A New Resource Based QoS Pricing Model

A New Resource Based QoS Pricing Model 1 MAHMOUD T. NOUMAN, 2 HUSSEIN S. EISSA, 3 SHERINE M. ABD EL-KADER 1 Senior Security Consultant, GSN-Egypt Co. 2, 3 Assistant Prof. at Electronics Research Institute, Computers and Systems Dept., Cairo, Egypt Abstract: The existence of a practical QoS pricing model is essential to facilitate practicing QoS commercially, a proposed model should satisfy certain properties as the ease of implementation and to be understood by participating parties. The Model presented here, is a resource based pricing model for QoS sessions. This model declares the relations between the QoS session parameters and the associated physical resources consumption. Also, in this paper, many case studies have been presented to give the proposed model a more visibility of implementation. Finally it has been concluded that both delay and bandwidth requirements for a session have the major influence over the session cost than the buffer parameter, and the obtained prices are very reasonable (on the average and based on the paper s assumptions, 1.2 USD/hour for a voice over IP session and 3 USD/hour for a video on demand session). 1. INTRODUCTION By time more and more ISPs (Internet Service Providers) are interested at opening a new revenue channels and QoS are supposed to be one of them. Here arises the problem of how to price this new service. Old fashioned pricing techniques are still handling the best effort service and of course they are not feasible to be applied in the QoS environment due to the involvement of other factors [1]. Many pricing schemes for QoS networks have been proposed with different directions. Some models are formulated based on technical direction, where prices are to be set based on technical aspects and other models are formulated with economical point of view [2]. Expected features are meant to be accepted from different parties involved at a QoS session. For a VoIP session those parties could be the call initiator, involved carriers, VoIP operator (application provider), and the recipient. The process of setting up a pricing model has to benefit from both economical and technical theories. Where the economical part tries to maximize the return value from a certain service or product, the technical side aims to draw boundaries and to relate requirements to prices with a precise approach. In this paper a new pricing model is introduced where it have the objectives of implement-ability and compliance with technical and economic aspects of a successful pricing model. 2. QOS PRICING The QoS pricing model is reasonably more complicated, since besides best effort parameters, the other factors have been raised. In a typical ISP environment implementing best effort mechanism, pricing model could be a flat pricing scheme where each user is charged a fixed amount per time unit [3]. Another scheme might include the amount of data transferred (data quota). Similar approaches do not identify pricing per a QoS session, where the session affects the network performance, and affects other users usage. Proposed models could be categorized as: static formulas where prices are calculated based on pre-defined parameters values and dynamic ones where prices are calculated based on instant parameters values measured in real-time. As a more technical approach for providing a cost function for QoS pricing, resource consumption models have been introduced. Whereas this approach does not provide the flexibility of economic oriented pricing schemes it still provides an acceptable and straightforward method for calculating prices. Among the models that have been introduced contained by the resource consumption pricing model, the following model represents a simple illustration and methodology for constructing a resource based formula. Ferrari and Delgrossi have introduced an appealing pricing formula in [4], a resource based formula where user is charged per expected resources consumed during a QoS session. This formula provides a simple and comprehensive way to calculate a resource based prices for QoS sessions and this formula shall be used initially to develop the proposed model next section. 3. PROPOSED MODEL Although of the existence of many QoS pricing schemes still there is a great need for a new formula that combines most of the benefits of static and dynamic pricing, and at the same time minimizes any resulted disadvantage [5]. The proposed formula consists of engineering and economic parts, the engineering part of the proposed formula have to be very strict at determining pricing from a technical point of view by other mean to determine the cost of the service or the baseline, while the economic part have to take care of the economic aspects. 3.1 Model parameters Technical pricing is used to measure the value of physical resources consumed during a QoS session. So in order to detect the resources consumed during a QoS session the model have to map the physical resources to the requirements of the QoS session. Since the proposed model supposed to obey most of properties of a QoS session previously mentioned, the resource consumption have to be estimated before the session begins and not measured during the session. Among network devices that might be involved during a QoS session, The work done here will concentrate on physical links and routers associated to it, since any other network elements would have a similar behavior, e.g. The same methodology that works for a router should work for an ATM switch or an application level gateway.

