Designing a green optical network unit using ARMA-based traffic prediction for quality of service-aware traffic

Bhar, Chayan; Chatur, Nilesh; Mukhopadhyay, Atri; Das, Goutam; Datta, Debasish

doi:10.1007/s11107-016-0671-y

Cited by 14 publications

(17 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…9, we show the impact of prediction accuracy of the incoming job request arrival rates on the NE utility values of the competing cloudlets. For the job request arrival rate prediction, we use the moving-average method based ARMA algorithm proposed in [33] and consider that job request arrival rates to each cloudlet remains stationary for 30 seconds. This algorithm works very efficiently when the incoming job requests are self-similar in nature and varies gradually over time.…”

Section: Resultsmentioning

confidence: 99%

“…Thus, a quick prediction of incoming job request arrival rate with 80-90% accuracy is possible [32]. Each cloudlet also estimates the transmission latency of the incoming job requests from the mobile devices and the intermediate transmission latencies with its neighboring cloudlets [33]. Each cloudlet periodically executes the learning algorithms at an interval of D Q and sends this information to the mediator for computation of NE load balancing strategies.…”

Section: System Model a Fundamental System Design Considerationsmentioning

confidence: 99%

“…Each cloudlet periodically executes the learning algorithms at an interval of D Q and sends this information to the mediator for computation of NE load balancing strategies. Nonetheless, the design of load-predictive algorithms is beyond the scope of this paper and hence, consider the algorithm in [33].…”

Section: System Model a Fundamental System Design Considerationsmentioning

confidence: 99%

See 2 more Smart Citations

A Game-Theoretic Approach for Non-Cooperative Load Balancing Among Competing Cloudlets

Mondal

Das

Wong

2020

IEEE Open J. Commun. Soc.

Self Cite

View full text Add to dashboard Cite

To deliver high performance and reliability to the mobile users in accessing mobile cloud services, the major interest is currently given to the integration of centralized cloud computing and distributed edge computing infrastructures. In such a heterogeneous network ecosystem, multiple cloudlets from different service providers coexist. However, to meet the stringent latency requirements of computation-intensive and mission-critical applications, overloaded cloudlets can offload some of the incoming job requests to their relatively under-loaded neighboring cloudlets. In this paper, we propose a novel economic and non-cooperative game-theoretic model for load balancing among competitive cloudlets. This model aims to maximize the utilities of all the competing cloudlets while meeting the end-to-end latency of the users. We characterize the problem as a generalized Nash equilibrium problem and investigate the existence and uniqueness of a pure-strategy Nash equilibrium. We design a variational inequality based algorithm to compute the pure-strategy Nash equilibrium. We show that all the competing cloudlets are able to maximize their utilities by employing our proposed Nash equilibrium computation offload strategy in both under-and overloaded conditions. We also show through numerical evaluations that our load balancing model outperforms some of the existing game-theoretic load balancing frameworks, especially in a highly overloaded condition.INDEX TERMS Cloudlet computing, non-cooperative load balancing, generalized Nash equilibrium, variational inequality.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: System Model a Fundamental System Design Considerationsmentioning

confidence: 99%

Section: System Model a Fundamental System Design Considerationsmentioning

confidence: 99%

See 1 more Smart Citation

A Game-Theoretic Approach for Non-Cooperative Load Balancing Among Competing Cloudlets

Mondal

Das

Wong

2020

IEEE Open J. Commun. Soc.

