Network service provisioning in uwb open mobile ... - IEEE Xplore

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 20, NO. 9, DECEMBER 2002

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Network Service Provisioning in UWB Open Mobile Access Networks Dario Di Sorte, Student Member, IEEE, Mauro Femminella, Student Member, IEEE, Gianluca Reali, Associate Member, IEEE, and Sven Zeisberg, Member, IEEE

Abstract—An innovative architecture to access information transport resources under short-term market conditions is presented. Ultra-wideband (UWB) technology in the centralized wireless access domain is believed to minimize the intrinsic performance limitations of the radio link and to provide flexible access in a very wide range of data rates of over 100 Mb/s, even in a strong multipath environment. The decoupling of user, infrastructure, and service provision in an open mobile access network (OMAN) is proposed to overcome current limitations of radio-based networks. A solution for the joint management of quality-of-service and mobility in the UWB domain is proposed, under the assumption of a resource management compliant with Differentiated Services framework. Moreover, a model for the “commoditization” of the network service is introduced. The commodity is identified as the transfer of information units between two end points of the network, measured by a function of the so-called “virtual delay,” that summarizes the parameters characterizing the performance of the transfer service. A description is given of this model, together with the definition of a pricing law to charge improved Internet protocol-based services. Such concepts are central in the end-to-end service set-up. Index Terms—Business model, Internet protocol (IP), mobility, open mobile access network (OMAN), per domain behavior, pricing, ultra-wideband (UWB).

I. INTRODUCTION

T

HE background of this paper is the WHYLESS.COM project, cofunded by the European Union. The network scenario of the WHYLESS.COM project consists of the open mobile access network (OMAN) paradigm. This paradigm is not another mobile radio access network, but rather a new platform for efficient information transport in an economic sense, supporting modern, small scale, electronic business and evolutionary growth. An important aspect is the decoupling of the user, the information transport resources, and the content provision services. WHYLESS.COM aims at combining advanced and scalable radio transmission technology and independent service provisioning, that is to say, ultra-wideband (UWB) air interface and instant resource brokerage of Internet protocol (IP) network domains, respectively. The UWB technology enables large data rates to be supported over

Manuscript received December 5, 2001, revised July 23, 2002. This work was supported in part by the European Union under the IST project WHYLESS.COM. D. Di Sorte, M. Femminella, and G. Reali are with the Department of Electronic Engineering and Information, University of Perugia, 06125 Perugia, Italy (e-mail: [email protected]; [email protected]; [email protected]). S. Zeisberg is with the Communications Laboratory of the Dresden University of Technology, 01062 Dresden, Germany (e-mail: [email protected]). Digital Object Identifier 10.1109/JSAC.2002.805625

short distances at relatively low frequencies without allocating dedicated spectral resources, and is, therefore, selected as the radio access technology for the OMAN. UWB radios can easily adapt the bit rate in a wide range, according to the terminal location, propagation conditions and service requirements, by simply changing some transmission parameters [1]–[3]. This allows great flexibility in data transmission without changing the air interface by means of reconfiguration, as in traditional, software-defined radio technology. Further advantages of UWB include ultra-low mean transmission power, enhanced penetration capability in indoor environments, inherent high precision location in the order of centimeters, low probability of detection, and minimized hardware complexity of the radio front end. From the service point of view, the set of software-controllable parameters is the real innovation introduced by the UWB technique, since this enables highly resilient and scalable networks to be created, which are more flexible than the present radio and cellular networks. These features have motivated the research on physical and MAC layers, carried out in the WHYLESS.COM project, to define appropriate air interface solutions that will exploit the large capabilities promised by UWB [1]–[3]. These aspects are extremely attractive for mobile operators and service providers, who foresee new business opportunities. The WHYLESS.COM vision offers the possibility of building up services based on heterogeneous traffic, that requires specific quality-of-service (QoS) in a novel network scenario consisting of independent IP domains, where, due to the application of UWB, the radio access link is not necessarily the bottleneck. We consider administratively independent IP domains, each of which is able to provide an external characterization of the traffic handled between any pair of input–output ports of the domain boundary, in terms of QoS parameters. We have identified the network commodity as the transfer of information units between network end points. We characterize this transfer by using a new parameter, the total virtual delay , that in our approach summarizes the QoS requirements of the transfer service [4], [5] and gives a standard measure of the level of the service. As regards the commodity measure and its price, we present a usage-based tariff model to charge added value network services on a per-call basis [4]. We consider a differentiated services (DiffServ) [6] compliant approach to guarantee QoS. We present the definition of a perdomain behavior (PDB) [7] in a UWB environment and provide a possible external characterization, which takes into account the peculiarities of the radio segment, in order to integrate it into the WHYLESS.COM business model. For this purpose, we point out some scalability issues and propose a solution based on

