Cyber Foraging: Bridging Mobile and Cloud Computing

The number of smartphone users has increased from 3.6 billion in 2016 to 6.25 billion by 2021, which shows that mobile phone usage has increased dramatically over the past few years. This is due to the development of mobile computing applications like commerce, healthcare, e-learning, etc. The use of mobile devices has resulted in an exponential rise in the amount of data generated and as a result the amount of energy consumed has increased. This is where cloud computing plays a major role. Cloud computing has transformed traditional mobile computing. The new mobile cloud not only provides on-demand services but also data storage and increased energy efficiency. Through mobile computing based on cloud computing, mobile device functions can be virtualized, reducing power consumption. In this paper, the authors survey application and potential of mobile cloud computing and present the energy-efficient ways. Also, the paper discusses development opportunities of mobile cloud computing. The research also mentions some of the major challenges in current mobile computing technology.

A foremost debated area in the IT world is Mobile Cloud Computing (MCC) which merges cloud computing and mobile computing; MCC is a prospective technology of mobile services that have been inaugurated together with the fast development in mobile applications and cloud computing technology. MCC is in the early phase of development, so it is essential to have in-depth knowledge of the technology to identify future research. Cloud computing has seen exceptional advancement in the past couple of years regarding its turn of application and development. Thus, development and research in cloud computing are scaling in a positive direction because of the increasing demand for cloud computing. On the other hand, no one is concerned about its effect on mental health. People are more concerned about the privacy, access, and security of their data over the cloud. Users are not aware of the data stored in cloud technology. Therefore, end users are always worried about the security and privacy of personal data. When cloud base services are used, users have mental stress because of the unknown place of the data storage. Consistent use of cloud-based services creates a sense of anxiety among users that are more particular about data privacy. The present article gives a transitory explanation of cloud computing and mobile computing. Applications such as M-healthcare, M-commerce, and M-gaming have been discussed to debate potential applications for mobile cloud computing.

Mobile cloud computing is a major research topic in Information Technology & Communications. It integrates cloud computing, mobile computing and wireless networks. While mainly built on cloud computing, it has to operate using more heterogeneous resources with implications on how these resources are managed and used. Managing the resources of a mobile cloud is not a trivial task, involving vastly different architectures. The process is outside the scope of human users. Using the resources by the applications at both platform and software tiers come with its own challenges. This paper presents different approaches in use for managing cloud resources at infrastructure and platform levels.

Cloud-based data storage has grown in popularity due to its flexibility and concerns about security and confidentiality. In computer science, cloud computing is a relatively new concept. Users are using fewer resources while increasing their reliance on cloud resources. Cloud computing, mobile computing, and wireless networks are combined in Mobile Cloud Computing (MCC). On the other hand, Mobiles provide vast computational resources to mobile consumers due to their capabilities. On the other hand, cloud computing refers to data centers that are accessible via the Internet to a large number of people. The purpose of this paper is to provide an overview of cloud computing and mobile cloud computing. The study covers delivery and deployment models of cloud computing and the main features of mobile cloud computing.

Mobile cloud computing introduces the cloud computing technology to the mobile Internet. It can greatly promote the development and application of cloud computing, and can promote the development and application of the Internet technology to a higher level. Mobile cloud computing system consists of mobile devices, wireless networks and cloud data centers. It combines cloud computing technology and mobile Internet technology. With the combination of cloud computing and mobile Internet, mobile cloud computing causes some new research issues belonging to the field of mobile cloud computing. This paper introduces some research directions of mobile cloud computing such as application partition, computation offloading, resource management and context-aware services as well as future research trends in brief.

Green computing and energy-saving have been important and hot research topics in mobile computing and cloud computing. In the recent years, many existing research results have been published to address energy saving issues and challenges in cloud computing or mobile computing. Today, the significant increase of mobile users and strong business interests in cloud computing and services drive an emergent opportunities and needs in mobile cloud computing. This brings a new attention to energy saving in mobile cloud computing and services. This paper first presents the research scope and classified issues in energy saving in mobile clouds. Then, it reviews the existing research results and techniques, and examines their strengths and weaknesses. Finally, the paper offers observations, and identifies the open issues and needs for future research.