Self Cite

View full text Add to dashboard Cite

show abstract

“…In general, the job request arrival process to cloudlets is a nonstationary process, but it possesses some pseudo-stationary characteristics such that the mean job request arrival rate varies gradually. This facilitates the cloudlets to predict the incoming job request arrival rate by employing efficient traffic prediction algorithms like auto-regressive and moving average (ARMA) algorithm [32]. The transmission latency of the incoming job requests and the intermediate transmission latencies with the neighboring cloudlets are also estimated by each cloudlet [33].…”

Section: System Modelmentioning

confidence: 99%

Centralized and Decentralized Non-Cooperative Load-Balancing Games among Federated Cloudlets

Mondal,

Das,

Wong

2020

Preprint

Self Cite

View full text Add to dashboard Cite

Edge computing servers like cloudlets from different service providers that compensate scarce computational, memory, and energy resources of mobile devices, are distributed across access networks. However, depending on the mobility pattern and dynamically varying computational requirements of associated mobile devices, cloudlets at different parts of the network become either overloaded or under-loaded. Hence, load balancing among neighboring cloudlets appears to be an essential research problem. Nonetheless, the existing load balancing frameworks are unsuitable for low-latency applications. Thus, in this paper, we propose an economic and non-cooperative load balancing game for low-latency applications among neighboring cloudlets, from same as well as different service providers. Firstly, we propose a centralized incentive mechanism to compute the unique Nash equilibrium load balancing strategies of the cloudlets under the supervision of a neutral mediator. With this mechanism, we ensure that the truthful revelation of private information to the mediator is a weakly-dominant strategy for both the under-loaded and overloaded cloudlets. Secondly, we propose a continuousaction reinforcement learning automata-based algorithm, which allows each cloudlet to independently compute the Nash equilibrium in a completely distributed network setting. We critically study the convergence properties of the designed learning algorithm, scaffolding our understanding of the underlying load balancing game for faster convergence. Furthermore, through extensive simulations, we study the impacts of exploration and exploitation on learning accuracy. This is the first study to show the effectiveness of reinforcement learning algorithms for load balancing games among neighboring cloudlets.

show abstract

“…However, it is well known that the power consumption figure of doze mode is quite high [3]. In [16], [20], we have proposed a novel protocol where ONUs dynamically swerve between the active mode and different low power modes where ONUs select the most suitable low power mode based on the sleep duration (time interval over which low power mode is employed) before entering into a low power mode. Once an ONU enters into a low power mode, a certain time interval is required to wake-up from the low power mode and to initiate the US [2] transmission.…”

Section: Introductionmentioning

confidence: 99%

Design of Energy-Efficient EPON: A Novel Protocol Proposal and Its Performance Analysis

Dutta

Das

2019

IEEE Trans. on Green Commun. Netw.

Self Cite

View full text Add to dashboard Cite

Economical and environmental concerns necessitate network engineers to focus on energy-efficient access network design. The optical network units (ONUs), being predominantly responsible for the energy consumption of Ethernet Passive Optical Network (EPON), motivates us towards designing a novel protocol for saving energy at ONU. The proposed protocol exploits different low power modes (LPM) and opts for the suitable one using traffic prediction. This scheme provides a significant improvement of energy-efficiency especially at high load (∼ 40%) over existing protocols. A better understanding of the performance and a deeper insight into several design aspects can only be addressed through a detailed mathematical analysis. The proposed protocol involves traffic prediction which infringes Markovian property. However, some pragmatic assumptions along with a proper selection of observation instances and state descriptions allow us to form a Discrete Time Markov Chain (DTMC) of the proposed algorithm. Thus, the primary objective of this paper is to propose a novel scheme for achieving energyefficiency at ONU and mathematically analyze the performance of it with the help of a DTMC. The analysis reveals that the energy-efficiency is more sensitive to the power consumption of doze mode as compared to other LPM while the effect of sleepto-wake-up time is minor.

show abstract

Designing a green optical network unit using ARMA-based traffic prediction for quality of service-aware traffic

Cited by 14 publications

References 15 publications

A Game-Theoretic Approach for Non-Cooperative Load Balancing Among Competing Cloudlets

A Game-Theoretic Approach for Non-Cooperative Load Balancing Among Competing Cloudlets

Centralized and Decentralized Non-Cooperative Load-Balancing Games among Federated Cloudlets

Design of Energy-Efficient EPON: A Novel Protocol Proposal and Its Performance Analysis

Contact Info

Product

Resources

About