A Low-Complexity Approach to Distributed Cooperative Caching with Geographic Constraints

Avrachenkov, Konstantin; Serbetci, Berksan

doi:10.1145/3078505.3078534

Cited by 27 publications

(42 citation statements)

References 23 publications

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“…We will provide a distributed asynchronous algorithm to address Problem 1 in which we iteratively update the placement policy at each cache. In [3], [4] we have showed that we can define an algorithm that can be viewed as the best response dynamics in a potential game for similar non-concave problems. We will present a similar algorithm here.…”

Section: Model and Problem Definitionmentioning

confidence: 99%

“…In [6], Dehghan et al have provided a utility-driven caching for a single cache, where each content has been associated with a utility, which is a function of the corresponding content hit probability. In [3] we have developed a distributed asynchronous algorithm that deals with the miss probability minimization by casting the problem into the framework of potential games for general networks, and showed that our algorithm converges to a Nash equilibrium, and in fact to the best Nash equilibrium in most practical scenarios. In [4] the developed algorithm has been used for the residual bandwidth minimization of VoD systems with several video partitioning mechanisms.…”

Section: Introductionmentioning

confidence: 99%

“…In [1], Applegate et al have presented an approach for optimal content placement for a large-scale VoD by formulating the problem as a mixed integer problem. The main difference between the present work; and [6] is the consideration of a network with many caches instead of a single cache, and [3], [4] is the considered performance measure, and [1] is the concept of video partitioning and the heterogeneity of the video popularities over the network. See [3], [10] for a more exhaustive review of the existing caching work.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Distributed Cooperative Caching for Utility Maximization of VoD Systems

Avrachenkov

Serbetci

2019

2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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We consider caching of VoD contents in a cellular network in which each base station is equipped with a cache. Videos are partitioned into chunks according to a layered coding mechanism and the goal is to place chunks in caches such that the expected utility is maximized. The utility depends on the quality at which a user is requesting a file and the chunks that are available. We impose alpha-fairness across files and qualities. We develop a distributed asynchronous algorithm for deciding which chunks to store in which cache.

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Section: Model and Problem Definitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Distributed Cooperative Caching for Utility Maximization of VoD Systems

Avrachenkov

Serbetci

2019

2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

Self Cite

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“…Each SBS i of MNO j is equipped with a limited size storage capacity, denoted s c i , j ( s c i , j > 0) that can be used as a cache to store the CP's popular content. All the cache‐enabled SBSs are assumed to have the same limited storage capacity …”

Section: Problem Formulationmentioning

confidence: 99%

“…The CP manages a local content library

scriptL

composed of the set of a finite number F ( F < ∞ ) of its popular files (denoted c f , 0 < f ≤ F ), where

scriptL = ({}, c_{1}, c_{2}, ⋯, c_{F})

. All

c_{f} ((), f \in F)

files are assumed to have the same unit size …”

Section: Problem Formulationmentioning

confidence: 99%

Incentive edge caching in software‐defined internet of vehicles: A Stackelberg game approach

Alioua

Senouci

Sedjelmaci

et al. 2018

Int J Communication

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In this paper, we investigate an incentive edge caching mechanism for an internet of vehicles (IoV) system based on the paradigm of software-defined networking (SDN). We start by proposing a distributed SDN-based IoV architecture. Then, based on this architecture, we focus on the economic side of caching by considering competitive cache-enablers market composed of one content provider (CP) and multiple mobile network operators (MNOs). Each MNO manages a set of cache-enabled small base stations (SBS). The CP incites the MNOs to store its popular contents in cache-enabled SBSs with highest access probability to enhance the satisfaction of its users. By leasing their cache-enabled SBSs, the MNOs aim to make more monetary profit. We formulate the interaction between the CP and the MNOs, using a Stackelberg game, where the CP acts first as the leader by announcing the popular content quantity that it which to cache and fixing the caching popularity threshold, a minimum access probability under it a content cannot be cached. Then, MNOs act subsequently as followers responding by the content quantity they accept to cache and the corresponding caching price. A noncooperative subgame is formulated to model the competition between the followers on the CP's limited content quantity.We analyze the leader and the follower's optimization problems, and we prove the Stackelberg equilibrium (SE). Simulation results show that our game-based incentive caching model achieves optimal utilities and outperforms other incentive caching mechanisms with monopoly cache-enablers whilst enhancing 30% of the user's satisfaction and reducing the caching cost. KEYWORDS incentive edge caching, internet of vehicle, software-defined networking, Stackelberg game INTRODUCTIONIn the last few years, Internet of Vehicles (IoV) has emerged as a promising technology for improving next-generation vehicular networks by advanced cloud/edge computing technologies. This rapid emergence has principally boosted by the vigorous development of wireless communication technologies, the explosive usage of in-vehicle mobile internet, and the appearance of the smart city concept. Internet of Vehicles is the instantiation of Internet of things (IoT) paradigm in vehicular scenarios to enable more intelligent and more connected vehicle with new IP-based applications. 1,2 Int J Commun Syst. 2019;32:e3787.wileyonlinelibrary.com/journal/dac

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Randomised geographic caching and its applications in wireless networks

Giovanidis¹,

Błaszczyszyn

2021

Edge Caching for Mobile Networks

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The randomised (or probabilistic) geographic caching is a proactive content placement strategy that has attracted a lot of attention, because it can simplify a great deal cache-management problems at the wireless edge. It diversifies content placement over caches and applies to scenarios where a request can be possibly served by multiple cache memories. Its simplicity and strength is due to randomisation. It allows one to formulate continuous optimisation problems for content placement over large homogeneous geographic areas. These can be solved to optimality by standard convex methods, and can even provide closed-form solutions for specific cases. This way the algorithmic obstacles from NP-hardness are avoided and optimal solutions can be derived with low computational cost. Randomised caching has a large spectrum of applications in real-world wireless problems, including femto-caching, multi-tier networks, device-to-device communications, mobility, mm-wave, security, UAVs, and more. In this chapter we will formally present the main policy with its applications in various wireless scenarios. We will further introduce some very useful extensions related to unequal file-sizes and content placement with neighbourhood dependence.

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A Low-Complexity Approach to Distributed Cooperative Caching with Geographic Constraints

Cited by 27 publications

References 23 publications

Distributed Cooperative Caching for Utility Maximization of VoD Systems

Distributed Cooperative Caching for Utility Maximization of VoD Systems

Incentive edge caching in software‐defined internet of vehicles: A Stackelberg game approach

Randomised geographic caching and its applications in wireless networks

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