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A Design and Implementation of Active NetworkSocket ProgrammingK.L. Eddie Law, Roy LeungThe Edward S. Rogers Sr. Department of Electrical and Computer EngineeringUniversity of TorontoToronto, Canadaeddie@, roy.leung@utoronto.caAbstract—The concept of programmable nodes and active networks introduces programmability into communication networks. Code and data can be sent and modified on their ways to destinations. Recently, various research groups have designed and implemented their own design platforms. Each design has its own benefits and drawbacks. Moreover, there exists an interoperability problem among platforms. As a result, we introduce a concept that is similar to the network socket programming. We intentionally establish a set of simple interfaces for programming active applications. This set of interfaces, known as Active Network Socket Programming (ANSP), will be working on top of all other execution environments in future. Therefore, the ANSP offers a concept that is similar to “write once, run everywhere.” It is an open programming model that active applications can work on all execution environments. It solves the heterogeneity within active networks. This is especially useful when active applications need to access all regions within a heterogeneous network to deploy special service at critical points or to monitor the performance of the entire networks. Instead of introducing a new platform, our approach provides a thin, transparent layer on top of existing environments that can be easily installed for all active applications.Keywords-active networks; application programming interface; active network socket programming;I. I NTRODUCTIONIn 1990, Clark and Tennenhouse [1] proposed a design framework for introducing new network protocols for the Internet. Since the publication of that position paper, active network design framework [2, 3, 10] has slowly taken shape in the late 1990s. The active network paradigm allows program code and data to be delivered simultaneously on the Internet. Moreover, they may get executed and modified on their ways to their destinations. At the moment, there is a global active network backbone, the ABone, for experiments on active networks. Apart from the immaturity of the executing platform, the primary hindrance on the deployment of active networks on the Internet is more on the commercially related issues. For example, a vendor may hesitate to allow network routers to run some unknown programs that may affect their expected routing performance. As a result, alternatives were proposed to allow active network concept to operate on the Internet, such as the application layer active networking (ALAN) project [4] from the European research community. In the ALAN project, there are active server systems located at different places in the networks and active applications are allowed to run in these servers at the application layer. Another potential approach from the network service provider is to offer active network service as the premium service class in the networks. This service class should provide the best Quality of Service (QoS), and allow the access of computing facility in routers. With this approach, the network service providers can create a new source of income.The research in active networks has been progressing steadily. Since active networks introduce programmability on the Internet, appropriate executing platforms for the active applications to execute should be established. These operating platforms are known as execution environments (EEs) and a few of them have been created, e.g., the Active Signaling Protocol (ASP) [12] and the Active Network Transport System (ANTS) [11]. Hence, different active applications can be implemented to test the active networking concept.With these EEs, some experiments have been carried out to examine the active network concept, for example, the mobile networks [5], web proxies [6], and multicast routers [7]. Active networks introduce a lot of program flexibility and extensibility in networks. Several research groups have proposed various designs of execution environments to offer network computation within routers. Their performance and potential benefits to existing infrastructure are being evaluated [8, 9]. Unfortunately, they seldom concern the interoperability problems when the active networks consist of multiple execution environments. For example, there are three EEs in ABone. Active applications written for one particular EE cannot be operated on other platforms. This introduces another problem of resources partitioning for different EEs to operate. Moreover, there are always some critical network applications that need to run under all network routers, such as collecting information and deploying service at critical points to monitor the networks.In this paper, a framework known as Active Network Socket Programming (ANSP) model is proposed to work with all EEs. It offers the following primary objectives.• One single programming interface is introduced for writing active applications.• Since ANSP offers the programming interface, the design of EE can be made independent of the ANSP.This enables a transparency in developing andenhancing future execution environments.• ANSP addresses the interoperability issues among different execution environments.• Through the design of ANSP, the pros and cons of different EEs will be gained. This may help design abetter EE with improved performance in future.The primary objective of the ANSP is to enable all active applications that are written in ANSP can operate in the ABone testbed . While the proposed ANSP framework is essential in unifying the network environments, we believe that the availability of different environments is beneficial in the development of a better execution environment in future. ANSP is not intended to replace all existing environments, but to enable the studies of new network services which are orthogonal to the designs of execution environments. Therefore, ANSP is designed to be a thin and transparent layer on top of all execution environments. Currently, its deployment relies on automatic code loading with the underlying environments. As a result, the deployment of ANSP at a router is optional and does not require any change to the execution environments.II. D ESIGN I SSUES ON ANSPThe ANSP unifies existing programming interfaces among all EEs. Conceptually, the design of ANSP is similar to the middleware design that offers proper translation mechanisms to different EEs. The provisioning of a unified interface is only one part of the whole ANSP platform. There are many other issues that need to be considered. Apart from translating a set of programming interfaces to other executable calls in different EEs, there are other design issues that should be covered, e.g., • a unified thread library handles thread operations regardless of the thread libraries used in the EEs;• a global soft-store allows information sharing among capsules that may execute over different environmentsat a given router;• a unified addressing scheme used across different environments; more importantly, a routing informationexchange mechanism should be designed across EEs toobtain a global view of the unified networks;• a programming model that should be independent