of cost-effective features to produce high-quality information for mobile (or smart device) users in real time. Moreover, our CIMS lessens the computation and storage complexities for mobile users, as well as cloud servers. Simulation analysis suggests that our approach is more efficient than existing domains.

A service composition model based on user experience in Ubi-cloud comp

The ubiquitous cloud computing environment supports software as service that allows for an efficient usage by the developer, user, and manager. But within ubiquitous cloud computing, numerous services are being provided by various service providers, making it difficult for the developer to find the service needed for system development or to apply and adopt it during development. In this paper, we propose a service composition model based on user experience where the user can find the type of service that he needs, construct a composition and apply it to the overall system development. The proposed model has three factors: service characteristics, personal information, and user preference. The service characteristics to apply the most appropriate service that the user intends to apply was taken into consideration, personal information that takes into account individual characteristics of the user and a user preference that takes into account the preferred parts in the field that the user seeks to develop was applied. To evaluate the suggested method, 100 people were recruited and surveyed on user satisfaction. The result shows that the proposed method performed better than the existing methods.

MUBaaS: mobile ubiquitous brokerage as a service

The use of multiple personalized mobile devices (e.g., smartphones and tablets) is on the increase. As such, users expect to access several network-based services across their n-devices. Previous studies proposed Ubiquitous Cloud Computing (UCC) where a single user or service consumer is facilitated to access multiple services from n-devices. However, seamless synchronization of data between the multiple devices can be hindered by intermittent loss of connectivity in mobile wireless networks due to user mobility. Another source of latency is non-scalable architectures that tend to be overburdened during peak loads. This work proposes a cloud-based application middleware, called Mobile Ubiquitous Brokerage as a Service (MUBaaS), which enables n-devices of a user to access multiple cloud services end-points in soft-real time. This is achieved by proposing distributed brokers that coordinates the transactions of the user while taking load balancing into account. Pilot evaluations of the proposed architecture prove real-time application synchronization with reasonable scalability.