M. Naghshineh and A. S. Acampora, "Design and control of microcellular networks with QoS provisioning for real-time traffic," in Proc. IEEE Universal Personal Communications, San Diego, USA, Sept. 1994, pp. 376--381.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....mechanisms, and (ii) Mobility triggered routing that considers QoS. In the past, these two problems have been addressed separately. The signaling aspect of QoS provisioning in mobile networks has been studied earlier in [16, 8] the scheduling aspect in [7, 12] and architectural considerations in [10]. However, these solutions do not fully consider the routing issues involved. On the other hand, Mobile IP is a recently proposed standard for routing in mobile networks [11] However, Mobile IP appears better suited for long term mobility, but is not designed to support frequent mobility. Other ....

M. Naghshineh and A. S. Acampora. Design and control of micro-cellular networks with QoS provisioning for data traffic. In Proc. International Conference on Communications (ICC), pages 249--256, Dallas, TX, June 1996.

....with the help of a base station and follow a rigid temporal structure which makes practical implementation complex. There are many QoS fair scheduling approaches where in all the scheduling activity is logically done at the base station which makes QoS guarantees in the downlink direction possible [5 7]. Reservation protocol based approaches to guarantee QoS have also been suggested [8, 9] An enhanced Class Based Queueing (CBQ) approach presented in [10] takes into account the channel state of the wireless link before scheduling packets on the link. The BARWAN (Bay Area Research Wireless Access ....

M. Naghshineh and A. S. Acampora, "Design and control of micro-cellular networks with QoS provisioning for data traffic," in Proc. International Conference on Communications (ICC), (Dallas, TX), pp. 249--256, June 1996.

....allocated for a user subject to meeting QoS constraint on drop probability. B. Related work and motivation Majority of the earlier research in the area of resource allocation was based purely on call admission control without keeping any reservation states. These schemes such as in [7] [8], 9] 10] 11] were mostly based on either dynamical or statical prediction of the steady state distribution of users demand in different cells. In contrast, in the recent past, several schemes based on keeping reservation states and per user monitoring were proposed in [1] 4] 3] 12] and ....

....experiment are shown in fig. 7. Figure 8 and 9 show the utilization versus the drop probability for residence time pdf I and II respectively. We observe that for a given drop probability, the utilization BU depends upon both the arrival and residence time pdf. For example, we observe from fig. [8,9] that using uniform pdf for both arrival and residence time gives higher utilization than the exponential pdfs. We also note from comparing the 0 0.01 0.02 0.03 Arrival pdf I: Exponential 0 20 40 60 80 100 0 0.05 0.1 Arrival pdf II: Exponential 0 20 40 60 80 100 0 0.01 0.02 0.03 ....

A. Acampora and M. Naghshineh, "Design and control of micro-cellular networks with QOS provisioning for data traffic," Wireless Network, vol. 3, pp. 249-256, September 1997.

....calls in each base station corresponding to a cell. 6] showed for a simplified queuing model of a single cell that guard channel type policies are optimal based on uniform mobility model. Admission decision based on manipulating the guard channels are denoted as cell based in this paper. [1] develops the regionbased call admission scheme, which is an extension of the cell based scheme in that it limits the number of new calls to a fixed fraction of the capacity of an entire region. Distributed call admission [5] admits a new call in a cell based on a probabilistic prediction of the ....

....subsection, which evaluates the admission, based on the spatial population distribution in the region. 3.2. Convolution Based Call Admission The objective of the call admission decision is to control the load in all the cells in a given region R. Just using the population of a single cell as in [1] or the region as in [2] in order to decide in admitting a call is not efficient. It may happen that a given cell x remain underloaded but leads to overload in some other cells due to users mobility. Therefore, admission decision needs to take into account overload and population states of other ....

A. Acampora and M. Naghshineh, "Design and control of micro-cellular networks with QOS provisioning for data traffic," Wireless Network, vol. 3, pp. 249-256, September 1997.

....the use of time aspects in users mobility towards minimizing the temporal resources allocated for a user subject to meeting QoS constraint on drop probability. Prior work in this area was based purely on call admission control without keeping any reservation states. These schemes such as in [5] [6], 7] 8] 9] were often based on either dynamical or statical prediction of the steady state distribution of users demand in different cells. In contrast, several schemes based on keeping reservation states and per user monitoring were proposed in [1] 3] 10] 11] and found to perform ....

A. Acampora and M. Naghshineh, "Design and control of microcellular networks with QOS provisioning for data traffic," Wireless Network, vol. 3, pp. 249-256, September 1997.

....type policies are optimal. The proof however, only holds for networks where all cells are behaving in the same manner and are sustaining the same incoming load, that is, for uniform models. Admission decision based on manipulating the guard channels are denoted as cell based in this paper. [1] develops the region based call admission scheme, which is an extension of the cell based scheme in that it limits the number of new calls to a fixed fraction of the capacity of an entire region. This achieves a guaranteed utilization for the entire region, but fails to account for possible tra#c ....

