A Game Theoretic Approach for Simultaneous Compaction and Equipartitioning of Spatial Data Sets

Gupta, U.; Ranganathan, N.

doi:10.1109/tkde.2009.110

Cited by 23 publications

(13 citation statements)

References 34 publications

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“…The resulting GPP can then be solved by any GPP solver [15,16]. Since the goal is to equipartition the graph, more specialized algorithms can also be used [17]. However, in SO-EPP, the set E is empty initially (due to a lack of information).…”

Section: Related Workmentioning

confidence: 99%

A Bayesian network based solution scheme for the constrained Stochastic On-line Equi-Partitioning Problem

Glimsdal

Granmo

2018

Appl Intell

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A number of intriguing decision scenarios revolve around partitioning a collection of objects to optimize some application specific objective function. This problem is generally referred to as the Object Partitioning Problem (OPP) and is known to be NP-hard. We here consider a particularly challenging version of OPP, namely, the Stochastic On-line Equi-Partitioning Problem (SO-EPP). In SO-EPP, the target partitioning is unknown and has to be inferred purely from observing an on-line sequence of object pairs. The paired objects belong to the same partition with probability p and to different partitions with probability 1 − p, with p also being unknown. As an additional complication, the partitions are required to be of equal cardinality. Previously, only sub-optimal solution strategies have been proposed for SO-EPP. In this paper, we propose the first optimal solution strategy. In brief, the scheme that we propose, BN-EPP, is founded on a Bayesian network representation of SO-EPP problems. Based on probabilistic reasoning, we are not only able to infer the underlying object partitioning with optimal accuracy. Table 1: Example constraints governing the placement of products in a warehouse. Number Products Constraint 1 shopping bags Must either be in the entrance-or counter section 2 whole milk, rolls/buns, tropical fruit Cannot be in the same section 3 white wine, specialty chocolate Must be in the same section 4yogurt Has to be in the cooler section 5 tropical fruit Cannot be in the cooler section frequently ordered products should be placed in easy to reach locations. Additionally, products that are often ordered together should be placed in near-proximity of each other. By doing so, we can systematically reduce the total travel time needed to collect orders. In more challenging order-picking scenarios, the governing product relationships may be unknown initially, and thus have to be learned over time by monitoring which products are ordered together. Additionally, nonrelated products may sporadically be ordered in conjunction, leading to stochastic order composition. This means that successful solution strategies must be able to operate in a stochastic environment. Furthermore, many order picking scenarios impose constraints when it comes to product placement. One could for instance require that a subset of the objects is located in a subset of the available locations, e.g., that all frozen objects should be in freezers, even when they are rarely purchased together. Other constraints could be that all products from a brand must be co-located on the request of the manufacturer, or that fragile objects must be placed in shelves close to the floor. To further exemplify the importance of dealing with constraints, several more are listed in Table 1 1 . Noting that each section of a warehouse can be represented as a CSO-EPP partition, and that products can be represented as CSO-EPP objects, we propose CSO-EPP as a model for order picking.In this paper, we present the first optimal solution scheme for SO-EPP and CSO-EP...

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Section: Related Workmentioning

confidence: 99%

A Bayesian network based solution scheme for the constrained Stochastic On-line Equi-Partitioning Problem

Glimsdal

Granmo

2018

Appl Intell

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“…For clustering, Gupta and Ranganathan [16,17] used a microeconomic game theoretic approach, which simultaneously optimizes two objectives, viz. compaction and equi-partitioning.…”

Section: Related Workmentioning

confidence: 99%

Cooperative privacy game: a novel strategy for preserving privacy in data publishing

Kumari

Chakravarthy²

2016

Hum. Cent. Comput. Inf. Sci.

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Achieving data privacy before publishing has been becoming an extreme concern of researchers, individuals and service providers. A novel methodology, Cooperative Privacy Game (CoPG), has been proposed to achieve data privacy in which Cooperative Game Theory is used to achieve the privacy and is named as Cooperative Privacy (CoP). The core idea of CoP is to play the best strategy for a player to preserve his privacy by himself which in turn contributes to preserving other players privacy. CoP considers each tuple as a player and tuples form coalitions as described in the procedure. The main objective of the CoP is to obtain individuals (player) privacy as a goal that is rationally interested in other individuals’ (players) privacy. CoP is formally defined in terms of Nash equilibria, i.e., all the players are in their best coalition, to achieve k-anonymity. The cooperative values of the each tuple are measured using the characteristic function of the CoPG to identify the coalitions. As the underlying game is convex; the algorithm is efficient and yields high quality coalition formation with respect to intensity and disperse. The efficiency of anonymization process is calculated using information loss metric. The variations of the information loss with the parameters $$\alpha$$ α (weight factor of nearness) and $$\beta$$ β (multiplicity) are analyzed and the obtained results are discussed.

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“…Freely available software, Action-Graph Games (AGG) [46,47], was used to run the simulation. In game theory, the traditional method for finding the NE is the simplicial subdivision algorithm [48], but Gupta and Ranganathan [49] suggest that the high level of complexity of this algorithm is largely governed by the quantity of strategies. A large quantity of strategies requires a longer period of time to find the NE.…”

Section: Existence Of Nementioning

confidence: 99%

“…A large quantity of strategies requires a longer period of time to find the NE. Thus the simplicial subdivision algorithm can only solve small-scale to medium-scale games [49]. To settle this issue, other authors [46,47] proposed a new algorithm, namely AGG, that aims to solve large-scale problems.…”

Section: Existence Of Nementioning

confidence: 99%

Game‐based cross‐layer channel allocation with SVC‐encoded multimedia streams in cognitive radio networks

Kuo

2012

Int J Network Mgmt

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The available unlicensed spectrum is increasingly being used by new wireless technologies, but past measurements show that the licensed spectrum is extremely underutilized. To address this issue, the IEEE 802.22 Working Group is developing a novel wireless air interface standard based on cognitive radios (CRs), i.e. IEEE 802.22 wireless regional area networks (WRANs). Moreover, over the last decade wireless multimedia applications have developed rapidly, raising significant concerns about the quality of service (QoS) of multimedia stream transmissions. In particular, the Joint Video Team (JVT) and ITU-T Video Coding Experts Group (VCEG) jointly proposed Scalable Video Coding (SVC) as the next-generation multimedia compression standard. However, the current IEEE 802.22 WRAN draft does not specify QoS mechanisms for SVC-encoded multimedia stream transmission in CR networks. To resolve this problem, we developed a cross-layer channel allocation algorithm (CLCAA) and a novel media access control (MAC) protocol to work with the algorithm. The CLCAA adapts to the characteristics of multimedia traffic and variations of wireless channels by determining the weighting of source-destination pair, which is determined by the deadlines of SVC-encoded multimedia streams, the queuing delay and channel conditions. The CLCAA then allocates transmission opportunities to source-destination pairs based on their weightings and game theory. We also conducted extensive simulations to demonstrate the efficiency of the CLCAA scheme. The simulation results show that the CLCAA scheme not only guarantees QoS for multimedia traffic but also achieves fairness across different streams.

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A Game Theoretic Approach for Simultaneous Compaction and Equipartitioning of Spatial Data Sets

Cited by 23 publications

References 34 publications

A Bayesian network based solution scheme for the constrained Stochastic On-line Equi-Partitioning Problem

A Bayesian network based solution scheme for the constrained Stochastic On-line Equi-Partitioning Problem

Cooperative privacy game: a novel strategy for preserving privacy in data publishing

Game‐based cross‐layer channel allocation with SVC‐encoded multimedia streams in cognitive radio networks

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