A distributed mechanism for Software-based mobility management

Basu, Debraj; Hussain, Ali Abdul; Hasan, Syed Faraz

doi:10.1109/icsess.2016.7883076

Cited by 4 publications

(4 citation statements)

References 17 publications

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“…Also, the EPC is aware of the aggregate traffic load per BS, but it does not have any knowledge about the energy side information (ESI) in the BSs (energy consumed, harvested, etc.). The lack of such information motivates the need for mobility and energy-aware procedures that can be deployed in the EPC, either in a centralized SDN controller or within subcontrollers (SC) as proposed in [88]. These shall perform mobility management tasks, while at the same time being aware of the available energy in the (energy harvesting) BSs.…”

Section: Deployment and Nature Of The Epc Control Logicmentioning

confidence: 99%

“…Virtualization has introduced the use of a centralized controller exploiting SDN in the EPC; however, this approach still lacks efficient power consumption management strategies, as it does not take into account daily traffic variations. Another management strategy that has to be investigated entails the use of a distributed approach [88], where some decisions may be made locally (e.g., at the BSs) to configure instructions remotely within a centralized controller. For example, in the case where the MEC platform is colocated with the BS, it can collect traffic statistics, make local decisions (thus ensuring fast reaction to data traffic and mobility variations), and then share them with the central controller when required, for example, when a BS has to be deactivated.…”

Section: Deployment and Nature Of The Epc Control Logicmentioning

confidence: 99%

See 1 more Smart Citation

Softwarization of Mobile Network Functions towards Agile and Energy Efficient 5G Architectures: A Survey

Dlamini

Rossi

Munaretto³

2017

Wireless Communications and Mobile Computing

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Future mobile networks (MNs) are required to be flexible with minimal infrastructure complexity, unlike current ones that rely on proprietary network elements to offer their services. Moreover, they are expected to make use of renewable energy to decrease their carbon footprint and of virtualization technologies for improved adaptability and flexibility, thus resulting in green and self-organized systems. In this article, we discuss the application of software defined networking (SDN) and network function virtualization (NFV) technologies towards softwarization of the mobile network functions, taking into account different architectural proposals. In addition, we elaborate on whether mobile edge computing (MEC), a new architectural concept that uses NFV techniques, can enhance communication in 5G cellular networks, reducing latency due to its proximity deployment. Besides discussing existing techniques, expounding their pros and cons and comparing state-of-the-art architectural proposals, we examine the role of machine learning and data mining tools, analyzing their use within fully SDN-and NFV-enabled mobile systems. Finally, we outline the challenges and the open issues related to evolved packet core (EPC) and MEC architectures.

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Section: Deployment and Nature Of The Epc Control Logicmentioning

confidence: 99%

Section: Deployment and Nature Of The Epc Control Logicmentioning

confidence: 99%

Softwarization of Mobile Network Functions towards Agile and Energy Efficient 5G Architectures: A Survey

Dlamini

Rossi

Munaretto³

2017

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…This method tries to solve the problem of network congestion and significant transmission delay brought on by cloud computing's centralized computation. Additionally, the real-time performance of the data calculating process is further ensured by the edge server's ability to respond to the user's request and task in a shorter amount of time [19]. At order to reduce the large data transmission delay experienced during long-distance communication, the server is placed in a network edge node that is closer to the device.…”

Section: Related Workmentioning

confidence: 99%

“…To determine the resource unit allocation indicator I * (t) , the ultimate υ is transformed into it using formula (19).…”

Section: Definitionmentioning

confidence: 99%

Non-orthogonal multiple access-based MEC for energy-efficient task offloading in e-commerce systems

Zheng,

Tahir,

Aurangzeb

et al. 2024

J Cloud Comp

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Mobile edge computing (MEC) reduces the latency for end users to access applications deployed at the edge by offloading tasks to the edge. With the popularity of e-commerce and the expansion of business scale, server load continues to increase, and energy efficiency issues gradually become more prominent. Computation offloading has received widespread attention as a technology that effectively reduces server load. However, how to improve energy efficiency while ensuring computing requirements is an important challenge facing computation offloading. To solve this problem, using non-orthogonal multiple access (NOMA) to increase the efficiency of multi-access wireless transmission, MEC supporting NOMA is investigated in the research. Computing resources will be divided into separate sub-computing that will be handled via e-commerce terminals or transferred to edge sides by reutilizing radio resources, we put forward a Group Switching Matching Algorithm Based on Resource Unit Allocation (GSM-RUA) algorithm that is multi-dimensional. To this end, we first formulate this task allocation problem as a long-term stochastic optimization problem, which we then convert to three short-term deterministic sub-programming problems using Lyapunov optimization, namely, radio resource allocation in a large timescale, computation resource allocating and splitting in a small-time frame. Of the 3 short-term deterministic sub-programming problems, the first sub-programming problem can be remodeled into a 1 to n matching problem, which can be solved using the block-shift-matching-based radio resource allocation method. The latter two sub-programming problems are then transformed into two continuous convex problems by relaxation and then solved easily. We then use simulations to prove that our GSM-RUA algorithm is superior to the state-of-the-art resource management algorithms in terms of energy consumption, efficiency and complexity for e-commerce scenarios.

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Performance Evaluation of Handover Protocols in Software Defined Networking Environment

Lee

Jaffry

Hasan

et al. 2018

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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A distributed mechanism for Software-based mobility management

Cited by 4 publications

References 17 publications

Softwarization of Mobile Network Functions towards Agile and Energy Efficient 5G Architectures: A Survey

Softwarization of Mobile Network Functions towards Agile and Energy Efficient 5G Architectures: A Survey

Non-orthogonal multiple access-based MEC for energy-efficient task offloading in e-commerce systems

Performance Evaluation of Handover Protocols in Software Defined Networking Environment

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