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the GRIP (Gauge&Gate Reservation with Independent Probing) protocol [8], [9], able to support micromobility. To complete the framework, given the differentiation of network services, it is necessary to define an appropriate pricing strategy, based on the actually used and/or reserved network resources (usage-based pricing), as stated in [10]. We stress that customers are willing to pay an added per-usage charge on a per-call basis, beyond the flat access charge, in order to both improve the QoS on demand (QoS charge) for particular applications, and to receive a privileged network service during congestion [11]. A survey of per-time and/or per-volume tariff models, that have recently been proposed, can be found in [12]. Given the complexity of the specification and delivery of particular services, customers might feel it inconvenient to have to control all aspects related to the final charge they will pay. For this reason, they may prefer to consult specialists before making a choice. For this purpose, we introduce brokering activities, both at application service level, performed by information brokers (IBs), and at network level, performed by resource brokers (RBs). The paper is organized as follows. In Section II, we provide a description of UWB peculiarities and its integration into the OMAN paradigm. In Section III, we present the network and business model. We introduce the entities and their mutual relations for the provision of application services for customers. In Section IV, we define a PDB, compliant with a domain using UWB access technology. The pricing strategy has a central role in establishing services. For this reason, in Section V, we propose the pricing law and tariff model. All the concepts introduced are shown jointly in Section VI, step by step, from the moment customer service is requested to the moment it is actually provided. Some concluding remarks are given in Section VII. II. OMAN IMPLEMENTATION THROUGH UWB The concept of an OMAN in the sense of WHYLESS.COM requires short-term trading of wireless and wired information transport resources. Whereas in the case of wired resources ownership is clear and is achieved by large, long-term investments, this is not necessarily the case in the wireless part. The OMAN concept foresees an on-demand short-term acquirement of spectral usage by the radio operator for a certain local region and for a certain mean transmission power. The operator does not own the spectrum, but will share it with any other operator in that local region. Unsynchronized, UWB, impulse radio technology will be applied in the air interface, in order to avoid any synchronism requirement between operators in the air interface (impossible in pure time-division multiple-access (TDMA) schemes) and to allow for the possibility to combine all available resources to get ultra-high, maximal data rates with a single radio front end (impossible for pure finite-division multiple-access (FDMA) schemes). UWB modulation is a special code-division multiple-access (CDMA) radio transmission principle forming the basis of the air interface, which is supposed to largely contribute to the feasibility of the OMAN. It provides the wireless PHYsical layer (PHY), which transports information over the air between radio access points

and mobile terminals connecting them to the network. The aim of the PHY is to fulfil the wide range of air interface requirements, which are derived from end user service contract for the individual user, as well as from the interference requirements in the given domain, and which are dynamically implemented by the local, radio resource manager by changing parameters in the air interface. The adoption of UWB technology is a key point in order to achieve the goal of an OMAN providing extremely high flexibility for a broad range of data rates and classes of services. Even if the UWB technology has been used in the United States and Russia for military applications, the basic principles of this technology have been proven to perform well in the civilian world [13]. A UWB system is defined as an intentional radio emission having a fractional bandwidth greater than, or equal to 20%, where the fractional bandwidth is the 10 db-bandwidth divided by the center frequency. UWB here means impulse radio based UWB. There are extremely short impulses constituting an ultra-wide bandwidth signal with ultra-low power spectral density. They are transmitted with very low duty cycles and follow link specific time-hopping (TH) codes. No time synchronization between different radio access points is necessary and all links use the same frequency band providing a low system overhead. Multiple access, as well as full duplex, can be achieved using the pure code division technique. Only the cross-correlation properties of the TH codes used determine mutual interference of different channels and link directions. This enables easy radio network evolution and growth without sophisticated cell cite planning algorithms, which would be based on radio propagation and frequency reuse patterns. It provides the basis for the scalability of the OMAN in terms of radio access points. UWB transmission is allowed to coexist with narrowband signals in their originally dedicated frequency bands. This way, interference from such narrowband signals will decrease the UWB system performance. The level of interference within an UWB system is a function of pulse shape, pulse position, and/or pulse amplitude modulation, pulse duration, data rates and, therefore, pulse repetition and temporal spreading, together with TH codes. The UWB transmission parameters can be chosen and changed “on the fly” in order to meet current system requirements or the aim of the requested radio service without necessarily increasing the interference level in a given area. Dynamic adjustment of the PHY parameters, e.g., processing gain, TH sequence, duty cycle and temporal pulse shape, as well as code rate and decoding complexity underline the flexibility inherent to UWB. Thus, an extremely adaptive PHY can be designed to fulfill the wide range of requirements. The described flexibility is not at all influenced by the fact that UWB can avoid any intermediate frequency processing. The total number of users in a high density, UWB system depends on duty cycle, target bit rate, and impulse shape, as shown in [1]. A maximum number of users can be supported for a certain target data rate and transmission quality. This number cannot be increased by increasing transmission power of individual users, due to the increase of interference at the same time, as seen in Fig. 1, calculated according to the rules outlined in [3]. This figure applies for correlation receivers under ideal

DI SORTE, et al.: NETWORK SERVICE PROVISIONING IN UWB OPEN MOBILE ACCESS NETWORKS

Fig. 3. Fig. 1. Number of users versus power increase of each user for different target bit error rates for uncoded transmission and 384 Kb/s single user data rate.