....subsection, which evaluates the admission, based on the spatial population distribution in the region. 4.2 Convolution Based Call Admission The objective of the call admission decision is to control the load in all the cells in a given region R. Just using the population of a single cell as in [1] or the region as in [2] in order to decide in admitting a call is not e#cient. It may happen that a given cell x remain underloaded but leads to overload in some other cells due to users mobility. Therefore, admission decision needs to take into account overload and population states of other ....

A. Acampora and M. Naghshineh, "Design and control of micro-cellular networks with QOS provisioning for data tra#c," Wireless Network, vol. 3, pp. 249-256, September 1997.

....the use of time aspects in users mobility towards minimizing the temporal resources allocated for a user subject to meeting QoS constraint on drop probability. Prior work in this area was based purely on call admission control without keeping any reservation states. These schemes such as in [5] [6], 7] 8] 9] were often based on either dynamical or statical prediction of the steady state distribution of users demand in different cells. In contrast, several schemes based on keeping reservation states and per user monitoring were proposed in [1] 3] 10] 11] and found to perform ....

A. Acampora and M. Naghshineh, "Design and control of microcellular networks with QOS provisioning for data traffic," Wireless Network, vol. 3, pp. 249-256, September 1997.

.... Intuitively, the simplest way is to fix the fraction for handoff calls [1] If we group a number of cells together, subject to a single CAC entity, then we get statistical gain over the cluster of cells by limiting new call admission to the predefined fraction of the cell cluster s total capacity [2]. An approach with a rather simple predicting method has been proposed [3] In which, to predict the user mobility, each cell exchanges the number of mobiles being served by it with the adjacent cells. One step further, All cells ahead in the mobile s moving direction which will be likely ....

....i.e. a cell can support maximum m calls at the same time. Then the new call blocking probability for a cell can be easily modeled by M=M=m=m queueing system (m server loss system) socalled Erlang s loss formula [7] An analysis of SPR case with handoff effects taken into account can be found in [2]. In TLG case, the probabilities should be somewhere in between those of SPR and APR according to the size of EGs and PGs. Therefore, the upper bound of the new call blocking probability of TLG is that of APR. So is the lower bound that of SPR. In formula, the probability is approximated by PNCB ....

[Article contains additional citation context not shown here]

M. Naghshineh, "Design and Control of Micro-Cellular Network with QOS Provisioning for Real-Time Traffic," "ICUPC", San Diego CA., 1994.

....channel. This is also called as forced termination probability. The CAC for mobile cellular network can be categorized into fixed and dynamic approach. CACs in the fixed category cannot consider dynamic variation of vehicular traffic. In fixed category, there are trunk reservation[3] threshold[5], and queueing[4] schemes. On the contrary, CACs in dynamic category react to the time varying status of vehicular traffic. Weighting Scheme[6] considers the number of ongoing calls in the cells within some pre defined number of hops. This scheme assigns an unequal weight to each cell to ....

Mahmoud Naghshineh and Anthony S. Acampora, "Design and Control of Micro-Cellular Networks with QoS Provisioning for Real-Time Traffic, " IEEE ICUPC '94, pp. 376-381, 1994.

....of Service) can be easily specified when it is first initiated. The QOS can be subsequently guaranteed throughout the duration of the connection. Some QOS parameters for a wire line ATM connection include peak cell rate (PCR) sustained cell rate (SCR) delay, jitter, and cell loss probability 9 [NA96]. However, guaranteeing QOS for a wireless ATM network is a lot more difficult than for its wire line counterpart because the end hosts are mobile. In this chapter, we are interested in the following QOS parameters: ffl New Call Blocking Probability: This is the percentage of new connection ....

M. Naghshineh and A. S. Acampora, "Design and Control of MicroCellular Networks with QOS provisioning for Data Traffic", Proceedings of IEEE ICC'95, Jun. 1996, p464-8.

....in each cell, the value of PB tends to 4:04 10 Gamma6 when fl tends to infinity. If we make the reasonable conjecture that the difference between PB and PH is an increasing monotic function of fl, the difference between them is bounded to 4:04 10 Gamma6 . Therefore, as was noted also in [15], the models considering handoff traffic as a Poisson process are reasonable when dealing with homogeneous traffic between a large number of cells. The new approximation approach that we have introduced in the previous section will always yield a better accuracy. Nevertheless, when considering ....

M. Naghshineh and A.S. Acampora, "Design and control of Micro-cellular Networks with QOS provisioning for Real-Time Traffic", ICUPC'94 , October 1994.

....fixed Point approximation method. This method is introduced in [Kel91] The generalization of the equivalent Erlang B formulation to inhomogeneous traffic and handover priority mechanisms is treated in [McM91] An algorithm for controlling call admission in micro cellular networks is proposed in [NaA94]. In this paper, the Erlang fixed Point approximation method is used to derive the performance metrics. A review of some models which do not take into consideration the mobility of the users is presented in [Eve94] In [Rap91] a subsequent work to [HoR86] is presented. This paper considers the ....