3.1.1 Physical links Physical links are one of the scarcest resources in a communication network, since they affect the data transferred significantly, a congested link can cause data loss. Also the cost of physical links vary depends on the area size and the area location. So in order to calculate the resource consumption of a physical link, the proposed model have to knew how much bandwidth have been consumed and for how much time. Assuming a link that has a capacity (L) with a cost P(L) per unit time and a QoS session that requires (l) bandwidth for (t) Time. Then the link cost for this session could be presented as shown in (1). 1 P (l) = L 3.1.2 Routers ( P(L) ) t(l) (1) Actually routers controls more than one parameter of QoS, i.e., how a router handles the traffic effects the delay that a packet will have, besides a router willingness to drop a packet determines the loss rate, so routers are considered as the servant of the precious WAN Links. So any router that intended to support QoS conversations have to support related protocols and standards, currently most ISP and carrier level do so, even if the features are not used yet. At Ferrari s model Buffer and computing resources was used instead to represent the router resource, where as previously illustrated the router holds the buffer and have the computing capabilities to sort out packets and perform its related tasks as operating routing protocols. Whereas our proposed model have been considered the router as one resource, since physically they are one unit, besides separating router components will increase the complexity of the pricing model, also the more important is although enabling QoS protocols will consume more of the computing power, it is supposed that the router still have the ability to serve the link with its full capacity (the link). The ISP assumed to purchase a router which has the ability to utilize the associated links. This may not be the case with LAN links, the associated routers may not serve a gigabit LAN link to the full of its capacity, but this is not the situation with ISPs, where WAN links costs too much, and relatively the router cost is smaller. Assuming that a packet will not be dropped from a router as long as it has a place in its buffer, therefore the router control the packet loss due to congestion factor, assuming a router with buffering capacity (B) that costs P(B) per unit time, also considering that this cost is the cost for the buffering function of it and is measured per memory units, and a QoS session that required (b) memory unit in order to maintain its packet loss rate constraint. Then the router cost for this session could be presented at (2). b P (b) = B ( P(B) ) t (2) As yet, the physical resources consumption for a QoS session assumed to be calculated, and have been related to a subset of QoS parameters, where as, other QoS parameters as delay have not yet been mapped to a pricing factor, besides the dynamic factors that affect pricing as time of day, and competitiveness parameter, how a competing service could affect the pricing of a QoS session. The following subsections will have a closer look to these parameters. 3.1.3 Delay Factor Although a router is the actual device that controls the delay, a required delay value will not affect the router resources consumption significantly, it may require higher processing power capabilities than normal situations, but assuming the ideal situation where the router processing power is able to serve its associated links with full utilization, then the computing resource inside the router is not a scarce resource yet and therefore setting individual price for it is not necessary. The actual affect is on the other users sharing the resources, by other mean, the required value of delay for a QoS session means that this session traffic will have higher priority over other sessions. In a QoS environment, the effect of a required delay value would be the blocking of other future QoS sessions due to the inability to satisfy its required delay boundaries. Thus the cost of a required delay value would be the lost profit of the expected future blocked sessions. Consider a system with the ability to support (n) identical QoS sessions with similar QoS constraints, the system is able to serve all the sessions with average delay value of (d avg ), assuming a session (s), requires a delay value of (d req ), assuming that the required value is smaller than the average one, therefore (m) of sessions will get blocked. The cost of such delay value P(d) would be the lost profit of m sessions P profit (m). P(d) m = = P (m profit d avg d req 1) In (3), the cost have been considered to be due to the lost profit for blocked sessions, this factor effected by the expected number of sessions, this leads to a dynamic factor which is network utilization. If on a specific time there is a less demand on the service, the price expected to be less, and if the demand is beyond the network capacity, the prices expected to increase. This increase amount in the price should be considered also as a congestion control method. When applying higher rates users with less interest with the service might prefer to wait until the prices gets lower, and only users willing to pay will get the service. 3.1.4 Utilization Expected number of sessions could be described using a well known factor as network utilization. In such a very dynamic metric, there is a need to specify how to integrate such (3)

