Coalitional Game Theoretic Approach for Cooperative Transmission in Vehicular Networks

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Coalitional Game Theoretic Approach for Cooperative Transmission in Vehicular Networks"

Transcription

1 Coalitional Game Theoretic Approach for Cooperative Transmission in Vehicular Networks arxiv:.795v [cs.gt] 8 Feb Tian Zhang, Wei Chen, Zhu Han, an Zhigang Cao State Key Laboratory on Microwave an Digital Communications, Tsinghua National Laboratory for Information Science an Technology (TNList) Department of Electronic Engineering, Tsinghua University, Beijing 84, China School of Information Science an Engineering, Shanong University, Jinan 5, China Department of Electrical an Computer Engineering, University of Houston, Houston, TX wchen, Abstract Cooperative transmission in vehicular networks is stuie by using coalitional game an pricing in this paper. There are several vehicles an roasie units (RSUs) in the networks. Each vehicle has a esire to transmit with a certain probability, which represents its ata burtiness. The RSUs can enhance the vehicles transmissions by cooperatively relaying the vehicles ata. We consier two kins of cooperations: cooperation among the vehicles an cooperation between the vehicle an RSU. First, vehicles cooperate to avoi interfering transmissions by scheuling the transmissions of the vehicles in each coalition. Secon, a RSU can join some coalition to cooperate the transmissions of the vehicles in that coalition. Moreover, ue to the mobility of the vehicles, we introuce the notion of encounter between the vehicle an RSU to inicate the availability of the relay in space. To stimulate the RSU s cooperative relaying for the vehicles, the pricing mechanism is applie. A non-transferable utility (NTU) game is evelope to analyze the behaviors of the vehicles an RSUs. The stability of the formulate game is stuie. Finally, we present an iscuss the numerical results for the -vehicle an -RSU scenario, an the numerical results verify the theoretical analysis. I. INTRODUCTION Vehicular networks, from which rivers can obtain useful messages such as traffic conitions an real-time information on roa to increase traffic safety an efficiency, has gaine much attention []. Meanwhile, vehicular networks can also provie entertainment content for passengers an collect ata for roa an traffic managers. In vehicular networks, vehicles an roasie units (RSUs) can communicate with each other through vehicle-to-vehicle (VV), roasie-to-vehicle (RV), vehicle-to-roasie (VR) an roasie-to-roasie (RR) communications. As an important mous operani of substantially improving coverage an communication efficiency in wireless networks, cooperative transmission has gaine consierable attention recently. In cooperative communications, some neighboring noes can be use to relay the source signal to the estination, hence forming a virtual antenna array to obtain spatial iversity. Decoe-an-forwar (DF) is a commonlyuse cooperative protocol []. In DF relaying, the relay noe first ecoes the receive signal from the source, re-encoes it, an then forwars it to the estination. For the purpose of improving the system spectral efficiency, the cooperative relaying with relay selection [], [4] has been introuce on one han. On the other han, the non-orthogonal relaying protocols have been investigate [5]. Since the coalitional game theory provies analytical tools to moel the behaviors of rational players when they cooperate, it is a powerful tool for esigning robust, practical, efficient, an fair cooperation strategies an has been extensively applie in communication an wireless networks, which inclues the vehicular networks [6]. In [7], the coalitional game theory was utilize to investigate the cooperation between rational wireless users, an the stability of the coalition was analyze. Cooperative transmission between bounary noes an backbone noes was stuie base on coalition games in [8]. In [9], banwith sharing was stuie by using coalition formation games in VR communications. In [], the coalition formation games for istribute cooperation among RSUs in vehicular networks were stuie. In [], the coalitional game theory was applie in stuying how to stimulate message forwaring in vehicular networks. The coalition formation problem for rational noes in a cooperative DF network was formulate in []. The coalitional game theoretic approach for seconary spectrum access in cooperative cognitive raio networks was stuie in []. The stability of cooperation in multi-access systems was analyze in [4]. In [5], the coalitional game was utilize to stuy the cooperative packet elivery in hybri wireless networks. In cooperative relay networks, there are costs (e.g., energy consumption, operational cost, banwith) at the relays for forwaring the other users signals. Hence, a proper compensation mechanism is inispensable to provie the relays with incentives to forwar the signals. Pricing mechanism was stuie accoringly [6]. In this paper, we investigate the cooperative transmission in vehicular networks uner the framework of the coalitional game theory an pricing mechanism. On one han, the vehicles can form coalitions to cooperatively scheule their transmissions. On the other han, the RSUs can join the coalitions to cooperate the transmission of the vehicles. In the consiere scenario, as the vehicles are ynamic with respect to the RSUs, the vehicles an RSUs may be very far away. In this case, the cooperative transmission may be unprofitable if not impossible. Accoringly, we propose the notion of encounter

2 Fig.. RSU RSU NoP RSU Cooperative transmission with coalitions in vehicular networks between the vehicles an RSUs. Two conitions shoul be satisfie before a RSU cooperates a vehicle s transmission: ) the RSU an vehicle are in the same coalition; ) the RSU an vehicle encounter each other. When the two conitions hol, the RSU can use cooperative transmission to help the vehicle. In return, the vehicle shoul pay for the RSU. We consier the problem as a non-transferable utility (NTU) game. The stability of the existing coalition is stuie. Numerical results emonstrate the efficiency of the propose game. The reminer of the paper is structure as follows. Section II presents the system moel. Next, the coalitional game approach for the consiere problem is propose in Section III. We first formulate a NTU game to moel the cooperative transmission in the consiere vehicular network, an then the analysis of the propose coalitional game is carrie out. In Section IV, the numerical results are iscusse. Finally, we conclue the paper in Section V. II. SYSTEM MODEL Consier a wireless network in Fig., which consists of a network operator (NoP), K vehicles, an M RSUs. The vehicles an RSUs can form coalitions an the RSUs can cooperate the transmissions of the vehicles when they are in the same coalition. Let enote the NoP, an V =,,,K} an R = K +,,,K + M} represent the set of the vehicles an RSUs, respectively. We consier the uplink communications from the vehicle to the NoP. Each i V has its transmission range i. When RSU i R is in the transmission range of vehicles j V, we call i encounters j. Vehicle i V is active in each time-slot with probability p i, inepenently of other vehicles. When two or more vehicles transmit simultaneously, it is calle a collision, an we suppose that the transmissions will fail when a collision occurs. The cooperative protocol utilize in this paper is the non-orthogonal ecoe-an-forwar (NDF) [5]. In the first half of the time-slot, the source transmit to the The concept of relay noe has been introuce in IEEE 8.6j for WiMAX networks. It is assume that within the transmission range, the correct ecoing at the receiver can be guarantee. relay an estination; In the secon half, the relay ecoes an forwars the source message. Meanwhile, the source transmits a new message to the estination. We assume that vehicles in the same coalition can cooperate to scheule the transmissions, an only one vehicle transmits at a time to avoi interference. In each coalition, a scheuler etermines the active user that can transmit while other active users remain silent. When vehicle j is scheule to transmit at a time-slot, it selects one RSU from the feasible RSU set (i.e., the set of RSUs that are in the same coalition with vehicle j an encounter vehicle j) as relay to assist its transmission. Then one vehicle only employs at most one RSU as relay for each transmission. Furthermore, as no more than one vehicle is scheule to transmit at a given time-slot, one RSU assists the most one vehicles at a given time-slot. When the vehicle j utilizes RSU i as relay for its transmission, RSU i charges vehicle j with price ξ ij per transmission. When some vehicles an RSUs form a coalition, the vehicles woul share the channel with each other in TDMA moe, an they nee to pay for the RSU s relaying. However, the vehicles can avoi collision an gain iversity as well as rate increase. On the other han, although there are costs in receiving an forwaring the vehicles signals [7], the RSUs coul achieve revenues by charging the vehicles. In a wor, both vehicles an RSUs have incentives to form coalitions. III. COALITIONAL GAME APPROACH In this section, we first formulate the coalitional game in Section III-A, an then we analyze the formulate game in Section III-B. A. Coalitional game formulation A coalitional gameg is uniquely efine by the pair(n,v), where N is the set of players, any non-empty subset S N is calle a coalition, an v is the coalition value, it quantifies the worth of a coalition in a game. In our paper, the players are the vehicles an RSUs, i.e., N = V R. S N is a coalition. Define S V := S u ans R := S r. Consier a time-slot, let i j enote i encounters j uring the whole time-slot an P ij = Pri j}. The ata rate increase of vehicle i with the cooperation from the RSU j is enote as ij. Formally, the scheuler in S is a map f S : S S such that f S (Ψ) Ψ for all Ψ S an f S (Ψ) = iff Ψ =. 4 The average effective throughput for vehicle i can be expresse as T i (S) = E Ψ fs(ψ)=i}} (+ζi (S)) ( p j ), j V\S u where E Ψ fs(ψ)=i}} enotes the ratio of time-slots that vehicle i is chosen to transmit. For example, we can assume f S (Ψ) chooses the minimal element from the set of active We assume that the selection is performe accoring to a uniform probability istribution for simplicity. 4 Similar efinitions can be foun in [4].