Fig. 2. Network model.

power control and optimum time synchronization conditions in a dispersionless radio channel (additive white Gaussian noise (AWGN) and multiuser interference only). Thus, the curves can be seen as an upper limit, as they are optimistic compared with real operating environments. In addition to the inherent interference from the UWB system, there is interference from many other existing communications and other electrical systems, as well as thermal noise, synchronization offset, and strong multipath propagation. If high data rates and/or low power operation are aimed at, e.g., for a class of terminals, a powerful channel coding scheme is advised as in any other communications system. III. NETWORK AND BUSINESS MODELS Fig. 2 shows the reference network architecture. It consists of hierarchically structured network service providers (NSPs), which provide network users with the network infrastructure. Access providers offer customers wired or wireless (hot spot) physical connectivity and make use of the service of backbone

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Reference environment.

NSPs. Different administrative domains are peer and economically independent. We consider heterogeneous peer domains, hierarchically related from the networking point of view. Moreover, we assume that each domain can differentiate network services to adequately support future, value-added services. The techniques used to support QoS inside domains are selected by NSPs arbitrarily. Apart from end users (customers) and NSPs, the separation of the network infrastructure from the other entities providing services in the network suggests that other entities exploiting network infrastructure should be included in the reference business model (Fig. 3): application service providers (ASPs), providing customers with application services and IP connectivity. According to our model, customers may contact an ASP in order to receive a specific service. When a request can be fulfilled, the contacted ASP can provide the requesting customer with the requested service and charge him according to their agreement. This is the highest abstraction level to describe business interactions between end user and ASP. If necessary, end users may consult an IB, which acts as mediator between customer requests and offers by ASPs, and provides information about which ASPs can provide the desired service and their “history,” that is the level of satisfaction of previous customers. After consulting the IB, the end user makes the explicit service request to the ASP selected. This entity could be very important when end users access the network in unfamiliar areas, for instance, outside their office/home. Many brokers can be expected to be needed in operation. Clearly, it is not realistic to ask customers to specify service by using technical parameters, such as traffic and QoS parameters. Typically, an end user can provide only qualitative information regarding the requested service level and ASPs must infer the appropriate QoS parameters from a qualitative description. As regards the technical aspects involved in the information transmission, the situation is further complicated. In general, we consider a number of independent domains, each one owned by an NSP and managed by a network resource manager (NRM). Each NRM is in charge of guaranteeing a set of edge-to-edge services to flows passing through the relevant domain. This means that a lot of decisions must be taken to maximize the QoS perceived by end users and their satisfaction, given their

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willingness to pay. For this reason, another player is necessary: the RB. It represents the interface between ASP requests and NSP offers, as regards network service support. On request issued by ASPs, it has the task of providing the cheapest path with an adequate QoS level, by selecting a number of paths through different administrative domains to deliver a service for a specific end user. The RB has the task of controlling the end-to-end path, the end-to-end QoS, and the end-to-end price. In this case too, several brokers might be needed in operation. All entities interacting in the framework must be trusted by a clearing house (CH), the role of which is not central in the exposition of this paper. In order to provide a service, two types of contracts must be stipulated: the first between the end user and the ASP concerning the application service and the second for network support among the ASP with each NRM involved in the end-to-end information transfer. In our model, we make the following assumptions: 1) NSPs charge a flat-rate tariff to provide customers with network connection access. In this case, end users receive a best effort service to support basic application services, which do not strictly need QoS guarantees to be satisfactorily supported. An instance of basic services is the set of procedures to enter the network and to become active, to request a service from an ASP, or to consult an IB web site. It is important to remark that, in this case, no brokerage activity by the RB concerning the network service is necessary; 2) for added value services NSPs charge an additional per-call usage fare, depending on the network support level; 3) the end-to-end price of the network support for performance guaranteed services is given by the sum of the single tariffs charged by the domains involved in the end-to-end transfer; and 4) ASPs are responsible for negotiating with NSPs the suitable transfer service to deliver a specific application service to end users and to pay for such a service. In addition, ASPs charge customers for the complete service, according to tariffs which are easily understandable by customers, such as per-time charges or fixed fees. IV. PER DOMAIN BEHAVIOR IN AN UWB DOMAIN In this section, we show a functional model of the NRM in a domain using UWB as access technology. For this purpose, the NRM task is twofold: 1) to provide customers with an admission control able to support mobility; and 2) to provide bandwidth estimation for a given service profile between a couple of ingress/egress points. Whereas this first function is needed in order to provide QoS guarantees to the traffic of admitted users, and refers to precise and continually updated information, the second kind of knowledge typically refers to macro-information (e.g., aggregate quantities and large time scales), unable to follow quick variations of traffic loads and related performance. Thus, we think it expedient to adopt a common approach in order to be able to cope with both of them. We assume that the service differentiation is based on the DiffServ approach [6]. Moreover, as suggested in [10], [14], we assume that an admission control function is implemented on top of the DiffServ. For this purpose, we have proposed a stateless, scalable admission control named GRIP [8]. In addition, we have demonstrated that this approach can support both QoS guarantees and mobility at

Fig. 4. Successful probing phase for wireless access.

