QoS-Aware Service Composition in Mobile Cloud Networks

Content delivery through cloud networks has gained popularity due to its effectiveness and reliability. Much progress has been made to allow for the easy integration of heterogeneous systems to compose services on the fly. Despite all efforts, the task of fast service composition has made the assumption of the presence of static searchable and updatable central repositories within cloud data centers. With today's dynamic and mobile environments, service providers' movements are unpredictable, thus a rejuvenated service composition mechanism for cloud environments is needed. This paper presents a cloudlet-supported service composition solution in cloud networks that can find a suitable mechanism to discover mobile media processing functions and seamlessly integrate them into media delivery sessions. Furthermore, the established sessions are monitored by a novel client-side QoS measurement collection mechanism and adapted dynamically to network, user, and service providers' changing conditions. Simulation results showcase the effectiveness of the presented solution in terms of composed service stability and QoS measurement collection accuracy.

[1]  Athanasios V. Vasilakos,et al.  A Survey on Service-Oriented Network Virtualization Toward Convergence of Networking and Cloud Computing , 2012, IEEE Transactions on Network and Service Management.

[2]  Frank Eliassen,et al.  Using architecture models for runtime adaptability , 2006, IEEE Software.

[3]  Wenye Wang,et al.  The unheralded power of cloudlet computing in the vicinity of mobile devices , 2013, 2013 IEEE Globecom Workshops (GC Wkshps).

[4]  Ahmed Karmouch,et al.  Ontology-based negotiation protocol and context-level agreements , 2008 .

[5]  Rahim Tafazolli,et al.  An Energy-Efficient Clustering Solution for Wireless Sensor Networks , 2011, IEEE Transactions on Wireless Communications.

[6]  Ahmed Karmouch,et al.  QoS-Based Composition of Service Specific Overlay Networks , 2015, IEEE Transactions on Computers.

[7]  Zhen Li,et al.  Rudder: a rule-based multi-agent infrastructure for supporting autonomic Grid applications , 2004, International Conference on Autonomic Computing, 2004. Proceedings..

[8]  Xiao Chen,et al.  Saving Energy by Adjusting Transmission Power in Wireless Sensor Networks , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[9]  S. Krause,et al.  OverSim: A Flexible Overlay Network Simulation Framework , 2007, 2007 IEEE Global Internet Symposium.

[10]  Zhen Li,et al.  Rudder: a rule-based multi-agent infrastructure for supporting autonomic Grid applications , 2004 .

[11]  Ahmed Karmouch,et al.  SORD: A Fault-Resilient Service Overlay for MediaPort Resource Discovery , 2009, IEEE Transactions on Parallel and Distributed Systems.

[12]  Boi Faltings,et al.  Reliable QoS monitoring based on client feedback , 2007, WWW '07.

[13]  Ahmed Karmouch,et al.  Decentralized Plan-Free Semantic-Based Service Composition in Mobile Networks , 2015, IEEE Transactions on Services Computing.

[14]  Zongpeng Li,et al.  sFlow: towards resource-efficient and agile service federation in service overlay networks , 2004, 24th International Conference on Distributed Computing Systems, 2004. Proceedings..

[15]  Schahram Dustdar,et al.  Comprehensive QoS monitoring of Web services and event-based SLA violation detection , 2009, MWSOC '09.

[16]  Keita Fujii,et al.  Semantics-based dynamic service composition , 2005, IEEE Journal on Selected Areas in Communications.

[17]  Keita Fujii,et al.  Component service model with semantics (CoSMoS): a new component model for dynamic service composition , 2004, 2004 International Symposium on Applications and the Internet Workshops. 2004 Workshops..

[18]  Philip K. McKinley,et al.  Dynamis: Dynamic Overlay Service Composition for Distributed Stream Processing , 2008, SEKE.