to any programming languages in active networks;• and finally, a translation mechanism to hide the heterogeneity of capsule header structures.A. Heterogeneity in programming modelEach execution environment provides various abstractions for its services and resources in the form of program calls. The model consists of a set of well-defined components, each of them has its own programming interfaces. For the abstractions, capsule-based programming model [10] is the most popular design in active networks. It is used in ANTS [11] and ASP [12], and they are being supported in ABone. Although they are developed based on the same capsule model, their respective components and interfaces are different. Therefore, programs written in one EE cannot run in anther EE. The conceptual views of the programming models in ANTS and ASP are shown in Figure 1.There are three distinct components in ANTS: application, capsule, and execution environment. There exist user interfaces for the active applications at only the source and destination routers. Then the users can specify their customized actions to the networks. According to the program function, the applications send one or more capsules to carry out the operations. Both applications and capsules operate on top of an execution environment that exports an interface to its internal programming resources. Capsule executes its program at each router it has visited. When it arrives at its destination, the application at destination may either reply it with another capsule or presents this arrival event to the user. One drawback with ANTS is that it only allows “bootstrap” application.Figure 1. Programming Models in ASP and ANTS.In contrast, ASP does not limit its users to run “bootstrap” applications. Its program interfaces are different from ANTS, but there are also has three components in ASP: application client, environment, and AAContext. The application client can run on active or non-active host. It can start an active application by simply sending a request message to the EE. The client presents information to users and allows its users to trigger actions at a nearby active router. AAContext is the core of the network service and its specification is divided into two parts. One part specifies its actions at its source and destination routers. Its role is similar to that of the application in ANTS, except that it does not provide a direct interface with the user. The other part defines its actions when it runs inside the active networks and it is similar to the functional behaviors of a capsule in ANTS.In order to deal with the heterogeneity of these two models, ANSP needs to introduce a new set of programming interfaces and map its interfaces and execution model to those within the routers’ EEs.B. Unified Thread LibraryEach execution environment must ensure the isolation of instance executions, so they do not affect each other or accessThe authors appreciate the Nortel Institute for Telecommunications (NIT) at the University of Toronto to allow them to access the computing facilitiesothers’ information. There are various ways to enforce the access control. One simple way is to have one virtual machine for one instance of active applications. This relies on the security design in the virtual machines to isolate services. ANTS is one example that is using this method. Nevertheless, the use of multiple virtual machines requires relatively large amount of resources and may be inefficient in some cases. Therefore, certain environments, such as ASP, allow network services to run within a virtual machine but restrict the use of their services to a limited set of libraries in their packages. For instance, ASP provides its thread library to enforce access control. Because of the differences in these types of thread mechanism, ANSP devises a new thread library to allow uniform accesses to different thread mechanisms.C. Soft-StoreSoft-store allows capsule to insert and retrieve information at a router, thus allowing more than one capsules to exchange information within a network. However, problem arises when a network service can execute under different environments within a router. The problem occurs especially when a network service inserts its soft-store information in one environment and retrieves its data at a later time in another environment at the same router. Due to the fact that execution environments are not allowed to exchange information, the network service cannot retrieve its previous data. Therefore, our ANSP framework needs to take into account of this problem and provides soft-store mechanism that allows universal access of its data at each router.D. Global View of a Unified NetworkWhen an active application is written with ANSP, it can execute on different environment seamlessly. The previously smaller and partitioned networks based on different EEs can now be merging into one large active network. It is then necessary to advise the network topology across the networks. However, different execution environments have different addressing schemes and proprietary routing protocols. In order to merge these partitions together, ANSP must provide a new unified addressing scheme. This new scheme should be interpretable by any environments through appropriate translations with the ANSP. Upon defining the new addressing scheme, a new routing protocol should be designed to operate among environments to exchange topology information. This allows each environment in a network to have a complete view of its network topology.E. Language-Independent ModelExecution environment can be programmed in any programming language. One of the most commonly used languages is Java [13] due to its dynamic code loading capability. In fact, both ANTS and ASP are developed in Java. Nevertheless, the active network architecture shown in Figure 2 does not restrict the use of additional environments that are developed in other languages. For instance, the active network daemon, anted, in Abone provides a workspace to execute multiple execution environments within a router. PLAN, for example, is implemented in Ocaml that will be deployable on ABone in future. Although the current active network is designed to deploy multiple environments that can be in any programming languages, there lacks the tool to allow active applications to run seamlessly upon these environments. Hence, one of the issues that ANSP needs to address is to design a programming model that can work with different programming languages. Although our current prototype only considers ANTS and ASP in its design, PLAN will be the next target to address the programming language issue and to improve the design of ANSP.Figure 2. ANSP Framework Model.F. Heterogeneity of Capsule Header StructureThe structures of the capsule headers are different in different EEs. They carries capsule-related information, for example, the capsule types, sources and destinations. This information is important when certain decision needs to be made within its target environment. A unified model should allow its program code to be executed on different environments. However, the capsule header prevents different environments to interpret its information successfully. Therefore, ANSP should carry out appropriate translation to the header information before the target environment receives