Advances in Mobile Cloud Computing and Big Data in the 5G Era

In the emerging 5G mobile computing environments, the need for cutting edge technologies regarding data transmission, storage and processing will be more critical than ever. In addition, handling of Big Data that is produced by Internet of Things (IoT) devices and extracting value out of it, is a real challenge for scientists and markets, towards providing extra profit to the society. In this context, this chapter aims to shortly present the correlation between Internet of Things and the expansion of Big Data. At first, a short reference to the evolution of IoT and Big Data is provided and their features are then introduced. In addition, the lifecycle of Big Data in IoT—from capturing to storage and analysis—is shortly described. Finally, two different approaches for the implementation of Big Data are presented, as well as issues in privacy and security are addressed.

The proliferation of data warehouses and the rise of multimedia, social media and the Internet of Things (IoT) generate an increasing volume of structured, semi-structured and unstructured data. Towards the investigation of these large volumes of data, big data and data analytics have become emerging research fields, attracting the attention of the academia, industry and governments. Researchers, entrepreneurs, decision makers and problem solvers view ‘big data’ as the tool to revolutionize various industries and sectors, such as business, healthcare, retail, research, education and public administration. In this context, this survey chapter presents a review of the current big data research, exploring applications, opportunities and challenges, as well as the state-of-the-art techniques and underlying models that exploit cloud computing technologies, such as the big data-as-a-service (BDaaS) or analytics-as-a-service (AaaS).

The highly computationally capable mobile devices and the continuously increasing demand for high data rates and mobility, which are required by several mobile network services, enabled the research on fifth-generation (5G) mobile networks that are expected to be deployed beyond the year 2020 in order to support services and applications with more than one thousand times of today’s network traffic. On the other hand, the huge and complex location-aware datasets exceed the capability of spatial computing technologies. In this direction, the mobile cloud computing (MCC) technology was introduced as the combination of cloud computing and mobile computing, enabling the end-users to access the cloud-supported services through mobile devices (e.g., smartphones, tablets, portable computers or wearable devices). The mobile applications exploit cloud technologies for data processing, storage and other intensive operations, as they are executed on resource providers external to the devices. This tutorial article is a comprehensive review of the current state-of-the-art and the latest developments on mobile cloud computing under the 5G era, which helps early-stage researchers to have an overview of the existing solutions, techniques and applications and investigate open research issues and future challenges in this domain.

Cloud computing, as an emerging computing paradigm for service provision on-demand, has blossomed into both academia and industry. One typical cloud service is cloud data storage and processing. By stepping into the era of 5G, Mobile Cloud Computing (MCC) becomes a perfect match to further leverage the limitations of resources and locations for advanced networking services. However, adopting mobile cloud implies placing critical applications and sensitive data in Cloud Service Providers (CSPs) and accessing them with mobile devices. This leads to serious security and usability issues, particularly on cloud data access control. In this chapter, we explore the objectives of data access control in MCC. Based on a literature review, we summarize open research issues in this area. In order to achieve secure and usable cloud data access, we adopt trust and reputation management and investigate three schemes for securing cloud data access based on trust and reputation that can be flexibly applied in different cloud data access scenarios. Furthermore, we evaluate the performance of the schemes through the analysis on security, complexity, scalability and flexibility, as well as scheme implementation. Particularly, important issues and challenges are also discussed in order to propose future research trends.

The recent development of communication devices and wireless network technologies continues to advance the new era of the Internet and the telecommunications. The vision for the Internet of Things (IoT) states that various “things”, which include not only communication devices but also every other physical object on the planet, are going to be connected and will be controlled across the Internet. The concept of the IoT has attracted significantly attention from many investigators in recent years. The incessant scientific improvements make possible to construct smart devices with huge potentials for sensing and connecting, allowing several enhancements based on the IoT paradigm. This chapter presents a review on research on IoT and analyses several IoT projects focused on IoT architectures, elements, Quality of Service (QoS) and currently open issues. The main objective of this chapter is to allow the reader to have an overview on the most important concepts and fundamental knowledge in IoT.

