Price dynamics of vertically differentiated information markets

Sairamesh, Jakka; Kephart, Jeffrey O.

doi:10.1145/288994.289000

Cited by 46 publications

(38 citation statements)

References 1 publication

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“…a highly priced service has a lower utility than a low priced service of the same quality. As in [24], a user's behaviour is modelled by the following utility function:…”

Section: Demand Model With Respect To Price and Qualitymentioning

confidence: 99%

Demand management for telecommunications services

Zachariadis

Barria

2007

Computer Networks

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In this paper we develop a novel method of controlling the demand in a multi-class, QoS-enabled network, using pricing and resource allocation for income maximisation. We first present a solution to the problem of calculating the optimal prices and QoS for a single link using a limiting regime approximation, which reduces the associated computational burden. A heuristic algorithm is then proposed that improves the limiting regime solution, achieving better results for links with small capacity. We further extend this approach to a multi-link network, where a distributed iterative algorithm is developed based on the solution of the single link model. Results from small and medium size networks show that, even when the assumptions we used do not hold, our approach yields results very close to the optimal ones (0.17% to 2.95% difference), which are computed by exhaustively searching in the decision space. Moreover, the calculation time using the proposed approach is approximately 1.5 minutes for problems which took more than 240 minutes to solve using exhaustive search.

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“…a highly priced service has a lower utility than a low priced service of the same quality. As in [24], a user's behaviour is modelled by the following utility function:…”

Section: Demand Model With Respect To Price and Qualitymentioning

confidence: 99%

Demand management for telecommunications services

Zachariadis

Barria

2007

Computer Networks

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“…Resource owners will determine p k j (l) based on a pricing strategy so as to maximize their profits and resource utilization. For the completeness of the paper, we assume that each owner agrees to follow the derivative-following pricing strategy [14]. For the details of this strategy, we refer reader to [14].…”

Section: Computational Economymentioning

confidence: 99%

“…For the completeness of the paper, we assume that each owner agrees to follow the derivative-following pricing strategy [14]. For the details of this strategy, we refer reader to [14]. Owners can update their prices in the GMD only before a new scheduling event and they are not allowed to alter the prices until the next scheduling event.…”

Section: Computational Economymentioning

confidence: 99%

Scheduling Independent Tasks with QoS Requirements in Grid Computing with Time-Varying Resource Prices

Doğan

Özgüner

2002

Grid Computing — GRID 2002

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Abstract. This paper considers the problem of scheduling a set of independent tasks with multiple QoS requirements, which may include timeliness, reliability, security, version, and priority, in a Grid computing system in which resource prices can vary with time during scheduling time intervals. This problem is referred to as the QoS-based scheduling problem with time-varying resource prices. In order to solve this problem, a static scheduling algorithm (QSMTS VP) is developed. The simulation studies carried out show that QSMTS VP is capable of meeting diverse QoS requirements of many users simultaneously and that QSMTS VP can react to the dynamics of the market. Thus, QSMTS VP is a promising heuristic that can be deployed in a computational market.

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“…In these models, buyers are assisted by automated purchasing algorithms that continually monitor prices and product attributes and purchase an item from the vendor that best satisfies the individual buyer's utility function. Several distinct variants of this model have been explored: a market for a simple commodity (in which some buyers perform only a limited search among the set of sellers) (14,15); a vertically differentiated market (in which the good may be offered at different levels of quality by different sellers) (16); and information filtering (17,18) and information bundling models (19) (in which the seller sets both the price and the parameters that determine the product's configuration).…”

Section: Emergent Behavior Of Economic Software Agentsmentioning

confidence: 99%

Software agents and the route to the information economy

Kephart

2002

Proc. Natl. Acad. Sci. U.S.A.

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Humans are on the verge of losing their status as the sole economic species on the planet. In private laboratories and in the Internet laboratory, researchers and developers are creating a variety of autonomous economically motivated software agents endowed with algorithms for maximizing profit or utility. Many economic software agents will function as miniature businesses, purchasing information inputs from other agents, combining and refining them into information goods and services, and selling them to humans or other agents. Their mutual interactions will form the information economy: a complex economic web of information goods and services that will adapt to the ever-changing needs of people and agents. The information economy will be the largest multiagent system ever conceived and an integral part of the world's economy. I discuss a possible route toward this vision, beginning with present-day Internet trends suggesting that agents will charge one another for information goods and services. Then, to establish that agents can be competent price setters, I describe some laboratory experiments pitting software bidding agents against human bidders. The agents' superior performance suggests they will be used on a broad scale, which in turn suggests that interactions among agents will become frequent and significant. How will this affect macroscopic economic behavior? I describe some interesting phenomena that my colleagues and I have observed in simulations of large populations of automated buyers and sellers, such as price war cycles. I conclude by discussing fundamental scientific challenges that remain to be addressed as we journey toward the information economy.

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Price dynamics of vertically differentiated information markets

Cited by 46 publications

References 1 publication

Demand management for telecommunications services

Demand management for telecommunications services

Scheduling Independent Tasks with QoS Requirements in Grid Computing with Time-Varying Resource Prices

Software agents and the route to the information economy

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