this capsule.III. ANSP P ROGRAMMING M ODELWe have outlined the design issues encountered with the ANSP. In the following, the design of the programming model in ANSP will be discussed. This proposed framework provides a set of unified programming interfaces that allows active applications to work on all execution environments. The framework is shown in Figure 2. It is composed of two layers integrated within the active network architecture. These two layers can operate independently without the other layer. The upper layer provides a unified programming model to active applications. The lower layer provides appropriate translation procedure to the ANSP applications when it is processed by different environments. This service is necessary because each environment has its own header definition.The ANSP framework provides a set of programming calls which are abstractions of ANSP services and resources. A capsule-based model is used for ANSP, and it is currently extended to map to other capsule-based models used in ANTSand ASP. The mapping possibility to other models remains as our future works. Hence, the mapping technique in ANSP allows any ANSP applications to access the same programming resources in different environments through a single set of interfaces. The mapping has to be done in a consistent and transparent manner. Therefore, the ANSP appears as an execution environment that provides a complete set of functionalities to active applications. While in fact, it is an overlay structure that makes use of the services provided from the underlying environments. In the following, the high-level functional descriptions of the ANSP model are described. Then, the implementations will be discussed. The ANSP programming model is based upon the interactions between four components: application client , application stub , capsule , and active service base.Figure 3. Information Flow with the ANSP.•Application Client : In a typical scenario, an active application requires some means to present information to its users, e.g., the state of the networks. A graphical user interface (GUI) is designed to operate with the application client if the ANSP runs on a non-active host.•Application Stub : When an application starts, it activates the application client to create a new instance of application stub at its near-by active node. There are two responsibilities for the application stub. One of them is to receive users’ instructions from the application client. Another one is to receive incoming capsules from networks and to perform appropriate actions. Typically, there are two types of actions, thatare, to reply or relay in capsules through the networks, or to notify the users regarding the incoming capsule. •Capsule : An active application may contain several capsule types. Each of them carries program code (also referred to as forwarding routine). Since the application defines a protocol to specify the interactions among capsules as well as the application stubs. Every capsule executes its forwarding routine at each router it visits along the path between the source and destination.•Active Service Base : An active service base is designed to export routers’ environments’ services and execute program calls from application stubs and capsules from different EEs. The base is loaded automatically at each router whenever a capsule arrives.The interactions among components within ANSP are shown in Figure 3. The designs of some key components in the ANSP will be discussed in the following subsections. A. Capsule (ANSPCapsule)ANSPXdr decode () ANSPXdr encode () int length ()Boolean execute ()New types of capsule are created by extending the abstract class ANSPCapsule . New extensions are required to define their own forwarding routines as well as their serialization procedures. These methods are indicated below:The execution of a capsule in ANSP is listed below. It is similar to the process in ANTS.1. A capsule is in serial binary representation before it issent to the network. When an active router receives a byte sequence, it invokes decode() to convert the sequence into a capsule. 2. The router invokes the forwarding routine of thecapsule, execute(). 3. When the capsule has finished its job and forwardsitself to its next hop by calling send(), this call implicitly invokes encode() to convert the capsule into a new serial byte representation. length() isused inside the call of encode() to determine the length of the resulting byte sequence. ANSP provides a XDR library called ANSPXdr to ease the jobs of encoding and decoding.B. Active Service Base (ANSPBase)In an active node, the Active Service Base provides a unified interface to export the available resources in EEs for the rest of the ANSP components. The services may include thread management, node query, and soft-store operation, as shown in Table 1.TABLE I. ACTIVE SERVICE BASE FUNCTION CALLSFunction Definition Descriptionboolean send (Capsule, Address) Transmit a capsule towards its destination using the routing table of theunderlying environment.ANSPAddress getLocalHost () Return address of the local host as an ANSPAddress structure. This isuseful when a capsule wants to check its current location.boolean isLocal (ANSPAddress) Return true if its input argument matches the local host’s address andreturn false otherwise.createThread () Create a new thread that is a class ofANSPThreadInterface (discussed later in Section VIA “Unified Thread Abstraction”).putSStore (key, Object) Object getSStore (key) removeSStore (key)The soft-store operations are provided by putSStore(), getSSTore(), and removeSStore(), and they put, retrieve, and remove data respectively. forName (PathName) Supported in ANSP to retrieve a classobject corresponding to the given path name in its argument. This code retrieval may rely on the code loading mechanism in the environment whennecessary.C. Application Client (ANSPClient)boolean start (args[])boolean start (args[],runningEEs) boolean start (args[],startClient)boolean start (args[],startClient, runningEE)Application Client is an interface between users and the nearby active source router. It does the following responsibilities.1. Code registration: It may be necessary to specify thelocation and name of the application code in some execution environments, e.g., ANTS. 2. Application initialization: It includes selecting anexecution environment to execute the application among those are available at the source router. Each active application can create an application client instance by extending the abstract class, ANSPClient . The extension inherits a method, start(), to automatically handle both the registration and initialization processes. All overloaded versions of start() accept a list of arguments, args , that are passed to the application stub during its initialization. An optional argument called runningEEs allows an application client to select a particular set of environment variables, specified by a list of standardized numerical environment ID, the ANEP ID, to perform code registration. If this argument is not specified, the default setting can only include ANTS and ASP. D. Application Stub (ANSPApplication)receive (ANSPCapsule)Application stubs reside at the source and destination routers to initialize the ANSP application after the application clients complete the