Mobile Cloud Computing Research – Issues, Challenges and Needs

MCC, or mobile cloud computing, is a new field. Mobile cloud computing is becoming a crucial component for mobile devices due to reliability and portability as data processing and storage take place outside of the mobile due to the widespread use of mobile devices and the variety of apps. It helps mobile devices conserve battery life and processing power, which is important for highpower mobile devices. Mobile cloud computing offers consumers to make calculations and use cloud services on their mobile devices. It is essential to gain a full understanding of current models and emerging trends because mobile Cloud computing is still in its infancy. The purpose of this survey is to identify and describe the main risks and obstacles associated with mobile cloud computing while alsoshowcasing emerging trends in this area.

Providing mobile cloud services requires seamless integration between various platforms to offer mobile users optimum performance. To achieve this, many fundamental problems such as bandwidth availability and reliability, resource scarceness, and finite energy must be addressed before rolling out such services. This chapter aims to explore technological challenges for mobile cloud computing in the area of resource management focusing on both parts of the infrastructure: mobile devices and cloud networks. Starting with introducing mobile cloud computing, it then stresses the importance of resource management in the operation of mobile cloud services presenting various types of resources available for cloud computing. Furthermore, it examines the various types of resource management techniques available for mobile clouds. Finally, future directions in the field of resource management for mobile cloud computing environment are presented.

Mobile cloud computing (MCC) is the availability of cloud computing services in a mobile environment. By providing optimal services for mobile users, MCC incorporates the elements of mobile networks and cloud computing. In mobile cloud computing, all the data and complicated computing modules can be processed in clouds, and mobile devices do not need a powerful configuration like CPU speed, memory capacity, etc. However, the mobile devices are facing up with many struggles in their resources (e.g., battery life, storage, and bandwidth) and communications (e.g., privacy, mobility, and security). These challenges have a significant effect on the improvement of service qualities. In this paper, a literature survey on the MCC and security issues in MCC has presented.

Following the growth of mobile device applications in the past years, mobile computing and cloud computing are suggesting a new computing paradigm. Demands for computing capability regarding potential technologies that are provided as mobile service are also growing. Meanwhile, necessity of Mobile cloud computing (MCC) is increasing due to the problems of mobile devices, such as resource poverty, battery constraint. However, clear definition is required as the concept of MCC is still ambiguous. Currently, it is necessary to classify the configuration methods of the resource-providing infrastructure environment of MCC. This paper provides a comprehensive overview of MCC and proposes a basic scheme. We suggest instance MCC (iMCC), which is a framework implementing offloading for the purpose of achieving efficient computing process and service provision. iMCC includes improved resource allocation method in MCC infrastructure as well as efficient offloading method. Finally, we summarize the conclusion and discuss future research.

As mobile computing has been developed for decades, a new model for mobile computing, namely, mobile cloud computing, emerges resulting from the marriage of powerful yet affordable mobile devices and cloud computing. In this paper we survey existing mobile cloud computing applications, as well as speculate future generation mobile cloud computing applications. We provide insights for the enabling technologies and challenges that lie ahead for us to move forward from mobile computing to mobile cloud computing for building the next generation mobile cloud applications. For each of the challenges, we provide a survey of existing solutions, identify research gaps, and suggest future research areas.

Quality of cloud service (QoS) is one of the crucial factors for the success of cloud providers in mobile cloud computing. Context-awareness is a popular method for automatic awareness of the mobile environment and choosing the most suitable cloud provider. Lack of context information may harm the users’ confidence in the application rendering it useless. Thus, mobile devices need to be constantly aware of the environment and to test the performance of each cloud provider, which is inefficient and wastes energy. Crowdsourcing is a considerable technology to discover and select cloud services in order to provide intelligent, efficient, and stable discovering of services for mobile users based on group choice. This article introduces a crowdsourcing-based QoS supported mobile cloud service framework that fulfills mobile users’ satisfaction by sensing their context information and providing appropriate services to each of the users. Based on user's activity context, social context, service context, and device context, our framework dynamically adapts cloud service for the requests in different kinds of scenarios. The context-awareness based management approach efficiency achieves a reliable cloud service supported platform to supply the Quality of Service on mobile device.