The goal of this chapter is to analyze existing solutions for self-aware Internet of Things. It will highlight, from a research perspective, the performance and limitations of existing architectures, services and applications specialized on healthcare. The chapter will offer to scientists from academia and designers from industry an overview of the current status of the evolution of applications based on Internet of Things and Big Data. It will also highlight the existing problems and benefits of the IoT for disabled people or people suffering from diseases and the research challenges found in this area.

Last decade has seen a major transformation in the mobile computing and wireless technologies. And with the development in the Cloud computing, Mobile cloud computing (MCC) is likely to be the next phase of innovation in the telecommunication world. Mobile cloud computing (MCC) services are expected to be a source of quick development with huge capabilities of 5G mobile network. To revise the new opportunities developed by this major, the demand for intelligent, efficient and secure network will continue to increase. So the 5G technology is expected to be heart of next generation in the digital world. In this chapter we will cover a few aspects of 5G covering the challenges and advancements in the existing and emerging communication technologies; mobile cloud computing architecture and how 5G along with Big Data will lead to an era of smart world where everything will be connected to everything in smart and secure way.

Commoditization and virtualization of wireless networks are changing the economics of mobile networks to help network providers, e.g. Mobile Network Operator (MNO), Mobile Virtual Network Operator (MVNO), move from proprietary and bespoke hardware and software platforms towards an open, cost-effective, and flexible cellular ecosystem. In addition, rich and innovative local services can be efficiently materialized through cloudification by leveraging the existing infrastructure. In this work, we present a Radio Access Network as a Service (RANaaS), in which a Cloudified Centralized Radio Access Network (C-RAN) is delivered as a service. RANaaS describes the service life-cycle of an on-demand, elastic, and pay as you go RAN instantiated on top of the cloud infrastructure. Due to short deadlines in many examples of RAN, the fluctuations of processing time, introduced by the virtualization framework, have a deep impact on the C-RAN performance. While in typical cloud environments, the deadlines of processing time cannot be guaranteed, the cloudification of C-RAN, in which signal processing runs on general purpose processors inside Virtual Machines (VMs), is a challenging subject. We describe an example of real-time cloudified LTE network deployment using the OpenAirInterface (OAI) LTE implementation and OpenStack running on commodity hardware. We also show the flexibility and performance of the platform developed. Finally, we draw general conclusions on the RANaaS provisioning problem in future 5G networks.

The Internet and Internet of Things (IoT) make the Smart City concept an achievable and attractive proposition. Efficient information abstraction and quick decision making, the most essential parts of situational awareness (SAW), are still complex due to the overwhelming amount of dynamic data and the tight constraints on processing time. In many urban surveillance tasks, powerful Cloud technology cannot satisfy the tight latency tolerance as the servers are allocated far from the sensing platform; in other words there is no guaranteed connection in the emergency situations. Therefore, data processing, information fusion and decision making are required to be executed on-site (i.e., near the data collection locations). Fog Computing, a recently proposed extension of Cloud Computing, enables on-site computing without migrating jobs to a remote Cloud. In this chapter, we firstly introduce the motivations and definition of smart cities as well as the existing challenges. Then the concepts and advantages of Fog Computing are discussed. Additionally, we investigate the feasibility of Fog Computing for real-time urban surveillance using speeding traffic detection as a case study. Adopting a drone to monitor the moving vehicles, a Fog Computing prototype is developed. The results validate the effectiveness of our Fog Computing based approach for on-site, online, uninterrupted urban surveillance tasks.

How much time do you spend stuck in traffic? Well, the average person spends around 43 hours a year stuck just because of the over-populated streets. The road infrastructure is something that cannot be easily improved, which is why the field of Intelligent Transportation Systems (ITS) has emerged. The most common example of such systems is the navigators which integrate the location monitoring of drivers with the services that help predict faster(or at least, most pleasant) alternative route(s). But, since everyone tries to find the optimal route, conflict of interest between the drivers can appear: one driver can choose to send bad data in order to give a false image of the map and gain advantages. The present chapter describes a solution to create a security mechanism in the context of ITS. The solution is a heterogeneous solution in which both symmetrical and asymmetrical encryption are used. Section 1 makes a short introduction into the field of ITS with its main challenges. The related work is then presented in Sect. 2. A theoretical approach (see Sect. 3) over the security mechanism proposed in the chapter is then made, followed by the practical description of the implementation (Sect. 4) and the constructive details (Sect. 5). Section 6 presents the experimental evaluation and the results of the security proposal. Finally, the conclusion are presented in the final Sect. 7 and some future work is mentioned.

