Heterogeneous cloudlet deployment and user‐cloudlet association toward cost effective fog computing

Yao, Hong; Bai, Changmin; Xiong, Muzhou; Zeng, Deze; Fu, Zhangjie

doi:10.1002/cpe.3975

Cited by 78 publications

(40 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous researchers have brought the cloud amenities nearer to the consumer by proposing the concept of FC. Providing resources such as processing power, storing, and commercial reason at the edge of the wireless is the main goals of it . End tools, fog, and cloud are applied to shape a 3‐level ordered amenity distribution design and support a variety of usages like augmented reality, web content delivery, and large data analysis.…”

Section: Introductionmentioning

confidence: 99%

“…Providing resources such as processing power, storing, and commercial reason at the edge of the wireless is the main goals of it. 27 End tools, fog, and cloud are applied to shape a 3-level ordered amenity distribution design and support a variety of usages like augmented reality, web content delivery, and large data analysis. Many privacy and security issues in the CC can be solved under the influence of FC because it is considered as an unimportant format for the cloud.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A comprehensive study on managing strategies in the fog environments

Wang

Panpan

Batiha

2019

Trans Emerging Tel Tech

View full text Add to dashboard Cite

Although cloud computing application is rising, some unanswered problems still exist because of its inner issues like untrustworthy inactivity, the absence of movement backing, and place awareness. Therefore, fog computing has appeared as a hopeful infrastructure to supply flexible resources at the edge of the network. Fog supplies processing, data, storing, and application amenities to ultimate operators. The management strategies have a great impact on fog computing, such as monitoring and optimizing, the correlated components for improving the performance, availability, security, and any fundamental operational requirement. However, as far as we know, no organized study exists about analyzing their importance in fog environments. This paper provides a detailed survey for covering the current state‐of‐the‐art in fog management. This paper classifies the management strategies into three main categories: data management, energy, and resource. We also presented a few prospects and problems like the suggestions for the upcoming studies in the associated methods requiring to be investigated in fog computing. Moreover, a new paradigm has been ensured by increasing fog functionality and resource consumption. In general, fog management strategies in computing environments still need improvements in the variety of its setting to convert to an on‐request method, decrease the associated overhead, and improve the performance. Therefore, proper management can maintain the least resource consumption, which will finish the extra decrease in energy usage. Therefore, we contribute to provide strong suggestions for future fog computing studies. This paper can handle the pace of publications and propose the outcomes of study and practice as an upcoming route for decision makers in healthcare. In principle, the increase of researchers, scientists and managers' awareness level would increase the managers' good and knowingly behavioral conduct on managing fog environments.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A comprehensive study on managing strategies in the fog environments

Wang

Panpan

Batiha

2019

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…Although there is an increasing number of researches in mobile cloudlet offloading technology [9][10][11], fewer researches about how to place cloudlets in a given network region are conducted [3,7,[12][13][14]. It is necessary to pay attention to how cloudlets should be placed in a given network since the suitable cloudlets placements contribute to enhancing the cloud service for dynamic context-aware mobile applications.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Adaptive Cloudlet Placement Approach for Mobile Application on Spark

Zhang

Wang

Zhou

et al. 2018

Security and Communication Networks

View full text Add to dashboard Cite

The applications of mobile devices are increasingly becoming computationally intensive while the computing capability of the user’s mobile device is limited. Traditional approaches offload the tasks of mobile applications to the remote cloud. However, the rapid growth of mobile devices has made it a challenge for the remote cloud to provide computing and storage capacities with low communication delays due to the fact that the remote cloud is geographically far away from mobile devices. Reducing the completion time of applications in mobile devices through the technical expending mobile cloudlets which are moving collocated with Access Points (APs) is necessary. To address the above issues, this paper proposes EACP-CA (Enhanced Adaptive Cloudlets Placement approach based on Covering Algorithm), an enhanced adaptive cloudlet placement approach for mobile applications in a given network area. We apply the CA (Covering Algorithm) to adaptively cluster the mobile devices based on their geographical locations, the aggregation regions of the mobile devices are identified, and the cloudlet destination locations are also confirmed according to the clustering centers. In addition, we can also obtain the traces between the original and destination locations of these mobile cloudlets. To increase the efficiency, we parallelize CA on Spark. Extensive experiments show that the proposed approach outperforms the existing approach in both effectiveness and efficiency.