3 vehicles Ψ. Let S u = s,,s Su } with s > > s Su, then } E Ψ fs(ψ)=s Su } = p s Su () an } E Ψ fs(ψ)=s k } S u = p sk i=k+ ( p si ),k =,, S u. () ζ i (S) is the average increase of ata rate for vehicle i an it is given by ζ i (S) = ij P ji ( P ki ) k ij + ik + P ji P ki ( P li ) j<k S r l j,l k S r ij + ik + il + P ji P ki P li j<k<l S r ij ( P ri )+ + P ji, n r j,r k,r l S r where n = S r. If S r =, i.e., n =, ζ i (S) =. Suppose ij = i, i.e., the ata increase for vehicle i is irrelevant to the selection of RSUs, then the average throughput for vehicle i can be simplifie as T i (S) = E Ψ fs(ψ)=i}} (+Pi i ) ( p j ), where P i = j V\S u ( P ji ) is the probability that at least one RSU in the coalition encounters vehicle i. Remark: If there are active vehicles outsie S at a given time-slot, at least one vehicle outsie S transmits simultaneously with the scheule vehicles in S no matter how the vehicles outsie S form coalitions. Thus, there is no collision if an only if (iff) all vehicles outsie S is inactive. For vehicle i, the average payment mae to the RSUs can be given by P i (S) = E Ψ fs(ψ)=i}} χi (S) with χ i (S) = ξ ji P ji ( P ki ) k ξ ji +ξ ki + P ji P ki ( P li ) j<k S r l j,l k S r ξ ji +ξ ki +ξ li + P ji P ki P li j<k<l S r ξ ji ( P ri )+ + P ji. n r j,r k,r l S r If n =, χ i (S) =. Assume ξ ij = ξ j, i.e., all the RSUs set the same price for vehicle j, then the average payment can be simplifie as P i (S) = E Ψ fs(ψ)=i}} Pi ξ i. Remark: The RSU charges the vehicles once the vehicles employs the RSU as the relay for a transmission, it oes not take the collisions into account. That is to say, the actions in other coalitions o not affect the charging. The payoff of vehiclei is etermine byu i (S) = α i T i (S) β i P i (S). For RSU j in S, the revenue charge from the vehicles can be given by R j (S) = } fs(ψ)=i} ηij (S)ξ ji, () E Ψ where η ij (S) is the probability that vehicle i employs RSU j as its relay for transmission, an it is given by [ η ij (S) = P ji ( P ki ) k + P ki ( P li ) k l j,l k S r + P ki P li ( P ri ) k<l,k j,l r j,r k,r l S r + + ]. (4) n k P ki Assume that RSU j receives the signal of vehicle i at cost c r ji an the cost of forwaring the signal to NoP as cf ji. The average cost of RSU j can be expresse as C j (S) = E Ψ fs(ψ)=i} } [ c f ji η ij(s)+p ji cji] r. (5) Remark: RSU j receives the message of vehicle i once it encounters vehicle i (with probability P ji ), an it forwars the message only when it is selecte as the relay by vehicle i (with probability η ij (S)). The payoff of RSU j is etermine by ũ j (S) = γ j R j (S) µ j C j (S). Define v(s) R Su + Sr be the set of feasible payoff vectors for S, we formulate the consiere cooperation problem as a coalitional NTU-game G : (V R,v). B. Analysis of the formulate coalitional game In this section, we first present two observations. Next, we analyze the stability of the game an propose a sufficient conition for the existence of the core. In the beginning, we have the following observation. Observation. Let f(s) = u i (S)+ ũ j (S) enote the sum payoff of S. When γ j = an β i =, we have f(s) = α i T i (S) µ j C j (S). That is to say, the pricing has no effect on the sum payoff in this case. Proof: First we can prove that χ i = η ij (S)ξ ji. Then E Ψ fs(ψ)=i}} χi } = E Ψ fs(ψ)=i} η ij (S)ξ ji (a) = } fs(ψ)=i} ηij (S)ξ ji. (6) E Ψ

4 (a) hols since E Ψ fs(ψ)=i}} is irrelevant to j Sr. Next, base on (6), we can erive } E Ψ fs(ψ)=i} χi = } E Ψ fs(ψ)=i} ηij (S)ξ ji. (7) Exchanging the summation orer on the right sie, we get P i (S) = R j (S). (8) When γ j = an β i =, f(s) = α i T i (S) µ j C j (S)+ P i (S) R j (S). Using (8), we erive f(s) = α i T i (S) µ j C j (S). Remark: Observation reveals the fact that the total revenues obtaine by the RSUs equal to the payments of all the vehicles. In aition, we obtain the secon observation. Observation. A coalitions shoul have at least one vehicle. Otherwise, ũ i (S) = = ũ i (i}) an v(s) = ũ i (S) =. i S That is to say, when there are only the RSUs, the RSUs have no stimuli to form coalitions an each RSU will act alone. Proof: When S u =, we get R j (S) = an C j (S) = accoring to () an (5), respectively. Thus, ũ i (S) =. Specifically, ũ i (i}) =. As ũ i (S) = ũ i (i}) in this case, each RSU will act alone. Remark: The function of the RSU is relaying the vehicle s signal. So when there is no vehicle, it is meaningless to group only the RSUs together. On the other han, when there is no} RSU in a coalition S, i.e., S V, u i (S) = E Ψ fs(ψ)=i} ( p j ) for j V\S i S an v(s) = u i (S) >. Specially when S = i}, i S we erive u i (i}) = p i ( p j ). Hence, when S j V\i} V & S i satisfying u i (S) > u i (i}), the vehicles will form coalitions to improve the utility. Specifically, let S = s,,s S } with s > > s S, base on () an (), we can erive that if ( p j ), i = S ; j S\s i} ( p j) (9) j S\s i } S ( p sk ) k=i+, otherwise, forming coalition S is profitable. 5 Specially, when p i = p, i.e., all vehicles have the same active probability, we can erive that (9) hols, then forming coalitions is always profitable in the case. 5 Although forming S may be not optimal, it is at least better than acting alone. Next, as the core is one of the most important stability concepts efine for coalitional games, we investigate the core of our propose coalitional game in the following. The efinition for the core of our coalitional game is given as follows. Defination. The core of (V R,v) is efine as C = x v(v R) : S, y v(s),s.t. y i > x i, i S }. The following observation gives a sufficient conition for the existence of the core. Observation. The core of (V R,v) is nonempty once the following conitions hol (S V R): ) α i >, β i >, γ j >, an µ j >. ) α i T i (S) > β i P i (S) or γ j R j (S) > µ j C j (S). ) α i T i (V R) β i P i (V R) > α i T i (S) β i P i (S), an γ j R j (V R) µ j C j (V R) > γ j R j (S) µ j C j (S). Proof: When ) hols, we can fin α i, β i, γ i, an µ j to satisfy ). If ) oes not hols, we have u i (i}) = ( p j ) u i (S) for i S u an ũ j (S) = j V/i} ũ j (j}) for j S r. Then, each vehicle an RSU will act alone. In this case, the core is empty. When ) hols, we can prove that (V R,v) is balance [8]. Thus, the core is nonempty accoring to the Bonareva-Shapley theorem [9]. Remark: The core is possibly non-empty in practice. For example, when the consiere vehicles wait for the traffic light, the vehicles as well as the nearby RSUs are probable to form the coalition together. IV. NUMERICAL RESULTS In this section, we emonstrate the numerical evaluations for the performance of the cooperative transmission scheme with coalitions. In the simulations, we assume that the noes are uniformly locate in a square area of km km. 6 The network topology changes at the beginning of each timeslot an remains static uring the whole time-slot. That is to say, the locations of the noes are generate accoring to the uniform istribution at the beginning of a time-slot, the locations o not change uring the time-slot, an we regenerate the locations at the beginning of the next time-slot. We consier the scenario that there are vehicles ( an vehicle ) an RSUs (RSU an ) in the area. Fig. shows the encounter probability with ifferent transmission ranges for an vehicle. In the simulations, we set = = an the probability is obtaine from 6 time-slots. We can observe that RSU &, &, RSU & vehicle, an & vehicle have similar encounter probabilities. It is because that since all noes are uniformly istribute, an vehicle as well as RSU an are exchangeable in location. In aition, we can see that the encounter probability increases with the increase of the transmission range. In the evaluations 6 The area has been ivie to.