IP level [9], also in environments characterized by high mobility (i.e., management of micro/picocells). Since details about GRIP can be found in referenced papers, in the following, we report only its main concepts and emphasize the procedure dedicated to estimate resource availability. A. Admission Control Function GRIP combines simple endpoint-driven admission control logic, traffic measurement, and DiffServ packet management within a network domain. It classifies packets by their function: probes, feedback, and data packets, on the basis of the DiffServ code point (DSCP) label included in the IP packet header [6]. The core algorithm uses the binary information, reception/lack-of-reception, of the probe to infer the network status at the network edge, whereas the decision to accept/reject a call is left to the source node. The probe travels across a number of heterogeneous routers and reaches the destination node only if no congestion is encountered along its path (Fig. 4). The notion of congestion is local: each core router within a GRIP-aware domain is in charge of determining whether a new call can be locally admitted. Regardless of the specific mechanism employed (in [8], we have proposed a measurement-based approach, based on the theoretical result presented in [15]), the only node capability that GRIP requires is to transform the internal accept/reject decision into the forwarding/dropping of the probe. Only if a feedback packet is received in return from the destination within a suitable time, is the connection accepted: in this case, control is given back to the user application, which can start transmitting information packets, labeled as data. The traffic is modeled by the fluid approximation and regulated by dual leaky buckets (DLBs) [15], characterizing the output process by means of the peak rate ( ), the sustainable ). rate ( ), and the token bucket size ( Source and destination of probes are the access/edge routers selected by the RB, as shown in Fig. 4. In addition, the access router has to check resource availability on the wireless link before injecting the probe packet into the wired part of the domain. As shown in Fig. 1, in the case of UWB technology, a maximum


Fig. 5. Local handoff and relevant probing message(s) for an uplink connection.

number of users with a given transmission quality can be evaluated. Since UWB is tolerant toward propagation problems, this information should be very stable, thus the accept/reject decision can be made on the wireless medium by monitoring the overall number of users sharing the channel and comparing it with the allowed maximum value. The GRIP operation is suitable for supporting mobility in conjunction with mobile IP. In this architecture, we envisage only local handoffs, since a global handoff would involve two or more domains and would require an interaction with other entities, due to contractual constraints (see Section III). To support terminal mobility at IP layer, we refer to the classical micro-mobility architecture [16]. Moreover, we assume that handoffs are triggered by the mobile node (MN). Upon handoff, the new access router sends a probe toward the destination, on behalf of the MN, with the aim of testing resource availability on the new edge-to-edge path. Obviously, probing for network resources must be limited to the local route, that is between the new access router and the first crossover node belonging to both old and new path. Whereas details depend on the capabilities of the specific micromobility protocol adopted, the algorithm works well with each of them, in line with the OMAN concept of flexibility provided by UWB. Without loss of generality, we can consider the case in which such crossover node is simply the egress edge router of the domain, which is required to implement the capabilities of a local mobility gateway (LMG, [9]). The LMG role due to handoffs is limited to relaying feedback packets (Fig. 5), thus, it does not need to be aware of the higher level flows. Hence, LMG is not required to have any additional state beyond those needed by the mobility management architecture. In short, the target of the GRIP algorithm in this architecture is to check whether the resources advertised to the RB are still available, before the NRM stipulates any contract. Thus, any disrupting phenomena, such as those due to impulse load or handoffs, are avoided. If the probe phase fails, the service request is denied and the contract cannot be established. B. Measuring Bandwidth Availability A further step is to use the module used in the preceding section to define services in a domain (per-domain behavior in

Fig. 6.

