Energy-Efficient Load-Balanced Heterogeneous Mobile Cloud

Chen, Chien-An; Stoleru, Radu; Xie, Geoffery G.

doi:10.1109/icccn.2017.8038422

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…Year Journal or conference name [52] 2014 Advances in engineering and technology [53] 2014 Recent trends in information technology [54] 2015 Computer science trends and technology [55] 2016 Knowledge-based engineering and innovation [56] 2017 Computer communications and networks [57] 2017…”

Section: Researchmentioning

confidence: 99%

“…The suggested method improves reliability and throughput, but it has a high overhead. An energy-efficient and load-balanced distributed storage and processing system has been proposed by researchers in [56]. They have proposed a Heterogeneous Mobile Cloud (HMC) computing design, in which the computation and communication resources are utilized to support data processing and data storage services in a group of mobile devices.…”

Section: A Review Of Distributed Approachesmentioning

confidence: 99%

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Fault-Tolerant Load Balancing in Cloud Computing: A Systematic Literature Review

et al. 2022

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Nowadays, cloud computing is growing daily and has been developed as an effective and flexible paradigm in solving large-scale problems. It has been known as an Internet-based computing model in which computing and virtual resources, such as services, applications, storage, servers, and networks, are shared among numerous cloud users. Since the number of cloud users and their requests are increasing rapidly, the loads on the cloud systems may be underloaded or overloaded. These situations cause different problems, such as high response time and power consumption. To handle the mentioned problems and improve the performance of cloud servers, load balancing methods have a significant impact. Generally, a load balancing method aims to detect under-loaded and overloaded nodes and balance the load among them. In the recent decade, this problem has attracted a lot of interest among researchers, and several solutions have been proposed. Considering the important role of fault-tolerant in load balancing algorithms, there is a lack of an organized and in-depth study in this field yet. This gap prompted us to provide the current study aimed to collect and review the available papers in the field of fault tolerance load balancing methods in cloud computing. The existing algorithms are divided into two categories, namely, centralized and distributed, and reviewed based on vital qualitative parameters, such as scalability, response time, reliability, availability, throughput, and overhead. In this regard, other criteria such as the type of detected faults and adopted simulation tools are taken into account.

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Section: Researchmentioning

confidence: 99%

Section: A Review Of Distributed Approachesmentioning

confidence: 99%

Fault-Tolerant Load Balancing in Cloud Computing: A Systematic Literature Review

et al. 2022

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Novel Approach for Load Balancing in Mobile Cloud Computing

Ranapana

Jayasena

2021

2021 6th International Conference on Information Technology Research (ICITR)

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DistressNet-NG: A Resilient Data Storage and Sharing Framework for Mobile Edge Computing in Cyber-Physical Systems

Sagor,

Haroon,

Stoleru

et al. 2024

ACM Trans. Cyber-Phys. Syst.

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Mobile Edge Computing (MEC) has been gaining a major interest for use in Cyber-Physical Systems (CPS) for Disaster Response and Tactical applications. These CPS generate a very large amount of mission-critical and personal data that require resilient and secure storage and sharing. In this article, we present the design, implementation, and evaluation of a framework for resilient data storage and sharing for MEC in CPS targeting the aforementioned applications. Our framework is built on the resiliency of three main components: EdgeKeeper, which ensures resilient coordination of the framework’s components; RSock, which provides resilient communication among CPS’s nodes; and R-Drive/R-Share which, leveraging EdgeKeeper and RSock, provides resilient data storage and sharing. EdgeKeeper employs a set of replicas and a consensus protocol for storing critical meta-data and ensuring fast reorganization of the CPS; RSock decides an optimal degree for replicating data that is communicated over lossy links. R-Drive employs an adaptive erasure-coded and encrypted resilient data storage; R-Share, leveraging RSock provides resilient peer-to-peer data sharing. We implemented our proposed framework on rapidly deployable systems (e.g. manpacks, testMobile Edge Clouds) and on Android devices, and integrated it with existing MEC applications. Performance evaluation results from three real-world deployments show that our framework provides resilient data storage and sharing in MEC for CPS.

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Energy-Efficient Load-Balanced Heterogeneous Mobile Cloud

Cited by 3 publications

References 15 publications

Fault-Tolerant Load Balancing in Cloud Computing: A Systematic Literature Review

Fault-Tolerant Load Balancing in Cloud Computing: A Systematic Literature Review

Novel Approach for Load Balancing in Mobile Cloud Computing

DistressNet-NG: A Resilient Data Storage and Sharing Framework for Mobile Edge Computing in Cyber-Physical Systems

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