The advancements in the field of mobile cloud computing (MCC) has challenged the scope and services of traditional mobile computing due to its overwhelming advantages such as reliability, scalability, extra storage and anywhere access. Mobile cloud computing is a vast platform that provides the services by integrating the advantages of mobile computing, cloud computing, and web services. There are various applications of mobile cloud computing in the field of mobile gaming, mobile healthcare, mobile learning etc. Despite MCC has achieved a lot of technical advancements with vast applications but there are still challenging issues like energy efficiency, resource management & optimization, data management & synchronization, trust, privacy, and security. There is the availability of a lot of research studies addressing the MCC based service models, applications, and different issues. In this research work, an analysis and evaluation of MCC based service models, applications, and issues are presented. The basic concept of mobile cloud computing, service models, applications, and issues are also discussed in brief.

Cloud computing is a service where storage and computing resources can be accessed on subscription basis. Cloud computing is powered by the concept of virtualization technology. The virtual machines (VM) are hosted in servers so that user's requests are serviced in an optimal manner. The process of moving a running virtual machine or application between different physical machines without disconnecting the client or application is referred to as Live Migration. System resources memory, storage, process and Network resources like connectivity that are allocated to the virtual machine are transferred from the original host machine to the destination machine. Live Migration is performed for achieving Energy efficiency, Load Balancing and High availability of physical servers in Cloud Data center. This paper presents a detailed survey on Live Migration of Virtual machines in cloud environment

Cloud computing and big data: Technologies and applications

In today’s fast moving world, mobile devices such as smartphones, tablets, and other PDAs are a central component in achieving effective and convenient communication. In today fast developing world of IT and commerce, the growth of mobile computing (MC) has become a force to be reckoned with. However, it is not without its own set of challenges; these devices are dependent on battery life span, storage, bandwidth, and security and mobility. These challenges have slowed down the growth of the service quality of these devices. The intrinsic challenges of mobile computing are being overcome by imputing and saving data in cloud computing. It is done by using various service providers aside from the mobile device service providers for hosting the mobile applications’ delivery. Mobile cloud computing is a branch of cloud computing and it provides ease of use and mobility to its users. Mobile cloud computing is described as services of cloud computing that are available in mobile environment. This study offers thorough knowledge of the capabilities and challenges faced in mobile cloud computing.

Edge computing is a new architecture to provide computing, storage, and networking resources for achieving the Internet of Things. It brings computation to the network edge in close proximity to users. However, nodes in the edge have limited energy and resources. Completely running tasks in the edge may cause poor performance. Cloud data centers (CDCs) have rich resources for executing tasks, but they are located in places far away from users. CDCs lead to long transmission delays and large financial costs for utilizing resources. Therefore, it is essential to smartly offload users’ tasks between a CDC layer and an edge computing layer. This work proposes a cloud and edge computing system, which has a terminal layer, edge computing layer, and CDC layer. Based on it, this work designs a profit-maximized collaborative computation offloading and resource allocation algorithm to maximize the profit of systems and guarantee that response time limits of tasks are strictly met. In each time slot, this work jointly considers CPU, memory, and bandwidth resources, load balance of all heterogeneous nodes in the edge layer, maximum amount of energy, maximum number of servers, and task queue stability in the CDC layer. Considering the abovementioned factors, a single-objective constrained optimization problem is formulated and solved by a proposed simulated-annealing-based migrating birds optimization procedure to obtain a close-to-optimal solution. The proposed method achieves joint optimization of computation offloading between CDC and edge, and resource allocation in CDC. Realistic data-based simulation results demonstrate that it realizes higher profit than its peers. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This work considers the joint optimization of computation offloading between Cloud data center (CDC) and edge computing layers, and resource allocation in CDC. It is important to maximize the profit of distributed cloud and edge computing systems by optimally scheduling all tasks between them given user-specific response time limits of tasks. It is challenging to execute them in nodes in the edge computing layer because their computation resources and battery capacities are often constrained and heterogeneous. Current offloading methods fail to jointly optimize computation offloading and resource allocation for nodes in the edge and servers in CDC. They are insufficient and coarse-grained to schedule arriving tasks. In this work, a novel algorithm is proposed to maximize the profit of distributed cloud and edge computing systems while meeting response time limits of tasks. It explicitly specifies the task service rate and the selected node for each task in each time slot by considering resource limits, load balance requirement, and processing capacities of nodes in the edge, and server and energy constraints in CDC. Real-life data-driven simulations show that the proposed method realizes a larger profit than several typical offloading strategies. It can be readily implemented and incorporated into large-scale industrial computing systems.

