El “texto” y la “escritura”: La literatura como un juego muy serio

The design of an auction-based mechanism for the composite service selection problem requires answering the following two questions (Fig 4.1):

1. What does an auction-based approach mean? What are the elements that build up an auction model?

2. There are already a variety of auction models, standard and arbitrary, that have been applied in other domains such as transportation, communication networks, resource scheduling. How an auction-based mechanism in

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composite service selection is different to other existing auction-based mechanisms?

To answer the first question, we studied a variety of auction models designed for different domains, in addition to the auction theory literature. The study helped us to identify the auction design elements which were discussed in subsection 2.4.2 (Auction Design Elements). The elements are: the bidding language (the auction protocol), allocation rules (the winner determination problem) and the payment rule (pricing scheme).

Fig 4.1. Designing an auction-based mechanism for composite service selection

The second question needs to be answered based on the specific characteristics and technologies associated with web services and the current approaches for the web service composition and the composite service selection problems. These specific characteristics differentiate an auction model for composite service selection from other existing models. They help us establish the specific requirements of our problem domain to an auction- based solution. In other words, they are the “requirements of the composite service selection problem” to an auction-based solution. The requirements are presented here, categorized based on the design elements of an auction model.

91 4.3.1.1 Bidding Language

Req 1. The bidding language must support multi-attribute bidding.

An important aspect of web services is the non-functional properties or quality of service attributes (QoS). These attributes are the constraints exhibit over the service functionality (O’Sullivan et al. 2002). Two providers that offer the same service functionality may have different values for the QoS attributes of their services. These attributes model the competitive advantage that providers may have over each other (Medjahed and Atif, 2007). Therefore, the design of the bidding language needs to support more than the traditional price-only bids. In addition to the price, bids specify the values offered for other quality attributes such as response time, availability and reputation.

Req 2. The bidding language must support combinatorial bidding.

As we discussed before in subsections 1.2.1 and 3.3, an important issue in composite service selection is the need to consider the dependency between services constituent a composition. The providers need to be able to bid for a combination of services to fully express their preferences. Thus, the bidding language needs to support multi-item bidding. Moreover, each provider should be able to submit multiple bids and there is no restriction on the number of winning bids of a provider.

4.3.1.2 Allocation Rules

Req 3. The auction model is a procurement auction (one buyer, multiple sellers).

Our design is based on the reverse or procurement auction models rather than a direct auction. The reason is that in composite service selection, it is the service requester who requires a set of different services to achieve a specific goal and it is very likely that these services need to be procured from different providers. Therefore, if the auction is designed as a direct auction, with service providers as bid-takers and service requesters as bidders, the service requesters may need to attend different auctions to procure all their required web services and, more importantly, win in all these auctions to be able to create the composition. Even if they win in all the auctions except for one, the composite service cannot be realized and the service requester has to withdraw from all other auctions. In

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most auction settings, withdrawing from an auction after winning it is not allowed or incurs a withdrawing cost.

Therefore, the design to suit our problem domain is the procurement model where the service requester is the bid-taker (auctioneer) and the service providers bid to offer their services. The auction is considered successful only if there are web services available for all the tasks of the composite service satisfying the requesters’ preferences and constraints. Consequently, the requester can commit to the result of a successful auction without concern for unwanted costs.

Req 4. Free-disposal does not exist.

To create the composite service, the service requester needs all the tasks to be successfully auctioned and find service providers to provision them. In auction theory, this is referred to as an auction without free disposal: the auctioneer has to sell (procure) all the items and the bidders cannot accept more than what they had bid for (Sandholm et al. 2002). Lack of free disposal makes it difficult to apply approximation methods for reducing the complexity of the problem which will be discussed in subsection 7.2.1, the time limitations of the proposed approaches.

Req 5. The auction model is a combinatorial auction.

The proposed design is based on combinatorial auction models. As discussed in subsection 2.3.3 (Combinatorial Auctions), in this model multiple items can be auctioned simultaneously and bidders can bid for combination or bundle of items. This auction model is important when there are dependencies between the items under auction: either they complement each other or can be substitute for each other.