5 Encounter probability Fig RSU & & RSU & vehicle & vehicle 4 5 Encounter probability with ifferent transmission ranges TABLE I POSSIBLE COALITIONAL STRUCTURE C :,,,4} C 6 :,},,4} C :,},,4} C :,,4},} C 7 :,,},4} C : },},,4} C :,},},4} C 8 : },,,4} C :,,4},} C 4 : },},},4} C 9 :,4},,} C 4 :,4},},} C 5 : },},,4} C : },4},,} C 5 : },4},,} vehicle RSU 4 5 Fig.. performance in C of utility performance, we set ij =.5, p i =.6, ξ ij =.5, c f ji =.5,cr ji =.,α i =,β i =, anγ j = µ j =. There are totally 5 coalitional structures for vehicles an RSUs as illustrate in Table I. Using Observation, we nee not consiering C an C. Meanwhile, as an vehicle as well as RSU an are exchangeable, 7 we only nee to consier C - C 7. 8 Fig. plots the utility performance for 4 noes when they form the coalition together(c ). The utility performance increases when we increase the transmission range. The reason is that the encounter probability will increase when the transmission range increases (see Fig. ). Consequently, 7 an vehicle are not exchangeable because of the scheuling when they are in the same coalition. However, as exchanging elements in the same coalition is meaningless, it oes not affect the analysis here. 8 C 8 is similar as C ; C 9 is similar as C 6 ; C, C 4 an C 5 are similar as C 5 ; an C is similar as C vehicle RSU (a) C vehicle RSU 4 5 (b) C Fig. 4. performance in C an C vehicle RSU 4 5 (a) C vehicle RSU 4 5 (b) C 5 Fig. 5. performance in C 4 an C 5 the probability of cooperative transmission will increase. As cooperative transmission coul benefit both the vehicle an RSU, 9 the utility performance increases. Another observation is that the utility performance for is better than that of vehicle, an the utility performance for RSU an RSU 4 is similar. This can be explaine as follows: when vehicle an vehicle are in the same coalition an both of them are active, the scheuler selects to transmit, i.e., the has higher transmission priory than vehicle. Consequently, the utility performance for is better. In contrast, RSU an have same priority in the relay selection of vehicle an they have same encounter probability with (or vehicle ), the same relaying price, an the same cost for receiving an forwaring, so they have similar utility performance. Fig. 4(a) - Fig. 6(a) illustrate the utility performance for C - C 7, respectively. As compare with Fig., the utility performance of eviently ecreases, an the utility performance of vehicle, RSU, an slightly ecreases in Fig. 4(a). Base on the scheuling scheme, the successful transmission probability of RSU is p =.6 in C. In contrast, it is p ( p ) =.4 in C. That is to say, the successful transmission probability obviously ecreases. Thus, the utility ecreases eviently. With respect to vehicle, the successful transmission probabilities are the same in C an C (i.e., ( p ) p =.4). However, there are no RSUs that are in the same coalition with vehicle in C. Then no cooperative transmission can be implemente for vehicle 9 Uner the simulation settings, cooperative transmission is preferable for both vehicle an RSU.

