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In todays scenario of Big Data, to reduce data management and maintenance cost, many companies and users starts shifting their data to cloud. To store or access data from remote storage (cloud storage) by using a desktop device as PC is not a problem but as the demand of smart mobile devices is increases day by day as compared to desktop devices if...
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With the emergence of cloud computing and Big Data, many companies are increasingly relying on the cloud to store and retrieve tremendous amounts of data to leverage the scalability and performance offered by cloud storage services. As a result, data retrieval time has become of a paramount importance for cloud users especially. However, current da...
Citations
... Enayet et al. [58] proposed a mobility-aware resource provisioning framework, named Mobi-Het to enable remote execution of big data tasks on the mobile cloud, which promises higher efficiency in timeliness and reliability. Islam et al. [59] developed an ant-colony based mobility and resourceaware VM migration model for the mobile cloud-based healthcare system in smart cities. Bedi et al. [60] proposed a multi-cloud storage technique for resource-constrained mobile devices to optimize mobile devices' resources and improve the performance of CPU usage, battery consumption, and data usage. Durga et al. [61] designed an efficient context-aware dynamic resource allocation that utilizes the client present context information to meet the performance requirements specified by user. ...
Mobile cloud computing augments smart-phones with computation capabilities by offloading computations to the cloud. Recent works only consider the energy savings of mobile devices while neglecting the cost incurred to the tasks which are offloaded. We might offload several tasks to minimize the total energy consumption of mobile devices; however, this could incur a huge monetary cost. Furthermore, these issues become more complex in considering the multi-tenant cloud, which is not addressed in literature adequately. Thus, to balance the trade-off between monetary cost and energy consumption of the mobile devices, we need to decide whether to offload the task to the cloud or run it locally. In this article, first, we have formulated a ‘MinEMC’ optimization problem to minimize both the energy as well as the monetary cost of the mobile devices. The ‘MinEMC’ problem is proven to be NP-hard. We formulate a special case with an equal amount of resource requirement by each task for which a polynomial-time solution is presented. Further various policies are proposed, the cloud can employ to solve the general case. Then we proposed an efficient heuristic named ‘Off-Mat’ based on distributed stable matching, the solution for which determines whether the tasks are to be offloaded or not under multi-constraints. We also analyze the complexity of this proposed heuristic algorithm. Finally, performance evaluation through simulation results demonstrates that the Off-Mat algorithm attains high-performance in computational tasks offloading and scale well as the number of tenants increases.
... Mobile networks, such as 3G/4G, vehicular ad hoc network (VANET) and Internet of Things (IoTs), generate tremendous amount of data every day [1]. To mitigate the burden of local data storage, subsequent updates and maintenance, people would like to have their data transferred through networks and eventually stored in cloud service provider (CSP) (see [2][3][4]). However, for some subjective or objective reasons, the data stored in CSP may be corrupted or even lost. ...
In recent years, how to design efficient auditing protocol to verify the integrity of users’ data, which is stored in cloud services provider (CSP), becomes a research focus. Homomorphic message authentication code (MAC) and homomorphic signature are two popular techniques to respectively design private and public auditing protocols. On the one hand, it is not suitable for the homomorphic-MAC-based auditing protocols to be outsourced to third-party auditor (TPA), who has more professional knowledge and computational abilities, although they have high efficiencies. On the other hand, the homomorphic-signature-based ones are very suitable for employing TPA without compromising user’s signing key but have very low efficiency (compared to the former case). In this paper, we propose a new auditing protocol, which perfectly combines the advantages of above two cases. In particular, it is almost as efficient as a homomorphic-MAC-based protocol proposed by Zhang et al. recently. Moreover, it is also suitable for outsourcing to TPA because it does not compromise the privacy of users’ signing key, which can be seen from our security analysis. Finally, numerical analysis and experimental results demonstrate the high-efficiency of our protocol.
... Multi-cloud Environments Rajeev Kumar Bedi et al. [71] The author proposed the approach for the efficient storage of mobile users using multi-cloud. The proposed system gives better resource utilization in terms of battery, uses of data, 8 and CPU. ...
Resource scheduling is a challenging job in multi-cloud environments. The multi-cloud technology attracted much research to work on it and look forward to solving the problems of vendors lock-in, reliability, interoperability, etc. The uncertainty in the multi-cloud environments with heterogeneous user demands made it a challenging job to dispense the resources on demand of the user. Researchers still focused on predicting efficient optimized resource allocation management from the existing resource allocation policies in multi-cloud environments. The research aims to provide a broad systematic literature analysis of resource management in the area of multi-cloud environments. The numbers of optimization techniques have been discussed among the open issues and future challenges in consideration due to flexibility and reliability in present environments. To analyses the literature work, it is necessary to cover the existing homogenous/heterogeneous user demands and cloud applications, and algorithms to manage it in multi-clouds. In this paper, we present the definition and classification of resource allocation techniques in multi-clouds and generalized taxonomy for resource management in cloud environments. In the last, we explore the open challenges and future directions of resource management in a multi-cloud environment.
... Bedi et al. [28] developed an efficient multi-cloud storage approach for resourceconstrained mobile devices to save resources of the mobile device. In this, authors implemented the proposed approach and compared the proposed approach with the previous multi-cloud storage systems by uploading a file on three CSPs and analyzed that the proposed approach is best for resources battery usage, CPU usage and data usage. ...
To store the sensitive and large amount of information on mobile devices is not recommended as it can be lost or stolen and the storage capacity is limited. Even the services of the single-cloud storage provider are not preferred due to issues like limited free storage, vendor lock-in and data loss. To deal with these issues, multi-cloud storage services are preferred which provide a single platform for multiple cloud storage services. From recent studies, it has been observed that the use of existing multi-cloud storage systems is uncommon by mobile users because they have lots of issues when accessed through resource-constrained mobile devices as they are consuming a lot of resources like CPU, battery and data (Internet usage) of mobile devices. So, in this paper, an efficient and secure multi-cloud storage approach is developed using the concept of fog computing to leverage augmentation of multi-cloud storage services on resource-constrained mobile devices.