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GRIP router operation.

the DiffServ jargon, [7]), by exploiting the intrinsic GRIP capabilities of conveying network status to the edges of the domain. It is worth noting that such services can be built by the NRM with a suitable configuration of router parameters (buffer, per class capacity and GRIP parameters, such as the threshold on flows number, ). Thus, predetermined minimum performance levels (in terms of packet loss probability and delay) to different traffic classes can be enforced between any pair of ingress/egress routers. The basic idea is to use a small number of bits in the DSCP field to mark dedicated packets, named discovery probe packets (DPPs), to communicate bandwidth availability for a given traffic class at the domain boundary. We encode a level of available bandwidth by means of a small number (e.g., two or three) of bits in the DSCP field. Depending on the value of the other bits in the DSCP field, the DPP in each router in the path between two edges is dispatched to the appropriate queue, as shown in Fig. 6. To determine the th bit of the selected set, we use the th DPP, thus, the number of the DPP to send is equal to the cardinality of the set of bits. This DPP exchange occurs for each service class between any pair of edge routers able to transport that kind of traffic, with the same mechanism used by GRIP in the admission control logic: the reception of a feedback relevant to a given DPP implies that the available bandwidth is greater than the value associated to this DPP. The value of the most significant bit of the set is determined by the first DPP, whereas the others are set to zero. If the relevant feedback packet is received at the source edge router before a time-out, it is set to one, otherwise to zero. According to the result of the first estimation, the most significant bit of the next DPP is determined; in turn, it is used to determine the second bit and so on. , representing At the end of the process, a binary number, along the the minimum amount of available bandwidth considered path, is generated. This mechanism is similar to the banyan algorithm used in the well-known Batcher-banyan ATM switch. Clearly, if the number of bits used is large, the estimation of the available bandwidth is accurate, but, on the other hand, the number of service classes implemented in the domain is small (the DSCP is a 6-bits field), whereas the resource overhead and the time needed to complete the procedure is high. Therefore, a tradeoff between types of services and precision of the estimation process is needed. However, two issues remain open: i) how

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to encode the available bandwidth in binary format and ii) the process time scale. As regards the former, some preliminary considerations apply. Since different queues in different routers are probably characterized by different buffer and capacity sizes, a percentage value is not suitable, thus, we need to deal with absolute values. Moreover, since we assume that GRIP is running in each router, an estimation of the queue status (i.e., number of ) is available, by means of the flows currently handled, estimation provided by measurements [8] or information from protocol layers under IP. This status information can be easily translated into a bandwidth value by means of the effective bandwidth concept. The dropping algorithm will operate according to the rule that the current DPP, with code , will be forwarded only if the estimated value of available bandwidth, , is higher than , where is the link speed. Generally speaking, some troubles may occur in the wireless link, due to its intrinsic variability. However, by using the UWB technology, the channel exhibits a very stable behavior as regards fading, thus enabling a reliable estimation to be made. The capacity of the wireless link can be evaluated as in [17], whereas, as far as the current/maximum number of UWB active users is concerned, the same aforementioned considerations also apply, including the effects of terminal mobility on this estimation. Thus, the simple mechanism explained above tries to identify the exact value by means of repeated, increasingly precise approximations. According to these considerations, the mapping between a given value of effective, available bandwidth and a DSCP is off-line configured by NRM. It is worth noting that the value of effective bandwidth needed to transport a flow with specific performance requirements depends on the queue parameters (buffer and capacity), whereas, in our approach, we provide an absolute estimation, without considering the context in which it is calculated. In any case, it is an intermediate value between the mean bit rate and the peak bit rate, so a rough estimation of available resources is obtainable. Finally, a nonlinear coding scheme between binary information and bandwidth availability can be used, in order to increase estimation precision when resources get scarce. As regards the issue of the process timescale, the repetition period of the discovery procedure is a tradeoff between overhead and information accuracy provided to the RB. In this regard, possible network status changes due to local handoff in the wireless domain have to be taken into account. In particular, in order to minimize the probability of service denial, a fixed period of the procedure could not be the optimal choice, since the domain has to provide updated information when transport resources are scarce. For this reason, a possible approach could be to increase the frequency of the process when the available bandwidth becomes very limited. The collected information can be used to create a “PDB table,” used to characterize edge-to-edge network services (behaviors), as in the example reported in Table I. Nevertheless, the edge-to-edge QoS provision can be effectively included in service brokerage only if it is supported by an appropriate pricing strategy, the main issues of which are shown in the following section.

TABLE I PDB TABLE PROVIDED BY UWB DOMAINS

V. NETWORK COMMODITY AND PRICING Our goal is to define an approach for the “commoditization” of the network service and the consequent introduction of usage-based tariffs to charge guaranteed network services. Such a model was introduced in [4], [5], and will be further developed below. We consider a domain implementing admission control and resource reservation capabilities in order to be able to offer a number of differentiated network services. A flow, characterized , ), needs an by a set of DLB traffic descriptors ( , amount of reserved network resources (bandwidth, buffer) to propagate through a route with specific QoS guarantees. We make a distinction between QoS features which characterize the edge-to-edge service offered by a domain, classifying them into QoS parameters negotiable between users and providers, and nonnegotiable QoS parameters. The QoS parameters that can be negotiated are those of maximum edge-to-edge delay, maximum delay jitter and loss probability; we will refer to them as service parameters. The transfer delay includes transmission time at the source, propagation delay, elaboration and transmission time and queuing delay at network nodes, as well as possible further delay contributions. Other QoS parameters, such as resilience, connection set-up time and channel reliability, referred to as network parameters, characterize the intrinsic quality of the network and cannot be negotiated. The following considerations apply: the network parameters play a fundamental role in — radio access networks, since channel variability and mobility support could be limiting factors for transmission quality, or could prove extremely expensive to manage; due to the known robustness and fading tolerant capa— bilities of the UWB, its use may represent a viable solution to the problem of transmission quality; the flexibility of the UWB technique simplifies — channel management procedures. As regards the service parameters, we observe that delay jitter and loss probability may be traded with an additional delay. In fact, a given delay jitter can be eliminated by using a playout buffer at the network egress; this means that jitter may be traded for queuing delay. Please note that the playout buffer is used as an equivalent model only and is not used in operation. Similarly, it is possible to adjust the packet loss probability due to buffer overflow in nodes by increasing the amount of buffer allocated to the flow. It means that also packet loss probability may be traded for queuing delay. Consequently, each network service with QoS guarantees can be modeled as a hypothetical