6 vehicle RSU 4 5 (a) C vehicle RSU 4 5 (b) C 7 Fig. 6. performance in C 6 an C 7, an the utility performance ecreases accoringly. In C, both an vehicle may utilize RSU (or ) for cooperative transmission. In contrast, only may utilize RSU (or ) in C, i.e., the probability of being utilize as a relay will ecrease in C. As being utilize as a relay is profitable in our settings, the utility performance of RSU () ecreases. Comparing Fig. 4(b) with Fig. 5(a), it can be observe that the utility performance of is much better in Fig. 4(b), an the utility performances of the other three noes (vehicle, RSU, an ) are the same. It can be explaine by using (9). Firstly, S =,} with s = an s =. Then we have ( p j ) = p =.4 <, i = ; j S\s i} [ ] S () ( p j ) ( p sk ) j S\s i} k=i+ = ( p )[ p ] =, i =. That is to say, the utility of RSU s = will increase an the utility of RSU s = will remain the same when they form the coalition, }. Finally, we can see that the utility performance in C is better than other coalitional structures an the utility is positive in all coalitional structures. Meanwhile, α i = >, β i = >, an γ j = µ j = >. Thus, the conitions in Observation hol. Applying Observation, we claim that the core of the coalitional game is nonempty uner the simulation settings. Furthermore, (u (C ),u (C ),u (C ),u 4 (C )) is in the core. V. CONCLUSION Cooperation among vehicles an cooperation between vehicle an RSU in vehicular networks have been stuie. We propose the notion of encounter to characterize the relative location between the vehicle an RSU when the vehicle is locomotive. Utilizing the coalitional game theory an pricing mechanism, we have formulate a NTU coalitional game to analyze the behaviors of the vehicles an RSUs. Moreover, the stability of the propose game is stuie. A sufficient conition for the non-empty of the core is obtaine. Numerical results for the -vehicle an -RSU scenario verify the theoretical analysis. ACKNOWLEDGMENT This work is partially supporte by the National Basic Research Program of China (97 Program) uner Grants CB66 an CB6, the National Nature Science Founation (NSF) of China uner Grants 688, 69, an 6, US NSF CNS-756, CNS- 9577, ECCS-878, CNS-95556, CNS-6568, an Qatar National Research Fun. REFERENCES [] G. Karagiannis, O. Altintas, E. Ekici, G. J. Heijenk, B. Jarupan, K. Lin, an T. Weil, Vehicular networking: a survey an tutorial on requirements, architectures, challenges, stanars an solutions, IEEE Commun. Surv. Tut., vol., no. 4, pp ,. [] J. N. Laneman, D. N. C. Tse, an G. W. Wornell, Cooperative iversity in wireless networks: efficient protocols an outage behavior, IEEE Trans. Inf. Theory, vol. 5, no., pp. 6-8, Dec. 4. [] A. Bletsas, A. Khisti, D. P. Ree, an A. Lippman, A simple cooperative iversity metho base on network path selection, IEEE J. Sel. Areas Commun., vol. 4, no., pp , Mar. 6. [4] T. Zhang, W. Chen, an Z. Cao, Opportunistic DF-AF selection relaying with optimal relay selection in Nakagami-m faing environments, Proc. the st IEEE International Conference on Communications in China (IEEE ICCC ), Beijing, China,. [5] R. U. Nabar, H. Bölcskei, an F. W. Kneubühler, Faing relay channels: performance limits an space-time signal esign, IEEE J. Sel. Areas Commun., vol., no. 6, pp. 99-9, Aug. 4. [6] W. Saa, Z. Han, M. Debbah, A. Hjφungnes, an T. Basar, Coalitional game theory for communication networks: a tutorial, IEEE Signal Process. Mag., vol. 6, no. 5, pp , Sep. 9. [7] S. Mathur, L. Sankar, an N. B. Manayam, Coalitions in cooperative wireless networks, IEEE J. Sel. Areas Commun., vol. 6, no. 7, pp Sep. 8. [8] Z. Han an H. Vincent Poor, Coalition games with cooperative transmission: a cure for the curse of bounary noes in selfish packet forwaring wireless networks, IEEE Trans. Commun., vol. 57, no., pp. -, Jan. 9. [9] D. Niyato, P. Wang, W. Saa, an A. Hjφungnes, Coalition formation games for banwith sharing in vehicle-to-roasie communications, Proc. IEEE WCNC, Syney, Australia, Apr.. [] W. Saa, Z. Han, A. Hjφungnes, D. Niyato, an E. Hossain, Coalition formation games for istribute cooperation among roasie units in vehicular networks, IEEE J. Sel. Areas Commun., vol. 9, no., pp. 48-6, Jan.. [] T. Chen, F. Wu, an S. Zhong, Stimulating cooperation in vehicular a hoc networks: a coalitional game-theoretic approach, IEEE Trans. Veh. Technol., vol. 6, no., pp , Feb.. [] D. Niyato, P. Wang, W. Saa, Z. Han, an A. Hjφungnes, Coalition formation games for relay transmission: stability analysis uner uncertainty, Proc. IEEE WCNC, Cancun, Mexico, Mar.. [] D. Li, Y. Xu, X. Wang, an M. Guizani, Coalitional game theoretic approach for seconary spectrum access in cooperative cognitive raio networks, IEEE Trans. Wireless Commun., vol., no., pp , Mar.. [4] N. Karamchanani, P. Minero, an M. Franceschetti, Cooperation in multi-access networks via coalitional game theory, Proc. Allerton Conf. Commun., Control, an Comp., UIUC, Illinois, USA, Sep. 8-,. [5] K. Akkarajitsakul, E. Hossain, an D. Niyato, Cooperative packet elivery in hybri wireless mobile networks: a coalitional game approach, IEEE Trans. Mobile Comput., accepte for publication. [6] N. Shastry an R. S. Ave, Stimulating cooperative iversity in wireless a hoc networks through pricing, Proc. IEEE ICC 6, Istanbul, Turkey, Jun. 6. [7] W. Saa, Z. Han, M. Debbah, an A. Hjφungnes, Distribute coalition formation framework for fair user cooperation in wireless networks, IEEE. Trans. Wireless Commun., vol. 8, no. 9, pp , Sep. 9. [8] R. B. Myerson, Game Theory: Analysis of Conflict. Cambrige, MA: Harvar Univ. Press, Sep. 99. [9] Z. Han, D. Niyato, W. Saa, T. Basar, an A. Hjφungnes, Game Theory in Wireless an Communication Networks: Theory, Moels an Applications, Cambrige Univ. Press, UK,.

Game Theoretic Modeling of Cooperation among Service Providers in Mobile Cloud Computing Environments

Game Theoretic Modeling of Cooperation among Service Providers in Mobile Cloud Computing Environments 2012 IEEE Wireless Communications an Networking Conference: Services, Applications, an Business Game Theoretic Moeling of Cooperation among Service Proviers in Mobile Clou Computing Environments Dusit

More information

10.2 Systems of Linear Equations: Matrices

10.2 Systems of Linear Equations: Matrices SECTION 0.2 Systems of Linear Equations: Matrices 7 0.2 Systems of Linear Equations: Matrices OBJECTIVES Write the Augmente Matrix of a System of Linear Equations 2 Write the System from the Augmente Matrix

More information

Factoring Dickson polynomials over finite fields

Factoring Dickson polynomials over finite fields Factoring Dickson polynomials over finite fiels Manjul Bhargava Department of Mathematics, Princeton University. Princeton NJ 08544 manjul@math.princeton.eu Michael Zieve Department of Mathematics, University

More information

JON HOLTAN. if P&C Insurance Ltd., Oslo, Norway ABSTRACT

JON HOLTAN. if P&C Insurance Ltd., Oslo, Norway ABSTRACT OPTIMAL INSURANCE COVERAGE UNDER BONUS-MALUS CONTRACTS BY JON HOLTAN if P&C Insurance Lt., Oslo, Norway ABSTRACT The paper analyses the questions: Shoul or shoul not an iniviual buy insurance? An if so,

More information

A Generalization of Sauer s Lemma to Classes of Large-Margin Functions

A Generalization of Sauer s Lemma to Classes of Large-Margin Functions A Generalization of Sauer s Lemma to Classes of Large-Margin Functions Joel Ratsaby University College Lonon Gower Street, Lonon WC1E 6BT, Unite Kingom J.Ratsaby@cs.ucl.ac.uk, WWW home page: http://www.cs.ucl.ac.uk/staff/j.ratsaby/

More information

Purpose of the Experiments. Principles and Error Analysis. ε 0 is the dielectric constant,ε 0. ε r. = 8.854 10 12 F/m is the permittivity of

Purpose of the Experiments. Principles and Error Analysis. ε 0 is the dielectric constant,ε 0. ε r. = 8.854 10 12 F/m is the permittivity of Experiments with Parallel Plate Capacitors to Evaluate the Capacitance Calculation an Gauss Law in Electricity, an to Measure the Dielectric Constants of a Few Soli an Liqui Samples Table of Contents Purpose

More information

Digital barrier option contract with exponential random time

Digital barrier option contract with exponential random time IMA Journal of Applie Mathematics Avance Access publishe June 9, IMA Journal of Applie Mathematics ) Page of 9 oi:.93/imamat/hxs3 Digital barrier option contract with exponential ranom time Doobae Jun

More information

A Data Placement Strategy in Scientific Cloud Workflows

A Data Placement Strategy in Scientific Cloud Workflows A Data Placement Strategy in Scientific Clou Workflows Dong Yuan, Yun Yang, Xiao Liu, Jinjun Chen Faculty of Information an Communication Technologies, Swinburne University of Technology Hawthorn, Melbourne,

More information

2r 1. Definition (Degree Measure). Let G be a r-graph of order n and average degree d. Let S V (G). The degree measure µ(s) of S is defined by,

2r 1. Definition (Degree Measure). Let G be a r-graph of order n and average degree d. Let S V (G). The degree measure µ(s) of S is defined by, Theorem Simple Containers Theorem) Let G be a simple, r-graph of average egree an of orer n Let 0 < δ < If is large enough, then there exists a collection of sets C PV G)) satisfying: i) for every inepenent

More information

A New Evaluation Measure for Information Retrieval Systems

A New Evaluation Measure for Information Retrieval Systems A New Evaluation Measure for Information Retrieval Systems Martin Mehlitz martin.mehlitz@ai-labor.e Christian Bauckhage Deutsche Telekom Laboratories christian.bauckhage@telekom.e Jérôme Kunegis jerome.kunegis@ai-labor.e

More information

GPRS performance estimation in GSM circuit switched services and GPRS shared resource systems *

GPRS performance estimation in GSM circuit switched services and GPRS shared resource systems * GPRS performance estimation in GSM circuit switche serices an GPRS share resource systems * Shaoji i an Sen-Gusta Häggman Helsinki Uniersity of Technology, Institute of Raio ommunications, ommunications

More information

UCLA STAT 13 Introduction to Statistical Methods for the Life and Health Sciences. Chapter 9 Paired Data. Paired data. Paired data