As the world is progressing quickly towards more connected mobile devices, the use of mobile collaborative applications is gaining an increasing popularity. For instance, real-time data streams and web applications (such as social networking and ad-hoc collaboration) are seamlessly incorporated in mobile applications. Despite this powerful evolution, the resource limitation (energy consumption and unstable connectivity) remains a serious problem against a safe concurrency control for an efficient and continuous use of mobile collaboration. In this chapter, we describe the data consistency issues when mobile applications support collaboration through the cloud. Based on human factors (such as high interactivity and data consistency), we present two concurrency control techniques for offloading and ensuring data synchronization among mobile devices and the cloud. The first technique relies on a client-server style to ensure safe coordination, while the second one supports a peer-to-peer mechanism to achieve a decentralized data synchronization.

The main storage schemes used in mobile cloud computing require appropriate resources and infrastructure to operate. It is forecasted that with the deployment of IoT devices, large volumes of mobile data will be generated constantly at a very high rate. Current and future 5G wireless mobile networks are called to support the operation of such databases. This chapter presents the most widely used database models in the context of mobile cloud, followed by the state of the art technologies in streaming data access and processing methods. It then demonstrates the importance of Cognitive Radios forming the basis for the operation of 5G wireless networks. Finally, a number of IEEE 802 standards are presented as possible candidates for delivering 5G wireless services.

In this chapter we study and introduce a smartphone-based telematics system for usage-based insurance (UBI). The smartphone has been identified as an enabler for future UBI, replacing the in-vehicle telecommunication hardware devices with a ubiquitous device with a plurality of sensors, means for data processing and wireless communication. We implemented and developed an end-to-end system including a telematics android-based application for client’s smartphones and a portal to collect, analyze and record driving patterns and score drivers. Also monitoring driver behavior, recording their driving events (safe and aggressive) and giving feedback of recorded events can enhance driver safety. So we developed an android-based application, which can estimate driving behavior, using data only from the accelerometer sensor or using orientation data of a sensor fusion method. Complementary, we developed a portal, where we can have access to an overall dashboard of all registered drivers. In the portal are presented scores, behaviors, trips reports and routes in maps of all recorded trips. With this way, we help the insurance carriers to assess better the risk of the drivers.

Majority of global traffic transferred through the Internet nowadays, as well as in the near future, is related with video delivery service. For this reason each solution focusing on improvement of media distribution is in the high interest of both research community and industry. Particularly, new solutions are required in mobile systems, since it is expected that mobile video traffic growth will be twice faster than wired streaming. In this chapter, a new approach for media delivery in 5G mobile systems is proposed. It assumes collaboration of small base stations and users’ terminals, which create ad hoc peer-to-peer cloud streaming platform. The proposed system provides high quality of content delivery due to network-awareness assured by introducing resource allocation mechanisms into 5G Radio Access Network infrastructure. The solution has been implemented in a proof of concept and the performance evaluation tests verified that the system offers significant improvement, in terms of quality and availability of the content as well as lower delays in media delivery, comparing to traditional VoD service.

Unlike regular DVD stores that allow the customer to choose from a relatively small number of products, online music platforms such as Spotify or YouTube offer large numbers of songs to their users, making the online selection process quite different from the conventional one. The goal of any recommendation system is to solve this issue by making suggestions that fit the user’s preferences. The InVibe project offers a free web platform for music listening that uses its custom recommendation system to help users explore the amount of music in a natural and exciting manner. The paper will focus on the collaborative filtering algorithms used to build the recommender system, the implementation of the web application and the overall architecture designed to integrate the recommender module with the web platform.