equivalent service with a given delay, without any delay jitter or losses. This equivalent service is characterized by a single parameter only, that is, a virtual end-to-end delay , which is computed from service parameters summing the edge-to-edge delay and the virtual components representing delay jitter and loss probability. It is our belief that representation of QoS parameters by a virtual delay component should be standardized in order to have a common reference for the QoS level provided by a given network service. A low value indicates a good service and vice versa. We call it “delay” since, from a technical point of view, all parameters can be ideally mapped in the time domain, as explained above. The weights of the different contributions must be defined according to customer sensibility. We identify the network commodity as the transfer of information units from an end point A to an end point B. As regards the service parameters, what is needed is a function of the virthat associates a measure (a technical cost) with tual delay the transfer of each information unit through a given domain, expressed in commodity units. In principle, each domain is free to use its own function according to its policy. Clearly, the funcis meaningful if it is a monotonic not increasing function , since, for services with no retion of . Moreover, source reservation and, therefore, with no performance guarantees, we assume that the measure of the commodity is nil. The cost to transfer an information unit from a point A to a point , where B with a virtual delay is is the cost of each commodity unit depending on: 1) network parameters; 2) the two points A and B (for instance, their distance or the number of nodes crossed in the relevant path); and 3) the policies of the relevant domain (e.g., its operational and maintenance cost). Due to the UWB characteristics mentioned value for UWB domains is expected to above, the typical be more competitive than the value achieved by using different radio transmission techniques. Clearly, the commodity price may fluctuate according to factors that are beyond technical considerations. Hence, we define the price of the transfer of an information unit as the quantity , where is a price variais tion factor that accounts for market fluctuations and the market commodity price, i.e., the price per commodity unit. Without resource reservation, there are no performance guaran. In this case, the price depends on access tees, therefore fee only (flat-rate charge). Note that the value of is arbitrarily decided by NSPs, according to their strategies. It could be subject to network congestion (congestion pricing), or it could be a function of the hours of the day (time of day pricing). Below, we assume that both the value of and the level of QoS are fixed during the connection. Let us consider a domain that guarantees the transfer of a flow from a couple of edge ports with a virtual delay . The actual commodity consumption rate , where at the ingress of such domain is is the instant service bandwidth. The potential com, where is the modity consumption rate is value of the bandwidth explicitly reserved to the flow, the value of which depends on both traffic and QoS parameters, and on the resource reservation protocol applied by the domain. Note that, in packet networks, the value of the reserved bandwidth is ) lower then, or equal to the peak rate of a flow ( (e.g., [15]).

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Charging services with pre-allocated network resources is a complex task. We can analyze this issue from different viewpoints. First of all, once the traffic and performance descriptors are defined, the amount of reserved resources is generally conservative, since they are often calculated by using assumptions from the worst case. Note that reservation generally precludes other flows of the same class from using the reserved resources. Therefore, network administrators prefer to charge in proportion to the reserved resources, which are related exclusively to the potential use of the service, that is, to the amount of necessary resources estimated in advance. Thus, network administrators also protect themselves against unfair behavior by users. At the same time, it is objectively difficult for users to predict their traffic rate process exactly, so that they consider it convenient to pay for the resources actually used instead of for estimated (and eventually overestimated) ones. Moreover, NRM can assign the unused reserved bandwidth to lower priority classes temporarily, for instance to the best effort traffic and get some revenues. Below, we propose a tariff model that depends on both the amount of reserved resources and their actual use. We define the instant price of the service at a given time as (1) The equation above means that the instant price cannot decrease below a fixed threshold. Equation (1) can be written as (2) If we indicate the duration of the connection and its starting time by and , respectively, the total cost of the network service through the relevant domain is

(3) Note that the second component is deterministic, that is, it depends on the connection duration and not on the traffic volume exchanged; we will refer to it as allocation charge. The first component is an additional per-usage charge, which is applied when the instant bandwidth is greater than the threshold value . This means that this component is related to the traffic (see Fig. 7). It means that, when the instant bandvolume , the actual use of the service is charged width is greater than is not necessarily (effective usage charge). We stress that the value of the reserved bandwidth; it could simply represent the value of bandwidth that the network administration wants to charge on a per-time basis. Therefore, from a broader point ranges from zero to the peak rate and of view, the value of acts as the tuning knob to assign weights to the allocation charge and effective usage charge components of the tariff. Moreover, the tariff model is such that the charge is higher for a bursty transmission rate; in fact, it is well known that bursty flows (in particular ON/OFF-shaped ones) stress network resources more than flows with a smoothed transmission rate [15].