As discussed in subsections 1.2.1 and 3.3, web services constituting a composite service are dependent on each other based on factors such as the sequence of execution time, resources consumed, input/output message or data, and user-specified constraints. These dependencies can create complementarity effect among the services which makes it attractive for service providers to offer them in bundles. As an example of the complementarity effect, consider a service provider who is interested in providing services for a set of consecutive services exchanging data. By provisioning for these dependent services and bidding for them as in one bundle, the provider can internalize some of the costs of interface compatibility required for data exchange. This can decrease

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the cost of service provisioning. Consequently, the discount in the bundle’s price can result in the provider’s increased competitiveness in the market for web services. Moreover, they can offer better qualities for the bundled services by having more control over the execution environment of the adjacent services in the composition.

Req 6. The auction’s objective is a single attribute optimization problem, based on the price.

Req 7. Quality of service constraints need to be supported in the allocation rules.

The objective function of the auction is designed to include only the price, rather than all the quality of service attributes. The price-based design leads to a cost-minimization objective function rather than a utility-maximization one, as discussed in subsection 3.8.3. The service requester’s requirements on other quality of service attributes are considered as allocation constraints to be taken into account while searching for the optimal solution.

It seems natural to assume that service requesters are mainly concerned about quality attributes meeting some criteria. In other words, service requesters can easily state their desired level of quality in terms of their minimum expectation from the quality of the service, rather than having a clear and perfect utility function that specifies the weight of different quality attributes toward each other. As discussed in subsections 3.3 and 3.8.3, eliciting these weights has been one of the challenges for the utility-maximizing approaches to composite service selection. An objective function aiming at maximizing the utility of user regarding the different quality attributes usually forces the researchers to include unrealistic assumptions on the model; such as the weights being known for the requesters and the quality attributes not being correlated.

Therefore, it is easier and more realistic to assume that instead of specifying weights for quality attributes, the service requester is interested in specifying the concerns they have regarding the quality level; such as what is the maximum response time acceptable or minimum availability required. In such a setting, the multi-attribute characteristics of web services have been taken into account, without having to deal with complexities of a utility-maximization objective function.

At the same time, if a requester cares about quality and aims to maximize the quality at the cost of more expensive services, they can achieve this objective even with the cost-

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minimizing formulation by specifying very high expectations on the quality of service levels.

Req 8. The auction model is single-shot and not iterative.

Having an iterative auction for a composite service means that the providers have to submit their bids, wait for the result of the first round of the auction, based on the provided information about the results of the first round revise their bids and re-submit the bids. They need to continue to do so until the final round of the auction. However, in the auction for service selection, the items under auction are web services which mostly offer small, limited, functionality at a relatively low price. Therefore, the service providers would likely prefer to attend more auctions for different composite services rather than spending more time (for evaluating their bids and improving their strategic behavior based on the result of the previous round) in a multi-round auction for the same composite service.

4.3.1.3 Payment Rules

Req 9. The pricing scheme of the proposed model is similar to a first price auction; the winners receive the amount they have bid.

Auction designers use the pricing scheme to install properties such as incentive compatibility in the mechanism. As discussed in subsection 2.4.2.3, the well-known incentive compatible mechanism for multiple items is called the Vickrey Clark Grove (VCG) mechanism. The payment rule in a VCG mechanism is so that any winner’s payment is independent from their own valuations for the items (their bids).

However, the VCG mechanism has serious drawbacks that make its application rather impractical, including: making bidding very complex for bidders, needs the bidders to reveal many information about their valuations, possibility of very low revenue outcome, highly susceptible to collusion, and most importantly not being budget-balanced which means that the mechanism need to be subsidized from outside.

Therefore, although in theory it is possible to adopt the VCG payment to achieve an incentive-compatible mechanism, it will not suit practical applications. As a result, we decided to follow the first price auction model for the payment which, in our case, means that the service providers will be paid the amount they have bid for if they win the auction, and zero otherwise.

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As discussed in subsection 2.4.1.7, the impossibility theorem in mechanism design (Myerson & Satterthwaite 1983) states that it is impossible to design an exchange mechanism which is incentive compatible, (interim) individually rational and budget- balanced that achieves efficiency in equilibrium. In this regard, the first price payment rule leads to an auction model which has the individual rationality and budget- balanced properties, but not the economic efficiency and incentive compatibility.

Individual rationality and budget-balanced are both very important in designing a mechanism with practical application. An auction with individual rationality does not leave any of the participants worse off, than had they not participated in the mechanism. An auction which is budget-balanced does not need subsidy or fund from outside. We will discuss the limitation of the proposed approach on incentive compatibility and economic efficiency later in subsection 7.2.2.