Community-based allocation and migration strategies for fog computing

Filiposka, Sonja; Mishev, Anastas; Gilly, Katja

doi:10.1109/wcnc.2018.8377095

Cited by 31 publications

(30 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other papers defined a general resource model and they did not focus on the specific resource components . Mahmud et al also considered a general resource value, but they additionally defined the service demand and device capacity in terms of the expected and offered processing times.…”

Section: Analysis Of the State Of The Artmentioning

confidence: 99%

“…43 Other papers defined a general resource model and they did not focus on the specific resource components. 26,29,61 Mahmud et al 44 also considered a general resource value, but they additionally defined the service demand and device capacity in terms of the expected and offered processing times. On the contrary, this model was sometimes simplified to a scalar value that represents a general capacity unit 27,35,[51][52][53] or with general resources slots.…”

Section: Node Constraintsmentioning

confidence: 99%

See 1 more Smart Citation

How to place your apps in the fog: State of the art and open challenges

et al. 2019

View full text Add to dashboard Cite

Summary Fog computing aims at extending the cloud towards the Internet of things so to achieve improved quality of service and to empower latency‐sensitive and bandwidth‐hungry applications. The fog calls for novel models and algorithms to distribute multiservice applications in such a way that data processing occurs wherever it is best placed, based on both functional and nonfunctional requirements. This survey reviews the existing methodologies to solve the application placement problem in the fog, while pursuing three main objectives. First, it offers a comprehensive overview on the currently employed algorithms, on the availability of open‐source prototypes and on the size of test use cases. Second, it classifies the literature based on the application and fog infrastructure characteristics that are captured by available models, with a focus on the considered constraints and the optimized metrics. Finally, it identifies some open challenges in application placement in the fog.

show abstract

Section: Analysis Of the State Of The Artmentioning

confidence: 99%

Section: Node Constraintsmentioning

confidence: 99%

How to place your apps in the fog: State of the art and open challenges

et al. 2019

View full text Add to dashboard Cite

show abstract

“…In this section, we present the results obtained by applying the proposed changes in the popular CloudSim simulator to add an extension with the fog architecture modules. The physical and virtual communities concept and the community detection algorithm have also been implemented in the simulator, together with the fog datacentre that is an additional branch of the complex network that was previously developed in CloudSim …”

Section: Implementation Of the Proposal And Simulation Resultsmentioning

confidence: 99%

“…This makes fog management particularly dependent on the geographical location of the IoT nodes. The main problem in case of mobile devices is the implementation of “follow‐me” (fm) services that can be supported by live VM or container migration to the closest fog nodes enabling continuous minimum delay …”

Section: Introductionmentioning

confidence: 99%

Mobile‐aware dynamic resource management for edge computing

Filiposka

Mishev

Gilly

2019

Trans Emerging Tel Tech

Self Cite

View full text Add to dashboard Cite

Shifting cloud computing capabilities close to the edge enables provisioning of low latency location‐based internet services that are adapted to user behaviour. However, this can be achieved neither with a simple move of the physical hosts closer to edge networks, nor continuing to abide by the same principles as the ones implemented in traditional cloud computing approaches. In order to accomplish the promised high quality of service, changes must be made to the resource management techniques so that they are adapted to the requirements of fog computing. This paper introduces a novel location‐based handoff management and its corresponding implementation of dynamic resource management modules that introduce resource allocation and migration strategies adapted specifically to fog computing. The aim is the implementation of the follow‐me behaviour of edge resources considering a tightly coupled perspective with the user location. The proposal is based on the concept of mapping physical areas to logical resource communities where the node mobility triggers migrations to the corresponding community. The results analysis from the simulation scenarios shows that the effectiveness of our community‐based dynamic resource management proposal in following the geographical trajectory of mobile users with wearable devices is over 80% even in highly saturated environments. The comparison with traditional resource management techniques clearly presents the advantages of our proposal, while the parameter wise in‐depth analysis discusses dependencies on the number of nodes, speed, and available resources.

show abstract

“…In the work of Filiposka et al, [19] the authors first introduced the concept of community to optimize resource management in fog computing and proposed that VMs be allocated to a set of fog devices using the community relationship of the devices and migrated as users move. They improved the previous scheme in follow-up work.…”

Section: Related Workmentioning

confidence: 99%

Mobility-aware dynamic service placement for edge computing

Liu¹,

Wang²,

Tian³

et al. 2019

EAI Endorsed Trans IoT

View full text Add to dashboard Cite

Edge computing provides capabilities similar to traditional cloud computing at network edge closer to users. Offloading applications from the cloud to the edge of the network can effectively diminish the latency of users waiting for applications to improve their quality of service(QoS). Due to the user mobility, however, the distance between the user and the edge device is constantly increasing, resulting in a degradation of the user's QoS. To satisfy the QoS of mobile users, applications should be dynamically migrated to follow the user mobility.In this paper, we propose a mobility-aware dynamic service placement policy that reduces the number of virtual machine migrations and diminishes user-perceived latency simultaneously. The proposed scheme filters out the invalid migration that the user handoffs to another access point before the migration is completed. The simulation trials demonstrate that our solution improves the QoS of users and reduces the number of application migrations.

show abstract

Community-based allocation and migration strategies for fog computing

Cited by 31 publications

References 5 publications

How to place your apps in the fog: State of the art and open challenges

How to place your apps in the fog: State of the art and open challenges

Mobile‐aware dynamic resource management for edge computing

Mobility-aware dynamic service placement for edge computing

Contact Info

Product

Resources

About