factor. For Example instant real time measurement of network utilization shall provide diverse values even in a short time scale, besides the technical complexity in such operation. Taking an average value of network utilization over a specified period of time seems more practical and reduces complexity, which is one of our goals when designing a practical pricing formula. The raised question is how much time should be the interval. Ref. [6] demonstrates that to achieve high accurate technical measures the time interval have to be in seconds, while to achieve predictability of a pricing formula, the time interval should be measured at least in hours which is an important goal. Next question is how many hours should be the time interval; at the same study it shows that you cannot exceed 24 hours in order to achieve high economic value. Since two part tariffs are acceptable by PSTN users, using a similar approach shall be acceptable by service users. The network load characters of a specified link shall decide how many hours of similar network load shall be clustered together. 3.2 Model Elasticity Service demand factor in congestion with user willingness to pay represent a method of congestion control, in another meaning, after determining the cost of the service, it is the ISP choice to raise the revenue in the case that the service demand is higher than the network can offer, and to lower the prices at the times where the network is not congested. Assuming an ISP that have the result price as a function of the previously mentioned physical resources costs (cost) and the service demand (S), therefore: Price= f (cost, S) 3.3 QoS Pricing Formula To formulate a QoS pricing formula, some few points have to be discussed first such as network connectivity costs, beside the cost of physical links and routers, the ISP have other costs as labor, switches and all initial and running costs. By assuming that QoS environment is not native for QoS and the customers need to reach the network first via dedicated/ dialup links. We assume that the customer has been already paid for the other costs by connecting to the network, and these costs have already calculated in the network connectivity pricing. So there will be a need to eliminate duplicate costs or routers and links since there cost is calculated at both QoS pricing and network connectivity pricing. Another constraint that have not a specific pricing value is the jitter, jitter in our assumption have been added to the delay factor to form the overall delay [7]. From (1), (2) and (3) ( P(L) + P(B) + P(D) ) ( time ) (5) Cost = From (4) Pr ice = f (cost, S, Time) It should be noted that the ISP could use more dynamic pricing factors other than service demand, but it have to obey the upper limit, which is competitive services. (6) (4) Fig. 1. Formula block diagram. A session of VoIP could not be priced more than similar PSTN one, even if the network is highly congested and there is a need to raise prices. As suggested at the highest rates in a multi part tariff, there should be a distance between the highest applicable tariff and the associated competitive service. Economic value of a QoS session varies very much; online gaming user might expect a less price than a business conference although the earlier might require more resources. At non congestion periods, ISPs could offer a reduced price, where the service is not used and making any profit out of the network is better than nothing. 4. RESULTS In this section five cases will be implemented for various usage scenarios and their resulted prices will be calculated. 4.1 Case Studies In order to give the proposed formula a more visibility an example should be provided to demonstrate how to calculate the cost of an assumed session. This paper demonstrates the calculation process on actual numbers in order to have a feeling on the trend between different variables. It should be noted that all the offered calculations are per hop unless otherwise specified. 4.1.1 Unit Session and Unit delay Throughout the next section there is a need to determine a unit session (U) to be practiced with different cases and thus deduct the difference in resulted prices. Assuming this unit session U with 64 kbps for bandwidth, 8 KByte for buffer, 5 ms for delay and the standard or unit delay is also 5 ms. So when calculating the cost of the unit session, the relative delay cost term should be eliminated from the pricing. Then the unit session will be priced as follow: l b P( U ) = P(L) + P(B) (7) L B In actual implementation, the model session would be chosen to match the more frequent demanded requirements. For example a VoIP with a specific codec might be the most wanted session through a specific network so choosing it as a model session will provide a more precise cost. 4.1.2 Different Cases In this subsection the price of the previously mentioned unit session have been calculated for different cases ranging from small sized ISP to a large sized one.

