TY - GEN
T1 - Time-waved monitoring and emergent self adaption of software components in open source cloud
AU - Rawshan, Lamisha
AU - Sakib, Kazi
AU - Imran, Asif
N1 - Publisher Copyright:
Copyright 2015 ACM.
PY - 2015/9/24
Y1 - 2015/9/24
N2 - Optimized resource utilization and low cost of service has enabled the cloud to become a popular service in today's world. However, rapid scaling, continuous attacks from hackers, dynamic resource provisioning and distributed nature has made it a complex system to manually monitor and manage by system administrators. This paper proposes an effective time-waved framework for monitoring the cloud and reporting undesirable activities with minimum time delay. Next, it presents a mechanism to self-adapt the attacked modules through allocation of healthy ancillary resources. Performance analysis of the proposed framework yields desirable time complexities of 17.0, 26.6, 27.3 and 18.6 seconds for 4 types of attacks tested here. Also, replacing paralyzed cloud virtual machines (vm) with healthy ones requires 8.4 seconds on average, resulting in desirable performance. The experimentation on open source platform show that the proposed schemes enable better monitoring of cloud services.
AB - Optimized resource utilization and low cost of service has enabled the cloud to become a popular service in today's world. However, rapid scaling, continuous attacks from hackers, dynamic resource provisioning and distributed nature has made it a complex system to manually monitor and manage by system administrators. This paper proposes an effective time-waved framework for monitoring the cloud and reporting undesirable activities with minimum time delay. Next, it presents a mechanism to self-adapt the attacked modules through allocation of healthy ancillary resources. Performance analysis of the proposed framework yields desirable time complexities of 17.0, 26.6, 27.3 and 18.6 seconds for 4 types of attacks tested here. Also, replacing paralyzed cloud virtual machines (vm) with healthy ones requires 8.4 seconds on average, resulting in desirable performance. The experimentation on open source platform show that the proposed schemes enable better monitoring of cloud services.
KW - Cloud computing integrity
KW - Cloud forensics
KW - Self-adaptation of cloud components
UR - https://www.scopus.com/pages/publications/84988928646
U2 - 10.1145/2832987.2833055
DO - 10.1145/2832987.2833055
M3 - Conference contribution
AN - SCOPUS:84988928646
T3 - ACM International Conference Proceeding Series
BT - ICEMIS 2015 - International Conference on Engineering and MIS 2015
PB - Association for Computing Machinery
T2 - 2015 International Conference on Engineering and MIS, ICEMIS 2015
Y2 - 24 September 2015 through 26 September 2015
ER -