TY - GEN
T1 - ARMM
T2 - 2010 7th IEEE Consumer Communications and Networking Conference, CCNC 2010
AU - Quttoum, Ahmad
AU - Otrok, Hadi
AU - Dziong, Zbigniew
PY - 2010
Y1 - 2010
N2 - In this paper, we are addressing the problem of autonomic resource management for Virtual Private Networks (VPNs). Resources management is one of the important problems facing most Internet Service Providers (ISPs). As a solution, the Autonomic Service Architecture (ASA) is proposed in the literature to automate the resources management. Although, this model is able to improve ISPs' performance by automatically adjusting the resources allocation of each customer, it still suffers from two main limitations. First, this model increases the ISPs' revenue in a non-optimal way. Second, this model has no mechanism to prevent customers' exaggeration that can lead to an inefficient resource utilization, and violate the contracted Service Level Agreements' (SLAs) terms. Customers might exaggerate by asking for more resources during and after the SLA negotiation session, especially in the case of multimedia streaming, where this can waste the available network resources. This is due to the fact that customers would like to guarantee their Quality of Services (QoS). To overcome the above limitations, we propose an Autonomic Resources Management Mechanism (ARMM) that increases the ISPs' revenue by allocating resources based on the auction mechanism, where resources are granted to the best bidders. Additionally, we propose a threat model based on Vickrey-Clarke-Groves (VCG) mechanism that is able to penalize exaggerated bidders according to the created inconvenience. Since in our framework, customers are assumed to be rational, they will avoid asking for more unneeded resources. Simulation results show that the ARMM model is able to efficiently utilize network resources, increase ISPs' profit, and customers' satisfaction rates.
AB - In this paper, we are addressing the problem of autonomic resource management for Virtual Private Networks (VPNs). Resources management is one of the important problems facing most Internet Service Providers (ISPs). As a solution, the Autonomic Service Architecture (ASA) is proposed in the literature to automate the resources management. Although, this model is able to improve ISPs' performance by automatically adjusting the resources allocation of each customer, it still suffers from two main limitations. First, this model increases the ISPs' revenue in a non-optimal way. Second, this model has no mechanism to prevent customers' exaggeration that can lead to an inefficient resource utilization, and violate the contracted Service Level Agreements' (SLAs) terms. Customers might exaggerate by asking for more resources during and after the SLA negotiation session, especially in the case of multimedia streaming, where this can waste the available network resources. This is due to the fact that customers would like to guarantee their Quality of Services (QoS). To overcome the above limitations, we propose an Autonomic Resources Management Mechanism (ARMM) that increases the ISPs' revenue by allocating resources based on the auction mechanism, where resources are granted to the best bidders. Additionally, we propose a threat model based on Vickrey-Clarke-Groves (VCG) mechanism that is able to penalize exaggerated bidders according to the created inconvenience. Since in our framework, customers are assumed to be rational, they will avoid asking for more unneeded resources. Simulation results show that the ARMM model is able to efficiently utilize network resources, increase ISPs' profit, and customers' satisfaction rates.
UR - http://www.scopus.com/inward/record.url?scp=77951282567&partnerID=8YFLogxK
U2 - 10.1109/CCNC.2010.5421818
DO - 10.1109/CCNC.2010.5421818
M3 - Conference contribution
AN - SCOPUS:77951282567
SN - 9781424451760
T3 - 2010 7th IEEE Consumer Communications and Networking Conference, CCNC 2010
BT - 2010 7th IEEE Consumer Communications and Networking Conference, CCNC 2010
Y2 - 9 January 2010 through 12 January 2010
ER -