A. Corporate Link Case: This case represents an example of a corporate link with T1 (1.54 Mbps) Tier one which costs 4 USD/month, CISCO 1841 that costs 85 USD/month, and the router will use 256KB of its memory as a buffer. So by substituting at (7), then P(U) equals around.45 US Cents. B. Small ISP Case: Assuming the case of sample-isp with 4T1 (6Mbps) Tier one which costs 15 USD/month, CISCO 2851 that costs 2 USD/month, and the router will use 2MB of its memory as a buffer. So P(U) equals around.39 US Cents. C. Medium size ISP Case: Assuming the Case of ISP with T3 (45Mbps) Tier one that costs 5 USD/month, CISCO 38 series that costs 4 USD/month, and the router will use 4MB of its memory as a buffer. So P(U) equals around.1827 US Cents. D. Larger ISP Case: Assuming the ISP with OC3 (155Mbps) Tier one which costs 1 USD/month, CISCO 76 series which costs 8 USD/month, and the router will use 8MB of its memory as a buffer. So P(U) equals around.114 US Cents. E. Application Service Provider Case: This example could be applied to the hosting center where application resides as media streaming server farm. This case has Gigabit Ethernet (1Mbps) Tier one that costs 35 USD/month, CISCO series costs 28 USD/month, and the router will use 64MB of its memory as a buffer. So P(U) equals around.6 US Cents. 4.1.3 QoS Session Parameters variation Data have been collected based on varying one parameter at a time over 1 points. Every parameter will vary to 1 times of its corresponding value of the unit session. All other parameters will be fixed for all the points. All calculations in this section have been used case C assumptions and results. Parameter A: Delay variation The delay is very important factor and at the same time is an intangible one. In our assumptions, the unit session (u) is our starting point with the same delay of 5 ms and the delay requirement will decrease by 5 ms for the next session. For all the 1 sessions, the price of 64kbps bandwidth is.45 US cents and the price of 8KB buffer is.226 US cents. Cost (US Cost (Cent) Cents).2.15.1.5 Delay Vs. Cost 5 45 4 35 3 25 2 15 1 5 Fig. 2. Delay vs. cost. The graph shows that varying the delay value have a significant impact over the resulted price although the delay value is not associated with the consumption of a physical resource. Rather, the increase is due to the parallel increase of the blocked sessions. Please note that this delay requirements is the delay required from the router to move packets from one interface to the other, the propagation delay and any other fixed delays is excluded and have no cost since it is fixed and out of our control. No. of No. blocked of sessions 1 8 6 4 2 Delay Vs. blocked sessions 5 45 4 35 3 25 2 15 1 5 Fig. 3. Delay vs. blocked sessions. The results shows that for a delay value of 25 ms the session costs double the price as the price of the unit session, because this requirement caused the system to block 1 unit session. Parameter B: Bandwidth Variation Starting from our unit session that has bandwidth of 64 kbps, we shall increase the bandwidth by 64kbps/session. For simplicity, the sessions will be constant bit rate. For all the 1 sessions, the price of 5 ms delay is zero and the price of 8KB buffer is.226 US cents. Cost (Cent) Cost (US Cents).18.16.14.12.1.8.6.4.2 Bandwidth Vs. Cost 64 128 192 256 32 384 448 512 576 64 Fig. 4. Bandwidth vs. costs. Bandwidth (K.bit) Bandwidth results are straightforward, the more bandwidth the session will consume the higher the cost linearly. Parameter C: Buffer variation In our tactic the buffer is used for not to lose packets. As long as there is a place for the session packets at the buffer, no data will be lost. As the above examples our sample sessions will start from the unit session requirement of 8 KB, and will increase by the value to the 1 points. For all the 1 sessions, the price of 5 ms delay is zero and the price of 64 kbps buffer is.494 US cents. Cost (Cent) Cost (US Cents).4.35.3.25.2.15.1.5 Buffer Vs. Cost 8 16 24 32 4 48 56 64 72 8 Fig. 5. Buffer consumption vs. costs. Buffer (KB) Compared to the resulted prices from varying bandwidth and delay which are almost having a similar effect over the