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TABLE II E-TABLE

Fig. 7.

Time intervals with effective usage charging.

5) Fig. 8.

Temporal sequence of interactions.

VI. PROCEDURE FOR END-TO-END SERVICE PROVISIONING In this section, we describe the typical sequence of the interactions that allow end users to obtain services from ASPs. The procedure evolves according to the following steps (see Fig. 8). 1) An end user, if necessary with the help of an IB, identifies an ASP able to provide a specific service. 2) The end user (or the IB on his behalf) issues a request to the ASP and describes qualitatively the desired quality (e.g., acceptable, good, excellent) and his willingness to pay. 3) The ASP translates the customer’s qualitative requirements into quantitative technical parameters, that is: a) DLB traffic descriptors; b) QoS parameters; and c) the utility function. As is well known, it measures the customer’s sensitivity toward the perceived QoS level and it is useful to think of such a utility as the customer’s willingness to pay as a function of the performance level. In our framework, the utility function is expressed as an amount of money versus the end-to-end virtual delay. This set information is sent to the RB, with the request to find the “best” path to deliver the application service to the end user. 4) The RB identifies the domains which could potentially be involved in the network service and checks their offers. For each pair of input–output ports, the offer is represented by a port-to-port table built on the basis of PDBs and pricing policies (see Table II). We refer to this port as , the e-Table. The offer relevant to the th service, , , includes: a) the QoS parameters. They are translated into a virtual delay value , characterizing the th

6) 7)

8) 9)

service; b) the available bandwidth for each service. According to this value, the RB can decide if the flow relevant to the requested application service can be allocated. For instance, it verifies if the peak (or average) flow rate is lower than the available bandwidth; and c) the value of the price parameters by which the tariff applied by the domain can be calculated. In particular, for the th service and for the specified flow, the per-unit volume and per-unit time charges are, respectively, and , where . The RB runs an interdomain routing algorithm in order to find a path able to satisfy the QoS requirements and to maximize the well-known customer surplus function, that is, the difference between the utility function and the tariff charged for the end-to-end transfer service. The interested reader may find the description of the routing algorithm in [5]. The RB communicates to the ASP the path found and the tariffs charged by the domains. The ASP can offer the customer the service with the relevant price (that depends on both network and application services). If he accepts, the agreement with the characteristics of the service requested and its price is drawn up. The ASP has to draw up one network service contract with each NSP involved in the end-to-end information transfer. The application may start and each domain involved implements its own accounting procedures to get information about network resource consumption (transport accounting). The accounting record is used to charge the ASP, which, in turn, collects consumption data to charge the end user making use of the service (content accounting). VII. CONCLUSION

In this work, we deal with a foreseen network scenario where multimedia application services, which need QoS guarantees to be supported satisfactorily, are delivered through brokerage. In this context, the UWB access technology offers a number of advantages, such as high rate and scalable data transmission. We have characterized the edge-to-edge operation of UWB DiffServ domains by means of a port-to-port table that includes performance and pricing parameters. We have defined the network commodity as the transfer of information units between


two end-points, and we have quantified it by using a function of the so-called virtual delay, that summarizes the QoS guarantees of the network service. Such result is used to define a suitable tariff model to charge IP network services with a guaranteed performance, which depends on the actually used and/or reserved resources.

