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The QoE i (T i ) is the ith user’s experience of the service
quality in a period of time T i, The u i (t) is the average
user’s service utility value measured K times in this
period of time T i . The b ij is the user’s allocated broadband
value of the service measured jth time in this period of
time T i.
4) Utility-policy Description.
After the preceding analysis, we can arrive at the
utility policy which describes the network performance
assessment model. Specific example is shown in Figure 5.
Figure 5 Example of Utility Policy.
D. Action-policy Generation
The action policy which is finally deployed and
executed in the mobile network equipment, is divided into
two categories: Resource allocation policy, which is
generated automatically by the "dynamic policy
generation module" according to predicating information
and has been done a thorough study by project team
members [10] ; the specific action policy set which are
transformed from the high-level abstraction strategy.
These policies work together to achieve the objective
described by goal policy and mainly include:
• Security Authorization Policy, completing
verification whether the user calling to access the
wireless cell is legal or not;
• QoS Configuration Policy, being configured in the
equipments that support QoS parameter
configuration at the bottom level, carrying out data
collection for the "network resource monitoring
module", and completing autonomic management
system’s monitoring functions;
• Admission Control Policy, enforcing the accessing
or switching process when the user calls for getting
the required resources for example bandwidth
through the dynamic policy;
• Resource Adaptation Policy .When the system
resources are inadequate, the dynamic policy
optimization mechanism produces the resource
adaptation policy to adjust the accessed user
resource allocation, for example, to extrude the
bandwidth of the elastic services or the lower
degrade user service.
IV. EXPERIMENT AND SIMULATION
Suppose the total accessed channel capacity of the
wireless cell is 10Mbps, the overall average arrival rate of
handoff call and new call is in line with the Poisson
distribution whose parameter is λ, and the service mean
duration meets the negative exponential distribution
whose parameter is 1/μ=120s. The resource allocation and
access control of the new call and handoff call are
enforced under the PBMRAM framework.
System supports four types of service, the property is
shown in Table 2, and the parameterεis set to 0.001.Two
wireless resource allocation methods used to compare
with PBMRAM are Utility Maximizing Allocation (UMA)
and Fixed Reservation Allocation(FRA).
Table 2 Analysis of Each Service’s Property Setting in the Model
Service
Type
conversational
class
stream
class
interactive
class
background
class
Averag
e
Rate
64
Kbps
256
Kbps
512
Kbps
64
Kbps
Average
Duration
B min B max Spref
60s 64
Kbps
64
Kbps
300s 64 350
Kbps Kbps
120s 30 1
Kbps Mbps
30s 0 100
Kbps
The new call dropping rate of these three wireless
resource allocation methods is shown in Figure 6.
Figure 6. New call Blocking Rate of Three Wireless Resource
Allocation Methods
The handoff dropping rate of these three wireless
resource allocation methods is shown in Figure 7. The
experimental results show that PBMRAM and UMA are
significantly superior to FRA in performance; moreover
PBMRAM has a variety of policy adaptive methods,
making it better than the simple UMA in performance.
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0.2
0.3
0.1
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