Identity-based mutual authentication and key agreement (ID-MAKA) between a mobile user and cloud service provider is necessary for accessing any cloud services. In recent years, there are a large number of ID-MAKA schemes had been proposed on mobile cloud computing services to make authentication and accessing process more usability, security, and scalability. In this paper, we propose a new ID-MAKA scheme for mobile cloud computing, which firstly achieves remote biometric-based authentication(remote servers authenticate user’s biometrics), single sign-on (a single credential and single registration for accessing multiple servers) and center-less authentication(the registration center does not participate in the access procedure) in one scheme. In order to realize this target, we design a ZK-token based on ECC and cryptographic hash function, and then artfully employ it to introduce the fuzzy extractor technology and zero-knowledge technology into our scheme. Therefore, the user can access multiple cloud computing servers by registering only once in the registration center, and cloud computing servers can complete the biometric-based remote authentication and key agreement for the user without the registration center participating. In this way, our scheme greatly improves usability, scalability, and security compared to other existing solutions. We give a formal security proof for our scheme by using Real-Or-Random(RoR) model and Burrows-Abadi-Needham (BAN) logic to show that the present scheme is secure and security analysis for other known attacks. Finally, according to the experiment result, our scheme has lower computation and communication cost compared with most existing related schemes.

Mobile cloud computing is high technology that extends existing IT capabilities and requirements. And it can also access to shareable remote computing resources pool through the network. As the concept of mobile cloud, many providers have served the mobile cloud services using their own service policies. In other words, there is no formal definition of quality criteria for mobile cloud service evaluation. To solve this problem, some quality models are proposed for cloud service evaluation. However, those did not include many metrics to evaluate the services. Even if the model included a number of criteria, it is difficult to identify whether the metrics are proper or not. Furthermore, most existing models were not concerned about mobile characteristics. Therefore, we propose a cloud service integration model to solve the problem as we mentioned above. First, we select additional metrics to satisfy the mobile characteristics. Second, we present an extended SLA model for modeling complex service-dependencies in mobile cloud services. Third, we describe a method of discovering relations between the metrics of service belonging to mobile cloud services and then using these relations for establishing newly generated SLA.

As the technology is developing with a huge rate, the functionality of smartphone is also getting higher. But the smartphones have some resource constraints like processing power, battery capacity, limited bandwidth for connecting to the Internet, etc. Therefore, to improve the performance of smartphone in terms of processing power, battery and memory, the technology namely, augmented execution is the best solution in the mobile cloud computing (MCC) scenario. Mobile cloud computing works as the combination of mobile computing and cloud computing. Augmented execution alleviates the problem of resource scarcity of smartphone. To get the benefits from the resource-abundant clouds, massive computation intensive tasks are partitioned and migrated to the cloud side for the execution. After executing the task at the cloud side, the results are sent back to the smartphone. This method is called as the computation offloading. The given survey paper focuses on the partitioning techniques in mobile cloud computing.

The widespread use of smartphones and other mobile devices has brought significant changes to the storage requirements of cloud systems, necessitating a reevaluation of security protocols. Mobile Cloud Computing (MCC) is a computing paradigm that combines the capabilities of mobile devices with the flexibility and scalability of cloud computing. MCC allows mobile users to access computational power, storage, and applications over the internet, facilitating resource-intensive tasks such as data analysis, gaming, and multimedia streaming on resource-constrained mobile devices. The integration of mobile and cloud technologies has revolutionized industries such as healthcare, education, and entertainment, offering benefits like enhanced mobility, improved resource utilization, and cost efficiency. Despite its advantages, MCC faces significant security challenges that could undermine user trust and disrupt its adoption. Since mobile devices and cloud servers are connected via insecure networks, malicious actors can exploit vulnerabilities in the system. This paper aims to analyze the primary security issues in MCC technology, focusing on data protection, authentication, access control, and other critical concerns. Unlike other issues, when dealing with business objectives, protection and privacy in financial activities are of paramount importance. This article examines mobile cloud computing, its technological model, and its role in detail. Keywords: Mobile cloud computing, Technology, Privacy issues, Security.