initialization and registration processes. It is responsible for receiving and serving capsules from the networks as well as actions requested from the clients. A new instance is created by extending the application client abstract class, ANSPApplication . This extension includes the definition of a handling routine called receive(), which is invoked when a stub receives a new capsule.IV. ANSP E XAMPLE : T RACE -R OUTEA testbed has been created to verify the design correctnessof ANSP in heterogeneous environments. There are three types of router setting on this testbed:1. Router that contains ANTS and a ANSP daemonrunning on behalf of ASP; 2. Router that contains ASP and a ANSP daemon thatruns on behalf of ANTS; 3. Router that contains both ASP and ANTS.The prototype is written in Java [11] with a traceroute testing program. The program records the execution environments of all intermediate routers that it has visited between the source and destination. It also measures the RTT between them. Figure 4 shows the GUI from the application client, and it finds three execution environments along the path: ASP, ANTS, and ASP. The execution sequence of the traceroute program is shown in Figure 5.Figure 4. The GUI for the TRACEROUTE Program.The TraceCapsule program code is created byextending the ANSPCapsule abstract class. When execute() starts, it checks the Boolean value of returning to determine if it is returning from the destination. It is set to true if TraceCapsule is traveling back to the source router; otherwise it is false . When traveling towards the destination, TraceCapsule keeps track of the environments and addresses of the routers it has visited in two arrays, path and trace , respectively. When it arrives at a new router, it calls addHop() to append the router address and its environment to these two arrays. When it finally arrives at the destination, it sets returning to false and forwards itself back to the source by calling send().When it returns to source, it invokes deliverToApp() to deliver itself to the application stub that has been running at the source. TraceCapsule carries information in its data field through the networks by executing encode() and decode(), which encapsulates and de-capsulates its data using External Data Representation (XDR) respectively. The syntax of ANSP XDR follows the syntax of XDR library from ANTS. length() in TraceCapsule returns the data length, or it can be calculated by using the primitive types in the XDRlibrary.Figure 5. Flow of the TRACEROUTE Capsules.V. C ONCLUSIONSIn this paper, we present a new unified layered architecture for active networks. The new model is known as Active Network Socket Programming (ANSP). It allows each active application to be written once and run on multiple environments in active networks. Our experiments successfully verify the design of ANSP architecture, and it has been successfully deployed to work harmoniously with ANTS and ASP without making any changes to their architectures. In fact, the unified programming interface layer is light-weighted and can be dynamically deployable upon request.R EFERENCES[1] D.D. Clark, D.L. Tennenhouse, “Architectural Considerations for a NewGeneration of Protocols,” in Proc. ACM Sigcomm’90, pp.200-208, 1990. [2] D. Tennenhouse, J. M. Smith, W. D. Sicoskie, D. J. Wetherall, and G. J.Minden, “A survey of active network research,” IEEE Communications Magazine , pp. 80-86, Jan 1997.[3] D. Wetherall, U. Legedza, and J. Guttag, “Introducing new internetservices: Why and how,” IEEE Network Magazine, July/August 1998. [4] M. Fry, A. Ghosh, “Application Layer Active Networking,” in ComputerNetworks , Vol.31, No.7, pp.655-667, 1999.[5] K. W. Chin, “An Investigation into The Application of Active Networksto Mobile Computing Environments”, Curtin University of Technology, March 2000.[6] S. Bhattacharjee, K. L. Calvert, and E. W. Zegura, “Self OrganizingWide-Area Network Caches”, Proc. IEEE INFOCOM ’98, San Francisco, CA, 29 March-2 April 1998.[7] L. H. Leman, S. J. Garland, and D. L. Tennenhouse, “Active ReliableMulticast”, Proc. IEEE INFOCOM ’98, San Francisco, CA, 29 March-2 April 1998.[8] D. Descasper, G. Parulkar, B. Plattner, “A Scalable, High PerformanceActive Network Node”, In IEEE Network, January/February 1999.[9] E. L. Nygren, S. J. Garland, and M. F. Kaashoek, “PAN: a high-performance active network node supporting multiple mobile code system”, In the Proceedings of the 2nd IEEE Conference on Open Architectures and Network Programming (OpenArch ’99), March 1999. [10] D. L. Tennenhouse, and D. J. Wetherall. “Towards an Active NetworkArchitecture”, In Proceeding of Multimedia Computing and Networking , January 1996.[11] D. J. Wetherall, J. V. Guttag, D. L. Tennenhouse, “ANTS: A toolkit forBuilding and Dynamically Deploying Network Protocols”, Open Architectures and Network Programming, 1998 IEEE , 1998 , Page(s): 117 –129.[12] B. Braden, A. Cerpa, T. Faber, B. Lindell, G. Phillips, and J. Kann.“Introduction to the ASP Execution Environment”: /active-signal/ARP/index.html .[13] “The java language: A white paper,” Tech. Rep., Sun Microsystems,1998.。
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INTRODUCTION
The Yong Jong Grand Bridge is located at the west coast of Korea, and was constructed to connect the new international airport at Yong Jong Island, Inchon, and the mainland. The bridge is 4.4 km long and is composed of three different bridge types—a suspension bridge (550 m), a truss bridge (2,250 m), and steel box bridges. The Grand Bridge (Gil and Cho 1998) has double decks; it will carry six highway lanes on the upper deck, and four highway lanes and dual tracks of a railway on the lower deck. The approach truss bridges are double-deck, Warren truss type bridges. The truss bridges are three-span continuous with a length of 125 m for each span. The width of the truss bridge is 36.1 m.
shoe and dead load of the neighboring truss bridges. The selfanchored suspension bridge typically has limited space for the main cable anchorage, which is located at the stiffening truss, so the air spinning method, which can contain more wires per strand than the parallel wire strand method, is employed to erect the main cables.
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The first dam for which there are reliable records was build on the Nile River sometime before 4000 B.C.It was used to divert the Nile and provide a site for the ancient city of Memphis.The oldest dam still in use is the Almanza Dam in Spain,which was constructed in the sixteenth ceentury.With the passage of time, materials and construction have improved, making possible the erection of such large dams as the Nurek Dam, which is being constructed in the U.S.S.R. On the vaksh River near the border of Afghanistan. This dam will be 1017ft(333m)high, of earth and rock fill. The failure of a dam may cause serious loss of life and property; consequently, the design and maintenance of dams are commonly under government surveillance. In the United States over 30000 dams are under the control of state authorities. The 1972 Federal Dam Safety Act (PL92-367) requires periodic inspections of dams by qualified experts. The failure of the Teton Dam in Idaho in June 1976 added to the concern for dam safety in the United States.1.Type of DamsDams are classified on the basis of