BC-Mobile Device Cloud: A Blockchain-Based Decentralized Truthful Framework for Mobile Device Cloud

Wang, Mu; Xu, Changqiao; Chen, Xingyan; Zhong, Lujie; Wu, Zhonghui; Wu, Dapeng

doi:10.1109/tii.2020.2983209

Cited by 24 publications

(13 citation statements)

References 26 publications

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“…Other approaches addressed scheduling computational offloading within ensembles of mobile devices, known as Mobile Device Clouds (MDC) or Mobile Edge Clouds [20], [40]- [42]. For example, Mtibaa at.…”

Section: Scheduling Offloading To Cloud and Fogmentioning

confidence: 99%

“…They consider multiple environments; a fully connected MDC with low disconnections, two hop connected MDC's with low disconnections as well as one hop opportunistically connected MDCs. In [42], authors formulate scheduling independent tasks in MDCs as a stochastic optimization problem that jointly minimizes the long-term processing cost and risk of task failing. They propose a Lyapunov-based online decision-making to decide on the amount of resource that should be provided by each worker.…”

Section: Scheduling Offloading To Cloud and Fogmentioning

confidence: 99%

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MAESTRO: Orchestrating Computational Offloading to Multiple FemtoClouds in Various Communication Environments

2022

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Many novel IoT-based applications demand low latency, large compute resources and high privacy. These requirements have motivated the emergence of fog and edge computing to complement the low-privacy and high-latency cloud. The idea of Fog computing is to place computational servers closer to the user, typically within the city's vicinity, to reduce latency. However, because of the high deployment cost of these servers at scale, and unreliable network infrastructures in many countries and areas, edge computing was proposed. Edge computing advocates leveraging compute resources, typically 0-hops away, on distributed ensembles of colocated devices called FemtoClouds. In this paper, we propose Maestro, a system that enables users to offload computational jobs to multiple FemtoClouds in their immediate vicinity. For Maestro, we propose an integrated architecture that includes two new scheduling algorithms for assigning computing workloads to FemtoClouds. Each of our scheduling algorithms is designed to allow the system to operate more efficiently given poor or strong network infrastructure. We implement a full prototype of our system to assess its performance on our experimental testbed. The results indicate that in communication-challenged environments, our specialized scheduler outperforms state-of-the-art schedulers by up to 55%, while in communication-friendly environments our other specialized scheduler outperforms state-of-the-art schedulers by up to 67%.

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Section: Scheduling Offloading To Cloud and Fogmentioning

confidence: 99%

Section: Scheduling Offloading To Cloud and Fogmentioning

confidence: 99%

MAESTRO: Orchestrating Computational Offloading to Multiple FemtoClouds in Various Communication Environments

2022

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“…Its purpose is to organize the data sent from the network layer and track the IoT and network environment carefully in real-time for fault finding. 25 There are different techniques associated with resource planning, resource positioning, resource arrangement, and assignment. 26 According to Figure 3, we illustrate a taxonomy on the existing BaaS models that are categorized into three main classes including data layer, network layer, and resource layer models.…”

Section: Brief Description Of Baas Taxonomymentioning

confidence: 99%

Blockchain as a service models in the Internet of Things management: Systematic review

Deng

Cai

et al. 2020

Trans Emerging Tel Tech

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Today, blockchain uses a list of various blocks for storing a distributed flat of invariable information that informs of a set of replicated logical things in the Internet of Things (IoT). In the blockchain, a set of blocks includes various transactions containing a cryptographic hash value and a timestamp. Blockchain‐as‐a‐service (BaaS) as a new service in cloud providers presents an infrastructure for accessing users to execute, manage, and monitor blockchain applications without high secured infrastructure requirements. Recently, BaaS concepts widely have used the management of IoT applications in different layers such as network, data, control, and resource. This paper provides a systematic review of recent research studies in BaaS models. The main goal behind this review is to categorize the applied scenarios, trends, evaluated Quality of Service (QoS) factors, new challenges, and open directions on BaaS models in IoT management. To evaluate the existing research studies in this field, five analytical research questions are proposed to analyze the technical aspects of each study. The analytical results based on existing research questions specify that the BaaS models are applied to network layer to manage IoT environment more than other layers. Also, security and privacy are two important factors to evaluate the existing BaaS models in cloud‐edge IoT environments. Finally, the integration of BaaS models on IoT environments with interconnections of cloud‐edge computing and software defined networks creates great secure opportunities for smart environment applications to monitor, manage, and improve all the atomic services and resources.

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“…Cloud‐edge computing is a hybrid concept to integrate cloud data centers and fog resource to communicate and serve IoT applications 3–5 . On the other hand, the arranging and selecting appropriate services to manage the existing resources expertly is a challenging issue to maximize quality of service (QoS) factors 6 .…”

Section: Introductionmentioning

confidence: 99%

Energy aware cloud‐edge service placement approaches in the Internet of Things communications

Heng

Yin

Zhao

2021

Int J Communication

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Summary In recent years, applying Internet of Things (IoT) applications has significantly increased to facilitate and improve quality of human life activities in various fields such as healthcare, education, industry, economics, etc. The energy aware cloud‐edge computing paradigm has developed as a hybrid computing solution to provide IoT applications using available cloud service providers and fog nodes for the smart devices and mobile applications. Since the IoT applications are developed in the form of several IoT services with various quality of service (QoS) metrics which can deploy on the cloud‐edge providers with different resource capabilities, finding an efficient placement solution as one of challenging topics to be measured for IoT applications. The service placement issue arranges IoT applications on the cloud‐edge providers with various capabilities of atomic services though sufficient different QoS factors to support service level agreement (SLA) contracts. This paper presents a technical analysis on the cloud‐edge service placement approaches in IoT systems. The key point of this technical analysis is to identify substantial studies in the service placement approaches which need additional consideration to progress more efficient and effective placement strategies in IoT environments. In addition, a side‐by‐side taxonomy is proposed to categorize the relevant studies on cloud‐edge service placement approaches and algorithms. A statistical and technical analysis of reviewed existing approaches is provided, and evaluation factors and attributes are discussed. Finally, open issues and forthcoming challenges of service placement approaches are presented.

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BC-Mobile Device Cloud: A Blockchain-Based Decentralized Truthful Framework for Mobile Device Cloud

Cited by 24 publications

References 26 publications

MAESTRO: Orchestrating Computational Offloading to Multiple FemtoClouds in Various Communication Environments

MAESTRO: Orchestrating Computational Offloading to Multiple FemtoClouds in Various Communication Environments

Blockchain as a service models in the Internet of Things management: Systematic review

Energy aware cloud‐edge service placement approaches in the Internet of Things communications

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