Wenye Wang Xinbing Wang Arne Nilsson
Department of Electrical and Computer Engineering, NC State University
March 2005
A New Admission Control Scheme A New Admission Control Scheme under Energy and QoS Constraints under Energy and QoS Constraints
for Wireless Networksfor Wireless Networks
2 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Agenda• Motivations• Relationship between admission control and
energy consumption• New call admission control scheme
– Victim selection algorithm (VSA)– Beneficiary selection algorithm (BSA)– Stochastic adjustment algorithm (SAA)
• Performance analysis– Markov chain model– Blocking probabilities: fixed/dynamic channel holding time– Energy consumption
• Numerical results• Conclusions and future work
3 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Motivations• Two important issues in future wireless networks
– Bandwidth utilization based on call admission control (CAC)
– Energy conservation• Why “another” admission control scheme?
– Existing work on admission control: interference-, mobility-, and priority-based etc.
– Existing work on energy/power management• At physical layer: power control based on channel fading
and interference, joint source and channel coding etc.• At medium access control (MAC) and application layer:
smart on-off schemes are proposed for energy consumption • CAC and energy saving are separate from each other
• Objective: develop a new admission control scheme under develop a new admission control scheme under constraints of energy consumption and QoSconstraints of energy consumption and QoS
4 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Call Admission Control and Energy Consumption
Energy Consumption Rate (ECR): is energy consumption of each successfully transmitted bit
– Total energy consumption E_{total} = ECR * =ECR*T*R
)()(1)( t
bfertbfer
tbt
bEPRR
P
EP
EEECR
⋅−=
−=
Ebt:Energy to transmit one bit
Pfer :Frame error rate,P:Transmission powerR:Transmission rate:Total amount of dataT:Time to transmit data
5 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Relationship between CAC and Energy Consumption: Example
• Energy consumption rates vary with terminals at different trans. rates
• BPSK Modulation
• Reed Soloman (RS) Code
• Consider Retransmission
6 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Admission Control Scheme Energy Consumption
• Victim Selection Algorithm (BSA)– When there is no enough number of channels,
victims are selected according to the lowest energy increasing rate.
• Beneficiary Selection Algorithm (BSA)– When there are some channels released, beneficiaries are chosen based on the highest
energy decreasing rate.• Stochastic Adjustment Algorithm (SAA)
– To achieve fairness among different classes of traffic by pre-block traffic flows
7 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Victim Selection Algorithm (VSA)
• All bandwidth has been allocated to ongoing sessions
• A new/handoff call arrives, how to find (sufficient) bandwidth for it?
– Search for all ongoing sessions, and find a victim, that is, the absolute value of the derivative of rr(R) (R) is the minimum.
– Note that if this terminal is operating at its lower-bound transmission rate, then this terminal cannot be a victim.
– Once a victim is identified, then the amount of BW bandwidth will be reduced.
Victim
8 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Beneficiary Selection Algorithm (BSA)
• Some bandwidth is released when a connection is finished
• Available bandwidth is reallocated to ongoing sessions
– Search for all ongoing sessions, and find a beneficiary terminal, that is, the absolute value of the derivative of rr(R) (R) is the maximum.
– Note that if this terminal is operating at its upper-bound transmission rate, then this terminal cannot be a beneficiary terminal.
– Once a beneficiary terminal is identified, the amount of BW bandwidth will be reallocated.
Beneficiary terminal
9 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Stochastic Adjustment Algorithm (SAA)
• Goal: to couple admission control with QoS requirements to achieve a balance/fairness among multiple classes
• Solution: pre-block some traffic, that is, to determine the rate of arrival requests blocked for each class, k, for a total number of K classes:
• Pricing model is used to create an objective function. For a simplified two-class system, e.g., handoff and new calls, we consider
€
M = [m1,m2,..,mk,....,mK ]
Min { B1 |Q + B2 |Q }s.t. B1 |Q < B2 |Q, m1 0, m2 0
10 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Performance Analysis: System Model
11 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Assumptions
• Poisson arrival process is enforced.