show abstract

“…8,9 The optimal offloading algorithm helps cloudlets to achieve low cost in terms of computation and communication costs. 8,9 The optimal offloading algorithm helps cloudlets to achieve low cost in terms of computation and communication costs.…”

mentioning

confidence: 99%

“…A cloudlet could be an initial solution to solve this problem, as it uses computational resources in the vicinity of users or smart devices in order to achieve local processes and overcome storage, network traffic, and latency restrictions. 8,9 The optimal offloading algorithm helps cloudlets to achieve low cost in terms of computation and communication costs. However, as cloudlets use Wi-Fi for communication between smart devices, this restricts its coverage area.…”

mentioning

confidence: 99%

An opportunistic resource management model to overcome resource‐constraint in the Internet of Things

Safa

Maple

Haghparast

et al. 2018

Concurrency and Computation

View full text Add to dashboard Cite

Experts believe that the Internet of Things (IoT) is a new revolution in technology and has brought many advantages for our society. However, there are serious challenges in terms of information security and privacy protection. Smart objects usually do not have malware detection due to resource limitations and their intrusion detection work on a particular network. Low computation power, low bandwidth, low battery, storage, and memory contribute to a resource-constrained effect on information security and privacy protection in the domain of IoT. The capacity of fog and cloud computing such as efficient computing, data access, network and storage, supporting mobility, location awareness, heterogeneity, scalability, and low latency in secure communication positively influence information security and privacy protection in IoT. This study illustrates the positive effect of fog and cloud computing on the security of IoT systems and presents a decision-making model based on the object's characteristics such as computational power, storage, memory, energy consumption, bandwidth, packet delivery, hop-count, etc. This helps an IoT system choose the best nodes for creating the fog that we need in the IoT system. Our experiment shows that the proposed approach has less computational, communicational cost, and more productivity in compare with the situation that we choose the smart objects randomly to create a fog.KEYWORDS cloud, Fog, information security, Internet of Things, privacy, resource INTRODUCTIONThe Internet has provided a backbone for connecting different objects to each other and has changed human life significantly. The ubiquitous things is a new concept that has been created by the interconnection and intercommunication amongst smart objects. 1 We are faced with a huge volume of data in this environment. Network traffic, increasing demands of real time, latency-sensitive applications, resource-constraints (computational power, storage, memory, etc) in actuators, mobility and geo-distribution of smart objects, and heterogeneity that are new challenges in the domain of IoT. 2 These weaknesses directly or indirectly influence information security and privacy violation in IoT systems. 3Resource-constraint in actuators jeopardises secure communication between different smart objects. 4 Messages need to be sent encrypted;they will be decrypted for process in the target. The result of the process should be encrypted and send to the same object or other smart objects.We have latency; this delays not only creates risk for information security, but it may also impact human safety in some applications of IoT, such as smart vehicles. Lightweight cryptography has been presented to overcome this challenge in vehicle-to-vehicle (V2V) communication and in many other secure communications in IoT. 5 Smart objects usually do not have malware detection due to limitation in resources; their intrusion detection only can detect attacks in particular networks (not hybrid). These are examples of common problems in the IoT domain.Cloud...

show abstract

Heterogeneous cloudlet deployment and user‐cloudlet association toward cost effective fog computing

Cited by 78 publications

References 30 publications

A comprehensive study on managing strategies in the fog environments

A comprehensive study on managing strategies in the fog environments

Enhanced Adaptive Cloudlet Placement Approach for Mobile Application on Spark

An opportunistic resource management model to overcome resource‐constraint in the Internet of Things

Contact Info

Product

Resources

About