resulted price, the buffer factor has the minimal effect over the resulted price, an increase less than 5% of the original unit price for the 1x of space of original buffer size of the unit session U. 4.1.4 Sample Sessions In this section, different services will be calculated. We are assuming that our network consists of 1 hops, each have the same configuration as mentioned at Case C. The applications requirements are assumed as follows: TABLE 1. APPLICATIONS REQUIREMENTS. Applications Delay B.W. Buffer Unit Session 5 64 8 VoIP 15 64 8 Online-Gaming 1 128 16 Video-on-demand 2 512 256 PN-256 5 256 128 By calculating the prices along the path, the following results are presented at table (2). TABLE 2. THE SESSIONS PRICES. Applications Blocked sessions Cost/Hop Total Cost Unit Session.18269.182694 VoIP 2.33.6898.68978 Online-Gaming 4.19616 1.96161 VOD -.75.175856 1.758556 VPN-256.94779.947788 Application A: IP telephony applications Our sample VoIP application offered constraints to provide quality similar to that of POTS. The obtained cost is less than 2 cents/minute for a distance of 1 hops, which is less than the cost of traditional overseas phone call. Thus the formula provides a very competitive price. Application B: Gaming applications In the graph we find that gaming application are priced higher than business related once. This is because applications as online gaming deemed to require stricter requirements than other types. An online gamer will lose the game if the shot packet is delayed. Meanwhile voice user will not end the call because of a lost packet. Application C: Video on demand Enabling QoS over a network will allow for the creation of new business expansions. At our example we used a stream of a 512kbps which is represents an acceptable quality. In this case, the obtained cost is approximately 4.2 cents/minute (i.e. less than 3 USD/hour). The VoD have a very nice feature which is that if the delay is constant, it will not bother how much is it. By other meaning a delay of 1 seconds is acceptable if it is constant. So when the model delay is 5 ms, the VoD session in our example required 2 ms. For its operation, which is higher than the 5 ms, this have lead to the labeled negative value at the previous table. The negative value means that an application of this delay requirement will allow another unexpected session(s) to be welcomed at the system (the opposite of a blocked session). In our example we have chosen to reward the session by subtracting the expected cost of these unexpected sessions from the total cost. It is the ISP decision either to follow this approach or roofing negative values to zeros. Application D: Virtual private networks Assuming the VPN tunnel of 256kbps has an obtained price round 2.5 cents/minute which is equivalent to around 1.5 USD/hour and this cost has to be compared to the cost of a L2 virtual dedicated link (PVC) for the same path (1 hops). 5. CONCLUSION From the obtained results it is shown that the delay and bandwidth requirements for a session have the major influence over the session cost than the buffer parameter. Price (US Price Cents).6.5.4.3.2.1 1 2 3 4 5 6 7 8 9 1 Fig. 6. Parameters costs. Parameter - Interval Cost-delay Cost-BW Cost-buffer From the obtained results, it is clear that the applications costs are feasible and competitive. Also, to decrease the costs of both VoD and the online gaming, the applications might prefer to split their session. For example, splitting the MPEG session by transmitting the I-frames using QoS session and the B-frames using the best effort, since the I- frame packet hold more important information than the B- frame one. The same previous technique could work for VPN, if there are a VPN between two sites, it will not be very economic to carry the whole VPN session over a QoS network. In such situation providing a QoS on demand VPN session for important data payload as server replications and syncing is more convenient. Finally, the delay factor is very costly and unfortunately many applications tend to have very strict delay boundaries (specially the entertainment and the real-time sessions). But some applications as remote controlling of machinery and remote therapy will have a higher economic impact than the real-time applications. REFERENCES [1] A. Odlyzko, The economics of the internet: Utility, utilization, pricing, and quality of service, In Proceedings of SIGCOMM '98, Vancouver, July 1998. 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