REFERENCES [1] M. Z. Win and R. A. Scholtz, “Ultra-wide bandwidth time-hopping spread-spectrum impulse radio for wireless multiple-access communication,” IEEE Trans. Commun., vol. 48, pp. 679–689, Apr. 2000. [2] H. Luediger, S. Zeisberg, M. G. di Benedetto, and N. Blefari Melazzi, “Outline of an open radio access network,” in European Wireless 2000, Dresden, Germany, Sept. 2000. [3] M. Z. Win, “Ultra-Wide Bandwidth Spread-Spectrum Techniques for Wireless Multiple-Access Communications,” Ph.D. thesis, Dept. Elect. Eng., Univ. Southern California, Los Angeles, 1998. [4] N. Blefari-Melazzi, D. Di Sorte, and G. Reali, “Usage-based pricing law to charge IP network services with performance guarantees,” in Proc. IEEE ICC 2002, vol. 4, New York, Apr.–May 2002, pp. 2652–2656. [5] D. Di Sorte and G. Reali, “Minimum price inter-domain routing algorithm,” IEEE Commun. Lett., vol. 6, pp. 165–167, Apr. 2002. [6] S. Blake, D. Black, M. Carlson, E. Davies, Z. Wang, and W. Weiss, “An architecture for differentiated services,” IETF RFC 2475, Dec. 1998. [7] K. Nichols and B. Carpenter, “Definition of differentiated services perdomain behaviors and rules for their specification,” IETF RFC 3086, Apr. 2001. [8] G. Bianchi, N. Blefari-Melazzi, and M. Femminella, “Per-flow QoS support over a stateless differentiated services IP domain,” in Computer Networks. New York: Elsevier, Sept. 2002, vol. 40, pp. 73–87. [9] G. Bianchi, N. Blefari-Melazzi, M. Femminella, and F. Pugini, “Joint support of QoS and mobility in a stateless IP environment,” in IEEE GLOBECOM 2001, vol. 6, San Antonio, TX, Nov. 2001, pp. 3454–3458. [10] G. Huston, “Next steps for the IP QoS architecture,” IETF RFC 2990, Nov. 2000. [11] J. Altmann and K. Chu, “A proposal for a flexible service plan that is attractive to users and Internet service providers,” in Proc. IEEE INFOCOM 2001, vol. 2, Anchorage, AK, Apr. 2001, pp. 953–958. [12] M. Falkner, M. Devetsikiotis, and I. Lambadaris, “An overview of pricing concepts for broadband IP networks,” IEEE Commun. Surveys, 2nd Quarter 2000. [13] T. W. Barrett, “History of ultrawideband (UWB) radar & communications: Pioneers and innovators,” in Proc. PIERS2000, Cambridge, MA, July 2000. [14] Y. Bernet et al., “A framework for integrated services operation over DiffServ networks,” IETF RFC 2475, Nov. 2000. [15] A. Elwalid, D. Mitra, and R. H. Wentworth, “A new approach for allocating buffers and bandwidth to heterogeneous, regulated traffic in an ATM node,” IEEE Trans. J. Select. Areas Commun., vol. 13, pp. 1115–1127, Aug. 1995. [16] A. T. Campbell et al., “Comparison of IP micromobility protocols,” IEEE Wireless Commun., vol. 9, pp. 72–82, Feb. 2002. [17] L. Zhao and A. M. Haimovich, “The capacity of an UWB multiple-access communications system,” in IEEE ICC 2002, vol. 3, New York, Apr. 2002, pp. 1964–1968.

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Dario Di Sorte (S’01) received the Laurea degree in electronic engineering (telecommunications) magna cum laude from the University of Perugia, Perugia, Italy, in January 2000 and is currently working toward the Ph.D. degree in the Department of Electronic and Information Engineering (DIEI), University of Perugia. His present research focuses on a number of issues in IP networks: the provisioning of IP QoS, the definition of a business model for the provisioning of application services in a future Internet scenario, and the definition of tariff models to charge IP guaranteed network services. He is working on SUITED and WHYLESS.COM projects, co-funded by the European Union. He is coauthor of a number of papers, published in international conferences and journals.

Mauro Femminella (S’01) received the Laurea degree in electronic engineering magna cum laude with the publication of his thesis, from the University of Perugia, Perugia, Italy, in 1999 and is currently working toward the Ph.D. degree in the Department of Information and Electronic Engineering, University of Perugia. His research interests focus on satellite networks, QoS, and mobility in IP networks. Currently, he is involved in IST (SUITED, WHYLESS.COM), MURST (RAMON), and ESA/CNIT projects. He is coauthor of a number of papers in international conferences and journals.

Gianluca Reali (S’95–A’98) received the Laurea degree in electronic engineering in 1991 and the Ph.D. degree in telecommunications in 1997 from the University of Perugia, Perugia, Italy, working on spread-spectrum techniques and CDMA. Since 1997, he has been a Researcher in the Department of Information and Electronic Engineering, University of Perugia. He collaborated with Alenia Spazio S.p.A. working on VSAT networks. He has also acted as Consulting Engineer for the Institute of Electronics, University of Perugia and CRA in Rome. His present research activity is in IP QoS techniques, particularly in transport and resource management protocols. He also coordinates the activity of the Telecommunication Networks Research Lab. He has been involved in the European ACTS projects, CABSINET, and ASSET. He has been working on the EU IST projects, SUITED, and WHYLESS.COM.

Sven Zeisberg (S’93–M’95) graduated from the Dresden University of Technology, Dresden, Germany, in 1994. Since 1995, he has been a Researcher in the Department of Electrical Engineering and Information Technology, Dresden University of Technology. He has been involved in several research projects concerning the physical layer of wireless communication systems. He has published more than 30 technical papers. His interests include, but are not limited to, digital signal processing, multicarrier communications, and ultra-wideband communications.