UCLA STAT 13 Introduction to Statistical Methods for the Life and Health Sciences. Chapter 9 Paired Data. Paired data. Paired data UCLA STAT 3 Introuction to Statistical Methos for the Life an Health Sciences Instructor: Ivo Dinov, Asst. Prof. of Statistics an Neurology Chapter 9 Paire Data Teaching Assistants: Jacquelina Dacosta

More information

Optimal Control Policy of a Production and Inventory System for multi-product in Segmented Market

Optimal Control Policy of a Production and Inventory System for multi-product in Segmented Market RATIO MATHEMATICA 25 (2013), 29 46 ISSN:1592-7415 Optimal Control Policy of a Prouction an Inventory System for multi-prouct in Segmente Market Kuleep Chauhary, Yogener Singh, P. C. Jha Department of Operational

More information

Voice Service Support over Cognitive Radio Networks

Voice Service Support over Cognitive Radio Networks Voice Service Support over Cognitive Radio Networks Ping Wang, Dusit Niyato, and Hai Jiang Centre For Multimedia And Network Technology (CeMNeT), School of Computer Engineering, Nanyang Technological University,

More information

Firewall Design: Consistency, Completeness, and Compactness

Firewall Design: Consistency, Completeness, and Compactness C IS COS YS TE MS Firewall Design: Consistency, Completeness, an Compactness Mohame G. Goua an Xiang-Yang Alex Liu Department of Computer Sciences The University of Texas at Austin Austin, Texas 78712-1188,

More information

Risk Management for Derivatives

Risk Management for Derivatives Risk Management or Derivatives he Greeks are coming the Greeks are coming! Managing risk is important to a large number o iniviuals an institutions he most unamental aspect o business is a process where

More information

Optimized Capacity Bounds for the Half-Duplex Gaussian MIMO Relay Channel

Optimized Capacity Bounds for the Half-Duplex Gaussian MIMO Relay Channel Optimize Capacity Bouns for the Half-Duplex Gaussian MIMO elay Channel Lennart Geres an Wolfgang Utschick International ITG Workshop on mart Antennas (WA) February 211 c 211 IEEE. Personal use of this

More information

ThroughputScheduler: Learning to Schedule on Heterogeneous Hadoop Clusters

ThroughputScheduler: Learning to Schedule on Heterogeneous Hadoop Clusters ThroughputScheuler: Learning to Scheule on Heterogeneous Haoop Clusters Shehar Gupta, Christian Fritz, Bob Price, Roger Hoover, an Johan e Kleer Palo Alto Research Center, Palo Alto, CA, USA {sgupta, cfritz,

More information

Sensitivity Analysis of Non-linear Performance with Probability Distortion

Sensitivity Analysis of Non-linear Performance with Probability Distortion Preprints of the 19th Worl Congress The International Feeration of Automatic Control Cape Town, South Africa. August 24-29, 214 Sensitivity Analysis of Non-linear Performance with Probability Distortion

More information

Data Center Power System Reliability Beyond the 9 s: A Practical Approach

Data Center Power System Reliability Beyond the 9 s: A Practical Approach Data Center Power System Reliability Beyon the 9 s: A Practical Approach Bill Brown, P.E., Square D Critical Power Competency Center. Abstract Reliability has always been the focus of mission-critical

More information

The Inefficiency of Marginal cost pricing on roads

The Inefficiency of Marginal cost pricing on roads The Inefficiency of Marginal cost pricing on roas Sofia Grahn-Voornevel Sweish National Roa an Transport Research Institute VTI CTS Working Paper 4:6 stract The economic principle of roa pricing is that

More information

Math 230.01, Fall 2012: HW 1 Solutions

Math 230.01, Fall 2012: HW 1 Solutions Math 3., Fall : HW Solutions Problem (p.9 #). Suppose a wor is picke at ranom from this sentence. Fin: a) the chance the wor has at least letters; SOLUTION: All wors are equally likely to be chosen. The

More information

Ch 10. Arithmetic Average Options and Asian Opitons

Ch 10. Arithmetic Average Options and Asian Opitons Ch 10. Arithmetic Average Options an Asian Opitons I. Asian Option an the Analytic Pricing Formula II. Binomial Tree Moel to Price Average Options III. Combination of Arithmetic Average an Reset Options

More information

THE problems of characterizing the fundamental limits

THE problems of characterizing the fundamental limits Beamforming and Aligned Interference Neutralization Achieve the Degrees of Freedom Region of the 2 2 2 MIMO Interference Network (Invited Paper) Chinmay S. Vaze and Mahesh K. Varanasi Abstract We study

More information

Sensor Network Localization from Local Connectivity : Performance Analysis for the MDS-MAP Algorithm

Sensor Network Localization from Local Connectivity : Performance Analysis for the MDS-MAP Algorithm Sensor Network Localization from Local Connectivity : Performance Analysis for the MDS-MAP Algorithm Sewoong Oh an Anrea Montanari Electrical Engineering an Statistics Department Stanfor University, Stanfor,

More information

ISSN: 2277-3754 ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) Volume 3, Issue 12, June 2014

ISSN: 2277-3754 ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) Volume 3, Issue 12, June 2014 ISSN: 77-754 ISO 900:008 Certifie International Journal of Engineering an Innovative echnology (IJEI) Volume, Issue, June 04 Manufacturing process with isruption uner Quaratic Deman for Deteriorating Inventory

More information

Lecture L25-3D Rigid Body Kinematics

Lecture L25-3D Rigid Body Kinematics J. Peraire, S. Winall 16.07 Dynamics Fall 2008 Version 2.0 Lecture L25-3D Rigi Boy Kinematics In this lecture, we consier the motion of a 3D rigi boy. We shall see that in the general three-imensional

More information

Option Pricing for Inventory Management and Control

Option Pricing for Inventory Management and Control Option Pricing for Inventory Management an Control Bryant Angelos, McKay Heasley, an Jeffrey Humpherys Abstract We explore the use of option contracts as a means of managing an controlling inventories

More information

MODELLING OF TWO STRATEGIES IN INVENTORY CONTROL SYSTEM WITH RANDOM LEAD TIME AND DEMAND

MODELLING OF TWO STRATEGIES IN INVENTORY CONTROL SYSTEM WITH RANDOM LEAD TIME AND DEMAND art I. robobabilystic Moels Computer Moelling an New echnologies 27 Vol. No. 2-3 ransport an elecommunication Institute omonosova iga V-9 atvia MOEING OF WO AEGIE IN INVENOY CONO YEM WIH ANOM EA IME AN

More information

Cross-Over Analysis Using T-Tests

Cross-Over Analysis Using T-Tests Chapter 35 Cross-Over Analysis Using -ests Introuction his proceure analyzes ata from a two-treatment, two-perio (x) cross-over esign. he response is assume to be a continuous ranom variable that follows

More information

Study on the Price Elasticity of Demand of Beijing Subway

Study on the Price Elasticity of Demand of Beijing Subway Journal of Traffic an Logistics Engineering, Vol, 1, No. 1 June 2013 Stuy on the Price Elasticity of Deman of Beijing Subway Yanan Miao an Liang Gao MOE Key Laboratory for Urban Transportation Complex

More information

A New Pricing Model for Competitive Telecommunications Services Using Congestion Discounts

A New Pricing Model for Competitive Telecommunications Services Using Congestion Discounts A New Pricing Moel for Competitive Telecommunications Services Using Congestion Discounts N. Keon an G. Ananalingam Department of Systems Engineering University of Pennsylvania Philaelphia, PA 19104-6315

More information

State of Louisiana Office of Information Technology. Change Management Plan

State of Louisiana Office of Information Technology. Change Management Plan State of Louisiana Office of Information Technology Change Management Plan Table of Contents Change Management Overview Change Management Plan Key Consierations Organizational Transition Stages Change