Compromise-resilient anonymous mutual authentication scheme for n by m-times ubiquitous mobile cloud computing services

Mobile cloud computing (MCC) is a technique or model, in which mobile applications are built, powered and hosted using cloud computing technology. It refers to the availability of Cloud Computing services in a mobile environment and it is the combination of the heterogeneous fields like mobile phone device, cloud computing and wireless networks. Of all that has been written about cloud computing, precious little attention has been paid to authentication in the cloud. In this paper we have designed a new effective security model for mobile cloud Database as a Service (DBaaS). A user can change his/her password, whenever demanded. Furthermore, security analysis realizes the feasibility of the proposed model for DBaaS and achieves efficiency. We also proposed an efficient authentication scheme to solve the authentication problem in MCC. The proposed solution which we have provided is based mainly on improved Needham-Schroeder’s protocol to prove the users’ identity to determine if this user is authorized or not. The results showed that this scheme is very strong and difficult to break it.

Mobile cloud computing has become a research hotspot in the fields of cloud computing and mobile computing. At present, many researches on offloading computation to cloud resource and their related work have been done and some achievements have been obtained in the field of mobile cloud computing. However, some problems of the current researches have also been found such as the separation between computation and data, limited network resource, and lack of location-aware, etc. In this paper, we have presented a novel mobile cloud computing model and proposed a heuristic approach MCC-particle swarm optimization (PSO) of placement selection of mobile applications’ partitions for minimizing the overall processing time and energy saving. The algorithm of the proposed MCC-PSO approach includes two parts. One is that it combines the PSO idea with the simulated annealing (SA) idea to achieve an improved PSO-based approach with the better global search’s ability. The other one is that it uses the probability theory and mathematical statistics and once again utilizes the SA idea to deal with the data obtained from the improved PSO-based process to get the final solution. And thus the whole approach achieves a long-term optimization of mobile cloud computing. The experimental results demonstrate that MCC-PSO evidently reduces the overall processing time of mobile applications and energy consumption of mobile devices while better guaranteeing the performance of executing mobile applications. MCC-PSO better achieves the idea of mobile cloud computing and makes the mobile cloud computing model more high-effective and meaningful.

Digital library cloud service is the development and extension of traditional digital library knowledge services under the environment of mobile cloud. Meanwhile, it’s also the new stage of knowledge services development. Based on the analysis of mobile cloud technology services model and its advantages, taking “end”, ”tube”, ”cloud” as the main line, this paper build up digital library mobile cloud knowledge services model from three aspects: knowledge collecting, knowledge processing and knowledge using. Thus, it point out the opportunities and challenges faced by mobile cloud services and present the strategies of implementing knowledge cloud services.

The resource reservation is one of the key techniques to ensure the quality of service (QoS) of a multimedia application. In mobile cloud computing (MCC), the resource reservation and allocation (RRA) in advance can significantly reduce the total provisioning cost of cloud service providers. However, the uncertain features of mobile users' demands for resources make RRA challengeable. In MCC, the QoS of a mobile application, such as voice IP or video, is determined by both of the radio resource (RR) and the cloud virtual machine resource (VMR) allocated to the mobile application, so we should jointly allocate these two types of resources. In this paper, RRA with uncertain demands of mobile users is formulated as a robust optimization model. Logarithmic utility functions are defined to capture the mobile users' satisfaction, which show how to match the allocations between RRs and VMRs according to the resource demands of the mobile applications. Then, a robust joint resource reservation and allocation algorithm in MCC (JRRA-MCC) is proposed to realize the optimal provisioning of RRs and VMRs. Simulation results show that the proposed JRRA-MCC can minimize the total resource provisioning cost of cloud service providers and enhance the resource utilization efficiently.