Incentive-Based Coded Distributed Computing Management for Latency Reduction in IoT Services—A Game Theoretic Approach

Kim, Nakyoung; Kim, Daejin; Lee, Joohyung; Niyato, Dusit; Choi, Jun Kyun

doi:10.1109/jiot.2020.3045277

Cited by 17 publications

(13 citation statements)

References 48 publications

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“…In [9], the Optimal Coded Network Service (OCNS) scheme is designed to mitigate the computing effect of straggling nodes. To motivate the participation of mobile devices in the CDC platform, the OCNS scheme proposes incentive mechanisms that distribute the incentive based on workload and completion time of mobile devices.…”

Section: Related Workmentioning

confidence: 99%

Collaborative Coded Distributed Computing Scheme: A Two-Phase Cooperative Game Approach

Kim

2023

IEEE Access

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As a modern communication paradigm, Artificial intelligence based Internet of Things (AIoT) can provide an interactive platform across the globe to enrich the quality of networking services. With the AIoT paradigm, coded distributed computing (CDC) has recently emerged to be a promising solution to address the straggling effects in conventional distributed computing systems. In this article, we propose a novel CDC control scheme in the AIoT platform. Based on the cooperative game theory, the main challenges of our scheme are i) the 𝑘 value decision for the CDC process, and ii) edge node resource allocation for offloading tasks. Using the ideas of coalition game and weighted Nash social welfare solution (WNSWS), our proposed scheme is developed as a two-phase game model to achieve a mutually desirable solution. At the first phase, a dynamic coalition formation is proceeded to select the most adaptable edge nodes for the offloading subtasks. At the second phase, the WNSWS is adopted to effectively share each edge node's computing resource. Based on the jointly design of these two cooperative games, we explore the synergy effect to optimize the CDC process. In the edge assisted distributed computing infrastructure, our reciprocal combinative approach can provide a fair-efficient solution through the sequential interactions of edge nodes and AIoT devices. In the performance evaluation, we provide extensive simulation analyses to show our scheme's superiority by comparing with the existing baseline protocols.

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Section: Related Workmentioning

confidence: 99%

Collaborative Coded Distributed Computing Scheme: A Two-Phase Cooperative Game Approach

Kim

2023

IEEE Access

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“…The workers adopt the dynamic voltage scaling technique, which allows workers to adaptively control the computing speed by scheduling CPU-cycle frequency [36]. Each worker tries to obtain a higher utility and keeps a good reputation value.…”

Section: A Utility Function Of Workersmentioning

confidence: 99%

Reliable Distributed Computing for Metaverse: A Hierarchical Game-Theoretic Approach

Jiang¹,

Kang²,

Niyato³

et al. 2021

Preprint

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The metaverse is regarded as a new wave of technological transformation that provides a virtual space for people to interact with each other through digital avatars. To achieve immersive user experiences in the metaverse, real-time rendering is the key technology. However, computing intensive tasks of real-time graphic and audio rendering from metaverse service providers cannot be processed efficiently on a single resource-limited mobile and Internet of Things (IoT) device. Alternatively, such devices can adopt the collaborative computing paradigm based on Coded Distributed Computing (CDC) to support metaverse services. Therefore, this paper introduces a reliable collaborative CDC framework for metaverse. In the framework, idle resources from mobile devices, acting as CDC workers, are aggregated to handle intensive computation tasks in the metaverse. A coalition can be formed among reliable workers based on a reputation metric which is maintained in a double blockchains database. The framework also considers an incentive to attract reliable workers to participate and process computation tasks of metaverse services. Moreover, the framework is designed with a hierarchical structure composed of coalition formation and Stackelberg games in the lower and upper levels to determine stable coalitions and rewards for reliable workers, respectively. The simulation results illustrate that the proposed framework is resistant to malicious workers. Compared with the random worker selection scheme, the proposed coalition formation and Stackelberg game can improve the utilities of both metaverse service providers and CDC workers.

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“…They do not consider the limited computational resources typically available in edge computing scenarios. Recent studies [22], [23] focus on applying CDC in edge computing. However, they mainly focus on incentive mechanisms for heterogeneous edge devices.…”

Section: Related Work a Coded Distributed Computing (Cdc)mentioning

confidence: 99%

“…Existing studies of resource management for CDC [21]- [23] focus on either the resource trade-off between computation and communication or the incentive mechanism for edge devices (e.g., smart phones and drones) to cooperate as a coalition and deliver latency-sensitive IoT services. There have been few studies on a federation among EIPs to provide CDC services in edge networks.…”

Section: Introductionmentioning

confidence: 99%

Dynamics in Coded Edge Computing for IoT: A Fractional Evolutionary Game Approach

Han¹,

Niyato²,

Leung³

et al. 2021

Preprint

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Recently, coded distributed computing (CDC), with advantages in intensive computation and reduced latency, has attracted a lot of research interest for edge computing, in particular, IoT applications, including IoT data pre-processing and data analytics. Nevertheless, it can be challenging for edge infrastructure providers (EIPs) with limited edge resources to support IoT applications performed in a CDC approach in edge networks, given the additional computational resources required by CDC. In this paper, we propose "coded edge federation", in which different EIPs collaboratively provide edge resources for CDC tasks.To study the Nash equilibrium, when no EIP has an incentive to unilaterally alter its decision on edge resource allocation, we model the coded edge federation based on evolutionary game theory. Since the replicator dynamics of the classical evolutionary game are unable to model economic-aware EIPs which memorize past decisions and utilities, we propose "fractional replicator dynamics" with a power-law fading memory via Caputo fractional derivatives. The proposed dynamics allow us to study a broad spectrum of EIP dynamic behaviors, such as EIP sensitivity and aggressiveness in strategy adaptation, which classical replicator dynamics cannot capture. Theoretical analysis and extensive numerical results justify the existence, uniqueness, and stability of the equilibrium in the fractional evolutionary game. The influence of the content and the length of the memory on the rate of convergence is also investigated.

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Incentive-Based Coded Distributed Computing Management for Latency Reduction in IoT Services—A Game Theoretic Approach

Cited by 17 publications

References 48 publications

Collaborative Coded Distributed Computing Scheme: A Two-Phase Cooperative Game Approach

Collaborative Coded Distributed Computing Scheme: A Two-Phase Cooperative Game Approach

Reliable Distributed Computing for Metaverse: A Hierarchical Game-Theoretic Approach

Dynamics in Coded Edge Computing for IoT: A Fractional Evolutionary Game Approach

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