Currently mobile devices like smartphones are equipped with high performance processors, memory, sensors and storage. Therefore they can do a lot of what traditional desktop and laptop computers do. Their emergence has led to many applications especially which are offered by the cloud computing. This technology is called mobile cloud computing. MCC combines the features of both mobile computing and cloud computing. Users of Mobile can get rich experience of various services from their own mobile applications that run on cloud servers. The only barrier which prevents those users to adopt mobile cloud computing is that there are risks in terms of security and privacy of the data and services. Because, mobile cloud computing has limitations in terms of data storage, bandwidth, heterogeneity, scalability, availability, reliability, and privacy [5]. So the security solution for it has become a research focus. In this paper, we are more interested in data security in mobile cloud computing environment. We propose a hybrid architecture based on Encryption as a Service. It empowers the cloud clients to be in control of their cryptographic operations and keys that they deploy in the cloud, independently of the cloud provider. Firstly, we outline cloud computing technology, then we explore mobile cloud computing environment and we analyze some encryption algorithms. Finally we propose our achitecure to solve the problem of privacy in MCC.

In mobile cloud computing, high energy consumption and service-level agreements (SLAs) violation are the challenging issues considering that the demand for computational power is growing rapidly, which requiring large-scale cloud data centers. The mobile cloud computing enables customers to outsource the large and complex tasks to the cloud data centers for the execution and result generations. To provide resources such as CPU, RAM, memory, and bandwidth cloud data centers host incoming tasks, due to the large data centers that provide the basic resources for the host operations, and it consumes a huge amount of energy, which results in very high operational costs. In order to improve the energy efficiency and SLA violation of a cloud data center, energy-aware methods for overloaded host detection and VM selection from an overloaded host are needed. Cloud computing research community felt the need to provide or improve the energy-efficient solutions that reduce the impact of the issues. In this paper, we have shown many existing algorithm for energy efficiency and SLA violation reduction.

The explosive growth of cloud computing had resulted in the growth of fields such as ubiquitous computing, mobile cloud computing, Big Data Analytics and Cyber Physical Systems etc., Mobile Cloud Computing (MCC) is the integration of Mobile computing and Cloud computing and has gained tremendous popularity in recent years. In MCC, mobile users access the cloud services with the mobile device. Generally, the users of mobile cloud can select their services from the broker using an agent. There is an agreement between the users and service provider called SLA. Data are of varying types and they require different security levels based on their requirement. Classification of Mobile user's data is a time-consuming process. A superior naive classifier for secure data classification in agent based mobile cloud computing is proposed in this paper. The agent classifies the user's data into three different groups namely, low, medium, high. Then, the data are encrypted using Advanced Encryption Standards (AES). Encrypted data is transferred to the broker for selecting for suitable service agent.But the broker has many to one relationship with service agents. Then the data is sent to the cloud service provider for storage. The stored data is then homomorphically encrypted which enables the cloud provider and cloud user to process the data without the need for decryption. Performance analysis demonstrates that our proposed method reduces classification time and provides better security and integrity on mobile cloud data.

Along with an explosive growth in mobile appli-cations and the emergence of the concept of cloud computing, in mobile cloud computing (MCC) has been familiarized as a potential technology for mobile users. Employing MCC to enable mobile users to realize the benefits of cloud computing in an environment friendly way is an effective strategy to meet today’s industrial demands. With the ever-increasing demand for MCC technology, energy efficiency has become extremely relevant in mobile cloud computing infrastructure. The concept of mobile cloud computing offers low cost and high availability to the mobile cloud users on pay-per-use basis. However, the challenges such as resource management and energy consumption are still faced by mobile cloud providers. If the allocation of the resources is not managed in a secure manner, the false allocation will lead to more energy consumption. This article demonstrates the importance of energy-saving mechanisms in cloud data centers and elaborates the importance of the “energy efficiency” relationship to promote the adoption of these mechanisms in practical scenarios. The utilization of resources are being maximized by minimizing the energy consumption. To achieve this, an integrated approach using Cuckoo Search (CS) with Artificial Neural network (ANN) is presented here. Initially, the Virtual Machines (VMs) are sorted as per their CPU utilization using Modified Best Fit Decreasing Approach (MBFD). This suffers from the increase in Service Level Agreement (SLA) violation along with many VM migrations. If the migration is not done at an appropriate host, which can hold the VM for long, Service Level Agreement Violation (SLAV) will be high.