More information

MSc. Econ: MATHEMATICAL STATISTICS, 1995 MAXIMUM-LIKELIHOOD ESTIMATION

MSc. Econ: MATHEMATICAL STATISTICS, 1995 MAXIMUM-LIKELIHOOD ESTIMATION MAXIMUM-LIKELIHOOD ESTIMATION The General Theory of M-L Estimation In orer to erive an M-L estimator, we are boun to make an assumption about the functional form of the istribution which generates the

More information

The Quick Calculus Tutorial

The Quick Calculus Tutorial The Quick Calculus Tutorial This text is a quick introuction into Calculus ieas an techniques. It is esigne to help you if you take the Calculus base course Physics 211 at the same time with Calculus I,

More information

Optimal Energy Commitments with Storage and Intermittent Supply

Optimal Energy Commitments with Storage and Intermittent Supply Submitte to Operations Research manuscript OPRE-2009-09-406 Optimal Energy Commitments with Storage an Intermittent Supply Jae Ho Kim Department of Electrical Engineering, Princeton University, Princeton,

More information

Low-Complexity and Distributed Energy Minimization in Multi-hop Wireless Networks

Low-Complexity and Distributed Energy Minimization in Multi-hop Wireless Networks Low-Complexity an Distribute Energy inimization in ulti-hop Wireless Networks Longbi Lin, Xiaojun Lin, an Ness B. Shroff Center for Wireless Systems an Applications (CWSA) School of Electrical an Computer

More information

Interference Mitigation Techniques for Spectral Capacity Enhancement in GSM Networks

Interference Mitigation Techniques for Spectral Capacity Enhancement in GSM Networks I.J. Wireless an Microwave Technologies, 04,, 0-49 Publishe Online January 04 in MECS(http://www.mecs-press.net) OI: 0.585/ijwmt.04.0.03 Available online at http://www.mecs-press.net/ijwmt Interference

More information

Minimizing Makespan in Flow Shop Scheduling Using a Network Approach

Minimizing Makespan in Flow Shop Scheduling Using a Network Approach Minimizing Makespan in Flow Shop Scheuling Using a Network Approach Amin Sahraeian Department of Inustrial Engineering, Payame Noor University, Asaluyeh, Iran 1 Introuction Prouction systems can be ivie

More information

Detecting Multiple Selfish Attack Nodes Using Replica Allocation in Cognitive Radio Ad-Hoc Networks

Detecting Multiple Selfish Attack Nodes Using Replica Allocation in Cognitive Radio Ad-Hoc Networks Detecting Multiple Selfish Attack Nodes Using Replica Allocation in Cognitive Radio Ad-Hoc Networks Kiruthiga S PG student, Coimbatore Institute of Engineering and Technology Anna University, Chennai,

More information

Log-Likelihood Ratio-based Relay Selection Algorithm in Wireless Network

Log-Likelihood Ratio-based Relay Selection Algorithm in Wireless Network Recent Advances in Electrical Engineering and Electronic Devices Log-Likelihood Ratio-based Relay Selection Algorithm in Wireless Network Ahmed El-Mahdy and Ahmed Walid Faculty of Information Engineering

More information

An intertemporal model of the real exchange rate, stock market, and international debt dynamics: policy simulations

An intertemporal model of the real exchange rate, stock market, and international debt dynamics: policy simulations This page may be remove to conceal the ientities of the authors An intertemporal moel of the real exchange rate, stock market, an international ebt ynamics: policy simulations Saziye Gazioglu an W. Davi

More information

Jitter effects on Analog to Digital and Digital to Analog Converters

Jitter effects on Analog to Digital and Digital to Analog Converters Jitter effects on Analog to Digital an Digital to Analog Converters Jitter effects copyright 1999, 2000 Troisi Design Limite Jitter One of the significant problems in igital auio is clock jitter an its

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 14 10/27/2008 MOMENT GENERATING FUNCTIONS

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 14 10/27/2008 MOMENT GENERATING FUNCTIONS MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 14 10/27/2008 MOMENT GENERATING FUNCTIONS Contents 1. Moment generating functions 2. Sum of a ranom number of ranom variables 3. Transforms

More information

CHAPTER 5 : CALCULUS

CHAPTER 5 : CALCULUS Dr Roger Ni (Queen Mary, University of Lonon) - 5. CHAPTER 5 : CALCULUS Differentiation Introuction to Differentiation Calculus is a branch of mathematics which concerns itself with change. Irrespective

More information

An Introduction to Event-triggered and Self-triggered Control

An Introduction to Event-triggered and Self-triggered Control An Introuction to Event-triggere an Self-triggere Control W.P.M.H. Heemels K.H. Johansson P. Tabuaa Abstract Recent evelopments in computer an communication technologies have le to a new type of large-scale

More information

11 CHAPTER 11: FOOTINGS

11 CHAPTER 11: FOOTINGS CHAPTER ELEVEN FOOTINGS 1 11 CHAPTER 11: FOOTINGS 11.1 Introuction Footings are structural elements that transmit column or wall loas to the unerlying soil below the structure. Footings are esigne to transmit

More information

Modelling and Resolving Software Dependencies

Modelling and Resolving Software Dependencies June 15, 2005 Abstract Many Linux istributions an other moern operating systems feature the explicit eclaration of (often complex) epenency relationships between the pieces of software

More information

Stock Market Value Prediction Using Neural Networks

Stock Market Value Prediction Using Neural Networks Stock Market Value Preiction Using Neural Networks Mahi Pakaman Naeini IT & Computer Engineering Department Islamic Aza University Paran Branch e-mail: m.pakaman@ece.ut.ac.ir Hamireza Taremian Engineering

More information

On the Potential of Network Coding for Cooperative Awareness in Vehicular Networks

On the Potential of Network Coding for Cooperative Awareness in Vehicular Networks On the Potential of Network Coding for Cooperative Awareness in Vehicular Networks Miguel Sepulcre, Javier Gozalvez, Jose Ramon Gisbert UWICORE, Ubiquitous Wireless Communications Research Laboratory,

More information

Optimal Control Of Production Inventory Systems With Deteriorating Items And Dynamic Costs

Optimal Control Of Production Inventory Systems With Deteriorating Items And Dynamic Costs Applie Mathematics E-Notes, 8(2008), 194-202 c ISSN 1607-2510 Available free at mirror sites of http://www.math.nthu.eu.tw/ amen/ Optimal Control Of Prouction Inventory Systems With Deteriorating Items

More information

Mannheim curves in the three-dimensional sphere

Mannheim curves in the three-dimensional sphere Mannheim curves in the three-imensional sphere anju Kahraman, Mehmet Öner Manisa Celal Bayar University, Faculty of Arts an Sciences, Mathematics Department, Muraiye Campus, 5, Muraiye, Manisa, urkey.

More information

A Blame-Based Approach to Generating Proposals for Handling Inconsistency in Software Requirements

A Blame-Based Approach to Generating Proposals for Handling Inconsistency in Software Requirements International Journal of nowlege an Systems Science, 3(), -7, January-March 0 A lame-ase Approach to Generating Proposals for Hanling Inconsistency in Software Requirements eian Mu, Peking University,

More information

A Novel Pathway for Portability of Networks and Handing-on between Networks

A Novel Pathway for Portability of Networks and Handing-on between Networks A Novel Pathway for Portability of Networks and Handing-on between Networks D. S. Dayana #1, S. R. Surya #2 Department of Computer Applications, SRM University, Chennai, India 1 dayanads@rediffmail.com

More information

M147 Practice Problems for Exam 2

M147 Practice Problems for Exam 2 M47 Practice Problems for Exam Exam will cover sections 4., 4.4, 4.5, 4.6, 4.7, 4.8, 5., an 5.. Calculators will not be allowe on the exam. The first ten problems on the exam will be multiple choice. Work

More information

Product Differentiation for Software-as-a-Service Providers

Product Differentiation for Software-as-a-Service Providers University of Augsburg Prof. Dr. Hans Ulrich Buhl Research Center Finance & Information Management Department of Information Systems Engineering & Financial Management Discussion Paper WI-99 Prouct Differentiation

