Browsing by Author "Gdowski, Robert"

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Combinatorial Recurrent Multi-Unit Auctions for Fog Services
(2016-01-01)
Safianowska, Maria Barbara
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Gdowski, Robert
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Huang, ChingYao
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
An emerging Fog Computing paradigm aims at reducing overall latency and end-to-end data transfer costs between IoT devices and analytic entity as in comparison to purely Cloud based solutions. In the near future, Fog services will be offered on virtual marketplaces by Fog Node owners. To facilitate the exchange in such volatile markets, we devise a recurrent, multi-unit, combinatorial auction with bidder drop and resource waste control and a two-step winner determination algorithm. Proposed solution extends on Participation Incentive Optimal Recurring Auction (PI-ORA) algorithm, which separately solves bidder drop problem for single-unit, non combinatorial auction, to include the case of multi-unit combinatorial auction which is necessary for Fog service markets. The results show stability and efficiency of the proposed algorithm.
Opportunities and Challenges of Joint Edge and Fog Orchestration
(2018-01-01)
Cominardi, Luca
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Abdullaziz, Osamah Ibrahiem
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Antevski, Kiril
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Chundrigar, Shahzoob Bilal
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Gdowski, Robert
Pushing contents, applications, and network functions closer to end users is necessary to cope with the huge data volume and low latency required in future 5G networks. Edge and fog frameworks have emerged recently to address this challenge. Whilst the edge framework was more infrastructure-focused and more mobile operator-oriented, the fog was more pervasive and included any node (stationary or mobile), including terminal devices. This article analyzes the opportunities and challenges to integrate, federate, and jointly orchestrate the edge and fog resources into a unified framework.
Preventing market collapse in auctions for perishable Internet of Things resources
(2017-11-29)
Safianowska, Maria B.
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Gdowski, Robert
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Huang, ChingYao
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電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
We are entering the era of digital business moments where autonomous things will buy and sell services from each other in order to make people's life easier. They will also negotiate in order to achieve the best price for their services which will result in Internet of Things auctions. Such auctions will be combinatorial and recurrent. Recurrent auctions pose a problem of bidder drop which leads to market collapse. Moreover, in Internet of Things, bidders will employ different strategies according to their pattern of consuming resources. We describe two bidding strategies which may lead to market collapse or very low revenue: opportunistic and periodic bidding. We devise two algorithms: revenue maximizing auction and highest bid lock auction, analyze their performance under these two bidding strategies, and compare them to traditional combinatorial auction. We find out that the revenue maximizing auction prevents market collapse under opportunistic bidding while highest bid lock auction provides the highest revenue under both strategies.
Revenue Maximizing Auction for Perishable IoT Resources
(2016-01-01)
Safianowska, Maria Barbara
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Gdowski, Robert
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Huang, ChingYao
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
In near future autonomous things will trade services on IoT marketplaces. However, in the resulting recurrent combinatorial auctions, the bidder drop causes the market collapse in a low competition scenario. Adding fairness can prevent this, however the resulting revenue is not optimal. We show that revenue may be improved above fairness solution by alternating winners only within minimum set of strongest bidders. We introduce and compare two algorithms: Proportional Fair Auction and Revenue Maximizing Auction. The second algorithm performs the best in both high and low competition scenario, making it best suited to IoT when revenue maximization is a goal.