....of fl, the fraction is close to zero and the guard channels policy is effective. However, when fl increases, the fraction approaches the unity and the policy is less effective. We conclude that more agressive policies should be adopted for higher values of fl. Such a policy is suggested in [NaA94] where the call admission decision is based on the global state information (number of calls in the neighborhood of the cell where a call is initiated) 56 AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA ....

[Article contains additional citation context not shown here]

M. Naghshineh and A.S. Acampora, "Design and control of Micro-cellular Networks with QOS provisioning for Real-Time Traffic", ICUPC'94 , October 1994.

....to 0:64 and the value of PB tends to 4:04 10 Gamma6 , when fl tends to infinity. If we make the reasonable conjecture that the difference between PB and PH is an increasing monotic function of fl, the difference between them is bounded to 4:04 10 Gamma6 . Therefore, as was noted also in [NaA94], the models considering handoff traffic as a Poisson process are reasonable when dealing with homogeneous traffic between a large number of cells. The new approximation approach that we have introduced in the previous section will always yield a better accuracy. Nevertheless, when considering ....

M. Naghshineh and A.S. Acampora, "Design and control of Micro-cellular Networks with QOS provisioning for Real-Time Traffic," In ICUPC'94 , October 1994.

....to 0:64 and the value of PB tends to 4:04 10 Gamma6 , when fl tends to infinity. If we make the reasonable conjecture that the difference between PB and PH is an increasing monotic function of fl, the difference between them is bounded to 4:04 10 Gamma6 . Therefore, as was noted also in [NaA94], the models considering handoff traffic as a Poisson process are reasonable when dealing with homogeneous traffic between a large number of cells. The new approximation approach that we have introduced in the previous section will always yield a better accuracy. Nevertheless, when considering ....

M. Naghshineh and A.S. Acampora, "Design and control of Micro-cellular Networks with QOS provisioning for Real-Time Traffic," In ICUPC'94 , October 1994.

....to 0:64 and the value of PB tends to 4:04 10 Gamma6 , when fl tends to infinity. If we make the reasonable conjecture that the difference between PB and PH is an increasing monotic function of fl, the difference between them is bounded to 4:04 10 Gamma6 . Therefore, as was noted also in [NaA94], the models considering handoff traffic as a Poisson process are reasonable when dealing with homogeneous traffic between a large number of cells. The new approximation approach that we have introduced in the previous section will always yield a better accuracy. Nevertheless, when considering ....

M. Naghshineh and A.S. Acampora, "Design and control of Micro-cellular Networks with QOS provisioning for Real-Time Traffic," In ICUPC'94 , October 1994.

.... new call blocking probability which measures the percentage of call requests that are turned down due to lack of resources (such as a cell site subscriber channel) and call hand off dropping probability which measures the percentage of calls dropped at handoff, also due to lack of resources [6]. Forced call termination probability measures the percentage of calls which are prematurely terminated. This includes calls dropped at hand off as well as calls dropped due to degradation (such as fading) of a channel. Figure 1: Mobile network architecture Figure 2: Mobile Survivability ....

M. Naghshineh, A.S. Acampora, "Design and Control of Micro-Cellular Networks with QOS Provisioning for Real-Time Traffic," ICUPC,, Oct. 1994.

....particular traffic class are described. In [1] a bandwidth reservation scheme for different classes of traffic (e.g. ABR and CBR traffic) is presented. A framework that is used to estimate future resource requirements and to perform call admission decisions in wireless networks is proposed in [2] [8] [6] In [7] a scheme for prioritizing hand off calls to adapt to the hand off and new call arrival rates is shown. An algorithm that allows a cluster of cells to pool bandwidth together for hand off connections is described in [9] In [5] a framework for prioritizing different mixtures of ....

Mahmoud Naghshineh and Anthony S. Acampora, "Design and Control of Micro-Cellular Networks with QOS provisioning for Data Traffic", ICC'95, IEEE, p464-8, June, 1996.

.... the congestion probability of hand off calls, but use only local state information (number of calls in the cell where a new call is initiated) for accepting a new call as opposed to the global state information (number of calls in the neighborhood of the cell where a new call is initiated) In [27], it is shown that by taking the global state information (as opposed to local state information) the wireless resources can be utilized more efficiently. Most importantly, the above referenced studies consider only one class of wireless traffic. Class Based QOS in Wireless Networks We consider ....

A. S. Acampora and M. Naghshineh, Design and Control of Micro-Cellular Networks with QOS Provisions for Real-Time Traffic, Paper in preparation.

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M. Naghshineh and A. S. Acampora, "Design and control of microcellular networks with QoS provisioning for real-time traffic," in Proc. IEEE Universal Personal Communications, San Diego, USA, Sept. 1994, pp. 376--381.

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