The More the Merrier: Enhancing Reliability of 5G Communication Services With Guaranteed Delay

Thiruvasagam, Prabhu Kaliyammal; Kotagi, Vijeth J.; Murthy, C. Siva Ram

doi:10.1109/lnet.2019.2902720

Cited by 25 publications

(11 citation statements)

References 5 publications

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“…In particular, the authors identify the traffic changes as primary threats to service resilience, and put in the field an orchestration system along with network slices as potential solutions. Authors in [11] propose a method for enhancing the reliability of an SFC in 5G communication services, where the involved VNFs have been modeled both as 𝑀/𝑀/1 and 𝑀/𝑀/𝑚 queueing systems. An 𝑀/𝑀/1 queueing model has been adopted also in [12], where a method to detect bottlenecks in SFCs based on network queue occupation has been devised, and in [13] to model the SFC scheduling process in data centers.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Performance and Availability Challenges in Designing Resilient 5G Architectures

Simone,

Mauro,

Natella

et al. 2024

IEEE Trans. Netw. Serv. Manage.

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This work proposes a stochastic characterization of resilient 5G architectures, where attributes such as performance and availability play a crucial role. As regards performance, we focus on the delay associated with the Packet Data Unit session establishment, a 5G procedure recognized as critical for its impact on the Quality of Service and Experience of end-users. To formally characterize this aspect, we employ the non-productform queueing networks framework where: 𝑖) main nodes of a 5G architecture have been realistically modeled as 𝐺/𝐺/𝑚 queues which do not admit analytical solutions; 𝑖𝑖) the decomposition method useful to catch subtle quantities involved in the chain of 5G interconnected nodes has been conveniently customized. The results of performance characterization constitute the input of the availability modeling, where we design a hierarchical scheme to characterize the probabilistic failure/repair behavior of 5G nodes combining two formalisms: 𝑖) the Reliability Block Diagrams, useful to capture the high-level interconnections between nodes; 𝑖𝑖) the Stochastic Reward Networks to model the internal structure of each node. The final result is an optimal resilient 5G setting that fulfills both a performance constraint (e.g., a temporal threshold) and an availability constraint (e.g., the so-called five nines) at the minimum cost, namely, with the smallest number of redundant elements. The theoretical part is complemented by an empirical assessment carried out through Open5GS, a 5G testbed that we have deployed to realistically estimate main performance and availability metrics.

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Section: Related Workmentioning

confidence: 99%

“…) Expression (11) represents the reward rate associated to the 𝑖th node with the pertinent steady-state probability 𝜋 𝑠,𝑖 , while ⊙𝑃 𝑘 indicates the number of tokens in place 𝑘.…”

Section: B Srn Availability Model Of An Open5gs Nodementioning

confidence: 99%

Performance and Availability Challenges in Designing Resilient 5G Architectures

Simone,

Mauro,

Natella

et al. 2024

IEEE Trans. Netw. Serv. Manage.

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“…The number of physical substrate nodes inside each InP is fixed at 40. The intra-domain link delay follows a uniform distribution U (1,6). The resource capacity of the intra-domain physical nodes and links follows a uniform distribution U(200,300).…”

Section: Simulation Environment and Settingsmentioning

confidence: 99%

“…This limits the service delivery of those networks and inhibits the infrastructure providers from optimally using the network resources in a dynamic manner [3], [4], [5]. In this regard, network virtualization has emerged as a promising technique to overcome this barrier by enabling the softwarisation of network functions [6], [7], [8]. As a result, services are instantiated as service chains consisting of an ordered set of Virtual Network Functions (VNFs) commonly referred to as Service Function Chains (SFCs), that can be dynamically deployed and scaled according to the real-time requirements [9], [10], [11], [4].…”

Section: Introductionmentioning

confidence: 99%

A deep reinforcement learning-based algorithm for reliability-aware multi-domain service deployment in smart ecosystems

Kibalya

Serrat

Gorricho

et al. 2020

Neural Comput & Applic

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The transition towards full network virtualization will see services for smart ecosystems including smart metering, healthcare and transportation among others, being deployed as Service Function Chains (SFCs) comprised of an ordered set of virtual network functions. However, since such services are usually deployed in remote cloud networks, the SFCs may transcend multiple domains belonging to different Infrastructure Providers (InPs), possibly with differing policies regarding billing and Quality-of-service (QoS) guarantees. Therefore, efficiently allocating the exhaustible network resources to the different SFCs while meeting the stringent requirements of the services such as delay and QoS among others, remains a complex challenge, especially under limited information disclosure by the InPs. In this work, we formulate the SFC deployment problem across multiple domains focusing on delay constraints, and propose a framework for SFC orchestration which adheres to the privacy requirements of the InPs. Then, we propose a Reinforcement Learning (RL) basedalgorithm for partitioning the SFC request across the different InPs while considering service reliability across the participating InPs. Such RL based algorithms have the intelligence to infer undisclosed InP information from historical data obtained from past experiences. Simulation results, considering both online and offline scenarios, reveal that the proposed algorithm results in

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“…In wireless communication technology, there has been a shift toward the development of fifth-generation (5G) technology in the millimetre-wave band as an improvement over existing fourth-generation (4G) technology to realize various future communication applications based on its ultralow delay, ultrahigh speed, and ultraconnectivity characteristics. [1][2][3] However, 5 G technology in the millimetre-wave band experiences high path losses, including low transmit signal capture because of the small effective antenna aperture size due to the shorter wavelength, significant absorption of energy by oxygen and water molecules in the atmosphere and the reduction in the signal-to-noise ratio (SNR) because of the high thermal noise caused by the wide bandwidth. [4][5][6] In addition, line of sight (LOS) is a critical issue, with the high directivity and low transmittance leading to attenuation and signal blockage by obstacles such as buildings.…”

Section: Introductionmentioning

confidence: 99%

Mechatronic Reconfigurable Intelligent‐Surface‐Driven Indoor Fifth‐Generation Wireless Communication

Jeong

Park

Phon

et al. 2022

Advanced Intelligent Systems

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Reconfigurable intelligent surface‐assisted wireless networks have been proposed to overcome the current technical issues in fifth‐generation (5G) wireless communication systems. Generally, the beam control functions of a reconfigurable intelligent surface require the independent phase control of the unit cells, and each unit cell requires an active device. Although reconfigurable intelligent surfaces are considered a promising solution for 5G and sixth‐generation (6G) wireless communication, their practical implementation faces a bottleneck at high frequencies (e.g., with the millimetre‐wave spectrum) because they require a large number of active devices, leading to high costs, parasitic effects, increased design complexity, and modulated signal distortion. Herein, a mechatronic reconfigurable intelligent surface is reported for indoor millimetre‐wave wireless communication. Our mechatronic device strengthens the innovative reflective beam control functions through rotatable unit structures and rack gear systems. Furthermore, the criteria required for future 5 G wireless communication are experimentally verified by transmitting and receiving quadrature phase‐shift keying 16‐/32‐/64‐quadrature amplitude modulation signals based on 5 G new radio (NR) frequency range two standards for indoor environments.

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The More the Merrier: Enhancing Reliability of 5G Communication Services With Guaranteed Delay

Cited by 25 publications

References 5 publications

Performance and Availability Challenges in Designing Resilient 5G Architectures

Performance and Availability Challenges in Designing Resilient 5G Architectures

A deep reinforcement learning-based algorithm for reliability-aware multi-domain service deployment in smart ecosystems

Mechatronic Reconfigurable Intelligent‐Surface‐Driven Indoor Fifth‐Generation Wireless Communication

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