the type and materials of construction, as gravity, arch, buttress, and earth. The first three types are usually constructed of concrete. A gravity dam depends on its own weight for stability and it straight in plan although sometimes slightly curved. Arch dams transmit most of the horizontal thrust of the water behind them to the abutments by arch action and have thinner cross sections than comparable gravity dams. Arch dams can be used only in narrow canyons where the walls are capable of withstanding the thrust produced by the arch action. The simplest of the many types of buttresses. Earth dams are embankments of rock or earth with provision for controlling seepage by means of an impermeable core or upstream blanket. More than one type of dam may be included in a single structure. Curved dams may combine both gravity and arch action to achieve stability. Long dams often have a concrete river section containning spollway and sluice gates and earth or rock-fill wing dams for the remainder of their length.The selection of the best type of dam for a given site is a problem in both engineering feasibility and cost. Feasibility is governed by topography, geology and climate. For example, because concrete spalls when subjected to alternate freezing and thawing, arch and buttress dams With thin concrete section are sometimes avoided in areas subject to extreme cold. The relative cost of the various type of dams depends mainly on the availability of construction materials near the site and the accessibility of transportation facilities. Dams are sometimes built in stages with the second or later stages constructed a decade or longer after the stage.The height of a dam is defined as the difference in elevation between the roadway, or spillway crest, and the lowest part of the excayated foundation. However, figures quoted for heights of dams are oftendetemined in other ways. Frequently the height is taken net height above the old riverbed.。
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Bid Compensation Decision Model for Projectswith Costly Bid PreparationS.Ping Ho,A.M.ASCE 1Abstract:For projects with high bid preparation cost,it is often suggested that the owner should consider paying bid compensation to the most highly ranked unsuccessful bidders to stimulate extra effort or inputs in bid preparation.Whereas the underlying idea of using bid compensation is intuitively sound,there is no theoretical basis or empirical evidence for such suggestion.Because costly bid preparation often implies a larger project scale,the issue of bid compensation strategy is important to practitioners and an interest of study.This paper aims to study the impacts of bid compensation and to develop appropriate bid compensation strategies.Game theory is applied to analyze the behavioral dynamics between competing bidders and project owners.A bid compensation model based on game theoretic analysis is developed in this study.The model provides equilibrium solutions under bid compensation,quantitative formula,and quali-tative implications for the formation of bid compensation strategies.DOI:10.1061/(ASCE )0733-9364(2005)131:2(151)CE Database subject headings:Bids;Project management;Contracts;Decision making;Design/build;Build/Operate/Transfer;Construction industry .IntroductionAn often seen suggestion in practice for projects with high bid preparation cost is that the owner should consider paying bid compensation,also called a stipend or honorarium,to the unsuc-cessful bidders.For example,according to the Design–build Manual of Practice Document Number 201by Design–Build In-stitute of America (DBIA )(1996a ),it is suggested that that “the owner should consider paying a stipend or honorarium to the unsuccessful proposers”because “excessive submittal require-ments without some compensation is abusive to the design–build industry and discourages quality teams from participating.”In another publication by DBIA (1995),it is also stated that “it is strongly recommended that honorariums be offered to the unsuc-cessful proposers”and that “the provision of reasonable compen-sation will encourage the more sought-after design–build teams to apply and,if short listed,to make an extra effort in the prepara-tion of their proposal.”Whereas bid preparation costs depend on project scale,delivery method,and other factors,the cost of pre-paring a proposal is often relatively high in some particular project delivery schemes,such as design–build or build–operate–transfer (BOT )contracting.Plus,costly bid preparation often im-plying a large project scale,the issue of bid compensation strat-egy should be important to practitioners and of great interest of study.Existing research on the procurement process in constructionhas addressed the selection of projects that are appropriate for certain project delivery methods (Molenaar and Songer 1998;Molenaar and Gransberg 2001),the design–build project procure-ment processes (Songer et al.1994;Gransberg and Senadheera 1999;Palaneeswaran and Kumaraswamy 2000),and the BOT project procurement process (United Nations Industrial Develop-ment Organization 1996).However,the bid compensation strat-egy for projects with a relatively high bid preparation cost has not been studied.Among the issues over the bidder’s response to the owner’s procurement or bid compensation strategy,it is in own-er’s interest to understand how the owner can stimulate high-quality inputs or extra effort from the bidder during bid prepara-tion.Whereas the argument for using bid compensation is intuitively sound,there is no theoretical basis or empirical evi-dence for such an argument.Therefore,it is crucial to study under what conditions the bid compensation is effective,and how much compensation is adequate with respect to different bidding situa-tions.This paper focuses on theoretically studying the impacts of bid compensation and tries to develop appropriate compensation strategies for projects with a costly bid preparation.Game theory will be applied to analyze the behavioral dynamics between com-peting bidders.Based on the game theoretic analysis and numeric trials,a bid compensation model is developed.The model pro-vides a quantitative framework,as well as qualitative implica-tions,on bid compensation strategies.Research Methodology:Game TheoryGame theory can be defined as “the study of mathematical models of conflict and cooperation between intelligent rational decision-makers”(Myerson 1991).Among economic theories,game theory has been successfully applied to many important issues such as negotiations,finance,and imperfect markets.Game theory has also been applied to construction management in two areas.Ho (2001)applied game theory to analyze the information asymme-try problem during the procurement of a BOT project and its1Assistant Professor,Dept.of Civil Engineering,National Taiwan Univ.,Taipei 10617,Taiwan.E-mail:spingho@.twNote.Discussion open until July 1,2005.Separate discussions must be submitted for individual papers.To extend the closing date by one month,a written request must be filed with the ASCE Managing Editor.The manuscript for this paper was submitted for review and possible publication on March 5,2003;approved on March 1,2004.This paper is part of the Journal of Construction Engineering and Management ,V ol.131,No.2,February 1,2005.