More information

Minimum-Energy Broadcast in All-Wireless Networks: NP-Completeness and Distribution Issues

Minimum-Energy Broadcast in All-Wireless Networks: NP-Completeness and Distribution Issues Minimum-Energy Broacast in All-Wireless Networks: NP-Completeness an Distribution Issues Mario Čagal LCA-EPFL CH-05 Lausanne Switzerlan mario.cagal@epfl.ch Jean-Pierre Hubaux LCA-EPFL CH-05 Lausanne Switzerlan

More information

Unbalanced Power Flow Analysis in a Micro Grid

Unbalanced Power Flow Analysis in a Micro Grid International Journal of Emerging Technology an Avance Engineering Unbalance Power Flow Analysis in a Micro Gri Thai Hau Vo 1, Mingyu Liao 2, Tianhui Liu 3, Anushree 4, Jayashri Ravishankar 5, Toan Phung

More information

Exponential Functions: Differentiation and Integration. The Natural Exponential Function

Exponential Functions: Differentiation and Integration. The Natural Exponential Function 46_54.q //4 :59 PM Page 5 5 CHAPTER 5 Logarithmic, Eponential, an Other Transcenental Functions Section 5.4 f () = e f() = ln The inverse function of the natural logarithmic function is the natural eponential

More information

INFLUENCE OF GPS TECHNOLOGY ON COST CONTROL AND MAINTENANCE OF VEHICLES

INFLUENCE OF GPS TECHNOLOGY ON COST CONTROL AND MAINTENANCE OF VEHICLES 1 st Logistics International Conference Belgrae, Serbia 28-30 November 2013 INFLUENCE OF GPS TECHNOLOGY ON COST CONTROL AND MAINTENANCE OF VEHICLES Goran N. Raoičić * University of Niš, Faculty of Mechanical

More information

Security Vulnerabilities and Solutions for Packet Sampling

Security Vulnerabilities and Solutions for Packet Sampling Security Vulnerabilities an Solutions for Packet Sampling Sharon Golberg an Jennifer Rexfor Princeton University, Princeton, NJ, USA 08544 {golbe, jrex}@princeton.eu Abstract Packet sampling supports a

More information

Hull, Chapter 11 + Sections 17.1 and 17.2 Additional reference: John Cox and Mark Rubinstein, Options Markets, Chapter 5

Hull, Chapter 11 + Sections 17.1 and 17.2 Additional reference: John Cox and Mark Rubinstein, Options Markets, Chapter 5 Binomial Moel Hull, Chapter 11 + ections 17.1 an 17.2 Aitional reference: John Cox an Mark Rubinstein, Options Markets, Chapter 5 1. One-Perio Binomial Moel Creating synthetic options (replicating options)

More information

arxiv:1309.1857v3 [gr-qc] 7 Mar 2014

arxiv:1309.1857v3 [gr-qc] 7 Mar 2014 Generalize holographic equipartition for Friemann-Robertson-Walker universes Wen-Yuan Ai, Hua Chen, Xian-Ru Hu, an Jian-Bo Deng Institute of Theoretical Physics, LanZhou University, Lanzhou 730000, P.

More information

4. Important theorems in quantum mechanics

4. Important theorems in quantum mechanics TFY4215 Kjemisk fysikk og kvantemekanikk - Tillegg 4 1 TILLEGG 4 4. Important theorems in quantum mechanics Before attacking three-imensional potentials in the next chapter, we shall in chapter 4 of this

More information

Detecting Possibly Fraudulent or Error-Prone Survey Data Using Benford s Law

Detecting Possibly Fraudulent or Error-Prone Survey Data Using Benford s Law Detecting Possibly Frauulent or Error-Prone Survey Data Using Benfor s Law Davi Swanson, Moon Jung Cho, John Eltinge U.S. Bureau of Labor Statistics 2 Massachusetts Ave., NE, Room 3650, Washington, DC

More information

Calibration of the broad band UV Radiometer

Calibration of the broad band UV Radiometer Calibration of the broa ban UV Raiometer Marian Morys an Daniel Berger Solar Light Co., Philaelphia, PA 19126 ABSTRACT Mounting concern about the ozone layer epletion an the potential ultraviolet exposure

More information

6.3 Microbial growth in a chemostat

6.3 Microbial growth in a chemostat 6.3 Microbial growth in a chemostat The chemostat is a wiely-use apparatus use in the stuy of microbial physiology an ecology. In such a chemostat also known as continuous-flow culture), microbes such

More information

On Adaboost and Optimal Betting Strategies

On Adaboost and Optimal Betting Strategies On Aaboost an Optimal Betting Strategies Pasquale Malacaria 1 an Fabrizio Smerali 1 1 School of Electronic Engineering an Computer Science, Queen Mary University of Lonon, Lonon, UK Abstract We explore

More information

A Theory of Exchange Rates and the Term Structure of Interest Rates

A Theory of Exchange Rates and the Term Structure of Interest Rates Review of Development Economics, 17(1), 74 87, 013 DOI:10.1111/roe.1016 A Theory of Exchange Rates an the Term Structure of Interest Rates Hyoung-Seok Lim an Masao Ogaki* Abstract This paper efines the

More information

Mathematics Review for Economists

Mathematics Review for Economists Mathematics Review for Economists by John E. Floy University of Toronto May 9, 2013 This ocument presents a review of very basic mathematics for use by stuents who plan to stuy economics in grauate school

More information

LECTURE 15: LINEAR ARRAY THEORY - PART I

LECTURE 15: LINEAR ARRAY THEORY - PART I LECTURE 5: LINEAR ARRAY THEORY - PART I (Linear arrays: the two-element array; the N-element array with uniform amplitue an spacing; broa - sie array; en-fire array; phase array). Introuction Usually the

More information

The one-year non-life insurance risk

The one-year non-life insurance risk The one-year non-life insurance risk Ohlsson, Esbjörn & Lauzeningks, Jan Abstract With few exceptions, the literature on non-life insurance reserve risk has been evote to the ultimo risk, the risk in the

More information

Dynamic Load Balance Algorithm (DLBA) for IEEE 802.11 Wireless LAN

Dynamic Load Balance Algorithm (DLBA) for IEEE 802.11 Wireless LAN Tamkang Journal of Science and Engineering, vol. 2, No. 1 pp. 45-52 (1999) 45 Dynamic Load Balance Algorithm () for IEEE 802.11 Wireless LAN Shiann-Tsong Sheu and Chih-Chiang Wu Department of Electrical

More information

Towards a Framework for Enterprise Architecture Frameworks Comparison and Selection

Towards a Framework for Enterprise Architecture Frameworks Comparison and Selection Towars a Framework for Enterprise Frameworks Comparison an Selection Saber Aballah Faculty of Computers an Information, Cairo University Saber_aballah@hotmail.com Abstract A number of Enterprise Frameworks

More information

Introduction to Integration Part 1: Anti-Differentiation

Introduction to Integration Part 1: Anti-Differentiation Mathematics Learning Centre Introuction to Integration Part : Anti-Differentiation Mary Barnes c 999 University of Syney Contents For Reference. Table of erivatives......2 New notation.... 2 Introuction

More information

A Universal Sensor Control Architecture Considering Robot Dynamics

A Universal Sensor Control Architecture Considering Robot Dynamics International Conference on Multisensor Fusion an Integration for Intelligent Systems (MFI2001) Baen-Baen, Germany, August 2001 A Universal Sensor Control Architecture Consiering Robot Dynamics Frierich

More information

DPillar: Scalable Dual-Port Server Interconnection for Data Center Networks

DPillar: Scalable Dual-Port Server Interconnection for Data Center Networks DPillar: Scalable Dual-Port Server Interconnection for Data Center Networks Yong Liao ECE Department University of Massachusetts Amherst, MA 3, USA Dong Yin Automation Department Northwestern Polytech

