A bandwidth allocation scheme to meet flow requirements in mobile edge computing

Yusuke, Ito; Koga, Hiroyuki; Iida, Katsuyoshi

doi:10.1109/cloudnet.2017.8071541

Cited by 8 publications

(5 citation statements)

References 12 publications

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“…To achieve this optimization, computation resources and offloading MCO decisions were the main constraints in the optimization process. Ito et al proposed a bandwidth allocation scheme based on collectible information to meet the requirements of each flow in mobile edge computing [6]. Energy-aware edge server placement is studied in [5] to find a more effective placement scheme with low energy consumption.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Matching Subcarrier Resource Allocation and Offloading Decision

Alhusenat

Alma'aitah

Hayajneh

2022

Int. j. commun. netw. inf. secur.

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A heterogeneous cellular network can define as a network that is composed of different cell sizes (macrocell (MeNB), small cell (SeNB), femtocell). Such heterogeneity of network is the backbone of the 5G networks where new applications on mobile devices need extensive computing power consumption and ultra-low latency constraints. Using a heterogeneous network will provide multiple paths in which the users’ data can flow through the network depending on the users’ available resources, remaining energy, etc. we study the heterogeneous network model, which contains MeNB, SeNB and femtocells. Also, we propose a matching subcarrier resource allocation and offloading decision (MSRAOD) algorithm, that depends on recourse allocation optimization. The main optimization goal has been set to minimize the total energy consumption of mobile users’ devices with acceptable latency requirements of the applications. Our proposed algorithm results show that the proposed algorithm enhances the average energy consumption of mobile users in the heterogeneous network.

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Section: Literature Reviewmentioning

confidence: 99%

“…The network model is a heterogeneous network with one MeNB cell, 𝐼 𝑠 SeNBs, and 𝐼 𝑓 Femtocells co-located as shown in Figure .1. An MEC server connected at the MeNB [6], and another server is at a Femtocell access point.…”

Section: Matching Subcarrier Resource Allocation and Offloading Decisionmentioning

confidence: 99%

Matching Subcarrier Resource Allocation and Offloading Decision

Alhusenat

Alma'aitah

Hayajneh

2022

Int. j. commun. netw. inf. secur.

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“…Optimizing the bandwidth in a fog/edge environment directly minimizes the delay resulting from the transmission process because the processing resources are located close to the end devices. In this context, Ito et al [45] proposed a bandwidth allocation scheme based on collectible information. Gia et al [46] introduced the processing of ECG (electrocardiogram) features using fog nodes, their results disclosed that fog helps to achieve more efficiency in bandwidth and low latency in the data processing.…”

Section: A General Review Of Iot-based Systems' Requirementsmentioning

confidence: 99%

Digital Agriculture and Intelligent Farming Business Using Information and Communication Technology: A Survey

Idrissi¹,

Beqqali²,

Riffi³

et al. 2022

Digital Agriculture, Methods and Applications

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Adopting new information and communication technology (ICT) as a solution to achieve food security becomes more urgent than before, particularly with the demographical explosion. In this survey, we analyze the literature in the last decade to examine the existing fog/edge computing architectures adapted for the smart farming domain and identify the most relevant challenges resulting from the integration of IoT and fog/edge computing platforms. On the other hand, we describe the status of Blockchain usage in intelligent farming as well as the most challenges this promising topic is facing. The relevant recommendations and researches needed in Blockchain topic to enhance intelligent farming sustainability are also highlighted. It is found through the examination that the adoption of ICT in the various farming processes helps to increase productivity with low efforts and costs. Several challenges are faced when implementing such solutions, they are mainly related to the technological development, energy consumption, and the complexity of the environments where the solutions are implemented. Despite these constraints, it is certain that shortly several farming businesses will heavily invest to introduce more intelligence into their management methods. Furthermore, the use of sophisticated deep learning and Blockchain algorithms may contribute to the resolution of many recent farming issues.

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“…Based on this, this paper selects the chain topology to deploy the MVN architecture. The MVN architecture adopts the chain topology, which is mainly composed of four parts: BS (Base Station), MECP (Multi-Access Edge Computing Point), gNB (5G Micro Base Station) and terminal [21]. BS is the root node of MVN tree topology, which gathers local information by connecting MECP and promotes MVN network to comprehensively manage traffic from a global perspective; MECP will process the collected delay sensitive information in time to shorten the delay; gNB can communicate with MECP for up to two hops and transmit the collected information of adjacent terminals; in order to realize the mobile coverage test of the target, static Test Points (TP) are set up at several representative locations on the target road section to test whether the connectivity and coverage of MVN network meet the requirements.…”

Section: System Model Of 5g Access Data Back Haul Linkmentioning

confidence: 99%

5G Network Data Migration Service Based on Edge Computing

2021

Symmetry

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With the development of mobile network technology, the continuous increase of mobile traffic has put forward higher requirements for quality of service (QoS) issues such as asymmetric transmission delay. The paper mainly studies the energy distribution problem on the migration data link from the terminal device to the edge node in the mobile edge network. Multiple data service packages are set up at each hop on the migration data link, and these data service packages compete with each other, and ultimately only one terminal provides and stores energy for this hop. The migration strategy of the data service package is affected by the edge node, and the edge node changes the migration strategy according to the migration strategy of the data service package. The paper is based on the formation of nodes between the data service packages of different nodes on the 5G network data link to jointly control the migration strategy, coordinate the migration strategy formulated, and better coordinate the migration strategy. In this competitive game model, the optimal migration strategy of nodes is found out according to the terminal equipment access requirements. Then according to the node stability rules, the composition of nodes when the nodes are stable is obtained, the migration strategy of stable nodes and the migration and spectrum strategies of operators are obtained, and the migration strategy of joint control provides energy for edge nodes.

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A bandwidth allocation scheme to meet flow requirements in mobile edge computing

Cited by 8 publications

References 12 publications

Matching Subcarrier Resource Allocation and Offloading Decision

Matching Subcarrier Resource Allocation and Offloading Decision

Digital Agriculture and Intelligent Farming Business Using Information and Communication Technology: A Survey

5G Network Data Migration Service Based on Edge Computing

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