©ASCE,ISSN 0733-9364/2005/2-151–159/$25.00.D o w n l o a d e d f r o m a s c e l i b r a r y .o r g b y N A N J I N G U N I VE R S I T Y OF o n 01/06/14. C o p y r i g h t A S C E . F o r p e r s o n a l u s e o n l y ; a l l r i g h t s r e s e r v e d .implication in project financing and government policy.Ho and Liu (2004)develop a game theoretic model for analyzing the behavioral dynamics of builders and owners in construction claims.In competitive bidding,the strategic interactions among competing bidders and that between bidders and owners are com-mon,and thus game theory is a natural tool to analyze the prob-lem of concern.A well-known example of a game is the “prisoner’s dilemma”shown in Fig.1.Two suspects are arrested and held in separate cells.If both of them confess,then they will be sentenced to jail for 6years.If neither confesses,each will be sentenced for only 1year.However,if one of them confesses and the other does not,then the honest one will be rewarded by being released (in jail for 0year )and the other will be punished for 9years in jail.Note that in each cell,the first number represents player No.1’s payoff and the second one represents player No.2’s.The prisoner’s dilemma is called a “static game,”in which they act simultaneously;i.e.,each player does not know the other player’s decision before the player makes the decision.If the payoff matrix shown in Fig.1is known to all players,then the payoff matrix is a “common knowledge”to all players and this game is called a game of “complete information.”Note that the players of a game are assumed to be rational;i.e.,to maximize their payoffs.To answer what each prisoner will play/behave in this game,we will introduce the concept of “Nash equilibrium ,”one of the most important concepts in game theory.Nash equilibrium is a set of actions that will be chosen by each player.In a Nash equilib-rium,each player’s strategy should be the best response to the other player’s strategy,and no player wants to deviate from the equilibrium solution.Thus,the equilibrium or solution is “strate-gically stable”or “self-enforcing”(Gibbons 1992).Conversely,a nonequilibrium solution is not stable since at least one of the players can be better off by deviating from the nonequilibrium solution.In the prisoner’s dilemma,only the (confess,confess )solution where both players choose to confess,satisfies the stabil-ity test or requirement of Nash equilibrium.Note that although the (not confess,not confess )solution seems better off for both players compared to Nash equilibrium;however,this solution is unstable since either player can obtain extra benefit by deviating from this solution.Interested readers can refer to Gibbons (1992),Fudenberg and Tirole (1992),and Myerson (1991).Bid Compensation ModelIn this section,the bid compensation model is developed on the basis of game theoretic analysis.The model could help the ownerform bid compensation strategies under various competition situ-ations and project characteristics.Illustrative examples with nu-merical results are given when necessary to show how the model can be used in various scenarios.Assumptions and Model SetupTo perform a game theoretic study,it is critical to make necessary simplifications so that one can focus on the issues of concern and obtain insightful results.Then,the setup of a model will follow.The assumptions made in this model are summarized as follows.Note that these assumptions can be relaxed in future studies for more general purposes.1.Average bidders:The bidders are equally good,in terms oftheir technical and managerial capabilities.Since the design–build and BOT focus on quality issues,the prequalification process imposed during procurement reduces the variation of the quality of bidders.As a result,it is not unreasonable to make the “average bidders”assumption.plete information:If all players consider each other tobe an average bidder as suggested in the first assumption,it is natural to assume that the payoffs of each player in each potential solution are known to all players.3.Bid compensation for the second best bidder:Since DBIA’s(1996b )manual,document number 103,suggests that “the stipend is paid only to the most highly ranked unsuccessful offerors to prevent proposals being submitted simply to ob-tain a stipend,”we shall assume that the bid compensation will be offered to the second best bidder.4.Two levels of efforts:It is assumed that there are two levelsof efforts in preparing a proposal,high and average,denoted by H and A ,respectively.The effort A is defined as the level of effort that does not incur extra cost to improve quality.Contrarily,the effort H is defined as the level of effort that will incur extra cost,denoted as E ,to improve the quality of a proposal,where the improvement is detectable by an effec-tive proposal evaluation system.Typically,the standard of quality would be transformed to the evaluation criteria and their respective weights specified in the Request for Pro-posal.5.Fixed amount of bid compensation,S :The fixed amount canbe expressed by a certain percentage of the average profit,denoted as P ,assumed during the procurement by an average bidder.6.Absorption of extra cost,E :For convenience,it is assumedthat E will not be included in the bid price so that the high effort bidder will win the contract under the price–quality competition,such as best-value approach.This assumption simplifies the tradeoff between quality improvement and bid price increase.Two-Bidder GameIn this game,there are only two qualified bidders.The possible payoffs for each bidder in the game are shown in a normal form in Fig.2.If both bidders choose “H ,”denoted by ͑H ,H ͒,both bidders will have a 50%probability of wining the contract,and at the same time,have another 50%probability of losing the con-tract but being rewarded with the bid compensation,S .As a re-sult,the expected payoffs for the bidders in ͑H ,H ͒solution are ͑S /2+P /2−E ,S /2+P /2−E ͒.Note that the computation of the expected payoff is based on the assumption of the average bidder.Similarly,if the bidders choose ͑A ,A ͒,the expected payoffswillFig.1.Prisoner’s dilemmaD o w n l o a d e d f r o m a s c e l i b r a r y .o r g b y N A N J I N G U N I VE R S I T Y OF o n 01/06/14. C o p y r i g h t A S C E . F o r p e r s o n a l u s e o n l y ; a l l r i g h t s r e s e r v e d .be ͑S /2+P /2,S /2+P /2͒.If the bidders choose ͑H ,A ͒,bidder No.1will have a 100%probability of winning the contract,and thus the expected payoffs are ͑P −E ,S ͒.Similarly,if the bidders choose ͑A ,H ͒,the expected payoffs will be ͑S ,P −E ͒.Payoffs of an n -bidder game can be obtained by the same reasoning.Nash EquilibriumSince the payoffs in each equilibrium are expressed as functions of S ,P ,and E ,instead of a particular number,the model will focus on the conditions for each possible Nash equilibrium of the game.Here,the approach to solving for Nash equilibrium is to find conditions that ensure the stability or self-enforcing require-ment of Nash equilibrium.This technique will be applied throughout this paper.First,check the payoffs of ͑H ,H ͒solution.For bidder No.1or 2not to deviate from this solution,we must haveS /2+P /2−E ϾS →S ϽP −2E͑1͒Therefore,condition (1)guarantees ͑H ,H ͒to be a Nash equilib-rium.Second,check the payoffs of ͑A ,A ͒solution.For bidder No.1or 2not to deviate from ͑A ,A ͒,condition (2)must be satisfiedS /2+P /2ϾP −E →S ϾP −2E͑2͒Thus,condition (2)guarantees ͑A ,A ͒to be a Nash equilibrium.Note that the condition “S =P −2E ”will be ignored since the con-dition can become (1)or (2)by adding or subtracting an infinitely small positive number.Thus,since S must satisfy either condition (1)or condition (2),either ͑H ,H ͒or ͑A ,A ͒must be a unique Nash equilibrium.Third,check the payoffs of ͑H ,A ͒solution.For bid-der No.1not to deviate from H to A ,we must have P −E ϾS /2+P /2;i.e.,S ϽP −2E .For bidder No.2not to deviate from A to H ,we must have S ϾS /2+P /2−E ;i.e.,S ϾP −2E .Since S cannot be greater than and less than P −2E at the same time,͑H ,A ͒solution cannot exist.Similarly,͑A ,H ͒solution cannot exist either.This also confirms the previous conclusion that either ͑H ,H ͒or ͑A ,A ͒must be a unique Nash equilibrium.Impacts of Bid CompensationBid compensation is designed to serve as an incentive to induce bidders to make high effort.Therefore,the concerns of bid com-pensation strategy should focus on whether S can induce high effort and how effective it is.According to the equilibrium solu-tions,the bid compensation decision should depend on the mag-nitude of P −2E or the relative magnitude of E compared to P .If E is relatively small such that P Ͼ2E ,then P −2E will be positive and condition (1)will be satisfied even when S =0.This means that bid compensation is not an incentive for high effort when the extra cost of high effort is relatively low.Moreover,surprisingly,S can be damaging when S is high enough such that S ϾP −2E .On the other hand,if E is relatively large so that P −2E is negative,then condition (2)will always be satisfied since S can-not be negative.In this case,͑A ,A ͒will be a unique Nash equi-librium.In other words,when E is relatively large,it is not in the bidder’s interest to incur extra cost for improving the quality of proposal,and therefore,S cannot provide any incentives for high effort.To summarize,when E is relatively low,it is in the bidder’s interest to make high effort even if there is no bid compensation.When E is relatively high,the bidder will be better off by making average effort.In other words,bid compensation cannot promote extra effort in a two-bidder game,and ironically,bid compensa-tion may discourage high effort if the compensation is too much.Thus,in the two-bidder procurement,the owner should not use bid compensation as an incentive to induce high effort.Three-Bidder GameNash EquilibriumFig.3shows all the combinations of actions and their respective payoffs in a three-bidder game.Similar to the two-bidder game,here the Nash equilibrium can be solved by ensuring the stability of the solution.For equilibrium ͑H ,H ,H ͒,condition (3)must be satisfied for stability requirementS /3+P /3−E Ͼ0→S Ͼ3E −P͑3͒For equilibrium ͑A ,A ,A ͒,condition (4)must be satisfied so that no one has any incentives to choose HS /3+P /3ϾP −E →S Ͼ2P −3E͑4͒In a three-bidder game,it is possible that S will satisfy conditions (3)and (4)at the same time.This is different from the two-bidder game,where S can only satisfy either condition (1)or (2).Thus,there will be two pure strategy Nash equilibria when S satisfies conditions (3)and (4).However,since the payoff of ͑A ,A ,A ͒,S /3+P /3,is greater than the payoff of ͑H ,H ,H ͒,S /3+P /3−E ,for all bidders,the bidder will choose ͑A ,A ,A ͒eventually,pro-vided that a consensus between bidders of making effort A can be reached.The process of reaching such consensus is called “cheap talk,”where the agreement is beneficial to all players,and no player will want to deviate from such an agreement.In the design–build or BOT procurement,it is reasonable to believe that cheap talk can occur.Therefore,as long as condition (4)is satis-fied,͑A ,A ,A ͒will be a unique Nash equilibrium.An important implication is that the cheap talk condition must not be satisfied for any equilibrium solution other than ͑A ,A ,A ͒.In other words,condition (5)must be satisfied for all equilibrium solution except ͑A ,A ,A͒Fig.2.Two-biddergameFig.3.Three-bidder gameD o w n l o a d e d f r o m a s c e l i b r a r y .o r g b y N A N J I N G U N I VE R S I T Y OF o n 01/06/14. C o p y r i g h t A S C E . F o r p e r s o n a l u s e o n l y ; a l l r i g h t s r e s e r v e d .S Ͻ2P −3E ͑5͒Following this result,for ͑H ,H ,H ͒to be unique,conditions (3)and (5)must be satisfied;i.e.,we must have3E −P ϽS Ͻ2P −3E͑6͒Note that by definition S is a non-negative number;thus,if one cannot find a non-negative number to satisfy the equilibrium con-dition,then the respective equilibrium does not exist and the equi-librium condition will be marked as “N/A”in the illustrative fig-ures and tables.Next,check the solution where two bidders make high efforts and one bidder makes average effort,e.g.,͑H ,H ,A ͒.The ex-pected payoffs for ͑H ,H ,A ͒are ͑S /2+P /2−E ,S /2+P /2−E ,0͒.For ͑H ,H ,A ͒to be a Nash equilibrium,S /3+P /3−E Ͻ0must be satisfied so that the bidder with average effort will not deviate from A to H ,S /2+P /2−E ϾS /2must be satisfied so that the bidder with high effort will not deviate from H to A ,and condi-tion (5)must be satisfied as argued previously.The three condi-tions can be rewritten asS Ͻmin ͓3E −P ,2P −3E ͔andP −2E Ͼ0͑7͒Note that because of the average bidder assumption,if ͑H ,H ,A ͒is a Nash equilibrium,then ͑H ,A ,H ͒and ͑A ,H ,H ͒will also be the Nash equilibria.The three Nash equilibria will constitute a so-called mixed strategy Nash equilibrium,denoted by 2H +1A ,where each bidder randomizes actions between H and A with certain probabilities.The concept of mixed strategy Nash equilib-rium shall be explained in more detail in next section.Similarly,we can obtain the requirements for solution 1H +2A ,condition (5)and S /2+P /2−E ϽS /2must be satisfied.The requirements can be reorganized asS Ͻ2P −3EandP −2E Ͻ0͑8͒Note that the conflicting relationship between “P −2E Ͼ0”in condition (7)and “P −2E Ͻ0”in condition (8)seems to show that the two types of Nash equilibria are exclusive.Nevertheless,the only difference between 2H +1A and 1H +2A is that the bidder in 2H +1A equilibrium has a higher probability of playing H ,whereas the bidder in 1H +2A also mixes actions H and A but with lower probability of playing H .From this perspective,the difference between 2H +1A and 1H +2A is not very distinctive.In other words,one should not consider,for example,2H +1A ,to be two bidders playing H and one bidder playing A ;instead,one should consider each bidder to be playing H with higher probabil-ity.Similarly,1H +2A means that the bidder has a lower probabil-ity of playing H ,compared to 2H +1A .Illustrative Example:Effectiveness of Bid Compensation The equilibrium conditions for a three-bidder game is numerically illustrated and shown in Table 1,where P is arbitrarily assumed as 10%for numerical computation purposes and E varies to rep-resent different costs for higher efforts.The “*”in Table 1indi-cates that the zero compensation is the best strategy;i.e.,bid compensation is ineffective in terms of stimulating extra effort.According to the numerical results,Table 1shows that bid com-pensation can promote higher effort only when E is within the range of P /3ϽE ϽP /2,where zero compensation is not neces-sarily the best strategy.The question is that whether it is benefi-cial to the owner