More information

Compare Authentication Algorithms for Mobile Systems in Order to Introduce the Successful Characteristics of these Algorithms against Attacks

Compare Authentication Algorithms for Mobile Systems in Order to Introduce the Successful Characteristics of these Algorithms against Attacks Compare Authentication Algorithms for Mobile Systems in Orer to Introuce the Successful Characteristics of these Algorithms against Attacks Shahriar Mohammai Assistant Professor of Inustrial Engineering

More information

Module 2. DC Circuit. Version 2 EE IIT, Kharagpur

Module 2. DC Circuit. Version 2 EE IIT, Kharagpur Moule 2 DC Circuit Lesson 9 Analysis of c resistive network in presence of one non-linear element Objectives To unerstan the volt (V ) ampere ( A ) characteristics of linear an nonlinear elements. Concept

More information

Safety Stock or Excess Capacity: Trade-offs under Supply Risk

Safety Stock or Excess Capacity: Trade-offs under Supply Risk Safety Stock or Excess Capacity: Trae-offs uner Supply Risk Aahaar Chaturvei Victor Martínez-e-Albéniz IESE Business School, University of Navarra Av. Pearson, 08034 Barcelona, Spain achaturvei@iese.eu

More information

Efficient Distributed Scheduling in Cognitive Radio Networks in the Many-Channel Regime

Efficient Distributed Scheduling in Cognitive Radio Networks in the Many-Channel Regime Efficient Distribute Scheuling in Cognitive Raio Networks in the Many-Channel Regime Dongyue Xue an Eylem Ekici Department of Electrical an Computer Engineering Ohio State University USA Email: {xue ekici}@ece.osu.eu

More information

INTRODUCTION TO BEAMS

INTRODUCTION TO BEAMS CHAPTER Structural Steel Design LRFD etho INTRODUCTION TO BEAS Thir Eition A. J. Clark School of Engineering Department of Civil an Environmental Engineering Part II Structural Steel Design an Analsis

More information

Lecture 17: Implicit differentiation

Lecture 17: Implicit differentiation Lecture 7: Implicit ifferentiation Nathan Pflueger 8 October 203 Introuction Toay we iscuss a technique calle implicit ifferentiation, which provies a quicker an easier way to compute many erivatives we

More information

Implementing IP Traceback in the Internet An ISP Perspective

Implementing IP Traceback in the Internet An ISP Perspective Implementing IP Traceback in the Internet An ISP Perspective Dong Wei, Stuent Member, IEEE, an Nirwan Ansari, Senior Member, IEEE Abstract--Denial-of-Service (DoS) attacks consume the resources of remote

More information

Example Optimization Problems selected from Section 4.7

Example Optimization Problems selected from Section 4.7 Example Optimization Problems selecte from Section 4.7 19) We are aske to fin the points ( X, Y ) on the ellipse 4x 2 + y 2 = 4 that are farthest away from the point ( 1, 0 ) ; as it happens, this point

More information

Supporting Adaptive Workflows in Advanced Application Environments

Supporting Adaptive Workflows in Advanced Application Environments Supporting aptive Workflows in vance pplication Environments Manfre Reichert, lemens Hensinger, Peter Daam Department Databases an Information Systems University of Ulm, D-89069 Ulm, Germany Email: {reichert,

More information

Cooperative Wireless Networks: From Radio to. Network Protocol Designs

Cooperative Wireless Networks: From Radio to. Network Protocol Designs Cooperative Wireless Networks: From Radio to 1 Network Protocol Designs Zhengguo Sheng, Zhiguo Ding, and Kin K Leung *Department of Electrical and Electronic Engineering, Imperial College, UK School of

More information

Inverse Trig Functions

Inverse Trig Functions Inverse Trig Functions c A Math Support Center Capsule February, 009 Introuction Just as trig functions arise in many applications, so o the inverse trig functions. What may be most surprising is that

More information

Web Appendices to Selling to Overcon dent Consumers

Web Appendices to Selling to Overcon dent Consumers Web Appenices to Selling to Overcon ent Consumers Michael D. Grubb MIT Sloan School of Management Cambrige, MA 02142 mgrubbmit.eu www.mit.eu/~mgrubb May 2, 2008 B Option Pricing Intuition This appenix

More information

Self-Backhauling Full-Duplex Access Node with Massive Antenna Arrays: Power Allocation and Achievable Sum-Rate

Self-Backhauling Full-Duplex Access Node with Massive Antenna Arrays: Power Allocation and Achievable Sum-Rate Self-Backhauling Full-Duplex Access Noe with Massive Antenna Arrays: Power Allocation an Achievable Sum-Rate Dani Korpi, Taneli Riihonen, an Mikko Valkama Department of Electronics an Communications Engineering,

More information

The influence of anti-viral drug therapy on the evolution of HIV-1 pathogens

The influence of anti-viral drug therapy on the evolution of HIV-1 pathogens DIMACS Series in Discrete Mathematics an Theoretical Computer Science Volume 7, 26 The influence of anti-viral rug therapy on the evolution of HIV- pathogens Zhilan Feng an Libin Rong Abstract. An age-structure

More information

An Empirical Approach - Distributed Mobility Management for Target Tracking in MANETs

An Empirical Approach - Distributed Mobility Management for Target Tracking in MANETs An Empirical Approach - Distributed Mobility Management for Target Tracking in MANETs G.Michael Assistant Professor, Department of CSE, Bharath University, Chennai, TN, India ABSTRACT: Mobility management

More information

Spectrum Trading with Insurance in Cognitive Radio Networks

Spectrum Trading with Insurance in Cognitive Radio Networks Spectrum Trading with Insurance in Cognitive Radio Networks 1/46 Spectrum Trading with Insurance in Cognitive Radio Networks Haiming Jin 1, Gaofei Sun 1, Xinbing Wang 1 and Qian Zhang 2 1 Department of

More information

IN RECENT years, there have been significant efforts to develop

IN RECENT years, there have been significant efforts to develop IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 5, NO. 3, MARCH 2006 525 Effective Bandwidth of Multimedia Traffic in Packet Wireless CDMA Networks with LMMSE Receivers: A Cross-Layer Perspective Fei

More information

Cooperative Multiple Access for Wireless Networks: Protocols Design and Stability Analysis

Cooperative Multiple Access for Wireless Networks: Protocols Design and Stability Analysis Cooperative Multiple Access for Wireless Networks: Protocols Design and Stability Analysis Ahmed K. Sadek, K. J. Ray Liu, and Anthony Ephremides Department of Electrical and Computer Engineering, and Institute

More information

Optimizing Multiple Stock Trading Rules using Genetic Algorithms

Optimizing Multiple Stock Trading Rules using Genetic Algorithms Optimizing Multiple Stock Traing Rules using Genetic Algorithms Ariano Simões, Rui Neves, Nuno Horta Instituto as Telecomunicações, Instituto Superior Técnico Av. Rovisco Pais, 040-00 Lisboa, Portugal.

More information

Professional Level Options Module, Paper P4(SGP)

Professional Level Options Module, Paper P4(SGP) Answers Professional Level Options Moule, Paper P4(SGP) Avance Financial Management (Singapore) December 2007 Answers Tutorial note: These moel answers are consierably longer an more etaile than woul be

More information

Support for Cognitive Vehicular Networks

Support for Cognitive Vehicular Networks Optimal Channel Access Management with QoS 1 Support for Cognitive Vehicular Networks Dusit Niyato, Member, IEEE, Ekram Hossain, Senior Member, IEEE, and Ping Wang, Member, IEEE Abstract We consider the

More information

Enterprise Resource Planning

Enterprise Resource Planning Enterprise Resource Planning MPC 6 th Eition Chapter 1a McGraw-Hill/Irwin Copyright 2011 by The McGraw-Hill Companies, Inc. All rights reserve. Enterprise Resource Planning A comprehensive software approach

More information