• Exponential service rate is used, which can be relaxed to any arbitrary distribution.
• For new calls and handoff calls, the same admission control scheme will be used.
12 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Analytical Model: Markov Chain
Call blocking probability for multi-class service model is obtained based on multi-dimension Markov Chain.
13 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Blocking Probabilities• Fixed channel holding time:
– The number of channels of a connection session does not affect channel holding time
– The channel holding time is assumed to be exponentially distributed
– The number of channels, or the bandwidth, affects only the quality of service, like the the resolution of an image.
• Dynamic channel holding time– The channel holding time is dependent on the number
of channels– More bandwidth means shorter transmission time
14 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Analysis of Energy Consumption
• The average energy consumption, EE,
– is the probability of each state– is the average energy consumption at
each state
• can be obtained based on the energy consumption rate, ECR matrix (aij is the ECR of class i with j channels,
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P(N)
€
E(N)
€
E(N)
15 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Simulations• Non-prioritized scheme (NPS): Simplest resource allocation
scheme with least overhead, which determines the admission based on a fixed bandwidth requirement.
• Adaptive resource allocation scheme (AREAS): it determines the admission based on several options of bandwidth requirements.
Parameters Class A Class BArrival Rate (call/min) [1,40] 10
Data Volume (kbyte) 180 180
Transmission Rate (kbps/channel) 8 8
# of Channels for NPS 7 3
# of Channels for AREAS {4, 7, 9} {2, 3, 5}
# of Channels for Our Scheme {4,9} {2,5}
16 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Case I: Blocking Probability • The results of simulations,
analysis of new scheme overlap with the results of AREAS: the energy-based admission control is able to reduce blocking probability as adaptive resource allocation scheme for QoS requirements.
• Adaptive resource allocation schemes are much more effective in reducing blocking probability than non-prioritized scheme
• The lower the bandwidth requirement (e.g., class-B), the lower the blocking probability.
17 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
• The throughput of Class-A increases as the arrival rate is increased, whereas the throughput of Class-B decreases because Class-A traffic is dominant for higher A.
• Higher throughput can be achieved by the new scheme
Case I: Throughput
Class-A Class-B
18 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
• Dynamic channel holding time is considered as Case II in which data volume is fixed. Thus, the more the bandwidth, the shorter the transmission time.
• The blocking probability of the new scheme is lower than both AREAS and NPS.
• The new scheme yields higher throughput.
Case II: Dynamic Channel Holding Time
Blocking Probability and throughput
Class-B
19 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
QoS Adjustment:
Blocking Probability • By sacrificing Class-B,
the blocking probability of Class-A is reduced significantly
• Before using stochastic QoS adjustment algorithm, the difference between blocking probabilities of two classes becomes bigger with increase of arrival rates.
• After the adjustment, the difference of blocking probability of two classes becomes smaller.
20 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Self-Similar Traffic:Blocking Probability and Throughput
• The new scheme is effective in reducing blocking probability and improving throughput for non-Poisson processes such as self-similar traffic
• The simulation takes longer time for self-similar traffic
Blocking Probability Throughput
21 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Energy Consumption
Arrival rate Energy (num. of calls/min)
Consumption Rate
5 20 35
NPS 9.8 9.8 9.8
AREAS 6.2 11.8 12
New Scheme 2.1 3.4 3.6
22 A New Admission Control SchemeA New Admission Control Scheme/ Wang et al, INFOCOM’05, Miami, FL
Conclusions• A new call admission control scheme is designed
based on energy consumption.• Three algorithms: victim selection algorithm (VSA),
beneficiary selection algorithm (BSA), and Stochastic adjustment algorithms (SAA) are proposed to reallocate bandwidth.
• Call blocking probability is analyzed for a multi-class system based on Markov model.
• Lower energy consumption is achieved without the expense of call blocking probability.
Thank you!