by incurring the cost of bid compensation when P /3ϽE ϽP /2.The answer to this question lies in the concept and definition of the mix strategy Nash equilibrium,2H +1A ,as explained previously.Since 2H +1A indicates that each bidderwill play H with significantly higher probability,2H +1A may already be good enough,knowing that we only need one bidder out of three to actually play H .We shall elaborate on this concept later in a more general setting.As a result,if the 2H +1A equilib-rium is good enough,the use of bid compensation in a three-bidder game will not be recommended.Four-Bidder Game and n-Bidder GameNash Equilibrium of Four-Bidder GameThe equilibrium of the four-bidder procurement can also be ob-tained.As the number of bidders increases,the number of poten-tial equilibria increases as well.Due to the length limitation,we shall only show the major equilibria and their conditions,which are derived following the same technique applied previously.The condition for pure strategy equilibrium 4H ,is4E −P ϽS Ͻ3P −4E͑9͒The condition for another pure strategy equilibrium,4A ,isS Ͼ3P −4E͑10͒Other potential equilibria are mainly mixed strategies,such as 3H +1A ,2H +2A ,and 1H +3A ,where the numeric number asso-ciated with H or A represents the number of bidders with effort H or A in a equilibrium.The condition for the 3H +1A equilibrium is3E −P ϽS Ͻmin ͓4E −P ,3P −4E ͔͑11͒For the 2H +2A equilibrium the condition is6E −3P ϽS Ͻmin ͓3E −P ,3P −4E ͔͑12͒The condition for the 1H +3A equilibrium isS Ͻmin ͓6E −3P ,3P −4E ͔͑13͒Illustrative Example of Four-Bidder GameTable 2numerically illustrates the impacts of bid compensation on the four-bidder procurement under different relative magni-tudes of E .When E is very small,bid compensation is not needed for promoting effort H .However,when E grows gradually,bid compensation becomes more effective.As E grows to a larger magnitude,greater than P /2,the 4H equilibrium would become impossible,no matter how large S is.In fact,if S is too large,bidders will be encouraged to take effort A .When E is extremely large,e.g.,E Ͼ0.6P ,the best strategy is to set S =0.The “*”in Table 2also indicates the cases that bid compensation is ineffec-Table pensation Impacts on a Three-Bidder GameEquilibriumE ;P =10%3H 2H +1A 1H +2A 3A E ϽP /3e.g.,E =2%S Ͻ14%*N/A N/N 14%ϽS P /3ϽE ϽP /2e.g.,E =4%2%ϽS Ͻ8%S Ͻ2%N/A 8%ϽS P /2ϽE Ͻ͑2/3͒P e.g.,E =5.5%N/AN/AS Ͻ3.5%*3.5%ϽS͑2/3͒P ϽEe.g.,E =7%N/A N/A N/A Always*Note:*denotes that zero compensation is the best strategy;and N/A =the respective equilibrium does not exist.D o w n l o a d e d f r o m a s c e l i b r a r y .o r g b y N A N J I N G U N I VE R S I T Y OF o n 01/06/14. C o p y r i g h t A S C E . F o r p e r s o n a l u s e o n l y ; a l l r i g h t s r e s e r v e d .tive.To conclude,in a four-bidder procurement,bid compensation is not effective when E is relatively small or large.Again,similar to the three-bidder game,when bid compensation becomes more effective,it does not mean that offering bid compensation is the best strategy,since more variables need to be considered.Further analysis shall be performed later.Nash Equilibrium of n -Bidder GameIt is desirable to generalize our model to the n -bidder game,al-though only very limited qualified bidders will be involved in most design–build or BOT procurements,since for other project delivery methods it is possible to have many bidders.Interested readers can follow the numerical illustrations for three-and four-bidder games to obtain the numerical solutions of n -bidder game.Here,only analytical equilibrium solutions will be solved.For “nA ”to be the Nash equilibrium,we must have P −E ϽS /n +P /n for bidder A not to deviate.In other words,condition (14)must be satisfiedS Ͼ͑n −1͒P −nE͑14͒Note that condition (14)can be rewritten as S Ͼn ͑P −E ͒−P ,which implies that it is not likely for nA to be the Nash equilib-rium when there are many bidders,unless E is very close to or larger than P .Similar to previous analysis,for “nH ”to be the equilibrium,we must have S /n +P /n −E Ͼ0for stability requirement,and condition (15)for excluding the possibility of cheap talk or nA equilibrium.The condition for the nH equilibrium can be reorga-nized as condition (16).S Ͻ͑n −1͒P −nE ͑15͒nE −P ϽS Ͻ͑n −1͒P −nE͑16͒Note that if E ϽP /n ,condition (16)will always be satisfied and nH will be a unique equilibrium even when S =0.In other words,nH will not be the Nash equilibrium when there are many bidders,unless E is extremely small,i.e.,E ϽP /n .For “aH +͑n −a ͒A ,where 2Ͻa Ͻn ”to be the equilibrium so-lution,we must have S /a +P /a −E Ͼ0for bidder H not to devi-ate,S /͑a +1͒+P /͑a +1͒−E Ͻ0for bidder A not to deviate,and condition (15).These requirements can be rewritten asaE −P ϽS Ͻmin ͓͑a +1͒E −P ,͑n −1͒P −nE ͔͑17͒Similarly,for “2H +͑n −2͒A ,”the stability requirements for bidder H and A are S /͑n −1͒ϽS /2+P /2−E and S /3+P /3−E Ͻ0,re-spectively,and thus the equilibrium condition can be written as ͓͑n −1͒/͑n −3͔͒͑2E −P ͒ϽS Ͻmin ͓3E −P ,͑n −1͒P −nE ͔͑18͒For the “1H +͑n −1͒A ”equilibrium,we must haveS Ͻmin ͕͓͑n −1͒/͑n −3͔͒͑2E −P ͒,͑n −1͒P −nE ͖͑19͒An interesting question is:“What conditions would warrant that the only possible equilibrium of the game is either “1H +͑n −1͒A ”or nA ,no matter how large S is?”A logical response to the question is:when equilibria “aH +͑n −a ͒A ,where a Ͼ2”and equilibrium 2H +͑n −2͒A are not possible solutions.Thus,a suf-ficient condition here is that for any S Ͼ͓͑n −1͒/͑n −3͔͒͑2E −P ͒,the “S Ͻ͑n −1͒P −nE ”is not satisfied.This can be guaranteed if we have͑n −1͒P −nE Ͻ͓͑n −1͒/͑n −3͔͒͑2E −P ͒→E Ͼ͓͑n −1͒/͑n +1͔͒P͑20͒Conditions (19)and (20)show that when E is greater than ͓͑n −1͒/͑n +1͔͒P ,the only possible equilibrium of the game is either 1H +͑n −1͒A or nA ,no matter how large S is.Two important practical implications can be drawn from this finding.First,when n is small in a design–build contract,it is not unusual that E will be greater than ͓͑n −1͒/͑n +1͔͒P ,and in that case,bid compensa-tion cannot help to promote higher effort.For example,for a three-bidder procurement,bid compensation will not be effective when E is greater than ͑2/4͒P .Second,when the number of bidders increases,bid compensation will become more effective since it will be more unlikely that E is greater than ͓͑n −1͒/͑n +1͔͒P .The two implications confirm the previous analyses of two-,three-,and four-bidder game.After the game equilibria and the effective range of bid compensation have been solved,the next important task is to develop the bid compensation strategy with respect to various procurement situations.Table pensation Impacts on a Four-Bidder GameEquilibriumE ;P =10%4H 3H +1A 2H +2A 1H +3A 4A E ϽP /4e.g.,E =2%S Ͻ22%*N/A N/A N/A S Ͼ22%P /4ϽE ϽP /3e.g.,E =3%2%ϽS Ͻ18%S Ͻ2%N/A N/A S Ͼ18%P /3ϽE ϽP /2e.g.,E =4%6%ϽS Ͻ14%2%ϽS Ͻ6%S Ͻ2%N/A S Ͼ14%P /2ϽE Ͻ͑3/5͒P e.g.,E =5.5%N/A 6.5%ϽS Ͻ8%3%ϽS Ͻ6.5%S Ͻ3%S Ͼ8%͑3/5͒P ϽE Ͻ͑3/4͒P e.g.,E =6.5%N/AN/AN/AS Ͻ4%*S Ͼ4%͑3/4͒P ϽEe.g.,E =8%N/A N/A N/A N/AAlways*Note:*denotes that zero compensation is the best strategy;and N/A=respective equilibrium does not exist.D o w n l o a d e d f r o m a s c e l i b r a r y .o r g b y N A N J I N G U N I VE R S I T Y OF o n 01/06/14. C o p y r i g h t A S C E . F o r p e r s o n a l u s e o n l y ; a l l r i g h t s r e s e r v e d .。
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